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Research Article

Twenty years of gender equality research: A scoping review based on a new semantic indicator

Contributed equally to this work with: Paola Belingheri, Filippo Chiarello, Andrea Fronzetti Colladon, Paola Rovelli

Roles Conceptualization, Formal analysis, Funding acquisition, Visualization, Writing – original draft, Writing – review & editing

Affiliation Dipartimento di Ingegneria dell’Energia, dei Sistemi, del Territorio e delle Costruzioni, Università degli Studi di Pisa, Largo L. Lazzarino, Pisa, Italy

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Visualization, Writing – original draft, Writing – review & editing

Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Department of Engineering, University of Perugia, Perugia, Italy, Department of Management, Kozminski University, Warsaw, Poland

Roles Conceptualization, Formal analysis, Funding acquisition, Writing – original draft, Writing – review & editing

Affiliation Faculty of Economics and Management, Centre for Family Business Management, Free University of Bozen-Bolzano, Bozen-Bolzano, Italy

Paola Belingheri,
Filippo Chiarello,
Andrea Fronzetti Colladon,
Paola Rovelli

Published: September 21, 2021
https://doi.org/10.1371/journal.pone.0256474
Reader Comments

9 Nov 2021: The PLOS ONE Staff (2021) Correction: Twenty years of gender equality research: A scoping review based on a new semantic indicator. PLOS ONE 16(11): e0259930. https://doi.org/10.1371/journal.pone.0259930 View correction

Gender equality is a major problem that places women at a disadvantage thereby stymieing economic growth and societal advancement. In the last two decades, extensive research has been conducted on gender related issues, studying both their antecedents and consequences. However, existing literature reviews fail to provide a comprehensive and clear picture of what has been studied so far, which could guide scholars in their future research. Our paper offers a scoping review of a large portion of the research that has been published over the last 22 years, on gender equality and related issues, with a specific focus on business and economics studies. Combining innovative methods drawn from both network analysis and text mining, we provide a synthesis of 15,465 scientific articles. We identify 27 main research topics, we measure their relevance from a semantic point of view and the relationships among them, highlighting the importance of each topic in the overall gender discourse. We find that prominent research topics mostly relate to women in the workforce–e.g., concerning compensation, role, education, decision-making and career progression. However, some of them are losing momentum, and some other research trends–for example related to female entrepreneurship, leadership and participation in the board of directors–are on the rise. Besides introducing a novel methodology to review broad literature streams, our paper offers a map of the main gender-research trends and presents the most popular and the emerging themes, as well as their intersections, outlining important avenues for future research.

Citation: Belingheri P, Chiarello F, Fronzetti Colladon A, Rovelli P (2021) Twenty years of gender equality research: A scoping review based on a new semantic indicator. PLoS ONE 16(9): e0256474. https://doi.org/10.1371/journal.pone.0256474

Editor: Elisa Ughetto, Politecnico di Torino, ITALY

Received: June 25, 2021; Accepted: August 6, 2021; Published: September 21, 2021

Copyright: © 2021 Belingheri et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its supporting information files. The only exception is the text of the abstracts (over 15,000) that we have downloaded from Scopus. These abstracts can be retrieved from Scopus, but we do not have permission to redistribute them.

Funding: P.B and F.C.: Grant of the Department of Energy, Systems, Territory and Construction of the University of Pisa (DESTEC) for the project “Measuring Gender Bias with Semantic Analysis: The Development of an Assessment Tool and its Application in the European Space Industry. P.B., F.C., A.F.C., P.R.: Grant of the Italian Association of Management Engineering (AiIG), “Misure di sostegno ai soci giovani AiIG” 2020, for the project “Gender Equality Through Data Intelligence (GEDI)”. F.C.: EU project ASSETs+ Project (Alliance for Strategic Skills addressing Emerging Technologies in Defence) EAC/A03/2018 - Erasmus+ programme, Sector Skills Alliances, Lot 3: Sector Skills Alliance for implementing a new strategic approach (Blueprint) to sectoral cooperation on skills G.A. NUMBER: 612678-EPP-1-2019-1-IT-EPPKA2-SSA-B.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The persistent gender inequalities that currently exist across the developed and developing world are receiving increasing attention from economists, policymakers, and the general public [e.g., 1 – 3 ]. Economic studies have indicated that women’s education and entry into the workforce contributes to social and economic well-being [e.g., 4 , 5 ], while their exclusion from the labor market and from managerial positions has an impact on overall labor productivity and income per capita [ 6 , 7 ]. The United Nations selected gender equality, with an emphasis on female education, as part of the Millennium Development Goals [ 8 ], and gender equality at-large as one of the 17 Sustainable Development Goals (SDGs) to be achieved by 2030 [ 9 ]. These latter objectives involve not only developing nations, but rather all countries, to achieve economic, social and environmental well-being.

As is the case with many SDGs, gender equality is still far from being achieved and persists across education, access to opportunities, or presence in decision-making positions [ 7 , 10 , 11 ]. As we enter the last decade for the SDGs’ implementation, and while we are battling a global health pandemic, effective and efficient action becomes paramount to reach this ambitious goal.

Scholars have dedicated a massive effort towards understanding gender equality, its determinants, its consequences for women and society, and the appropriate actions and policies to advance women’s equality. Many topics have been covered, ranging from women’s education and human capital [ 12 , 13 ] and their role in society [e.g., 14 , 15 ], to their appointment in firms’ top ranked positions [e.g., 16 , 17 ] and performance implications [e.g., 18 , 19 ]. Despite some attempts, extant literature reviews provide a narrow view on these issues, restricted to specific topics–e.g., female students’ presence in STEM fields [ 20 ], educational gender inequality [ 5 ], the gender pay gap [ 21 ], the glass ceiling effect [ 22 ], leadership [ 23 ], entrepreneurship [ 24 ], women’s presence on the board of directors [ 25 , 26 ], diversity management [ 27 ], gender stereotypes in advertisement [ 28 ], or specific professions [ 29 ]. A comprehensive view on gender-related research, taking stock of key findings and under-studied topics is thus lacking.

Extant literature has also highlighted that gender issues, and their economic and social ramifications, are complex topics that involve a large number of possible antecedents and outcomes [ 7 ]. Indeed, gender equality actions are most effective when implemented in unison with other SDGs (e.g., with SDG 8, see [ 30 ]) in a synergetic perspective [ 10 ]. Many bodies of literature (e.g., business, economics, development studies, sociology and psychology) approach the problem of achieving gender equality from different perspectives–often addressing specific and narrow aspects. This sometimes leads to a lack of clarity about how different issues, circumstances, and solutions may be related in precipitating or mitigating gender inequality or its effects. As the number of papers grows at an increasing pace, this issue is exacerbated and there is a need to step back and survey the body of gender equality literature as a whole. There is also a need to examine synergies between different topics and approaches, as well as gaps in our understanding of how different problems and solutions work together. Considering the important topic of women’s economic and social empowerment, this paper aims to fill this gap by answering the following research question: what are the most relevant findings in the literature on gender equality and how do they relate to each other ?

To do so, we conduct a scoping review [ 31 ], providing a synthesis of 15,465 articles dealing with gender equity related issues published in the last twenty-two years, covering both the periods of the MDGs and the SDGs (i.e., 2000 to mid 2021) in all the journals indexed in the Academic Journal Guide’s 2018 ranking of business and economics journals. Given the huge amount of research conducted on the topic, we adopt an innovative methodology, which relies on social network analysis and text mining. These techniques are increasingly adopted when surveying large bodies of text. Recently, they were applied to perform analysis of online gender communication differences [ 32 ] and gender behaviors in online technology communities [ 33 ], to identify and classify sexual harassment instances in academia [ 34 ], and to evaluate the gender inclusivity of disaster management policies [ 35 ].

Applied to the title, abstracts and keywords of the articles in our sample, this methodology allows us to identify a set of 27 recurrent topics within which we automatically classify the papers. Introducing additional novelty, by means of the Semantic Brand Score (SBS) indicator [ 36 ] and the SBS BI app [ 37 ], we assess the importance of each topic in the overall gender equality discourse and its relationships with the other topics, as well as trends over time, with a more accurate description than that offered by traditional literature reviews relying solely on the number of papers presented in each topic.

This methodology, applied to gender equality research spanning the past twenty-two years, enables two key contributions. First, we extract the main message that each document is conveying and how this is connected to other themes in literature, providing a rich picture of the topics that are at the center of the discourse, as well as of the emerging topics. Second, by examining the semantic relationship between topics and how tightly their discourses are linked, we can identify the key relationships and connections between different topics. This semi-automatic methodology is also highly reproducible with minimum effort.

This literature review is organized as follows. In the next section, we present how we selected relevant papers and how we analyzed them through text mining and social network analysis. We then illustrate the importance of 27 selected research topics, measured by means of the SBS indicator. In the results section, we present an overview of the literature based on the SBS results–followed by an in-depth narrative analysis of the top 10 topics (i.e., those with the highest SBS) and their connections. Subsequently, we highlight a series of under-studied connections between the topics where there is potential for future research. Through this analysis, we build a map of the main gender-research trends in the last twenty-two years–presenting the most popular themes. We conclude by highlighting key areas on which research should focused in the future.

Our aim is to map a broad topic, gender equality research, that has been approached through a host of different angles and through different disciplines. Scoping reviews are the most appropriate as they provide the freedom to map different themes and identify literature gaps, thereby guiding the recommendation of new research agendas [ 38 ].

Several practical approaches have been proposed to identify and assess the underlying topics of a specific field using big data [ 39 – 41 ], but many of them fail without proper paper retrieval and text preprocessing. This is specifically true for a research field such as the gender-related one, which comprises the work of scholars from different backgrounds. In this section, we illustrate a novel approach for the analysis of scientific (gender-related) papers that relies on methods and tools of social network analysis and text mining. Our procedure has four main steps: (1) data collection, (2) text preprocessing, (3) keywords extraction and classification, and (4) evaluation of semantic importance and image.

Data collection

In this study, we analyze 22 years of literature on gender-related research. Following established practice for scoping reviews [ 42 ], our data collection consisted of two main steps, which we summarize here below.

Firstly, we retrieved from the Scopus database all the articles written in English that contained the term “gender” in their title, abstract or keywords and were published in a journal listed in the Academic Journal Guide 2018 ranking of the Chartered Association of Business Schools (CABS) ( https://charteredabs.org/wp-content/uploads/2018/03/AJG2018-Methodology.pdf ), considering the time period from Jan 2000 to May 2021. We used this information considering that abstracts, titles and keywords represent the most informative part of a paper, while using the full-text would increase the signal-to-noise ratio for information extraction. Indeed, these textual elements already demonstrated to be reliable sources of information for the task of domain lexicon extraction [ 43 , 44 ]. We chose Scopus as source of literature because of its popularity, its update rate, and because it offers an API to ease the querying process. Indeed, while it does not allow to retrieve the full text of scientific articles, the Scopus API offers access to titles, abstracts, citation information and metadata for all its indexed scholarly journals. Moreover, we decided to focus on the journals listed in the AJG 2018 ranking because we were interested in reviewing business and economics related gender studies only. The AJG is indeed widely used by universities and business schools as a reference point for journal and research rigor and quality. This first step, executed in June 2021, returned more than 55,000 papers.

In the second step–because a look at the papers showed very sparse results, many of which were not in line with the topic of this literature review (e.g., papers dealing with health care or medical issues, where the word gender indicates the gender of the patients)–we applied further inclusion criteria to make the sample more focused on the topic of this literature review (i.e., women’s gender equality issues). Specifically, we only retained those papers mentioning, in their title and/or abstract, both gender-related keywords (e.g., daughter, female, mother) and keywords referring to bias and equality issues (e.g., equality, bias, diversity, inclusion). After text pre-processing (see next section), keywords were first identified from a frequency-weighted list of words found in the titles, abstracts and keywords in the initial list of papers, extracted through text mining (following the same approach as [ 43 ]). They were selected by two of the co-authors independently, following respectively a bottom up and a top-down approach. The bottom-up approach consisted of examining the words found in the frequency-weighted list and classifying those related to gender and equality. The top-down approach consisted in searching in the word list for notable gender and equality-related words. Table 1 reports the sets of keywords we considered, together with some examples of words that were used to search for their presence in the dataset (a full list is provided in the S1 Text ). At end of this second step, we obtained a final sample of 15,465 relevant papers.

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https://doi.org/10.1371/journal.pone.0256474.t001

Text processing and keyword extraction

Text preprocessing aims at structuring text into a form that can be analyzed by statistical models. In the present section, we describe the preprocessing steps we applied to paper titles and abstracts, which, as explained below, partially follow a standard text preprocessing pipeline [ 45 ]. These activities have been performed using the R package udpipe [ 46 ].

The first step is n-gram extraction (i.e., a sequence of words from a given text sample) to identify which n-grams are important in the analysis, since domain-specific lexicons are often composed by bi-grams and tri-grams [ 47 ]. Multi-word extraction is usually implemented with statistics and linguistic rules, thus using the statistical properties of n-grams or machine learning approaches [ 48 ]. However, for the present paper, we used Scopus metadata in order to have a more effective and efficient n-grams collection approach [ 49 ]. We used the keywords of each paper in order to tag n-grams with their associated keywords automatically. Using this greedy approach, it was possible to collect all the keywords listed by the authors of the papers. From this list, we extracted only keywords composed by two, three and four words, we removed all the acronyms and rare keywords (i.e., appearing in less than 1% of papers), and we clustered keywords showing a high orthographic similarity–measured using a Levenshtein distance [ 50 ] lower than 2, considering these groups of keywords as representing same concepts, but expressed with different spelling. After tagging the n-grams in the abstracts, we followed a common data preparation pipeline that consists of the following steps: (i) tokenization, that splits the text into tokens (i.e., single words and previously tagged multi-words); (ii) removal of stop-words (i.e. those words that add little meaning to the text, usually being very common and short functional words–such as “and”, “or”, or “of”); (iii) parts-of-speech tagging, that is providing information concerning the morphological role of a word and its morphosyntactic context (e.g., if the token is a determiner, the next token is a noun or an adjective with very high confidence, [ 51 ]); and (iv) lemmatization, which consists in substituting each word with its dictionary form (or lemma). The output of the latter step allows grouping together the inflected forms of a word. For example, the verbs “am”, “are”, and “is” have the shared lemma “be”, or the nouns “cat” and “cats” both share the lemma “cat”. We preferred lemmatization over stemming [ 52 ] in order to obtain more interpretable results.

In addition, we identified a further set of keywords (with respect to those listed in the “keywords” field) by applying a series of automatic words unification and removal steps, as suggested in past research [ 53 , 54 ]. We removed: sparse terms (i.e., occurring in less than 0.1% of all documents), common terms (i.e., occurring in more than 10% of all documents) and retained only nouns and adjectives. It is relevant to notice that no document was lost due to these steps. We then used the TF-IDF function [ 55 ] to produce a new list of keywords. We additionally tested other approaches for the identification and clustering of keywords–such as TextRank [ 56 ] or Latent Dirichlet Allocation [ 57 ]–without obtaining more informative results.

Classification of research topics

To guide the literature analysis, two experts met regularly to examine the sample of collected papers and to identify the main topics and trends in gender research. Initially, they conducted brainstorming sessions on the topics they expected to find, due to their knowledge of the literature. This led to an initial list of topics. Subsequently, the experts worked independently, also supported by the keywords in paper titles and abstracts extracted with the procedure described above.

Considering all this information, each expert identified and clustered relevant keywords into topics. At the end of the process, the two assignments were compared and exhibited a 92% agreement. Another meeting was held to discuss discordant cases and reach a consensus. This resulted in a list of 27 topics, briefly introduced in Table 2 and subsequently detailed in the following sections.

https://doi.org/10.1371/journal.pone.0256474.t002

Evaluation of semantic importance

Working on the lemmatized corpus of the 15,465 papers included in our sample, we proceeded with the evaluation of semantic importance trends for each topic and with the analysis of their connections and prevalent textual associations. To this aim, we used the Semantic Brand Score indicator [ 36 ], calculated through the SBS BI webapp [ 37 ] that also produced a brand image report for each topic. For this study we relied on the computing resources of the ENEA/CRESCO infrastructure [ 58 ].

The Semantic Brand Score (SBS) is a measure of semantic importance that combines methods of social network analysis and text mining. It is usually applied for the analysis of (big) textual data to evaluate the importance of one or more brands, names, words, or sets of keywords [ 36 ]. Indeed, the concept of “brand” is intended in a flexible way and goes beyond products or commercial brands. In this study, we evaluate the SBS time-trends of the keywords defining the research topics discussed in the previous section. Semantic importance comprises the three dimensions of topic prevalence, diversity and connectivity. Prevalence measures how frequently a research topic is used in the discourse. The more a topic is mentioned by scientific articles, the more the research community will be aware of it, with possible increase of future studies; this construct is partly related to that of brand awareness [ 59 ]. This effect is even stronger, considering that we are analyzing the title, abstract and keywords of the papers, i.e. the parts that have the highest visibility. A very important characteristic of the SBS is that it considers the relationships among words in a text. Topic importance is not just a matter of how frequently a topic is mentioned, but also of the associations a topic has in the text. Specifically, texts are transformed into networks of co-occurring words, and relationships are studied through social network analysis [ 60 ]. This step is necessary to calculate the other two dimensions of our semantic importance indicator. Accordingly, a social network of words is generated for each time period considered in the analysis–i.e., a graph made of n nodes (words) and E edges weighted by co-occurrence frequency, with W being the set of edge weights. The keywords representing each topic were clustered into single nodes.

The construct of diversity relates to that of brand image [ 59 ], in the sense that it considers the richness and distinctiveness of textual (topic) associations. Considering the above-mentioned networks, we calculated diversity using the distinctiveness centrality metric–as in the formula presented by Fronzetti Colladon and Naldi [ 61 ].

Lastly, connectivity was measured as the weighted betweenness centrality [ 62 , 63 ] of each research topic node. We used the formula presented by Wasserman and Faust [ 60 ]. The dimension of connectivity represents the “brokerage power” of each research topic–i.e., how much it can serve as a bridge to connect other terms (and ultimately topics) in the discourse [ 36 ].

The SBS is the final composite indicator obtained by summing the standardized scores of prevalence, diversity and connectivity. Standardization was carried out considering all the words in the corpus, for each specific timeframe.

This methodology, applied to a large and heterogeneous body of text, enables to automatically identify two important sets of information that add value to the literature review. Firstly, the relevance of each topic in literature is measured through a composite indicator of semantic importance, rather than simply looking at word frequencies. This provides a much richer picture of the topics that are at the center of the discourse, as well as of the topics that are emerging in the literature. Secondly, it enables to examine the extent of the semantic relationship between topics, looking at how tightly their discourses are linked. In a field such as gender equality, where many topics are closely linked to each other and present overlaps in issues and solutions, this methodology offers a novel perspective with respect to traditional literature reviews. In addition, it ensures reproducibility over time and the possibility to semi-automatically update the analysis, as new papers become available.

Overview of main topics

In terms of descriptive textual statistics, our corpus is made of 15,465 text documents, consisting of a total of 2,685,893 lemmatized tokens (words) and 32,279 types. As a result, the type-token ratio is 1.2%. The number of hapaxes is 12,141, with a hapax-token ratio of 37.61%.

Fig 1 shows the list of 27 topics by decreasing SBS. The most researched topic is compensation , exceeding all others in prevalence, diversity, and connectivity. This means it is not only mentioned more often than other topics, but it is also connected to a greater number of other topics and is central to the discourse on gender equality. The next four topics are, in order of SBS, role , education , decision-making , and career progression . These topics, except for education , all concern women in the workforce. Between these first five topics and the following ones there is a clear drop in SBS scores. In particular, the topics that follow have a lower connectivity than the first five. They are hiring , performance , behavior , organization , and human capital . Again, except for behavior and human capital , the other three topics are purely related to women in the workforce. After another drop-off, the following topics deal prevalently with women in society. This trend highlights that research on gender in business journals has so far mainly paid attention to the conditions that women experience in business contexts, while also devoting some attention to women in society.

https://doi.org/10.1371/journal.pone.0256474.g001

Fig 2 shows the SBS time series of the top 10 topics. While there has been a general increase in the number of Scopus-indexed publications in the last decade, we notice that some SBS trends remain steady, or even decrease. In particular, we observe that the main topic of the last twenty-two years, compensation , is losing momentum. Since 2016, it has been surpassed by decision-making , education and role , which may indicate that literature is increasingly attempting to identify root causes of compensation inequalities. Moreover, in the last two years, the topics of hiring , performance , and organization are experiencing the largest importance increase.

https://doi.org/10.1371/journal.pone.0256474.g002

Fig 3 shows the SBS time trends of the remaining 17 topics (i.e., those not in the top 10). As we can see from the graph, there are some that maintain a steady trend–such as reputation , management , networks and governance , which also seem to have little importance. More relevant topics with average stationary trends (except for the last two years) are culture , family , and parenting . The feminine topic is among the most important here, and one of those that exhibit the larger variations over time (similarly to leadership ). On the other hand, the are some topics that, even if not among the most important, show increasing SBS trends; therefore, they could be considered as emerging topics and could become popular in the near future. These are entrepreneurship , leadership , board of directors , and sustainability . These emerging topics are also interesting to anticipate future trends in gender equality research that are conducive to overall equality in society.

https://doi.org/10.1371/journal.pone.0256474.g003

In addition to the SBS score of the different topics, the network of terms they are associated to enables to gauge the extent to which their images (textual associations) overlap or differ ( Fig 4 ).

https://doi.org/10.1371/journal.pone.0256474.g004

There is a central cluster of topics with high similarity, which are all connected with women in the workforce. The cluster includes topics such as organization , decision-making , performance , hiring , human capital , education and compensation . In addition, the topic of well-being is found within this cluster, suggesting that women’s equality in the workforce is associated to well-being considerations. The emerging topics of entrepreneurship and leadership are also closely connected with each other, possibly implying that leadership is a much-researched quality in female entrepreneurship. Topics that are relatively more distant include personality , politics , feminine , empowerment , management , board of directors , reputation , governance , parenting , masculine and network .

The following sections describe the top 10 topics and their main associations in literature (see Table 3 ), while providing a brief overview of the emerging topics.

https://doi.org/10.1371/journal.pone.0256474.t003

Compensation.

The topic of compensation is related to the topics of role , hiring , education and career progression , however, also sees a very high association with the words gap and inequality . Indeed, a well-known debate in degrowth economics centers around whether and how to adequately compensate women for their childbearing, childrearing, caregiver and household work [e.g., 30 ].

Even in paid work, women continue being offered lower compensations than their male counterparts who have the same job or cover the same role [ 64 – 67 ]. This severe inequality has been widely studied by scholars over the last twenty-two years. Dealing with this topic, some specific roles have been addressed. Specifically, research highlighted differences in compensation between female and male CEOs [e.g., 68 ], top executives [e.g., 69 ], and boards’ directors [e.g., 70 ]. Scholars investigated the determinants of these gaps, such as the gender composition of the board [e.g., 71 – 73 ] or women’s individual characteristics [e.g., 71 , 74 ].

Among these individual characteristics, education plays a relevant role [ 75 ]. Education is indeed presented as the solution for women, not only to achieve top executive roles, but also to reduce wage inequality [e.g., 76 , 77 ]. Past research has highlighted education influences on gender wage gaps, specifically referring to gender differences in skills [e.g., 78 ], college majors [e.g., 79 ], and college selectivity [e.g., 80 ].

Finally, the wage gap issue is strictly interrelated with hiring –e.g., looking at whether being a mother affects hiring and compensation [e.g., 65 , 81 ] or relating compensation to unemployment [e.g., 82 ]–and career progression –for instance looking at meritocracy [ 83 , 84 ] or the characteristics of the boss for whom women work [e.g., 85 ].

The roles covered by women have been deeply investigated. Scholars have focused on the role of women in their families and the society as a whole [e.g., 14 , 15 ], and, more widely, in business contexts [e.g., 18 , 81 ]. Indeed, despite still lagging behind their male counterparts [e.g., 86 , 87 ], in the last decade there has been an increase in top ranked positions achieved by women [e.g., 88 , 89 ]. Following this phenomenon, scholars have posed greater attention towards the presence of women in the board of directors [e.g., 16 , 18 , 90 , 91 ], given the increasing pressure to appoint female directors that firms, especially listed ones, have experienced. Other scholars have focused on the presence of women covering the role of CEO [e.g., 17 , 92 ] or being part of the top management team [e.g., 93 ]. Irrespectively of the level of analysis, all these studies tried to uncover the antecedents of women’s presence among top managers [e.g., 92 , 94 ] and the consequences of having a them involved in the firm’s decision-making –e.g., on performance [e.g., 19 , 95 , 96 ], risk [e.g., 97 , 98 ], and corporate social responsibility [e.g., 99 , 100 ].

Besides studying the difficulties and discriminations faced by women in getting a job [ 81 , 101 ], and, more specifically in the hiring , appointment, or career progression to these apical roles [e.g., 70 , 83 ], the majority of research of women’s roles dealt with compensation issues. Specifically, scholars highlight the pay-gap that still exists between women and men, both in general [e.g., 64 , 65 ], as well as referring to boards’ directors [e.g., 70 , 102 ], CEOs and executives [e.g., 69 , 103 , 104 ].

Finally, other scholars focused on the behavior of women when dealing with business. In this sense, particular attention has been paid to leadership and entrepreneurial behaviors. The former quite overlaps with dealing with the roles mentioned above, but also includes aspects such as leaders being stereotyped as masculine [e.g., 105 ], the need for greater exposure to female leaders to reduce biases [e.g., 106 ], or female leaders acting as queen bees [e.g., 107 ]. Regarding entrepreneurship , scholars mainly investigated women’s entrepreneurial entry [e.g., 108 , 109 ], differences between female and male entrepreneurs in the evaluations and funding received from investors [e.g., 110 , 111 ], and their performance gap [e.g., 112 , 113 ].

Education has long been recognized as key to social advancement and economic stability [ 114 ], for job progression and also a barrier to gender equality, especially in STEM-related fields. Research on education and gender equality is mostly linked with the topics of compensation , human capital , career progression , hiring , parenting and decision-making .

Education contributes to a higher human capital [ 115 ] and constitutes an investment on the part of women towards their future. In this context, literature points to the gender gap in educational attainment, and the consequences for women from a social, economic, personal and professional standpoint. Women are found to have less access to formal education and information, especially in emerging countries, which in turn may cause them to lose social and economic opportunities [e.g., 12 , 116 – 119 ]. Education in local and rural communities is also paramount to communicate the benefits of female empowerment , contributing to overall societal well-being [e.g., 120 ].

Once women access education, the image they have of the world and their place in society (i.e., habitus) affects their education performance [ 13 ] and is passed on to their children. These situations reinforce gender stereotypes, which become self-fulfilling prophecies that may negatively affect female students’ performance by lowering their confidence and heightening their anxiety [ 121 , 122 ]. Besides formal education, also the information that women are exposed to on a daily basis contributes to their human capital . Digital inequalities, for instance, stems from men spending more time online and acquiring higher digital skills than women [ 123 ].

Education is also a factor that should boost employability of candidates and thus hiring , career progression and compensation , however the relationship between these factors is not straightforward [ 115 ]. First, educational choices ( decision-making ) are influenced by variables such as self-efficacy and the presence of barriers, irrespectively of the career opportunities they offer, especially in STEM [ 124 ]. This brings additional difficulties to women’s enrollment and persistence in scientific and technical fields of study due to stereotypes and biases [ 125 , 126 ]. Moreover, access to education does not automatically translate into job opportunities for women and minority groups [ 127 , 128 ] or into female access to managerial positions [ 129 ].

Finally, parenting is reported as an antecedent of education [e.g., 130 ], with much of the literature focusing on the role of parents’ education on the opportunities afforded to children to enroll in education [ 131 – 134 ] and the role of parenting in their offspring’s perception of study fields and attitudes towards learning [ 135 – 138 ]. Parental education is also a predictor of the other related topics, namely human capital and compensation [ 139 ].

Decision-making.

This literature mainly points to the fact that women are thought to make decisions differently than men. Women have indeed different priorities, such as they care more about people’s well-being, working with people or helping others, rather than maximizing their personal (or their firm’s) gain [ 140 ]. In other words, women typically present more communal than agentic behaviors, which are instead more frequent among men [ 141 ]. These different attitude, behavior and preferences in turn affect the decisions they make [e.g., 142 ] and the decision-making of the firm in which they work [e.g., 143 ].

At the individual level, gender affects, for instance, career aspirations [e.g., 144 ] and choices [e.g., 142 , 145 ], or the decision of creating a venture [e.g., 108 , 109 , 146 ]. Moreover, in everyday life, women and men make different decisions regarding partners [e.g., 147 ], childcare [e.g., 148 ], education [e.g., 149 ], attention to the environment [e.g., 150 ] and politics [e.g., 151 ].

At the firm level, scholars highlighted, for example, how the presence of women in the board affects corporate decisions [e.g., 152 , 153 ], that female CEOs are more conservative in accounting decisions [e.g., 154 ], or that female CFOs tend to make more conservative decisions regarding the firm’s financial reporting [e.g., 155 ]. Nevertheless, firm level research also investigated decisions that, influenced by gender bias, affect women, such as those pertaining hiring [e.g., 156 , 157 ], compensation [e.g., 73 , 158 ], or the empowerment of women once appointed [ 159 ].

Career progression.

Once women have entered the workforce, the key aspect to achieve gender equality becomes career progression , including efforts toward overcoming the glass ceiling. Indeed, according to the SBS analysis, career progression is highly related to words such as work, social issues and equality. The topic with which it has the highest semantic overlap is role , followed by decision-making , hiring , education , compensation , leadership , human capital , and family .

Career progression implies an advancement in the hierarchical ladder of the firm, assigning managerial roles to women. Coherently, much of the literature has focused on identifying rationales for a greater female participation in the top management team and board of directors [e.g., 95 ] as well as the best criteria to ensure that the decision-makers promote the most valuable employees irrespectively of their individual characteristics, such as gender [e.g., 84 ]. The link between career progression , role and compensation is often provided in practice by performance appraisal exercises, frequently rooted in a culture of meritocracy that guides bonuses, salary increases and promotions. However, performance appraisals can actually mask gender-biased decisions where women are held to higher standards than their male colleagues [e.g., 83 , 84 , 95 , 160 , 161 ]. Women often have less opportunities to gain leadership experience and are less visible than their male colleagues, which constitute barriers to career advancement [e.g., 162 ]. Therefore, transparency and accountability, together with procedures that discourage discretionary choices, are paramount to achieve a fair career progression [e.g., 84 ], together with the relaxation of strict job boundaries in favor of cross-functional and self-directed tasks [e.g., 163 ].

In addition, a series of stereotypes about the type of leadership characteristics that are required for top management positions, which fit better with typical male and agentic attributes, are another key barrier to career advancement for women [e.g., 92 , 160 ].

Hiring is the entrance gateway for women into the workforce. Therefore, it is related to other workforce topics such as compensation , role , career progression , decision-making , human capital , performance , organization and education .

A first stream of literature focuses on the process leading up to candidates’ job applications, demonstrating that bias exists before positions are even opened, and it is perpetuated both by men and women through networking and gatekeeping practices [e.g., 164 , 165 ].

The hiring process itself is also subject to biases [ 166 ], for example gender-congruity bias that leads to men being preferred candidates in male-dominated sectors [e.g., 167 ], women being hired in positions with higher risk of failure [e.g., 168 ] and limited transparency and accountability afforded by written processes and procedures [e.g., 164 ] that all contribute to ascriptive inequality. In addition, providing incentives for evaluators to hire women may actually work to this end; however, this is not the case when supporting female candidates endangers higher-ranking male ones [ 169 ].

Another interesting perspective, instead, looks at top management teams’ composition and the effects on hiring practices, indicating that firms with more women in top management are less likely to lay off staff [e.g., 152 ].

Performance.

Several scholars posed their attention towards women’s performance, its consequences [e.g., 170 , 171 ] and the implications of having women in decision-making positions [e.g., 18 , 19 ].

At the individual level, research focused on differences in educational and academic performance between women and men, especially referring to the gender gap in STEM fields [e.g., 171 ]. The presence of stereotype threats–that is the expectation that the members of a social group (e.g., women) “must deal with the possibility of being judged or treated stereotypically, or of doing something that would confirm the stereotype” [ 172 ]–affects women’s interested in STEM [e.g., 173 ], as well as their cognitive ability tests, penalizing them [e.g., 174 ]. A stronger gender identification enhances this gap [e.g., 175 ], whereas mentoring and role models can be used as solutions to this problem [e.g., 121 ]. Despite the negative effect of stereotype threats on girls’ performance [ 176 ], female and male students perform equally in mathematics and related subjects [e.g., 177 ]. Moreover, while individuals’ performance at school and university generally affects their achievements and the field in which they end up working, evidence reveals that performance in math or other scientific subjects does not explain why fewer women enter STEM working fields; rather this gap depends on other aspects, such as culture, past working experiences, or self-efficacy [e.g., 170 ]. Finally, scholars have highlighted the penalization that women face for their positive performance, for instance when they succeed in traditionally male areas [e.g., 178 ]. This penalization is explained by the violation of gender-stereotypic prescriptions [e.g., 179 , 180 ], that is having women well performing in agentic areas, which are typical associated to men. Performance penalization can thus be overcome by clearly conveying communal characteristics and behaviors [ 178 ].

Evidence has been provided on how the involvement of women in boards of directors and decision-making positions affects firms’ performance. Nevertheless, results are mixed, with some studies showing positive effects on financial [ 19 , 181 , 182 ] and corporate social performance [ 99 , 182 , 183 ]. Other studies maintain a negative association [e.g., 18 ], and other again mixed [e.g., 184 ] or non-significant association [e.g., 185 ]. Also with respect to the presence of a female CEO, mixed results emerged so far, with some researches demonstrating a positive effect on firm’s performance [e.g., 96 , 186 ], while other obtaining only a limited evidence of this relationship [e.g., 103 ] or a negative one [e.g., 187 ].

Finally, some studies have investigated whether and how women’s performance affects their hiring [e.g., 101 ] and career progression [e.g., 83 , 160 ]. For instance, academic performance leads to different returns in hiring for women and men. Specifically, high-achieving men are called back significantly more often than high-achieving women, which are penalized when they have a major in mathematics; this result depends on employers’ gendered standards for applicants [e.g., 101 ]. Once appointed, performance ratings are more strongly related to promotions for women than men, and promoted women typically show higher past performance ratings than those of promoted men. This suggesting that women are subject to stricter standards for promotion [e.g., 160 ].

Behavioral aspects related to gender follow two main streams of literature. The first examines female personality and behavior in the workplace, and their alignment with cultural expectations or stereotypes [e.g., 188 ] as well as their impacts on equality. There is a common bias that depicts women as less agentic than males. Certain characteristics, such as those more congruent with male behaviors–e.g., self-promotion [e.g., 189 ], negotiation skills [e.g., 190 ] and general agentic behavior [e.g., 191 ]–, are less accepted in women. However, characteristics such as individualism in women have been found to promote greater gender equality in society [ 192 ]. In addition, behaviors such as display of emotions [e.g., 193 ], which are stereotypically female, work against women’s acceptance in the workplace, requiring women to carefully moderate their behavior to avoid exclusion. A counter-intuitive result is that women and minorities, which are more marginalized in the workplace, tend to be better problem-solvers in innovation competitions due to their different knowledge bases [ 194 ].

The other side of the coin is examined in a parallel literature stream on behavior towards women in the workplace. As a result of biases, prejudices and stereotypes, women may experience adverse behavior from their colleagues, such as incivility and harassment, which undermine their well-being [e.g., 195 , 196 ]. Biases that go beyond gender, such as for overweight people, are also more strongly applied to women [ 197 ].

Organization.

The role of women and gender bias in organizations has been studied from different perspectives, which mirror those presented in detail in the following sections. Specifically, most research highlighted the stereotypical view of leaders [e.g., 105 ] and the roles played by women within firms, for instance referring to presence in the board of directors [e.g., 18 , 90 , 91 ], appointment as CEOs [e.g., 16 ], or top executives [e.g., 93 ].

Scholars have investigated antecedents and consequences of the presence of women in these apical roles. On the one side they looked at hiring and career progression [e.g., 83 , 92 , 160 , 168 , 198 ], finding women typically disadvantaged with respect to their male counterparts. On the other side, they studied women’s leadership styles and influence on the firm’s decision-making [e.g., 152 , 154 , 155 , 199 ], with implications for performance [e.g., 18 , 19 , 96 ].

Human capital.

Human capital is a transverse topic that touches upon many different aspects of female gender equality. As such, it has the most associations with other topics, starting with education as mentioned above, with career-related topics such as role , decision-making , hiring , career progression , performance , compensation , leadership and organization . Another topic with which there is a close connection is behavior . In general, human capital is approached both from the education standpoint but also from the perspective of social capital.

The behavioral aspect in human capital comprises research related to gender differences for example in cultural and religious beliefs that influence women’s attitudes and perceptions towards STEM subjects [ 142 , 200 – 202 ], towards employment [ 203 ] or towards environmental issues [ 150 , 204 ]. These cultural differences also emerge in the context of globalization which may accelerate gender equality in the workforce [ 205 , 206 ]. Gender differences also appear in behaviors such as motivation [ 207 ], and in negotiation [ 190 ], and have repercussions on women’s decision-making related to their careers. The so-called gender equality paradox sees women in countries with lower gender equality more likely to pursue studies and careers in STEM fields, whereas the gap in STEM enrollment widens as countries achieve greater equality in society [ 171 ].

Career progression is modeled by literature as a choice-process where personal preferences, culture and decision-making affect the chosen path and the outcomes. Some literature highlights how women tend to self-select into different professions than men, often due to stereotypes rather than actual ability to perform in these professions [ 142 , 144 ]. These stereotypes also affect the perceptions of female performance or the amount of human capital required to equal male performance [ 110 , 193 , 208 ], particularly for mothers [ 81 ]. It is therefore often assumed that women are better suited to less visible and less leadership -oriented roles [ 209 ]. Women also express differing preferences towards work-family balance, which affect whether and how they pursue human capital gains [ 210 ], and ultimately their career progression and salary .

On the other hand, men are often unaware of gendered processes and behaviors that they carry forward in their interactions and decision-making [ 211 , 212 ]. Therefore, initiatives aimed at increasing managers’ human capital –by raising awareness of gender disparities in their organizations and engaging them in diversity promotion–are essential steps to counter gender bias and segregation [ 213 ].

Emerging topics: Leadership and entrepreneurship

Among the emerging topics, the most pervasive one is women reaching leadership positions in the workforce and in society. This is still a rare occurrence for two main types of factors, on the one hand, bias and discrimination make it harder for women to access leadership positions [e.g., 214 – 216 ], on the other hand, the competitive nature and high pressure associated with leadership positions, coupled with the lack of women currently represented, reduce women’s desire to achieve them [e.g., 209 , 217 ]. Women are more effective leaders when they have access to education, resources and a diverse environment with representation [e.g., 218 , 219 ].

One sector where there is potential for women to carve out a leadership role is entrepreneurship . Although at the start of the millennium the discourse on entrepreneurship was found to be “discriminatory, gender-biased, ethnocentrically determined and ideologically controlled” [ 220 ], an increasing body of literature is studying how to stimulate female entrepreneurship as an alternative pathway to wealth, leadership and empowerment [e.g., 221 ]. Many barriers exist for women to access entrepreneurship, including the institutional and legal environment, social and cultural factors, access to knowledge and resources, and individual behavior [e.g., 222 , 223 ]. Education has been found to raise women’s entrepreneurial intentions [e.g., 224 ], although this effect is smaller than for men [e.g., 109 ]. In addition, increasing self-efficacy and risk-taking behavior constitute important success factors [e.g., 225 ].

Finally, the topic of sustainability is worth mentioning, as it is the primary objective of the SDGs and is closely associated with societal well-being. As society grapples with the effects of climate change and increasing depletion of natural resources, a narrative has emerged on women and their greater link to the environment [ 226 ]. Studies in developed countries have found some support for women leaders’ attention to sustainability issues in firms [e.g., 227 – 229 ], and smaller resource consumption by women [ 230 ]. At the same time, women will likely be more affected by the consequences of climate change [e.g., 230 ] but often lack the decision-making power to influence local decision-making on resource management and environmental policies [e.g., 231 ].

Research gaps and conclusions

Research on gender equality has advanced rapidly in the past decades, with a steady increase in publications, both in mainstream topics related to women in education and the workforce, and in emerging topics. Through a novel approach combining methods of text mining and social network analysis, we examined a comprehensive body of literature comprising 15,465 papers published between 2000 and mid 2021 on topics related to gender equality. We identified a set of 27 topics addressed by the literature and examined their connections.

At the highest level of abstraction, it is worth noting that papers abound on the identification of issues related to gender inequalities and imbalances in the workforce and in society. Literature has thoroughly examined the (unconscious) biases, barriers, stereotypes, and discriminatory behaviors that women are facing as a result of their gender. Instead, there are much fewer papers that discuss or demonstrate effective solutions to overcome gender bias [e.g., 121 , 143 , 145 , 163 , 194 , 213 , 232 ]. This is partly due to the relative ease in studying the status quo, as opposed to studying changes in the status quo. However, we observed a shift in the more recent years towards solution seeking in this domain, which we strongly encourage future researchers to focus on. In the future, we may focus on collecting and mapping pro-active contributions to gender studies, using additional Natural Language Processing techniques, able to measure the sentiment of scientific papers [ 43 ].

All of the mainstream topics identified in our literature review are closely related, and there is a wealth of insights looking at the intersection between issues such as education and career progression or human capital and role . However, emerging topics are worthy of being furtherly explored. It would be interesting to see more work on the topic of female entrepreneurship , exploring aspects such as education , personality , governance , management and leadership . For instance, how can education support female entrepreneurship? How can self-efficacy and risk-taking behaviors be taught or enhanced? What are the differences in managerial and governance styles of female entrepreneurs? Which personality traits are associated with successful entrepreneurs? Which traits are preferred by venture capitalists and funding bodies?

The emerging topic of sustainability also deserves further attention, as our society struggles with climate change and its consequences. It would be interesting to see more research on the intersection between sustainability and entrepreneurship , looking at how female entrepreneurs are tackling sustainability issues, examining both their business models and their company governance . In addition, scholars are suggested to dig deeper into the relationship between family values and behaviors.

Moreover, it would be relevant to understand how women’s networks (social capital), or the composition and structure of social networks involving both women and men, enable them to increase their remuneration and reach top corporate positions, participate in key decision-making bodies, and have a voice in communities. Furthermore, the achievement of gender equality might significantly change firm networks and ecosystems, with important implications for their performance and survival.

Similarly, research at the nexus of (corporate) governance , career progression , compensation and female empowerment could yield useful insights–for example discussing how enterprises, institutions and countries are managed and the impact for women and other minorities. Are there specific governance structures that favor diversity and inclusion?

Lastly, we foresee an emerging stream of research pertaining how the spread of the COVID-19 pandemic challenged women, especially in the workforce, by making gender biases more evident.

For our analysis, we considered a set of 15,465 articles downloaded from the Scopus database (which is the largest abstract and citation database of peer-reviewed literature). As we were interested in reviewing business and economics related gender studies, we only considered those papers published in journals listed in the Academic Journal Guide (AJG) 2018 ranking of the Chartered Association of Business Schools (CABS). All the journals listed in this ranking are also indexed by Scopus. Therefore, looking at a single database (i.e., Scopus) should not be considered a limitation of our study. However, future research could consider different databases and inclusion criteria.

With our literature review, we offer researchers a comprehensive map of major gender-related research trends over the past twenty-two years. This can serve as a lens to look to the future, contributing to the achievement of SDG5. Researchers may use our study as a starting point to identify key themes addressed in the literature. In addition, our methodological approach–based on the use of the Semantic Brand Score and its webapp–could support scholars interested in reviewing other areas of research.

Supporting information

S1 text. keywords used for paper selection..

https://doi.org/10.1371/journal.pone.0256474.s001

Acknowledgments

The computing resources and the related technical support used for this work have been provided by CRESCO/ENEAGRID High Performance Computing infrastructure and its staff. CRESCO/ENEAGRID High Performance Computing infrastructure is funded by ENEA, the Italian National Agency for New Technologies, Energy and Sustainable Economic Development and by Italian and European research programmes (see http://www.cresco.enea.it/english for information).

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Twenty years of gender equality research: A scoping review based on a new semantic indicator

Paola belingheri.

1 Dipartimento di Ingegneria dell’Energia, dei Sistemi, del Territorio e delle Costruzioni, Università degli Studi di Pisa, Largo L. Lazzarino, Pisa, Italy

Filippo Chiarello

Andrea fronzetti colladon.

2 Department of Engineering, University of Perugia, Perugia, Italy

3 Department of Management, Kozminski University, Warsaw, Poland

Paola Rovelli

4 Faculty of Economics and Management, Centre for Family Business Management, Free University of Bozen-Bolzano, Bozen-Bolzano, Italy

Associated Data

All relevant data are within the manuscript and its supporting information files. The only exception is the text of the abstracts (over 15,000) that we have downloaded from Scopus. These abstracts can be retrieved from Scopus, but we do not have permission to redistribute them.

Introduction

Data collection

Text processing and keyword extraction

Classification of research topics

Evaluation of semantic importance

Overview of main topics

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In addition to the SBS score of the different topics, the network of terms they are associated to enables to gauge the extent to which their images (textual associations) overlap or differ ( Fig 4 ).

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The following sections describe the top 10 topics and their main associations in literature (see Table 3 ), while providing a brief overview of the emerging topics.

Compensation

Decision-making

Career progression

Performance

Several scholars posed their attention towards women’s performance, its consequences [e.g., 170 , 171 ] and the implications of having women in decision-making positions [e.g., 18 , 19 ].

Organization

Human capital

Emerging topics: Leadership and entrepreneurship

Research gaps and conclusions

Lastly, we foresee an emerging stream of research pertaining how the spread of the COVID-19 pandemic challenged women, especially in the workforce, by making gender biases more evident.

Supporting information

Acknowledgments.

Funding Statement

P.B and F.C.: Grant of the Department of Energy, Systems, Territory and Construction of the University of Pisa (DESTEC) for the project “Measuring Gender Bias with Semantic Analysis: The Development of an Assessment Tool and its Application in the European Space Industry. P.B., F.C., A.F.C., P.R.: Grant of the Italian Association of Management Engineering (AiIG), “Misure di sostegno ai soci giovani AiIG” 2020, for the project “Gender Equality Through Data Intelligence (GEDI)”. F.C.: EU project ASSETs+ Project (Alliance for Strategic Skills addressing Emerging Technologies in Defence) EAC/A03/2018 - Erasmus+ programme, Sector Skills Alliances, Lot 3: Sector Skills Alliance for implementing a new strategic approach (Blueprint) to sectoral cooperation on skills G.A. NUMBER: 612678-EPP-1-2019-1-IT-EPPKA2-SSA-B.

Data Availability

The intellectual structure of gender equality research in the business economics literature

Original Paper
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Published: 12 May 2023
Volume 18 , pages 1649–1680, ( 2024 )

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Francisco Díez-Martín ORCID: orcid.org/0000-0002-9888-833X 1 ,
Giorgia Miotto ORCID: orcid.org/0000-0002-0973-6597 2 &
Cristina Del-Castillo-Feito ORCID: orcid.org/0000-0002-7903-1365 1

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In both the public and private sectors, gender equality is a major issue faced by modern management. It is also a primary concern for the global sustainable development defined by the UN 2030 Agenda. Gender equality, as a research topic, has been explored from many different social, economic and political sides; nevertheless, gender equality in business economics is still a very promising research field since the everchanging global organisational environment requires frequent updates and polysemic approaches. The aim of this study is to identify and visualise the intellectual structure and dynamics of gender equality research on business economics literature through a bibliometric quantitative literature analysis. Our results found 12 main lines of research. They also identify the trending topics, sources of knowledge, and literature dissemination paths along these lines between 2001 and 2020. This work contributes to the field of gender issues by showing its intellectual structure and providing a research agenda and identifying future research lines and gaps in the area.

What is Qualitative in Research

Defining csr: problems and solutions.

Women’s entrepreneurship and culture: gender role expectations and identities, societal culture, and the entrepreneurial environment

Avoid common mistakes on your manuscript.

1 Introduction

Gender equality is a major issue in modern management, both in the public and private sectors (Báez et al. 2018 ), and it is a primary concern for the global sustainable development defined by the UN 2030 Agenda (Miotto et al. 2019 ). Gender equality, as a research topic, has been explored from many different social, economic and political perspectives; nevertheless, gender equality in business economics is still a very promising research field since the everchanging global organisational environment requires frequent updates and polysemic approaches (Belingheri et al. 2021 ). The more recent research topics on gender equality in business economics focus on women on boards of directors (Nguyen et al. 2020 ), salary gaps (Wang et al. 2019 ), risk-taking and financial performance impacts (Baixauli-Soler et al. 2017 ; Papanastasiou and Bekiaris 2020 ), CSR and information disclosure (Pucheta-Martínez et al. 2021 ), and family businesses (Kubíček and Machek 2019 ; González et al. 2020 ).

The increasing number of publications on gender issues makes it difficult to monitor the evolution of this field of research. Knowledge accumulation reduces the assimilation capacity of researchers, making it difficult to keep up to date. This has led to the elaboration of several literature reviews on gender issues during the twenty-first century. Most of these literature reviews are focused on the following main topics: gender and entrepreneurship (Moreira et al. 2019 ), women on boards of directors (Terjesen et al. 2009 ; Cabrera-Fernández et al. 2016 ; Kent Baker et al. 2020 ; Nguyen et al. 2020 ), women in international business (Bullough et al. 2017 ), and gender and corporate social responsibility (Amorelli and García-Sánchez 2021 ). We would also like to highlight a literature review about gender equality in business from 2011 that analyses the research in this field from 1995 to 2010 (Broadbridge and Simpson 2011 ).

These literature reviews are focused on specific topics; nevertheless, there is a lack of a multidisciplinary and interconnected overview of the gender equality field that may deeply understand the cause and effect of the different issues involved (Kirsch 2018 ). Existing literature reviews fail to provide a comprehensive, clear picture of what has been studied thus far and, therefore, the most relevant and promising future research lines should occur in this area (Belingheri et al. 2021 ).

In addition, some key issues in understanding the state of the art in this field of research have not been solved, mainly due to the qualitative nature of previous research. Furthermore, several recent studies have not been included in any generic bibliographic analysis about gender issues in business. These previous investigations identify the main lines of research on gender issues; nevertheless, there is no study that classifies the intellectual structure of the research field, the trends that have caught the attention of researchers, or the investigations that have facilitated the dissemination of knowledge connecting different lines of research. The intellectual structure definition is a comprehensive analysis of the domain of a study field; it is a structured way to define the boundaries and the map of discipline (Hota et al. 2020 ).

Knowing the intellectual structure of the field is key to defining research objectives that contribute to current studies, helping to incorporate new research areas into the field, and defining a relevant and updated research agenda (Carayannis et al. 2021 ). Bibliometric techniques are designed to achieve this purpose: systematically design and visualise the intellectual structure and mapping of a research field (Donthu et al. 2021 ; Silva et al. 2021 ). Unlike qualitative literature reviews, such as systematic reviews, bibliometric methods apply quantitative criteria to analyses large amounts of information and to discover knowledge networks and their structure (Zupic and Cater 2015 ). In addition, this methodology reduces the subjectivity grade of qualitative research associated with researcher bias.

To date, a nonbibliometric literature review of gender equality in business economics has been performed. Previous researchers, such as Broadbridge and Simpson ( 2011 ), performed a qualitative literature review, whereas all other literature analyses focused on specific topics linked to gender issues. Taking into consideration the need to improve the theoretical framework of gender equality in business (Hong et al. 2020 ), the aim of this study is to identify and visualize the intellectual structure and dynamics of gender equality research in the business economics literature and academic field. The research questions we would like to answer are as follows:

RQ1. Which are the most relevant research topics in the gender equality field in the business economics discipline?

RQ2. What are the most influential documents in the field of gender equality in business economics?

RQ3. What are the sources of knowledge on gender equality in business economics?

RQ4. How has gender equality research in business economics evolved in the last twenty years?

RQ5. How are the different topics related to gender equality interconnected?

RQ6. Which are the most relevant topics that will define the future research agenda in this field?

The novelty of this study lies in these specific aspects. First, for the first time in this knowledge area, we use a bibliometric method suitable to review a large corpus of documents using a quantitative technique able to perform an objective and unbiased analysis that provides accountable and trustworthy data (Donthu et al. 2021 ; Kumar et al. 2022 ). Second, we provide a holistic perspective of gender equality in the business economics field, avoiding a focus on only one issue, broadening the spectrum of the research and allowing a wider, more inclusive and multidisciplinary assessment (organisational behaviour, people management, legitimacy, etc.). Third, we highlighted the connections of the entire research field of gender equality studies in the business economics literature. Fourth, we define an update and analytic state of the art in terms of gender equality in business economics, and we propose a future, relevant and useful research agenda.

This document is organised as follows: the next section explains the methodology, and we describe the bibliometric techniques and concepts used. Afterword, the results section explains the main lines of research on the field, trends and connections. Finally, the results are discussed, and a research agenda is suggested.

2 Methodology

The study of the intellectual structure of gender equality research in the business economics literature was carried out using bibliometric data. To do so, this study adopts methodological procedures similar to those of previous bibliometric research in the field (e.g. Kumar et al. 2022 ) and implements the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) protocol, which consists of three major stages: article assembling, arranging and assessing (Paul et al. 2021 ).

2.1 Assembling

To assemble the corpus of articles on the defined research field, we identify the search keywords related to gender equality in the business economics literature. These keywords are included and organised into the following search string: “gender diversity" or "gender gap" or “gender equality” or “gender parity” or “gender equity”. These search keywords have been chosen taking into consideration previous research on gender equality that refer to all these topics as highly linked and related to an equal sharing of opportunities of progress, properties, paid work, money, decision-making power and time management between men and women (Furlotti et al. 2019 ; Miotto and Vilajoana-Alejandre 2019 ; Mehng et al. 2019 ). These concepts are also included in international reports, indices and institutional policies such as “The 2019 Report on Equality between Women and Men in the European Union” (European Commission 2019 ), the “Sustainable Development Goal 5” indicators (United Nations 2019 ), the “Gender Development Index” (United Nations Development Programme 2020 ), the “Gender Empowerment Measure” (United Nations Development Programme 2020 ) and the “Global Gender Gap Report” (GGI) (World Economic Forum 2019 ).

We use the abovementioned search string through the Web of Science (WoS) document titles, abstracts, and keywords. Even if the Web of Science (WoS) includes les articles tan the Scopus database, in the business economics fields, the percentage of unique and overlapping citations in Scopus and WoS are very similar (Martín-Martín et al. 2018 ). In addition, WoS is the most widely used database in the business economics literature (Zupic and Cater 2015 ), even if scientometric scholars have not yet decided which database is the best one (Pranckutė 2021 ). The search resulted in 22,263 documents.

2.2 Arranging

To arrange the corpus of articles returned from the assembling stage, we applied these filters in the WoS database: research area and publication year. We filtered the corpus of articles taking into consideration the business economic research area. This led to a reduced corpus of 3456 articles. We focused on articles published during the twenty-first century, and the timeframe of the study was 2001–2020. Although the first articles on this subject were published in 1984, from the twenty-first century, there was a high increase, and since then, more than 20 documents have been published annually. This timeframe definition led to a corpus consisting of 3316 documents. Finally, we identified 51 documents whose references were invalid or unreadable. This filter was important because the bibliometric analysis that we apply (co-citations) uses references as the source of analysis. Thus, the final research sample consisted of 3265 documents.

2.3 Assessing

This study applies a bibliometric analysis approach to assess a corpus of 2,816 articles on gender equality. Bibliometric methodology uses quantitative techniques with the aim of summarising large quantities of bibliometric data to show the intellectual structure of a research field (Donthu et al. 2021 ).

Inspired by previous bibliometric research on the business economics field (e.g., Díez-Martín et al. 2021 ), this study performs a bibliometric analysis using science mapping based on cocitation analysis in CiteSpace. Science mapping is a useful technique to explore the relationships between research constituents. It offers an organised visual representation of the characteristics and relationships among different studies in a scientific area (Mukherjee et al. 2022 ). As opposed to the manual analysis of quantitative and qualitative data, science mapping is a more efficient and objective methodology due to automated data analysis (Lim et al. 2022 ; Mukherjee et al. 2022 ).

Cocitation is a science mapping technique (Cobo et al. 2011 ; Mukherjee et al. 2022 ). It defines the frequency with which two papers ‘A’ and ‘B’ are cited together by a third paper ‘C’ (Small 1973 ). The idea behind this approach is that when two papers are cited together, they will probably share similar theories, assumptions, concepts or methods. Co-citation analysis is one of the most widely used methods for bibliometric research in social science disciplines (Zupic and Cater 2015 ) and is useful for uncovering relationships between cocited publications (foundational knowledge) (Mukherjee et al. 2022 ). Cocitation analysis highlights networks between different studies and can detect paradigm shifts, trends and schools of thought from a long-term perspective (e.g. Delgado-Alemany et al. 2022 ). To enrich the assessment of the bibliometric analysis, we used two network metrics (Donthu et al. 2021 ): burstness and betweenness centrality. These indicators provide additional valuable information about the network.

We used CiteSpace software for the cocitation analysis based on previous and well-known reviews of bibliometric software tools (Moral-Munoz et al. 2019 ). CiteSpace is a Java-based scientific detection and visualisation software that analyses the evolution of a research field through bibliometric co-citation (Chen 2006 ). Previous research in business economics used this software to understand the intellectual structure of a body of knowledge (Cruz-Suárez et al. 2020 ; Pascual-Nebreda et al. 2021 ).

Furthermore, this study provides a proposal of a future research agenda and research gaps based on the analysis of the most relevant topics and networks. The next section shows the findings of the study.

In the following two sections, we show the results that answer the research questions. In the first section, we show the main lines of research on gender equality in business economics (RQ1). This section also shows which are the most influential documents on gender equality, identifying the documents that have received more attention by the scholars of this area and that have become trending topics (RQ2). In addition, we describe the sources of knowledge of each main research line (RQ3). The second section describes the evolution of gender equality research in business economics in the last twenty years (RQ4). Furthermore, we highlight the research articles that are the node of connection between the different lines of research related to gender equality (RQ5). Finally, we propose a future research agenda, highlighting the most relevant topics that will define the future research lines in this field (RQ6).

3.1 Main lines of research

The main lines of research on gender issues in the business economics literature are shown in Table 1 (RQ1). We found 12 main research lines. Each research line is a cluster generated by CiteSpace and based on co-citations. To confirm that our clusters are homogeneous between themselves (cohesion) and differentiated from the others (separation), we use the silhouette value. This measure is used to identify the quality of a cluster configuration. Each cluster shows a Silhouette value greater than 0.845, above the recommended 0.7 (Chen et al. 2010 ). In addition, to measure the network quality, CiteSpace uses the modularity Q (from 0 to 1), which identifies the capability of a network to be decomposed into multiple components or clusters (Chen et al. 2010 ). In this study, the gender research network shows a reasonably well-coupled distribution of the clusters, reaching a Modularity Q of 0.7495.

Furthermore, Table 1 shows the number of trending topics of each line of research (RQ2). CiteSpace detects trends (burst documents) by applying the algorithm of Kleinberg ( 2003 ). The burstness identifies the most relevant documents that have been considered a source of a research trend, since they have received a high number of citations during a specific timeframe (Kim and Chen 2015 ; Hou et al. 2018 ). Supplementary material of Appendix 1 shows the results of the burst analysis, which illustrates the trending topics in the research field from 2001 to 2020.

The main lines of research on gender issues in the business economics literature are described below. The order of the description of the clusters is based on the size of the research line. Supplementary material of Appendix 2 identifies the documents included in each cluster. These documents represent the main sources of knowledge on gender equality in business economics (RQ3).

Cluster #1–Risk Management–is the greatest line of research in the field of gender in the business economics literature. It contains the largest number of referenced documents (93). This indicates that most research in this field has focused on the study of how gender risk profiles on boards of directors affect corporate financial performance. According to several authors, the lower risk-taking attitude and the higher risk aversion in firms run by female CEOs have lower leverage, less volatile earnings, and a higher chance of survival than otherwise similar firms run by male CEOs (Cumming et al. 2015 ; Faccio et al. 2016 ). In addition, the inclusion of women on boards of directors may improve fraud control and lower the impact of risky financial operations (Lucas-Pérez et al. 2015 ). Specifically, these papers analyse how gender board composition affects conservativism or risk tolerance in the decision-making process from the financial side (Berger et al. 2012 ; Palvia et al. 2015 ; Hutchinson et al. 2015 ; Bennouri et al. 2018 ). Gender differences and approaches in risk-taking tolerance affect corporate financial performance (Hoogendoorn et al. 2013 ), dividend pay-out policies (Ye et al. 2019 ), forecast accuracy and audit quality (Gul et al. 2013 ), increase ROA and ROE, and significantly decrease Tobin’s Q (Bennouri et al. 2018 ). This line of research has become the second main research trend in the field since 2017, based on seven burst documents (Supplementary material of Appendix 1 shows the results of the burst analysis, which illustrates trending topics in the research field during 2001–2020). Furthermore, the sources of knowledge in cluster #1 show an average year of publication in 2016. This cluster group shows recent and updated articles and research theories.

Cluster #2–Board Performance–represents the second largest areas of research, with more than 80 research papers. The mean year of the investigations on this cluster is 2015. Academics in this area have focused on analysing the relationship between gender diversity on boards of directors and firm performance (Lückerath-Rovers 2013 ; Chapple and Humphrey 2014 ). This line of research has become the main research trend in the field since 2017 (13 burst documents, see Supplementary material of Appendix 1). For example, they analyses the relevance of the morality or legitimacy of gender diverse boards from the point of view of stakeholders’ perceptions (Gregory-Smith et al. 2014 ; Perrault 2015 ). This cluster also analysed quota issues and their usefulness (Seierstad 2016 ) Characteristics such as firm size, type of business, industry, focus on innovation (Cabeza-García et al. 2021 ), size of the board (Strøm et al. 2014 ) or country gender parity have been studied to monitor the impact of gender board diversity and company outcomes (Post and Byron 2015 ).

Researchers on Cluster #3–Quotas and Tokenism–are focused on the presence of women in the companies’ boards of directors and, specifically, on the application of quotas to guarantee the presence of female directors. This practice has been internationally discussed and often adopted. Quota implementation has been considered formally, including quotas in the national legal framework, or informally, as a best practice in several private organizations (Adams and Funk 2012 ). In this context, researchers analyse whether and how organisations should ensure the presence of women in the boardroom and their real impact on governance and performance. (Adams and Ferreira 2009 ; Ahern and Dittmar 2012 ) . Research indicates that women on board performance improves when a critical mass of women is reached, since according to the tokenism literature, women may be reticent to advocate for other women in powerful positions (Torchia et al. 2011 ). For example, with the presence of at least three women and above, CSR indicators improve (Post et al. 2011 ). However, the appointment of women to a board driven by tokenism does not improve corporate performance and results (Abdullah 2014 ). This line of research has been the most trending topic of the field, particularly between 2010 and 2015 (39 burst papers). In fact, the average year of publication of the sources of knowledge in cluster #3 is 2010. Although it is one of the most prolific lines of research in this field and has been trending since 2005, the scientific advances published in this cluster are based on more consolidated and old papers. In other words, advances in this line of research are taking place at a slower rate than those from lines of research with a more recent average year of publication.

Cluster #4–CSR–refers to articles focused on how gender diversity on boards of directors influences CSR performance, strategies and policies. Specifically, the quality and quantity of nonfinancial information and data companies run by women are disclosed compared with organisations managed mainly by men. For example, several authors affirm that diverse and inclusive boards of directors tend to disclose more and better quality information about environmental impact (Frias-Aceituno et al. 2013 ; Amran et al. 2014 ; Liao et al. 2015 ) and that gender diversity has a positive influence on CSR. Researchers suggest that female talent can play a strategic role in enabling firms to manage their social responsibility and sustainable practices appropriately (Setó-Pamies 2015 ), and this CSR output may improve corporate legitimacy (Zhang et al. 2013 ; Díez-Martín et al. 2021 ) and firm value (Fernández-Gago et al. 2016 ). Nevertheless, gender diversity is a key factor for CSR performance if female members are not chosen due to quota allocation since the control of the board of directors’ assignment is negative for the CSR decision-making process (Hafsi and Turgut 2013 ). Others focus their research on finding insights into the link between board diversity and CSR, particularly the importance of linking gender diversity and CSR decision-making processes (Rao and Tilt 2016 ) and the minimum number of women (at least 3) that may make the difference in CSR strategy decisions (Fernandez-Feijoo et al. 2014 ). This is a relatively recent cluster, with an average year of publication of 2016. Seven research trends were created between 2001 and 2020.

Cluster #5–Team Diversity–represents a relatively wide area of research with 76 academic papers. The mean year of the papers in this cluster is 2006; therefore, it includes one of the oldest areas of research within the gender equality field and the most trending before 2010. It generated 15 burst papers between 2001 and 2010. This cluster addresses the topic of team diversity and team outcomes, the differences between group members and their effect on group performance (van Knippenberg and Schippers 2007 ). Researchers have analysed the characteristics or factors that lead firms to appoint more women to top management teams and their outcomes on a firm’s performance. Along this line, they identify the effects of team diversity on firm performance in diverse contexts (Horwitz and Horwitz 2007 ; Joshi and Roh 2009 ). For instance, female top managers’ qualifications are relevant for improving organisational performance (Smith et al. 2006 ). Academics study the elements that motivate the decisions of firms regarding including or not including women on their boards of directors, suggesting that fulfilling internal or external demands has a strong influence (Farrell and Hersch 2005 ; Francoeur et al. 2008 ) and that, in many cases, board diversity is influenced by a firm’s external business environment and requirements (Brammer et al. 2007 ). In other situations, gender diversity in top management positions transcends external factors (Krishnan and Park 2005 ).

Cluster #6–Pay Gap–focuses on the existence of the gender pay gap, the reasons for this issue, and the differences between industries, kind of organisation and countries (Blau and Kahn 2003 , 2006 ; Albrecht et al. 2003 ; Arulampalam et al. 2007 ). The mean year of publication of the sources of knowledge of this cluster is 2005, representing one of the oldest areas of research in the field. It was the second trending line of research before 2010 (10 burst papers). Researchers have shown that the gender gap typically widens towards the top of the wage distribution (the “glass ceiling” effect), and in a few cases, it also widens at the bottom (the “sticky floor” effect) (Albrecht et al. 2003 ; Arulampalam et al. 2007 ). According to these cluster’s papers, the cause of this gap has its rut in the rise of married female labour force participation that occurred in the last century, when several households must decide whether a married woman should work or not, and in most cases, a second salary was necessary to maintain the family (Blau and Kahn 2003 ; Greenwood et al. 2005 ; Attanasio et al. 2008 ). The segregation of women into lower‐paying occupations, industries, and establishments accounts for a sizable fraction of the sex gap in wages (Bayard et al. 2003 ). Nevertheless, women are promoted at roughly the same rate as men but may receive smaller wage increases upon promotion; women are just as likely as men to be promoted but find themselves stuck at the bottom of the wage scale for the new job class (Booth et al. 2003 ). The increase in educational levels contributed decisively towards greater wage inequality (Machado and Mata 2005 ), since higher levels of wage compression (measured in absolute or relative terms) are positively related to training (Almeida-Santos and Mumford 2005 ).

Cluster #7–Competitiveness–research is about the study of the differences between women and men when acting in a competitive environment (Croson and Gneezy 2009 ; Buser et al. 2017 ). There is evidence that demonstrates that women are less inclined to enter competition. They feel less comfortable in a highly competitive environment, and this attitude increases with age (Datta Gupta et al. 2013 ; Andersen et al. 2013 ). Researchers have explained this gender gap by stating that men are more overconfident (Niederle and Vesterlund 2005 ). This attitude affects and limits women’s career progress (Balafoutas and Sutter 2012 ) or the participation of women in science (Fryer and Levitt 2010 ; Moss-Racusin et al. 2012 ). This cluster is very useful for researchers seeking to justify differentiation in gender-biased career orientation and professional progress. Along this line, some results suggest that preferences over uncertainty can be just as important as preferences over competition in driving job-entry choices (Flory et al. 2015 ). This line of research has been the second most trending topic between 2010 and 2015 (24 burst papers). The average year of publication of the sources of knowledge in cluster #7 is 2011.

Researchers on cluster #8–Innovation–try to set a theoretical framework for the relationship between gender and innovation (Agnete Alsos et al. 2013 ) through the analysis of how gender diversity within R&D teams impacts firm innovation but also how gender policies aimed at creating, maintaining, and disrupting institutions (Lawrence et al. 2011 ). The number of papers within this cluster is 23; therefore, it is one of the smallest areas of study within the field. The mean year of the publications is 2011. The results show that innovation is more advanced in higher gender diverse teams (Van Dijk et al. 2012 ; Díaz-García et al. 2013 ). Additionally, the relation between gender and other types of diversity, such as age, education or ethnicity, are also studied when considering the effect on innovation (Østergaard et al. 2011 ). The average year of publication of the sources of knowledge in this cluster is 2011. This line of research generated 7 trending topics between 2010 and 2015.

Cluster #9–Wage Gap Reasons–focuses on the reasons that explain the gender wage gap. The average year of publication of the sources of knowledge in this cluster is 2015, and it generated 3 trending topics between 2010 and 2020. This cluster stresses the idea that the origin of this breach resides in the different roles between women and men in family management and the time dedicated to family care. While convergence between men and women in traditional human capital factors (education and experience) played an important role in the narrowing of the gender wage gap, these factors explain relatively little of the wage gap since women exceed men in educational attainment and have greatly reduced the gender experience gap (Blau et al. 2013 ). Nonetheless, labour-market experience remains an important factor in analysing female wages (Blau and Kahn 2017 ). Women are less likely to work in results-driven companies, with highly variable salaries linked to employees’ objective achievement. Furthermore, women receive only 90% of the firm-specific pay premiums earned by men, and this practice will contribute to the gender wage gap since women are less likely to work at high-paying firms or if women negotiate worse wage bargains than men (Card et al. 2016 ). The salary gender gap would be considerably reduced if firms did not economically reward individuals who laboured long hours, something that is very common, for example, in industries such as the corporate, financial, and legal worlds and less common in technology, science, and health (Goldin 2014 ). To explain women’s shorter time dedicated to work, researchers focus their attention on the analysis of family structure and management: motherhood and children’s education are two factors that explain why women’s income, in middle age, has a gap of up to 32% compared with men’s salary (Angelov et al. 2016 ). Motherhood is one of the most important factors of the gender salary gap (Adda et al. 2017 ). Studies show that, for example, the Motherhood delay leads to a substantial increase in earnings of 9% per year of delay, an increase in wages of 3%, and an increase in work hours of 6 (Miller 2011 ). Likewise, when a woman becomes more likely to earn more than a man, marriage rates decline. In couples where the wife earns more than the husband, the wife spends more time on household chores; moreover, those couples are less satisfied with their marriage and are more likely to divorce (Bertrand and Pan 2013 ).

Cluster # 10–Productivity–research is about gender and productivity. Progress in this line of research is slowing down. The average year of publication of the sources of knowledge in this cluster is 2011, and it generated 3 trending topics before 2010. According to these articles, women progress less and more slowly in their professional careers, and their salaries are lower than those of men for three main reasons: less advanced training, differences in career interruptions (specifically motherhood), and differences in weekly hours (specifically to take care of the kids) (Bertrand et al. 2010 ; Becker et al. 2010 ). The three of them are related to a lack of productivity. The cluster analyses the link between gender and productivity in several industries, environments and countries (Peterman et al. 2011 ; Kilic et al. 2015 ).

Cluster #11–TMT–is one of the smallest areas of research within the gender equality field, including only 9 papers. The mean year of the investigations is 2016; thus, it is one of the most recent topics among the updated research. Within this cluster, researchers explore the effect of female representation in top management teams (TMT) and firm performance (Schwab et al. 2016 ; Jeong and Harrison 2017 ). Several investigations focus on the effect of gender diversity in TMT and financial operations, such as initial public offerings or mergers and acquisitions (Parola et al. 2015 ; Quintana-García and Benavides-Velasco 2016 ). Additionally, the presence of female top managers is positively related to entrepreneurial outcomes in established firms, although these results are weakened in firms with many women among their employees since many times a female top manager is less likely to favour lower-level female employees, as her categorisation as a member of the TMT restricts gender-based favouritism (Lyngsie and Foss 2017 ). Moreover, aspects related to quotas on women on top management teams are also covered, identifying, for example, how the presence of a woman on a top management team (TMT) reduces the likelihood that another woman occupies a position on that team (Dezso et al. 2016 ).

Cluster # 12–Labour Force Access–is the oldest and smallest line of research in this field. The average year of publication of the sources of knowledge in this cluster is 2002. It analyses factors that have caused an increase in women's access to the labour market, and references the revolution that transformed women’s opportunities (Goldin 2006 ). Aspects such as fertility and motherhood are analysed: for example, birth control availability, such as the contraceptive pill, are considered key factors for increasing female employment (Goldin and Katz 2002 ). Moreover, women are currently more educated, attending college and graduate education (Jacob 2002 ; Charles and Luoh 2003 ), and marriage and motherhood ages are later, for example, as a result of the possibility of in vitro fecundation (Gershoni and Low 2021 )., These aspects reduce the gender gap in career achievement. For example, the growing presence of a new type of man–one brought up in a family in which the mother worked–has been a significant factor in the increase in female labour force participation over time (Fernandez et al. 2004 ). Social policies are also considered in the female labour force, and their results in different countries. Nevertheless, for all women around the world, attaining the combination of reproductive empowerment and decent work is a challenge. Career advancement is interrupted by childbearing (Petrongolo 2004 ) despite social protection policies (Finlay 2021 ).

3.2 Connection between lines of research: turning points

In the following section, we show the research network of gender issues in the business economics academic literature (Fig. 1 ). We describe the evolution of the field (RQ4), and we highlight the connections between the main lines of research from 2001 to 2020 (RQ5). To identify the nodes that connect the different research topics, we use betweenness centrality (Bc). This indicator quantifies the number of times that a node acts as the most direct bridge (along the shortest path) between two other nodes (Chen et al. 2009 ).

Research network on gender issues in the business economics literature (2001–2020)

To deeply comprehend the research network development, a diagonal observation perspective is recommended, from left to right. In this way, we can better understand how research on gender issues in the business economics literature has evolved. We can see that the research focus shifted from studies about the issues of women's access to the labour market (year 2002) to different topics such as risk management, firms’ performance and CSR.

During the first decade of the twenty-first century, studies on gender focused on analysing the factors that favour women's access to the labour market (cluster #12), the gender pay gap and its causes (cluster #6), and gender diverse working team performances (cluster #5). During these decades, the papers that have contributed the most to the research field, being the main intellectual bridges that connect different approaches in this field, are Arulampalam et al. ( 2007 ) and Smith et al. ( 2006 ). The first paper connects research between clusters #12 and #6 by bridging the gender pay gap and the factors conditioning access to the labour force and career progress, such as the provision of childcare (Bc = 0.13). The second analyses the effects of management diversity and female quotas in the corporate context (Bc = 0.19). This research shows that the positive effects of women in top management strongly depend on the qualifications of female top managers and not on their numbers or quotas, signalling a research diffusion path between clusters #5 and #3.

The second decade of the twenty-first century has seen a growth in the number of lines of research on gender issues. Researchers ponder the consequences of gender quotas and tokenism (cluster #3), relative to women’s productivity in the corporate environment, especially in management positions (cluster #10), and the effects on innovation (cluster #8). They also explore the role that competitiveness plays as a determinant of the gender gap (cluster #7). The research line about productivity is strictly linked to the gender pay gap (cluster #6), since it relates women’s performance and productivity with the salary gap. Nevertheless, the other research lines (#3, #8, #7) all converge into cluster #2 about women on boards and firm performance. Moreover, the most recent and updated research topics (#1, #4 and #11) are linked through cluster #2.

If we consider the evolution of gender topic research related to business economics, gender quotas and tokenism (#3) and woman on board performance (#2) represent the nodes and main line of connection of the actual knowledge network. On the one hand, it is observed that the research lines of the beginning of the century connect with cluster #3. At this stage, Adams and Ferreira (Adams and Ferreira 2009 ) research is a keystone of this cluster and of the whole network (Bc = 0.21). The article affirms that when gender diversity in boards of directors is regulated by female quotas or driven by tokenism, it does not ensure a higher level of efficiency and effectivity of the boards and does not necessarily improve firm performance. On the other hand, it is also observed that the most current lines of research are connected with cluster #2. The keystone article of this cluster is Lückerath-Rovers ( 2013 ), and it investigates the financial performance of Dutch companies both with and without women on their boards (Bc = 0.21). The research shows that the presence of women in top management is a logical consequence of a more innovative, modern, and transparent enterprise, and it may improve stakeholders’ management and reputation; nevertheless, it cannot prove that there is a positive relationship between gender board diversity and a firm’s economic and financial performance.

An interesting node that connects cluster #2 and cluster #7 is represented by Charness and Gneezy’s ( 2012 ) article that demonstrates that women are more conservative about investment, and they appear to be more financially risk averse than men (Bc = 0.10). A different attitude in terms of risk taking and competitiveness may positively and negatively affect companies’ performance if their management teams are more gender inclusive. Cluster #7 represents the link with cluster #9, where researchers, in addition to competitiveness, take into consideration and propose wage gap causes.

4 Research agenda

During the twenty-first century, research on gender issues in the business economics literature has largely advanced. This progress has led to broad and useful knowledge creation and spread, but at the same time, it has also revealed new research gaps that should be addressed. In this paper, we propose a future research agenda (RQ6) based on the actual context. To design this research agenda, we follow the same process as Díez-Martín et al. ( 2021 ). We identified the most relevant and existing gaps based on our reading of the newest trending topic documents (i.e., newest burst documents) and reflection of extant gaps under each major theme.

In Table 2 , we describe the proposed research agenda, identifying the main topics, research questions and primary authors and sources of knowledge.

4.1 Beyond women on board and TMT: the middle management

Many studies analyse the influence of the presence of women on boards of directors on their effects on firm performance (Jane Lenard et al. 2014 ; Liu et al. 2014 ; Nguyen et al. 2020 ). The evolving role of women in society and the application of female quotas imposed by several countries have led researchers to dig into these aspects (Bøhren and Staubo 2014 ; Bertrand et al. 2018 ). Nevertheless, there are very few studies about women in middle management, since the literature on business economics has not yet addressed this topic, probably because it is much easier to obtain information about boards of directors, as the disclosure of this information is mandatory by law in most countries (Kent Baker et al. 2020 ). We learned much about gender diversity on boards and top management; nevertheless, research should better understand the presence and effect of gender diversity in middle management (Ferrary and Déo 2022 ), which is important for daily firm management. We should understand if and how gender diversity in middle management also affects firm performance if inclusive teams are more productive, committed, innovative, risk-taking biased, socially responsible, and accountable. We should examine whether diversity in middle management can make the difference, positively or negatively, or if there are no relevant differences, since strategic decisions depend only on top management teams. Thus, we encourage future research to pursue a better understanding of the role of women in middle management:

What is the gender composition of firms’ middle management?

What are the effects of gender diversity in middle management?

How does gender diversity in middle management affect firm performance?

Are inclusive teams more productive, committed, innovative, risk-taking biased, socially responsible, or accountable?

Can diversity in middle management make the difference, positively or negatively, or there are no relevant differences, since strategic decisions depend only on top management teams?

4.2 Human resources and people management

Few research studies on gender diversity are related to people management. For example, previous studies show that women in the recruiting process tend to increase board gender diversity (Hutchinson et al. 2015 ) or that flexible working schedules and compensation improve firms’ gender inclusion (Goldin 2014 ; Nguyen et al. 2020 ). Nevertheless, there are several aspects related to human resources management that have not yet been covered, such as recruiting process practices and gender diversity; salary gender gap from the people management perspective; working conditions and gender equal career opportunities; the effect of tokenisation at all firm management levels; and external and internal factors that improve or decrease gender equality in management positions. Therefore, we encourage future research to answer the following questions:

How is gender diversity managed and led in recruiting process practices?

How is the gender salary gap managed and dealt with from the people management perspective?

How are human resources departments dealing with the working conditions of women and gender-equal career opportunities?

How can we mitigate the effect of tokenization at all firm management levels?

What are the external and internal factors that improve or decrease gender equality in management positions?

4.3 Organisational behaviour

There are mechanisms that mediate the relationship between gender diversity and firm outcomes (Lucas-Pérez et al. 2015 ). Organisational behaviour variables may affect gender equality teams and firm outcomes (Cabrera-Fernández et al. 2016 ). Corporate leadership and internal communication have a moderating effect on gender issues (Adams 2016 ; Fernández-Temprano and Tejerina-Gaite 2020 ). Future research should focus on the main organisational internal dimensions that may improve gender inclusion and firm performance at the same time (Saitova and di Mauro 2021 ). What are the main soft skills and practices that increase internal gender equality and external competitiveness? At this point, we posit the following research questions:

How does internal organisational management improve gender inclusion and firm performance at the same time?

What are the main soft skills and practices that increase internal gender equality and external competitiveness?

4.4 What about customers?

According to stakeholder management and institutional theory, gender equality policies are very much appreciated and are considered a commitment to the common good (García-Sánchez et al. 2020 ). This alignment with stakeholders’ expectations increases corporate legitimacy (Díez-Martín et al. 2021 ) and access to economic and human resources (Blanco-González et al. 2020 ). Research studies have focused mainly on the impact on specific stakeholders such as shareholders and employees (Perrault 2015 ), ignoring customers. Future investigations should analyse whether gender policies may influence customer behaviours such as purchase intention, brand advocacy, and brand perceived ethicality. Applying behaviour theories (Hegner et al. 2017 ), researchers could understand the relationship between gender diversity and customer behaviour from a different and novel approach. Therefore, we propose the following research questions for future undertaking:

Do gender equality policies influence customer behaviours such as purchase intention, brand advocacy, and brand perceived ethicality?

Is there a relationship between gender diversity in organisations and customer behaviour?

4.5 Wage gap reasons

The gender salary gap is still a global issue (Wang et al. 2019 ). In most Western countries, for example, access to the labour market and to higher education are variables that may not affect the salary gap as in the past since women are as educated as men (Kleinjans et al. 2017 ). Many factors have recently been considered key to explaining the salary gap, such as family caring, motherhood, cultural prejudice, and self-esteem. Nevertheless, a deeper analysis of these aspects should be performed to overcome these obstacles and reduce the salary gap. Examples include children’s education about equal responsibility in family caring, use of technology to improve flexible working schedules for parents, performance evaluation based on results and not on working hours, cultural prejudice that avoids women’s career progress and gender-equal work-life balance opportunities. Therefore, we propose the following research questions:

Does access to the labour market affect the salary gap?

Does access to higher education affect the salary gap?

Which other variables may affect the salary gap: family caring, motherhood, cultural prejudice, self-esteem, etc.

Could children’s education about equal responsibility in family caring reduce the salary gap in the future?

Does the use of technology to improve flexible working schedules for parents, performance evaluation based on results and not on working hours, and a gender-equal work-life balance opportunity help reduce the salary gap?

4.6 Tangible and intangible assets

Most gender issues research focuses on corporate tangible assets such as financial performance and ROI (Reddy and Jadhav 2019 ). Nevertheless, there are very important intangible assets, such as reputation, that may be a very relevant source of competitive advantage (Miotto et al. 2020 ). There are several studies about women’s inclusion on boards of directors and their impact on the media and public opinion (de Anca and Gabaldon 2014 ) and on firm reputation (Bear et al. 2010 ; Navarro-García et al. 2020 ), but there is an unfulfilled research gap about other gender issues in business economics and their impact on external stakeholders’ opinions and expectations. Gender equality policies, if properly communicated, may be a source of positive reputation and corporate legitimacy (Blanco-González et al. 2020 ). In this regard, we call for new research on how organisational gender issue management improves tangible and intangible corporate assets:

Does women’s inclusion on boards of directors have a positive impact on the media, public opinion and firm reputation?

Does gender equality policies impact external stakeholders’ opinions and expectations?

May gender equality policies, if properly communicated, be a source of positive reputation and corporate legitimacy?

How may organisational gender issues management improve corporate reputation and legitimacy?

4.7 Gender in corporate governance and business ethics

Gender diversity and inclusion, specifically about boards of directors’ membership, is one of the most topical corporate governance issues (Nguyen et al. 2020 ). In terms of corporate governance, it has been demonstrated that there are ethical implications that force women to be included in top management positions (Kagzi and Guha 2018 ) and that female corporate leaders are more respectful of the legal framework and behave more ethically than men, decreasing the firm’s negative exposure (Ben-Amar et al. 2017 ). Nevertheless, there are few studies that analyse the relationship between gender issues management and business ethics from a broad and comprehensive perspective. Future research could focus on perceived organisational ethicality and business ethics from a firm gender equality strategy and policies perspective:

What is the relationship between gender issues management and business ethics?

Are perceived organisational ethicality and business ethics connected with the firm gender equality strategy and policies perspective and how?

4.8 Size and geography matter

Many studies have focused on multinational companies and large corporations. These studies have not considered small and medium-sized enterprises. In addition, few studies have compared different countries and the heterogeneous contexts that may affect gender issues, for example, in terms of legal framework, good governance recommendations and women rights development status. Some countries institutionalize gender quotas in private companies, while in others, girls’ right to education is still not ensured.

The priorities in gender issues of some nations are different from others due to institutional and socioeconomic differences (Post and Byron 2015 ). In this multicultural environment, future researchers should test previously raised hypotheses in new contexts. They should take into consideration different kinds of companies: public and private, large and small, in different industries, and from more and less developed countries. The creation of collaborative networks of researchers from different countries working on gender issues in business economics could be a useful and important project to carry out soon. In this regard, we call for new research on:

How are gender issues considered and managed in small- and medium-sized companies?

Is the kind of industry an important variable in terms of gender equality policies?

Are the priorities in gender issues of some nations different from others due to institutional and socioeconomic differences?

In the actual multicultural environment, future researchers should test previously raised hypotheses in new contexts.

How is gender equality perceived in different kinds of organisations, such as public and private, large and small, in different industries, and from more and less developed countries?

How are gender issues in business economics perceived and addressed in different countries?

5 Conclusions

This paper defines and visualises the intellectual structure of the research field of gender in the business economics literature from 2001 to 2020. The intellectual structure definition is a comprehensive analysis of the domain of a study field; it is a structured way to define the boundaries and the map of a discipline (Hota et al. 2020 ; Silva et al. 2021 ; Carayannis et al. 2021 ). The intellectual structure mapping answers the paper’s research question, providing information and details about which are the most relevant research topics in the gender equality field in the business economics discipline? (RQ1. What are the most influential documents in the field of gender equality in business economics? (RQ2.) What are the sources of knowledge on gender equality in business economics? (RQ3.) How has gender equality research in business economics evolved in the last twenty years? (RQ4.) How are the different topics related to gender equality interconnected? (RQ5.) Which are the most relevant topics that will define the future research agenda in this field? (RQ6.)

To date, there are no other studies of this nature for this research field. Our research complements previous qualitative literature reviews applying a quantitative analysis of large volumes of documents. In addition to the use of a systematic and objective bibliometric methodology, the novelty of this research stands on the broader scope and perspective of the analysis of the research field. Previous papers have focused mainly on specific topics, such as women on boards of executives (Kent Baker et al. 2020 ) or gender entrepreneurship (Moreira et al. 2019 ).

This research is based on the quantitative accuracy of a bibliometric review of more than 3000 documents, and its main contribution is the identification of the main research lines, trends and evolution, knowledge sources and extent of gender issues research on business economics. We visualise how the knowledge of this research field is organised, identify past and future challenges, and propose a future relevant research agenda.

The study identifies the most important sources of knowledge on gender issues in business economics from 2001 to 2020 (Supplementary material of Appendix 2). The quantitative applied methodology ensures a high level of objectivity and academic consistency, which provides unique value to the study, being the first one in this field. Previous literature reviews did not achieve such a broad intellectual scope since they were limited by the use of a qualitative and subjective approach (Broadbridge and Simpson 2011 ) or because they focused only on specific topics, such as gender board diversity (Kent Baker et al. 2020 ). The paper organization based on research lines is very useful for researchers that may use this structure as a starting point for their investigations. Moreover, practitioners may have an organised and clear idea of the trending topics about gender issues in business economics and a guideline to follow up on these matters.

Our results highlight the main topics and challenges in gender issues research from 2001 to 2020. We could summarise these topics in the following questions: which are the main factors that influence women's access to work? In what environments, industries, sectors and countries does the gender salary gap persist, and what are the main causes of this issue? Are quota policies helpful? How does gender diversity influence company performance and results? How does gender diversity in management positions affect CSR policies, information disclosure and corporate accountability? How does gender inclusion affect innovation and productivity? How do intrinsic variables (risk profile, competitiveness) influence firms’ results?

These topics have been combined and organized into 12 large research areas, shaping the intellectual structure of gender equality in the business economics academic field. Some of these lines of research confirm previous literature review results and conclusions. For example, researchers have always focused their attention on women on boards’ performance (Cabrera-Fernández et al. 2016 ; Kent Baker et al. 2020 ; Khatib et al. 2021 ), as shown in cluster #2, and this is one of the most relevant topics in the gender issues field. Top managers and CEOs could use this research to make relevant decisions about their boards of executive composition, taking into consideration the impact of gender diversity and inclusion.

Moreover, researchers have worked to analyse the relationship between gender diversity and CSR policies and information disclosure (Pucheta-Martínez et al. 2018 ; Amorelli and García-Sánchez 2021 ), as shown in #4. The gender bias in risk taking attitude and management (cluster #1) have been represented in prior literature reviews and are found to be key factors in entrepreneurship (Moreira et al. 2019 ). Managers should take into consideration the different gender leadership styles according to the type of industry and strategy. For example, some sectors or positions need a riskier style of decision-making progress, while other environments may need a different kind of emotional and social intelligence in their management teams.

Nevertheless, as a novelty of this bibliometric analysis, we identify new relevant research areas such as the wage gap #9, the effect of the gender differences in competitiveness #7, the consequence of a different risk management on firms’ performance #1 (actually the broadest area of research), or the results of gender diversity, not only in the boards of directors but also in the middle management teams #12. To date, middle management has not been considered as important in terms of gender inclusion; nevertheless, in the current competitive and uncertain environment, middle positions need to be cared for as much as top management.

The originality of this bibliometric review also stands on the identification of the main nodes of the knowledge network and connections within gender issues in business economics research. The turning points (Bc papers) highlight the intellectual transition between different research areas. They are useful for enhancing new multidisciplinary and multidimension academic findings and managerial implications.

The burst paper identification (Supplementary material of Appendix 1) highlights the most relevant papers, i.e., the ones that truly focused most of the researchers’ attention and interest during a specific timeframe. We could feature the evolution and challenges that researchers have experienced in this field. In the first two decades of the twenty-first century, research trending topics focused on understanding the reason for the gender pay gap (Blau and Kahn 2003 ; Arulampalam et al. 2007 ). Since 2010, there has been a proliferation of new topics: gender quotas (Nielsen and Huse 2010 ; Torchia et al. 2011 ), performance analysis based on gender (Dezsö and Ross 2012 ), women and innovation (Díaz-García et al. 2013 ), and women and competitiveness (Niederle et al. 2013 ). During the end of the second decade of the twenty-first century, researchers focused their effort to better understand gender firms’ performance based on the gender perspective, specifically to comprehend the existence of very different and, sometimes, contradictory academic results and findings on this topic (Seierstad 2016 ). A very interesting paper about gender and competitiveness is considered a tipping point, identifying the different risk-taking attitudes and management styles between men and women as key factors that may affect organizational competitiveness and performance (Hutchinson et al. 2015 ). Scholars have recently pointed out that during an uncertainty situation, men and women use different mindsets when assessing organisations (Díez-Martín et al. 2022 ). Managers should be aware of the importance of gender inclusivity in their teams since the teams’ composition and dynamics affect companies’ performance and competitiveness.

The analysis of the burst papers also highlights that researchers have overcome some of the main challenges in gender issues since the beginning of the twenty-first century. Currently, research on the gender pay gap and women's access to the labour market is not very relevant. Researchers focus on the gender effects on firms’ performance and their causes.

This research provides important implications for business managers, policymakers, and academics. For business managers, improving their knowledge about the effect of integrating gender policies in businesses can encourage them to develop and implement projects to foster corporate operations and improve efficiency. The broader scope and perspective of our analysis enables the improvement of business decisions related to several aspects. Regarding human resources management, the research has demonstrated gender-biased behaviour that can have an impact on organisations´ performance. Examples include risk-taking attitude, risk tolerance, risky financial operations, fraud control, chance of survival, and behaviour under competitive or uncertainty environments. This knowledge could be considered in employee selection processes or talent management. In addition, considering the effect that diversity in teams has on firm performance (more gender-diverse teams enhance innovation, tend to disclose more and better-quality information about environmental issues, and have a positive influence on CSR), managers could build and manage teams in a more efficient manner. Moreover, business managers that aim to attract diverse talent should consider that women are less motivated to work in results-driven companies based on objective achievement. Regarding stakeholder management, managers should assume that gender equality management in their company could generate implications related to external perceptions about corporate identity and image. Both variables are evaluated by stakeholders who issue legitimacy assessments.

Policymakers have an important role in ensuring gender equality in every area. In the business field, research papers show that inequality in terms of gender is decreasing. However, a salary gap still exists. This situation involves the need to implement policies to support and incentivise gender equality in companies. Nevertheless, many initiatives implemented by policymakers have not achieved the expected results; in fact, many policies related to the establishment of quotas have been questioned and have proven less efficient in reducing the gender gap. Coercive measures are not reaching the required results. In contrast, the most successful policies have resulted from transformative events based on technological innovations that have improved the lives of families. Policymakers could focus their initiatives and resources on enhancing technological innovations with this purpose. Family (management and care) appears to be a key reason for some gender inequalities, such as the wage gap. Thus, policymakers could favour the development of an institutional context that cares for family issues and that could influence organisational behaviour.

For scholars, this research enables us to improve the existing knowledge of gender equality in the business field. The research agenda may be used for the constitution of new theoretical frameworks, as a guide for researchers in future projects, a guideline for relevant topics, a source of innovative methodology, and as a list of potential future collaborators.

Finally, this study presents some limitations, as with any bibliometric review based on co-citations. The analysis is comprehensive, but the chosen filters may limit the scope and dimension of the database. Co-citation analysis is biased on older research, which is more likely to be co-cited. Although the results are obtained through quantitative indicators, researchers’ interpretations may affect the study’s results and conclusions.

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Díez-Martín, F., Miotto, G. & Del-Castillo-Feito, C. The intellectual structure of gender equality research in the business economics literature. Rev Manag Sci 18 , 1649–1680 (2024). https://doi.org/10.1007/s11846-023-00671-8

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On Economic Inequality

Master of Trinity College, Cambridge

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This book, which was first published in 1973, presents a systematic treatment of the conceptual framework as well as the practical problems of the measurement of economic inequality. Alternative approaches are evaluated in terms of their philosophical assumptions, economic content, and statistical requirements. In a new annexe added in 1997, which is as large as the original book, Amartya Sen, jointly with James Foster, critically surveys the literature that followed the publication of the first edition of the book, and evaluates the main analytical issues in the appraisal of economic inequality and poverty. The technical and non‐technical sections of the book are not presented separately, but it is possible to skip or skim through the formal sections and go directly from the intuitive presentation of the axioms to the intuitive explanation of the results.

Professor of Economics

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The economic gains from equity

Final Paper by Buckman et al
Comment by Fortin
Comment by Hurst
General Discussion
Data & Programs

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Shelby r. buckman , shelby r. buckman graduate student - stanford university laura y. choi , laura y. choi vice president, community development - federal reserve bank of san francisco mary c. daly , and mary c. daly president and chief executive officer - federal reserve bank of san francisco lily m. seitelman lily m. seitelman graduate student - boston university discussants: nicole fortin and nicole fortin professor - university of british columbia erik hurst erik hurst frank p. and marianne r. diassi distinguished service professor of economics - booth school of business, university of chicago, deputy director - becker friedman institute @erikhurst.

September 8, 2021

The paper summarized here is part of the Fall 2021 edition of the Brookings Papers on Economic Activity (BPEA) , the leading conference series and journal in economics for timely, cutting-edge research about real-world policy issues. The conference draft of the paper was presented on September 9, 2021 at the Fall 2021 BPEA conference . The final version was published in the Fall 2021 edition by Brookings Institution Press on June 7, 2022. Read all papers published in this edition here» Submit a proposal to present at a future BPEA conference here»

Longstanding racial and ethnic disparities in the United States have hurt not only the people who experience the disparities but have hurt all Americans by depressing U.S. economic output by trillions of dollars over the past 30 years, suggests a paper discussed at the Brookings Papers on Economic Activity (BPEA) conference on September 9.

The authors— Shelby R. Buckman, Laura Y. Choi, Mary C. Daly¸ and Lily M. Seitelman, all of the Federal Reserve Bank of San Francisco—considered differences from 1990 to 2019 among white, Black, and Hispanic men and women, ages 25-64. They looked at disparities using five metrics: employment (the percentage of people with jobs); hours worked; educational attainment (the level of education completed); educational utilization (the extent to which people are in jobs that fully use their education); and earnings gaps not explained by those factors.

Then, in The economic gains from equity , they conducted a thought experiment, asking: “How much larger would the U.S. economic pie be if opportunities and outcomes were more equally distributed by race and ethnicity?” Their answer is $22.9 trillion over the 30-year period.

“The persistence of systemic disparities is costly, and eliminating them has the potential to produce large economic gains,” the authors write. Standard economic models often assume markets work efficiently and thus suggest explanations—such as unmeasured differences in productivity or cultural differences—that would support the existence and persistence of racial and ethnic gaps. The authors instead assume talent and job and educational preferences are distributed evenly across race and ethnicity. They then show the economic effects of disparities that hold people back from fully realizing their potential.

The persistence of systemic disparities is costly, and eliminating them has the potential to produce large economic gains

“The opportunity to participate in the economy and to succeed based on ability and effort is at the foundation of our nation and our economy,” they write. “Unfortunately, structural barriers have persistently disrupted this narrative for many Americans, leaving the talents of millions of people underutilized or on the sidelines. The result is lower prosperity, not just for those affected, but for everyone.”

“With considerable pressures weighing on U.S. economic potential in coming decades, the time seems right to take a new perspective and imagine what’s possible if equity is achieved,” the authors conclude.

The authors note in the paper that they built on the work of others and cite in particular the work, dating to 1985, of four African-American economists: William A. Darity, Patrick L. Mason, William E. Spriggs, and the late Rhonda M. Williams.

Acknowledgments

David Skidmore authored the summary language for this paper.

Buckman, Shelby R., Laura Y. Choi, Mary C. Daly¸ and Lily M. Seitelman. 2021. “The Economic Gains from Equity.” Brookings Papers on Economic Activity , Fall. 71-111.

Fortin, Nicole. 2021. “Comment on ‘The Economic Gains from Equity’.” Brookings Papers on Economic Activity , Fall. 112-130.

Hurst, Erik. 2021. “Comment on ‘The Economic Gains from Equity’.” Brookings Papers on Economic Activity , Fall. 130-135.

Conflict of Interest Disclosure

Shelby R. Buckman is a graduate student in economics at Stanford University and a past employee at FRBSF during which time she did the majority of her contribution to this paper; Laura Y. Choi is vice president of community development at the Federal Reserve Bank of San Francisco; Mary C. Daly is president and chief executive officer of the Federal Reserve Bank of San Francisco, CRIW member, and IZA research fellow; Lily M. Seitelman is a graduate student in economics at Boston University and a past employee at FRBSF during which time she did the majority of her contribution to this paper. Beyond these affiliations, the authors did not receive financial support from any firm or person for this paper or from any firm or person with a financial or political interest in this paper. They are currently not officers, directors, or board members of any organization with an interest in this paper. No outside party had the right to review this paper before circulation. The views expressed in this paper are those of the authors and do not necessarily reflect those of the Federal Reserve Bank of San Francisco. Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the National Science Foundation. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1840990 and Grant No. DGE-1840990.

hIstory of bpea

Discussants

Economic Studies

Brookings Papers on Economic Activity

Janice C. Eberly, Samuel G. Hanson, Jón Steinsson, Daniel K. Tarullo, David Wessel

June 6, 2024

Phillip Levine, Luke Pardue

June 5, 2024

Tara Watson, Gabriela Goodman

June 4, 2024

Insights & Impact

It Was All a Dream: Improving Access, Equity, and Economic Outcomes for Adult Learners in Rural Locations

Posted on 06.01.2024

This post was originally published by WestEd’s Center for Economic Mobility.

By Dr. Alexandria M. Wright and Dr. Laura Lara-Brady

In this blog post, we explain the Adult Education on-ramps to postsecondary opportunities, the opportunity cost of education, and the support needed for adult learners in rural communities.

For many, economic mobility, or the concept of increasing one’s economic status over time, goes hand-in-hand with the “American Dream”—the idea that anyone, no matter their background, wealth, race, or geographical location, can achieve their goals and improve their economic status by working hard and educating themselves. But to achieve those dreams, people in all communities need to be connected to equitable and accessible on-ramps to economic mobility.

Postsecondary education programs, including community colleges, career and technical education, apprenticeships, on-the-job training, and 4-year universities and beyond, are crucial levers for achieving economic mobility. This is especially the case for rural communities, which face unique opportunities and challenges in accessing the education and training that results in achieving economic mobility. Research shows that rural students graduate from high school at a higher rate (90%) than students from cities (82%) or suburbs (89%). But rural communities often have limited access to education and employment opportunities, and they have limited resources for essentials like adequate housing or childcare—all possible contributors to the fact that only about 55 percent of rural students directly enroll in college. In the big picture, this means that a higher percentage of rural adults over age 25 hold a high school degree as their highest level of educational attainment compared with adults in cities and suburban areas .

The Center for Economic Mobility partners with communities to connect educational institutions with employers and enhance existing curricula that reflect high-demand skills in careers that provide family-sustaining wages and meet the adult learner where they are.

There are three main ways the Center for Economic Mobility connects educational institutions and employers to support this work:

creating accessible entry points to postsecondary education for adults living in rural communities
highlighting the importance of career pathways that lead to family-sustaining wages using earn-while-you-learn models
ensuring sustainability for training and wraparound services

These are all key ingredients of pathways to economic mobility for rural communities.

Strengthening On-Ramps: Increasing Access to Education and Training Programs

The unique conditions of rural communities require particular coordination to achieve student success. Evidence-based research has demonstrated that engaging Adult Education Integrated Education & Training (IET) programs—which combine occupational skills training with Adult Education services—provides learners with a refresher on basic reading, writing, and arithmetic skills in a contextualized format alongside industry credentials that can propel adult learners into new career pathways. Enforcing competency in basic skills readily supports student success, giving adult learners a boost as they continue their educational and career journeys. Adult Education pathways like these offer an easy-to-access on-ramp to short-term education and training that meets rural adult learners where they are while increasing their value in the labor market through the attainment of industry credentials in fields such as digital technology, manufacturing, and supply chain and transportation. This reduces the opportunity cost of education by decreasing the time spent in the classroom and offering adult learners an immediate gain in the labor market while they begin their career pathway.

While Adult Education is federally funded through the Adult Education and Family Literacy Act , the funding does not support development of new IET programming. Seeking small amounts of funding that can support the development of IET programming can provide an exponential return on investment as adult learners move through training and into good jobs that support economic mobility. By connecting adult learners to living wage employment through these programs, rural communities can expect to see positive ripples throughout their local economy as more people experience economic mobility.

Addressing the Opportunity Cost of Education for Adult Learners in Rural Communities

While the modern era has placed increasing pressure on financial resources for everyone, economic opportunity is simply less available in rural communities due mainly to limited commerce, reduced transit corridors, and sparse capital for investment. This presents a difficult choice for adult learners: Get an education or go to work. In this sense, education and income become a zero-sum game. One way to address the increasing cost of education, particularly for adult learners in rural communities, is to highlight opportunities that allow adult learners to work while they earn school credit.

The Center for Economic Mobility has created a dashboard that shows the relationship between educational pathways, skills, and jobs using region-specific labor market data that can help educators and adult learners explore which pathways are likely to lead to family-sustaining jobs in their respective regions. Practitioners can use this information to develop resources for adult learners about opportunities for further study and employment and to support conversations with faculty and counselors about how institutions’ academic options align with regional opportunities.

Additionally, earn-while-you-learn opportunities, such as Registered Apprenticeship Programs and Work Experience or On-the-Job-Training, provide rural learner-workers with access to living wage employment while concurrently supporting continued education. These opportunities are funded and operated through local workforce systems , which help address income barriers for adult learners while simultaneously supporting workers along their educational and career paths. These investments will inevitably assist adult learners as they move up the career ladder and obtain higher wages.

Engaging with the Business Services team at local America’s Job Centers , typically branded as the local state employment office, will help connect learner-workers to these various programs. Supported by federally funded mandates to provide employer incentives, Business Services can also assist with direct job placement for qualified workers. Harnessing these public resources is essential in rural communities that often lack resources due to low population densities.

Meeting the Basic Needs of Adult Learners in Rural Communities

Even with accessible on-ramps to securing short-term, industry-credentialed training and paid work experience, students in rural communities often encounter additional barriers that prevent them from taking advantage of these opportunities. Adult learners encounter many barriers on their educational journeys. One of the most common obstacles is lack of access to such basic needs and services such as reliable transportation, affordable childcare, healthy food, affordable health care, and work clothing.

The federal workforce system provides access to a variety of support services for qualified individuals through the Job Seeker Services side of the local America’s Job Center. Support services include immediate access to cash assistance through TANF (Temporary Assistance for Needy Families), food benefits from SNAP, transportation support, and childcare support to name a few. The Center for Economic Mobility has supported rural communities by understanding the unique needs of adult learners and then working with colleges, adult schools, workforce systems, and community-based organizations to align their offerings and support the unique needs of adult learners.

Ensuring that student advisors are aware of Job Seeker Services will help learner-workers have even greater access to earn-while-you-learn opportunities and assistance with direct job placement. Access to these crucial services can be elusive for the average citizen without the proper support.

At its core, rural workforce development can be far more complicated than similar initiatives in metropolitan areas. The staff at the Center for Economic Mobility understand this. By implementing some of the actions noted above, rural educational institutions can help learner-workers truly live the dream rather than being resigned to sit on the sidelines in a marginalized space that dictates it can only be a dream. The Center for Economic Mobility works with partners to create accessible entry points, scale effective models, and connect the dots to support adult learners’ basic needs, rural educational institutions can help learner-workers live their version of the “American Dream” and reach their fullest potential.

The Center for Economic Mobility specializes in instructional design for Adult Education IET programming, offers subject matter expertise in bridging education and workforce systems, and provides technical assistance to educational institutions and systems. Our technical assistance includes regional pathway mapping to good jobs that targets high-impact career pathways aligned with local workforce system priority industries. Let’s connect as we build a future where every student’s dream has a chance to become a living, breathing, paycheck-earning reality.

Dr. Alexandria Wright is a Senior Research Associate for Economic, Labor Market & Educational Data at WestEd. She specializes in strategic planning to build strong economies in rural America and American Indian Nations and in the design of key performance indicators across economic, social, and environmental dimensions of a community.

Dr. Laura Lara-Brady is a Senior Project Manager at WestEd. Her degree and background focus on building student and community-centered higher education systems in which marginalized communities can thrive. She leads a number of statewide and national projects centered on large initiatives such as Guided Pathways and the alignment of K–12 and higher education systems with regional needs. Her work includes engaging partners and organizations to amplify and align their efforts and create meaningful and sustainable systemic change that supports the needs of marginalized communities. Dr. Laura Lara-Brady was born and raised in Guadalajara, Mexico.

Subscribe to the E-Bulletin for regular updates on research, free resources, services, and job postings from WestEd.

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Diving Deeper into Postsecondary Value, IHEP Research Series Explores Equity and Economic Outcomes

Washington, DC (May 29, 2024) –   Higher education has long been recognized as a key driver of economic opportunity, but new research, spearheaded by the Institute for Higher Education Policy (IHEP), is diving deeper into questions of postsecondary value and equity. The “Elevating Equitable Value: Investigating Economic Outcomes of Postsecondary Education” series, informed by data from the Equitable Value Explorer tool along with state-level data, surveys, and additional sources, is exploring pressing questions about postsecondary value. Research released today by Trellis Strategies, the American Association of State Colleges and Universities (AASCU), Wayne State University, and the Research Institute at Dallas College completes the seven-paper series.

“Earning a college degree can change the trajectory of students’ lives, their families, and their communities, for generations to come, but the benefits are not evenly distributed,” said IHEP President Mamie Voight . “By unpacking the nuances of value delivery across different contexts, this research strengthens the evidence-base showing that college is worth the investment. It also can inform policymakers and institutions about targeted strategies to improve the returns on postsecondary education for all students.”

Field-based researchers across the country built on the work of the Postsecondary Value Commission by exploring critical questions on post-college outcomes in their own specific context:

How Can Policy and Practice Shape Equitable Value?

Several papers in the series explored how institutional policy and practice can ensure all students benefit from a college degree. Research by Trellis Strategies underscores the connection between student financial well-being during college and future economic returns. A ten-percentage-point decrease in the number of students experiencing financial instability during college was correlated with higher economic returns to students, especially at four-year public schools. The authors highlight the importance of programs that expand access to emergency aid, promote financial literacy, and enhance transparency around college costs and financial aid options.

A study by the American Association of State Colleges and Universities (AASCU) found that all 33 institutions participating in their Student Success Equity Intensive program had earnings that exceeded the Postsecondary Value Commission’s minimum economic return threshold, but equity gaps persist. Institutions serving a larger proportion of Black, Latinx, and Indigenous students or Pell Grant recipients saw a smaller economic return – the amount by which earnings exceed those of a typical high school graduate, plus the cost of their education – demonstrating the need for continued efforts to promote student success and the financial value of college degrees.

Another key finding shows a strong link between faculty composition and student outcomes. Research by Frederick Tucker of the City University of New York reveals that institutions with more tenured or tenure-track faculty, alongside a smaller proportion of full-time adjuncts, see stronger economic returns for students. This is particularly true at Minority-Serving Institutions (MSIs) and colleges serving a large share of Pell Grant recipients.

How Does Postsecondary Value Differ By and Within States?

The research in this series adds to our growing understanding of how certain states are delivering value. For example, a project by Wayne State University found that while postsecondary education generally leads to higher earnings in Michigan, disparities exist. Public, four-year universities in the state provided the highest economic return, exceeding the minimum threshold by over $22,000, while most other types of institutions in the state offered a smaller but still positive return. Michigan ranked high nationally in terms of the amount that students’ earnings typically exceed the minimum economic return threshold, despite having a moderate ranking in median post-college earnings.

The Research Institute at Dallas College’s analysis paired data from the Equitable Value Explorer with state longitudinal data to measure the economic return at more than 500 Hispanic-Serving Institutions (HSIs) nationwide, in addition to outcomes for all Hispanic students in Texas. Overall, economic returns were positive for Hispanic students, but disparities persisted even within Hispanic communities, particularly for immigrants, those from low-income backgrounds and women.

What is the Role of Geography in the Postsecondary Value Equation?

Location plays a significant role in education options and economic returns. Two papers in the series examined the geographic dimension of value. The American Institutes for Research’s study found that community college students generally earn more after college than those with only a high school diploma in their region. However, community colleges serving a higher percentage of underrepresented students tend to deliver a lower economic value, underscoring the need for additional support to ensure these institutions can effectively serve their students.

Boston College researchers’ analysis of rural-serving institutions (RSIs) found that while median post-college earnings may be slightly lower compared to urban and suburban institutions, RSIs are typically more affordable. The majority of RSIs still provide a positive economic return for students after factoring in these relatively low education costs, highlighting their vital role in expanding access to higher education in underserved areas.

IHEP is expanding and strengthening the community of researchers, practitioners and advocates exploring postsecondary value through an equity lens, by providing the tools necessary for researchers, associations, and institutions to tackle these critical questions. For more information about the Equitable Value Explorer, please visit: https://equity.postsecondaryvalue.org/

Supporting the Whole Student Through Holistic Advising: Reflections on ED’s Raise The Bar Summit

Investing in Student Success: IHEP’s Federal Funding Priorities for FY25

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1 0000000404811396 https://isni.org/isni/0000000404811396 International Monetary Fund
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Contributor Notes

We study whether higher gender equality facilitates economic growth by enabling better allocation of a valuable resource: female labor. By allocating female labor to its more productive use, we hypothesize that reducing gender inequality should disproportionately benefit industries with typically higher female share in their employment relative to other industries. Specifically, we exploit within-country variation across industries to test whether those that typically employ more women grow relatively faster in countries with ex-ante lower gender inequality. The test allows us to identify the causal effect of gender inequality on industry growth in value-added and labor productivity. Our findings show that gender inequality affects real economic outcomes.

1. Introduction

“ Gender equality is more than a moral issue; it is a vital economic issue. For the global economy to reach its potential, we need to create conditions in which all women can reach their potential. ”

— Former IMF Economic Counsellor Maurice Obstfeld, March 23, 2017 ( IMF 2017 )

Worldwide, productivity growth and the pace of human development are slowing ( ILO 2017 ), and women’s full and effective participation in the workforce and decent work for all are critical to inclusive and sustainable economic growth 1 . While women account for half of the total population, they remain an underused resource, constituting less than a third of the actual workforce ( Lagarde 2013 ). According to the report of the United Nations (UN) High-Level Panel on Women’s Economic Empowerment, 700 million fewer women than men of working age were in paid employment in 2016, and even when women are paid, they tend to work in jobs with relatively low earnings, poor working conditions, and limited career prospects (UN 2016) . Implementing policies that remove labor market distortions and create a level playing field for all gives women the opportunity to develop their potential and to participate in economic life more visibly ( IMF 2013 ). Furthermore, women are more likely to invest their resources in education and the health of their children, building human capital to fuel future growth (see, for example, Schultz 2002 ). Helping women fully participate in the economy is not only growth promoting, but it also diversifies the economies, reduces income inequality, mitigates demographic shifts, and contributes to financial sector stability ( Gonzales and others 2015 ; Kochhar and others 2017 ; IMF 2018a ). In many countries, constraints such as discriminatory laws, a lack of legal protection, unfavorable social norms, and a lack of access to real and financial assets have held women back, which, in turn, have held back the economies ( World Development Report (WDR) 2012 ). Gender equality and the empowerment of women are, thus, not merely issues of human rights, but also economic necessities, and central to the development agenda ( IMF and WB 2007 ; IMF 2017).

An extensive body of work documents gender inequality in both opportunities (for example, education, health, and finance) and outcomes (for example, employment and earnings), with a particularly rich literature studying the determinants of gender wage gap 2 . The literature dating back at least to Boserup (1970) has emphasized the positive effects of gender equality on development. A number of theoretical contributions have proposed that gender inequality may hamper economic development (for example, Galor and Weil 1996 ; Lagerlöf 2003 ), largely due to its effects on the creation of human capital and on fertility. In Figure 1 , we plot GDP per capita growth against the gender inequality index for the period of the 1990s for a sample of countries for which the data are available and show that the two variables are, indeed, negatively correlated. Most empirical contributions to date also document a significant negative effect of gender inequality on growth (see Cuberes and Teignier 2014 for a comprehensive literature review) 3 .

Gender inequality and real GDP per capita growth

Citation: IMF Working Papers 2020, 119; 10.5089/9781513546278.001.A001

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Despite a large number of contributions on the topic, empirically identifying a causal impact of gender inequality on economic growth is a major challenge. The standard methodology in this macroeconomic literature is to use a regression analysis to relate the countries’ per capita income growth to different proxies of gender inequality, controlling for standard growth covariates, such as population growth, level of investment, openness to trade, and governmental and institutional quality (see, for example, Gonzales and others 2015 ). Such cross-country approaches, however, raise endogeneity concerns—well known in the economic growth literature. Reverse causality is an issue in studying the role of gender inequality for economic progress, as the two are closely related: in one direction, development alone can play a major role in reducing gender inequality; in the other direction, higher gender equality may support development ( Duflo 2012 ; Stotsky 2006 ; IMF 2013 ). Furthermore, there may be some omitted factors that both enhance the growth of and narrow the gender gap. One avenue to take to address these challenges would be to use an instrumental variable analysis, but a plausible instrument to identify the relationship would require finding a variable that contributes to growth only through its impact on gender inequality—which poses a challenge of its own 4 .

This paper contributes to the literature on gender inequality and economic growth making a step forward in causal inference by focusing on a particular channel through which higher gender equality may support economic growth: by allocating female labor to its more productive use. We argue that higher gender equality enables firms to make better use of available labor resources, which boosts growth (see, for example, Barsh and Yee 2012 and Cornell Center for Advanced Human Resource Studies (CAHRS) 2011 ). To the extent that different industries typically have different gender compositions, we exploit the heterogeneity across manufacturing industries to identify the causal effect of gender inequality on economic growth. By focusing on the differential effect of gender inequality on economic growth within countries between industries, we address the bulk of the endogeneity concerns that arise in aggregate level cross-country studies.

We hypothesize that higher gender equality should disproportionately benefit industries with a typically greater share of women in their employment relative to other industries. This effect may operate through both extensive and intensive margins of employment. On the extensive margin, higher gender equality translates into a bigger pool of talent to recruit from, due to additional women in the labor force (Cuberes and Teignier 2016; Kochhar and others 2017 ). Higher productivity of the marginal worker, in turn, raises industries’ productivity and thus boosts industries’ growth. Similarly, on the intensive margin, higher gender equality enables women to fully develop their potential in the labor market—for example, by making their career ladders higher—which is also growth promoting ( Islam and Amin 2016 ). The effects on both margins would be more evident for high-female-share industries as, on the extensive margin, a larger share of newly hired women join these industries and, on the intensive margin, unlocking women’s potential at work is more beneficial to industries that have a greater share of female labor in their total employment 5 .

To test our hypothesis, we adapt the difference-in-differences (DiD) application by Rajan and Zingales (1998—henceforth RZ) studying the finance-growth nexus. The DiD estimator rests on the assumptions that there are industry-inherent features that do not vary across countries and that they are properly measured using the data from a benchmark country ( Beck 2009 ). We identify an industry’s intrinsic gender composition by looking at its share of female labor in total labor in Sweden (the country with by far the lowest GII in the relevant period), under the assumption that the labor market in this country in the observed period is relatively frictionless regarding women’s access and attitudes to jobs across different industries. We further assume that these estimated industries’ “clean” gender compositions carry over to other countries, which enables us to investigate whether industries that typically employ more women grow relatively faster in countries that, a priori, have lower gender inequality. This assumption implies that, ceteris paribus, a high-female-share industry such as wearing apparel , should grow relatively faster than wood , which has a low share of female labor in its total employment, in more gender-equal countries.

In the context of our analysis that exploits the dynamics in the labor market, high development on the gender equality front (such as in Sweden) is assumed to entail a large reduction of frictions on both the demand side of labor (due to, for example, discrimination in the labor market) and the supply side (due to, for example, gender social norms). Thus, in the absence of gender-based frictions, the bulk of the heterogeneity in gender compositions across industries may be attributed to the industry-specific relative marginal product of labor (MPL) between men and women—reflecting women’s comparative advantage in a given industry. Namely, the higher the women’s relative MPL, the higher the incentive for an industry to employ them. This is somewhat different from an implicit assumption by RZ in the context of the capital markets analysis, where the high financial development (such as in the US) is assumed to remove the constraints solely on the supply side of credit. Except for differences in the assumptions driving the identification of the industries’ features in a benchmark country, our methodology is equivalent to their empirical method.

Furthermore, in line with their approach, our assumptions do not impose that the industry’s gender composition in a benchmark country is the optimal one. Neither do we argue that such horizontal segregation, reflected in the differences in gender compositions of labor across industries, is by any means desirable. Instead, we exploit this heterogeneity of gender compositions across industries as an exogenous source of variation that facilitates identifying the causal effect of gender inequality on real economic outcomes.

To this end, we use industry-level employment data on manufacturing from the UN Industrial Development Organization (UNIDO) database and country-level data on a composite gender inequality index (GII), which have been released by the IMF ( Stotsky and others 2016 ). Unlike the narrower inequality measures used in the majority of the previous literature studying a link between gender inequality and development, which mostly focuses on inequality in education, we use a broader measure of gender inequality that evaluates both equality of opportunities and outcomes—including women’s empowerment, female reproductive health, and labor market variables ( Gaye and others 2010 ; UN Development Programme (UNDP) 2014 ).

Our findings suggest that gender inequality has a causal effect on real economic outcomes at the industry level. Using a large sample of emerging-market and developing economies, we show that the industries with a typically greater share of women in their employment compared to other industries grow relatively faster in more gender-equal countries. Our estimates predict that an industry at the 75th percentile of the female share in total employment, compared to an industry at the 25th percentile, grows 1.7 percentage points faster in terms of value-added (and 1.2 percentage points faster in terms of labor productivity) when it is located in a country at the 25th percentile of gender inequality rather than in one at the 75th percentile. The estimated magnitude of the effect is rather large, considering that the real annual growth rate of value-added is, on average, 2.2 percent per year, whereas the average growth of labor productivity is 1.2 percent. Our results are robust to using different measures of gender inequality and to a wide range of alternative explanations such as outliers, measurement error, omitted variables, and reverse causality.

2. Hypothesis and Methodology

We hypothesize that industries with a typically greater share of women in their employment compared to other industries grow relatively slower in countries that, a priori, have higher gender inequality. Both extensive and intensive margins of employment may relate to this effect. On the extensive margin, higher gender equality would lead to more and better educated women entering the labor force and thus to a larger pool of talent for firms to hire from. Higher productivity of the marginal worker, in turn, raises industries’ productivity and boosts industries’ growth. On the intensive margin, higher gender equality would empower women to fulfill their full potential in the labor market—for example, by promoting them to managerial positions (or positions of influence)—which is also growth promoting. The effects on both margins would be more evident for high-female-share industries: on the extensive margin, a larger share of newly hired women joins industries that typically hire more women; on the intensive margin, unlocking women’s potential at work is more beneficial to industries that have a greater share of female labor in their total employment 6 .

We follow the identification strategy first proposed by RZ in studying the finance-growth nexus. To assess the impact of gender inequality on industry growth, we use variation across industries in their gender compositions and variation across countries in their level of gender inequality. To test our hypothesis, we estimate the following DiD model:

The dependent variable is the average real growth rate of value-added in industry i in country k over the period of the 1990s. We control for the country and industry characteristics by using a set of dummy variables for each country and industry (μ κ and ν i respectively). Many of the core determinants of growth, such as differences in capital accumulation of different industries, will be captured by industry fixed effects, while factors such as institutional differences will be captured by country fixed effects. We also control for industry i ’s value-added share of manufacturing in country k in 1990 ( X i,κ ) to deal with possible convergence effects, which varies across industries and countries and thus is not captured by country nor industry fixed effects ( Rajan and Subramanian 2011 ). Our main coefficient of interest is for the interaction term of a share of female labor in total employment of industry i , estimated from a benchmark country over a given period, and country k ‘s level of gender inequality in 1990—the DiD estimator. If our hypothesis is correct, γ should be negative.

We use all country-level variables from the first year of the analysis, following RZ. Thus, this test analyzes how ex-ante gender inequality affects ex-post growth in industries depending on their gender compositions. As opposed to aggregate-level cross-country studies on the gender inequality-growth nexus, this strategy enables us to analyze within-country differences across industries based on the interactions between industries’ female shares and a country’s gender inequality. An industry’s female share is defined as a number of female employees to total employees in the country with the least gender frictions in the labor markets—Sweden, having the lowest gender inequality index. Having calculated this ratio for each year, we take simple averages across years for the corresponding periods, as presented in Table 1 .

Industries’ female shares (%) in countries with the lowest gender inequality index (GII)

There are two main assumptions in this specific DiD application by RZ. First, there are some intrinsic reasons that lead certain industries to typically employ more female labor than others. We propose that the main reason for observed horizontal segregation—that is, the differences in gender compositions of labor across industries—lies in the industry-specific relative MPL between women and men. Second, these differences across industries carry over countries, so that an industry’s female share identified from a benchmark country (with small frictions) can be used as a proxy for its gender composition in other countries. Although we know that female shares in an industry may differ between Sweden and Turkey, for our identification to work all we need is a sort of ordering. For example, if the wearing apparel industry employs more female labor than the wood industry in Sweden, it also employs more female labor in Turkey. In line with this assumption, the WDR (2012) documents that economic development seems to have a limited impact on gender segregation in employment. Perhaps somewhat surprisingly, the report finds little, if any, relationship between GDP per capita and standard measures of segregation (sectoral and occupational) along gender dimension and that gender segregation in employment is quite persistent (over time) and consistent (across countries). The WDR highlights that the segregation arises due to a combination of gender-differentiated barriers in access to economic opportunities—including discrimination and gender norms—and sorting based on gender-based preferences. In our identification strategy, however, we assume that even with the full elimination of such frictions, horizontal segregation of employment would still persist due to industry-specific relative MPL between women and men. Namely, the higher the women’s relative MPL in an industry with respect to men’s, and thus their comparative advantage, the higher the incentive for an industry to employ them 7 . We document little variation of industries’ gender composition in our sample either over time or within a group of our benchmark countries (that is, the countries with relatively high gender equality, which we use to identify industries’ gender compositions). Figure 2 plots the mean and standard deviation for industries within Sweden over the period of the 1980s and shows that the variation of the female share in an industry across time is rather low, around 4 percent of the mean—as is the case in our alternative benchmark countries. Table 1 shows that the industries’ gender compositions are also rather similar between Sweden and these countries, as confirmed by their high correlations reported in Panel B of Table 3 . Hence, our assumption of stable patterns of industries’ gender compositions is reasonable.

Mean and standard deviation of the share of female labor in total labor within each industry over the 1980s in Sweden

Gender inequality index (GII) by countries in 1990

Descriptive statistics

Data on actual industries’ gender compositions are typically not available for a large majority of countries. But even if they were, the data would not be useful for our purpose, as a share of female labor in total employment of an industry in a given country is an equilibrium outcome in the labor market, likely distorted by existing gender-based frictions (for example, discrimination). As we are interested in industries’ intrinsic heterogeneity arising from women’s relative MPLs compared to men’s in a given industry, such data would be contaminated 8 . We thus start by computing the share of female labor in total labor in Sweden. In a country with full gender equality, industries’ actual gender compositions would not be contaminated by gender-based frictions in the labor market, thus there would be no identification problem. Gender equality in Sweden in the 1980s was sufficiently high to make it reasonable to assume that employment of female labor by an industry in Sweden throughout this period was likely to be a relatively clean measure of women’s relative MPL compared to men’s within a given industry 9 . In order to smooth temporal fluctuations in gender composition, we aggregate this measure over time. Specifically, we obtain a share of women in total labor employed per industry in each year, and then take the average over the 1980s. We thus use the lagged period with respect to our growth statistics on emerging-market and developing economies under study—which cover the 1990s. We assume that (the bulk of) the change in an industry’s relative MPLs of women and men, shaping an industry’s intrinsic gender composition, arises due to the technological shocks that change the nature of the available jobs within an industry. Women generally perform more routine tasks that are more prone to automation ( IMF 2018c ; Brussevich and others 2019 ). For example, mechanization of much of the physically less demanding work in mining (such as handpicking and sorting ore) led to fewer and fewer women working in the mine, just as in the other industries during the industrialization period ( Abrahamsson and others 2014 ). To the extent that such technological advances are worldwide and that our regression sample consists of emerging-market and developing economies in the 1990s, the state of production technologies in Sweden in the 1980s makes a suitable proxy (especially given our focus on the manufacturing sector). Our results are robust to using alternative dates and countries for benchmarking. Our benchmark countries should provide a sufficiently convincing reference point for identifying industries’ gender compositions, for which they need to have low gender inequality relative to the sample under analysis. That is, similar to RZ, the benchmark countries should have relatively less (gender-based) frictions. Thus, we do not study the developed economies, as these have high levels of gender inequality comparable to our benchmark countries, but we focus our analysis on the emerging-market and developing economies 10 .

3.1. Data on industries

We use the ISIC 2-digit industry-level dataset from UNIDO (Revision 3), which restricts our analysis to manufacturing sectors (ISIC 15–37) 11 . We use industry-level value-added data in current US dollars. The nominal value-added was changed to the real value-added using the Producer Price Index (PPI) from the US, since the PPI data are not available for many of our countries 12 .

We also draw data on the number of employees and the number of female employees from UNIDO for six countries that we use in calculating female labor shares: Australia, Austria, Canada, Ireland, New Zealand, and Sweden—our main benchmark country. These are the countries with the lowest gender inequality index and the data available on female employees for the corresponding periods. We drop the observations with a value-added share of manufacturing smaller than 0 or greater than 1. We drop the industries for which female employment data are missing for the majority of our benchmark countries or for most years in the relevant period. Our final sample consists of 17 industries.

We calculate the value-added share of an industry in a country’s total manufacturing value-added in 1990. Whenever value-added in 1990 is missing for an industry, we use it from 1991, 1992, or 1993, if it is available. If it is not available for any of these years, we do not use that observation. Labor productivity of an industry is calculated as the real value-added divided by the number of employees. We use the country-industry observations for which the average growth rate for a sector (over the 1990s) is calculated as the average of at least three data points on growth rates. For industries’ external finance dependence (which we use in one of our robustness checks), we adopt the measures from Popov (2014) for US firms in the 1980s for corresponding industries.

3.2. Data on countries

3.2.1. Measures of gender inequality

In our main analysis, we use a composite index for gender inequality (GII). The GII considers inequality both in opportunities and outcomes and consists of subindexes on reproductive health (maternal mortality and adolescent fertility), female empowerment (education and political representation), and labor market (participation rate). Based on the calculations by Stotsky and others (2016) , the IMF has the most comprehensive gender inequality database, which goes back to the year 1990. The IMF calculates this index for approximately 100 economies in the world; the index ranges from 0 to 1, where higher GII indicates higher gender inequality. Sweden is the country with the lowest GII in the 1990s. Its GII has a sizable gap with respect to the rest of the developed economies, thus we use Sweden as the benchmark country in our basic results; we do, however, perform robustness checks using five other countries, with among the lowest GII and female employment data available in UNIDO.

Table 2 tabulates the GII for different countries in 1990. Panel A consists of the emerging-market and developing economies in our main regression sample, and Panel B provides the statistics on the countries used to identify industries’ gender compositions. GII in 1990 in our sample varies from approximately 0.3 in Hungary to approximately 0.8 in Morocco. In our benchmark countries, the GII in 1990 is significantly lower in comparison to Panel A—as low as 0.093 in Sweden to 0.284 in New Zealand.

We also employ several other proxies for gender inequality in our robustness checks, namely, the adolescent fertility rate, relative infant mortality, relative labor force participation, the gender parity index (GPI), and the women’s rights law score. The adolescent fertility rate, measured as the number of births per 100 women ages 15–19 years, captures the detrimental health, economic, and social risks and consequences associated with early childbearing. Premature motherhood tends to prevent women from pursuing further education, and thus to obtain higher-skilled jobs ( Gaye and others 2010 ). The relative infant mortality ratio, which is the ratio of infant female mortality to infant male mortality, indicates gender inequality in infant health, where excess female infant mortality rates relative to male rates reflect the discriminatory treatment of women (see, for example Sen 1989 , 1990 ). The GPI, which is the ratio of female students to male students, measures the gender parity in schooling. The relative labor participation ratio, measured by the labor participation rate of males relative to females, captures the relative underrepresentation of women in the workforce—an important component of gender inequality. The women’s rights law score captures the strength of the legal framework for enforcing gender equality. It is constructed using Women’s Legal Rights data that contain questions related to women’s legal rights replied as “Yes” or “No,” depending on the presence of laws in a country. We construct the law score for each country by dividing the number of negative answers by the number of total replied (that is, codified) questions for each country in 1990. Panel C of Table 3 shows that although these measures capture different components of gender inequality, their pairwise correlations—among themselves and those with GII—are pointing in the right direction.

3.2.2. Covariates

We control for institutional quality using a measure of political competition from the Polity IV database (see, for example, Cavallo and Cavallo 2010 , and Durdu and others 2019 ) . The index ranges from 0 to 10, with a higher value indicating greater political competition. We proxy financial development by broad money from the World Bank’s World Development Indicators (WDI), given that the data on equity markets and credit are not available for a large fraction of our countries in the 1990s (see, for example, King and Levine 1993 ). We follow Barro (1991) , among others, and use the teacher-student ratio in secondary education (a measure of the quality of education) as a proxy for the stock of human capital in a country. Gender inequality is likely to bias many human capital measures, as lower gender inequality leads to higher human capital stock. However, the teacher-student ratio would be less affected, since gender inequality would affect both the denominator (as more girls go to school) and the numerator (as more girls become teachers). We draw this variable from the WDI database. From the same source, we also get data on real GDP and population, both in logs; foreign direct investment (FDI) inflows, export and import, all scaled by GDP; trade over GDP (as a measure of the openness of a country); and population density, being the number of people divided by land area (km square), used in logs 13 . Summary statistics of the sample are provided in Panel A of Table 3 .

We first provide suggestive evidence supporting our hypothesis by documenting growth differentials between high- and low-female-share industries in high and low gender inequality countries. In Table 4 , we summarize the residual growth rate obtained after partialling out industry and country fixed effects for the top and bottom quartiles of industries—ranked based on their female employment. The results show that only the high-female-share industries tend to grow significantly faster in countries with lower gender inequality compared to countries with higher gender inequality. This suggests that the observed patterns of realized growth rate differentials are systematic and that the effect of gender-based frictions is particularly detrimental to industries that typically have a high share of women in their labor.

Gender inequality and actual growth rates in different industries

4.1. Baseline results

Table 5 reports our baseline results. Since the specification controls for country and industry fixed effects ( Equation 1 ), the only effects that are identified are those relative to the variables that vary both across countries and across industries. Thus, Table 5 reports only our main coefficient of interest—the coefficient of the interaction between the share of female labor in the total of an industry’s employment and a country’s GII, and the coefficient of an industry’s value-added share in total manufacturing. The dependent variable is an industry’s value-added growth.

Industry value-added growth and gender inequality

We start by estimating the industries’ gender compositions using our preferred benchmark country—Sweden. As seen in the first column of Table 5 , using this benchmark country, the coefficient estimate for the interaction term is negative and highly statistically significant 14 . To assess the magnitude of this coefficient estimate, we compute the differential growth rates. Specifically, we compare how much faster an industry at the 75 th percentile of female shares (estimated from Sweden, that is, rubber and plastics products ) grows compared to an industry at the 25 th percentile of female shares (that is, non-metallic mineral products ), when it is located in a country at the 25th percentile of gender inequality ( Costa Rica ) rather than in one at the 75th percentile ( Cameroon ). We set the industry’s initial value-added share of manufacturing at its overall mean. The coefficient estimate predicts that an industry at the 75 th percentile of female shares compared to an industry at the 25 th percentile of female shares grows 1.7 percentage points faster in terms of value-added in Costa Rica than in Cameroon . To put the magnitudes in perspective, the real value-added growth rate is, on average, 2.2 percent per year, so the estimated differential growth rate of 1.7 percentage points is substantial. The rest of the columns of the table report the same statistics, with industries’ female shares estimated from alternative benchmark countries (which have among the lowest GII and female employment data available in UNIDO): Australia, Austria, Canada, Ireland, and New Zealand. The statistical significance of our results is unaffected by the use of alternative benchmark countries, whereas the estimates’ magnitude increases in some cases.

As we focus on the differential effects, a potential concern is that, given an increase in female labor participation underlying lower GII, our results may be driven by a disproportionate increase in labor supply of one industry over the other, without real productivity gains. To test this, in Table 6 , we show that our results are very similar if we use real labor productivity growth in the 1990s (value-added based) as a dependent variable instead of real value-added growth over the same period. The coefficient estimate predicts that an industry at the 75 th percentile of female shares compared to an industry at the 25 th percentile of female shares grows 1.2 percentage points faster in terms of value-added labor productivity in Costa Rica than in Cameroon . The value-added labor productivity growth rate is, on average, 1.2 percent per year, so the estimated differential growth rate of 1.2 percentage points is large.

Labor productivity growth (value-added based) and gender inequality

4.2. Alternative measures of gender inequality

In Table 7 , we test the robustness of our results using alternative measures of gender inequality, including the adolescent fertility rate, relative infant mortality, relative labor participation, GPI, and the women’s rights law score. Each of these measures captures a specific aspect of gender inequality in opportunities or outcomes. In comparison, GII is a broader index that reflects different manifestations of gender inequality and is more encompassing than any of these alternative (narrower) measures. GII is, therefore, more suitable to capture the multidimensional concept of gender inequality. However, it may spark concerns of a measurement error due to the composite nature of the index. A higher value of the adolescent fertility rate, relative infant mortality, and relative labor participation and a lower value of GPI and the women’s rights law score indicate higher gender inequality. The results reassure us that our conclusions are robust to using these narrower measures of gender inequality, while showing that inequality in both opportunities (as measured by women’s rights law, education, and health) and outcomes (employment) plays a role for growth. The table reports the results using gender compositions estimated from Sweden, and we get very similar results for each of these inequality measures if we use the alternative benchmark countries (results not reported).

Industry growth and alternative gender inequality measures

4.3. Omitted variable bias

In Table 8 , we aim to address some endogeneity concerns. First, we control for various factors, all in the form of an interaction term with the female share in employment. In column (1), we control for GDP, as the log of real GDP per capita. As the economies develop, gender inequality may decrease, resulting in reverse causality. In column (2), we control for population, as the log of total population. If the population is too low in a country, women may work due to the very high demand for labor, which may bias the gender inequality index that comprises a measure of labor participation. In column (3), we control for population density, as the log of the ratio of population to total area. In less population-dense areas, gender inequality may pose a stronger obstacle to female employment, as women have to commute (alone) farther distances in order to work, which may be an issue due to social norms and/or safety. Also, densely populated areas are usually more urbanized and thus more developed, but also less traditional, which is likely to result in lower gender inequality. In column (4), we control for the female share in population as the ratio of the number of females to the number of males in a country. If there are a lot of women in the population (for example, due to a civil war that results in disproportionate male casualties) or few women (for example, due to cultural preferences for male offspring), these demographic features may bias gender compositions of industries 15 . In columns (5)–(7), we control for export, import, openness, and FDI, respectively. Export and import are measured as a share of GDP. Openness is measured as export plus import divided by GDP. FDI is measured as the net inflows as a share of GDP. These factors may contribute to greater productivity and thus favor growth 16 . Furthermore, trade activities may also reduce gender inequality, as documented by Juhn and others (2014) , which can result in a spurious correlation between gender inequality and economic growth. In columns (9) and (10), we control for financial development (measured by broad money as a share of GDP) and for institutional quality (proxied by political competition measure from the Polity IV database), respectively. Both factors can be correlated with GII and are also highly relevant determinants of growth. In column (11), we control for human capital, as the teacher-to-student ratio in the secondary education (see, for example, Barro 1991 ), as GII gives rise to higher labor participation and a more educated female population; therefore, it may be a proxy for human capital in a country. Neither of these additional controls significantly alters our results. We conclude that our results are unlikely to be biased by omitted variables.

Robustness checks (GII and gender compositions in Sweden)

4.4. Reverse causality

As economic growth also lowers gender inequality, although we use GII from 1990 and relate it to growth outcomes in the following decade, using lagged GII may still expose us to reverse causality concerns if GII is highly persistent over time (as shown in Figure 3 , GII indeed varies little throughout our period). To address this concern, in the last column of Table 8 , we estimate our model on a subsample of smaller industries. In doing so, we mitigate the issue of reverse causality by restricting our sample to industries that are relatively small (less than a median of value-added shares in their respective countries) and are thus less likely to be responsible for the rate of economic growth in a country. In addition, it is less likely that any underlying heterogeneity among small industries in a given country will drive country-level gender equality. One such example would be different countries having a comparative advantage in different industries, which would be reflected in the particularly high demand for labor for specific industries in specific countries. This, in turn, may drive industries’ growth differentials between countries and also, through women’s job creation, have a potential feedback loop to gender equality. Namely, it is plausible that in a country with a comparative advantage in some high-female-share industry (country A), a higher demand for labor in that industry will increase that country’s female employment more than in a country where the comparative advantage lies in an industry that typically employs few women (country B). As a result, higher female employment in country A may eventually lead to higher gender equality than in country B. If this is true, then it would be wrong to infer from our results that gender equality benefits high-female-share industries more; instead, it might imply that countries that have a comparative advantage in these industries would have both higher gender equality and higher growth gap between high-female-share industries and those inherently employing fewer women. It is, however, less likely that differences in a comparative advantage between small industries in a given country are macro relevant. In this subsample analysis, our coefficient estimate of the interaction term between female share and GII remains statistically significant and roughly doubles in magnitude. The increase in the magnitude of the estimated effect is likely due to the higher growth potential of smaller industries.

Mean and standard deviation of gender inequality index (GII) over the 1990s

4.5. External finance dependence

Table 9 reports the results controlling for external finance dependence of an industry and financial development, which are the focus of RZ. Extensive literature documents the importance of finance for growth (see, for example, Levine 2005 ) and equality (see IMF 2020 for a recent discussion), which may bias our results. We show that our results are not a simple artifact of using the DiD application by RZ and some spurious correlations between our main variables of interest—which are external finance dependence and financial development in their study, and gender composition and gender equality in ours. We obtain the data on industries’ external financing from Popov (2014) for US firms in the 1980s for corresponding industries. The interaction term between external finance dependence and financial development is positive, in line with RZ, albeit insignificant. We see that the external finance dependence is also insignificant when interacted either with GII on its own or alongside an interaction term with female share. Financial development also does not seem to be a relevant omitted factor in our analysis. Our main coefficient of interest throughout Table 9 remains close to our baseline estimates in Table 5 .

External finance dependence versus gender composition: Tests with financial development and external dependence on finance

4.6. Additional robustness checks

Additional robustness checks are provided in Table 10 . We use GII as a proxy for gender inequality. In column (1), we test whether our results are robust to potential outliers. We drop the two countries with the highest and the lowest GII in our sample (Morocco and Hungary, respectively) to show that they do not drive our results. In column (2), rather than using a linear measure of gender composition, using data on Swedish industries, we construct a dummy to indicate relatively high versus relatively low female shares in industries. For industries above the median female share in Sweden, we assign 1, indicating that these industries rely on female labor relatively more than the rest of industries (for which we assign 0). In column (3), in a related robustness check, we use a categorical variable to classify industries’ female shares in four categories based on quartiles of the distribution. Industries below the 25th percentile of female shares in Sweden are assigned 1 as the level of female shares, industries between the 25th percentile and the 50th percentile are assigned 2, and so on. Next, we study the robustness of our results to the alternative measurements of industries’ female labor shares. In column (4), for each industry, we take the average of female shares across six benchmark countries and assign this value as the female share of the industry. In column (5), for each industry, we find the maximum of female shares across six benchmark countries and assign this value as the female share of the industry. In column (6), we winsorize the mean growth rates 1 and 99 percent, instead of restricting it between -1 and 1. The results from all these alternative specifications are similar to our baseline results.

Additional robustness checks

5. Conclusion

We study whether gender inequality inhibits economic growth by constraining the use of female labor potential. Specifically, we adapt the difference-in-differences (DiD) application by Rajan and Zingales (1998) , who studied the finance-growth nexus, which facilitates identifying a causal impact of gender inequality on real outcomes at the industry level. Using a sample of industry-employment data on emerging market and developing economies in the 1990s from UNIDO and a country-level composite index on gender inequality (GII), constructed by Stotsky and others (2016) , we exploit within-country variation and show that high-female-share industries grow relatively faster in countries that are more gender equal. By focusing on the differential effect of gender inequality on economic growth within countries between industries with different gender compositions, we are able to address the bulk of the endogeneity concerns that arise in aggregate level cross-country studies. Furthermore, we do a series of robustness checks to rule out alternative explanations such as outliers, measurement error, omitted variables, and reverse causality. Our findings suggest that gender inequality has a causal effect on real economic outcomes at the industry level.

We focus on a particular mechanism through which higher gender equality may support economic growth: by allocating female labor to its more productive use. While our empirical aproach restricts our analysis to the manufacturing sector of a group of emerging-market and developing countries in the 1990s, the channel we identify is likely present in other sectors, time periods, and countries.

We thus provide empirical support to the argument that gender equality is macrocritical, and should be assigned a high priority on the policymakers’ agenda. Policies designed to ensure a level playing field for women, such as improving the rule of law and women’s legal rights in particular, women’s health, access to education, financial services, and technology ( Jain-Chandra and others 2018 ; Stotsky 2016 ), are not only a matter of human rights, equity, and social justice, but relevant policy levers to boost economic growth—benefiting the economy as a whole.

Abrahamsson , L. , E. Segerstedt , M. Nygren , J. Johansson , B. Johansson , I. Edman , and A. Åkerlund , 2014 . Mining and Sustainable Development: Gender, Diversity and Work Conditions in Mining .

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Description of variables

We thank Martin Čihák, Michael Clemens, Robert Cull, Norman Loayza, Wolf Wagner, our discussants Giuseppe Migali and Alberto Vindas Q., and participants at the 2018 Belgrade Young Economists Conference, 2018 Annual Conference Development Economics and Policy (University of Zurich and ETH Zurich), 2018 WEIA Annual Meeting, 2019 American Economic Association Meetings (Atlanta), 2019 Georgetown Center for Economic Research Conference, and seminars at the University of Guelph, Goethe University, and the International Monetary Fund and World Bank Malaysia Hub for their useful comments.

See, for example, the UN 2030 Agenda for Sustainable Development ( UN 2015 ).

See WDR (2012) for the global trends in gender inequality, and Blau and Kahn (2017) for a recent review on gender wage gap literature. A recent study by Deléchat and others (2018) discusses gender gap in financial inclusion and its determinants.

For instance, Hill and King (1995) , Dollar and Gatti (1999) , Lorgelly and Owen (1999) , Tzannatos (1999) , Forbes (2000) , Seguino (2000) , Klasen (1999 , 2002), Knowles, Lorgelly, and Owen (2002) , Yamarik and Ghosh (2003) , Abu-Ghaida and Klasen (2004) , Klasen and Lamanna (2009) , and Loko and Diouf (2009) all find that a higher degree of gender inequality in education and/or employment is detrimental to economic growth. In stark contrast are the findings in Barro and Lee (1993 , 1994) and several subsequent papers ( Barro and Lee 1996 ; Barro and Sala-i-Martin 2003 ) that report a negative association between female primary and secondary schooling and macroeconomic gains, controlling for male schooling. The authors attribute the finding to a large gender gap in schooling, which is a proxy for a country’s backwardness. This result, however, does not stand up to more rigorous econometric tests (see, for example, Stokey 1994 ; Caselli and others 1996 ; Forbes 2000 ; Kazandjian and others 2016 ).

In a cross-country study, Klasen (2002) uses the instrumental variable method to address the endogeneity of gender inequality in education and to relate it to economic development. Esteve-Volart (2004) uses the instrumental variable technique at the subnational level, providing suggestive evidence that gender discrimination in the labor market may hamper economic growth. Kazandjian and others (2016) use the instrumental variable generalized method of moments technique (IV-GMM) to show that gender inequality impedes output diversification and lowers exports. Hakura and others (2016) use the system-GMM estimations to show that income and gender inequality jointly impede growth in sub-Saharan Africa, mostly in the initial stages of development.

“High-female-share” does not strictly imply that the share of women in an industry’s employment is higher than the share of men (that is, >50 percent), but that it is high relative to other industries.

Our methodology focuses on the differentials in industry growth rates, thus it does not imply that the low-female-share industries do not grow. We also do not rule out potential complementarities between female and male labor as a relevant determinant of industry growth, as proposed by IMF 2018b . Any such complementarities could provide an additional boost to productivity beyond the direct effect of hiring (or promoting) a more talented woman over a less talented man.

Discrimination—often one of the main gender-based frictions in the labor market—artificially restricts the demand for female labor, as recognized by the IMF 2013. However, such artificial barriers are lower in countries with lower GII. Sweden not only has by far the lowest GII in the world, but it seems to be among only a few countries in which a large share of the population is aware of gender discrimination laws in the hiring process (more than 50 percent in 2007, according to the IMF).

Our identification exploits the interaction between an industry’s gender composition estimated from a benchmark country (a proxy for women’s comparative advantage in an industry) and a country’s gender inequality. The complicating issue in using actual gender compositions would be that these are distorted by gender inequality, due to existing gender biases in the labor market.

The first equal opportunities act in Sweden was introduced in 1980 by which gender discrimination in the workplace has been made illegal. In 1990, Sweden had by far the lowest GII in the IMF country ranking.

Note that in Panel A of Table 2 , the country with the lowest GII in our regression sample of emerging-market and developing economies (Hungary) has a higher GII (that is, higher gender inequality) than the benchmark country with the highest GII (New Zealand) in Panel B.

Even if the data on the service sector would have been available, services would be less suited for the analysis due to likely lower variation in gender compositions across industries, given that services are documented to be more gender equal in employment than other sectors in both developing and developed economies ( Weinberg 2000 ; Borghans, Weel, and Weinberg 2014 ; IMF 2018b ).

This is consistent with, for example, Guiso and others (2004) and Erman and Kaat (2019) , as well as being the standard practice in previous studies of developing countries using UNIDO data.

Whenever a country-level variable is missing in 1990, if available, we use it from the earliest year available in the 1990s. If it is not available until 1993, we do not use that observation in the corresponding robustness check.

In calculating the growth rate of value-added in industries, we reduce the impact of the outliers by constraining growth between -1 and +1, following RZ. Only a few observations are affected in the sample. We note that the signs and significance levels of coefficients do not change if we keep these observations, although the explanatory power of the regression is lower. Our results are also robust if we winsorize industry growth by 1–99 percent.

The phenomenon of “missing women,” referring to the shortfall in the number of women relative to men expected in a population, was first noted by Amartya Sen ( Sen 1990 ). A smaller family size—whether desired by parents or imposed by the government—is found to be among the main causes (see, for example, Jayachandran (2017) for a description of cultural and religious traditions that lead parents in India and China to fervently desire at least one son, and Zhang (2017) on the evolution of China’s one-child policy and its effects on family outcomes).

See, for example, De Loecker (2013) , which documents the positive effect of export on productivity. Kasahara and Rodrigue (2008) show that import increases productivity, and Frankel and Romer (1999) document a positive effect of trade on income, whereas Nair‐Reichert and Weinhold (2001) suggest that the efficacy of FDI is growth promoting.

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Broadband Internet Access, Economic Growth, and Wellbeing

Between 2000 and 2008, access to high-speed, broadband internet grew significantly in the United States, but there is debate on whether access to high-speed internet improves or harms wellbeing. We find that a ten percent increase in the proportion of county residents with access to broadband internet leads to a 1.01 percent reduction in the number of suicides in a county, as well as improvements in self-reported mental and physical health. We further find that this reduction in suicide deaths is likely due to economic improvements in counties that have access to broadband internet. Counties with increased access to broadband internet see reductions in poverty rate and unemployment rate. In addition, zip codes that gain access to broadband internet see increases in the numbers of employees and establishments. In addition, heterogeneity analysis indicates that the positive effects are concentrated in the working age population, those between 25 and 64 years old. This pattern is precisely what is predicted by the literature linking economic conditions to suicide risk.

We are grateful to participants at the Association of Public Policy and Management and the Washington Area Labor Symposium conferences for their helpful comments. Any errors or conclusions are our own. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

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Affordable High-Speed Internet is Spurring Economic Growth and Boosting Small Businesses

Heather Boushey, Chief Economist, Investing in America Cabinet

Access to affordable, reliable, high-speed internet is a cornerstone of the American economy and essential for economic growth. This is also a bipartisan view—Congress has found that “[a]ccess to affordable, reliable, high-speed broadband is essential to full participation in modern life in the United States.” However, nearly a quarter of American households continue to lack access to high-speed internet at home due to high costs, and in certain communities, a lack of necessary infrastructure. In particular, communities of color, Native communities, rural communities, and low-income households are disproportionately disconnected. That’s why, as part of his Internet for All initiative, President Biden committed to connecting every household in America by 2030, deploying over $80 billion in federal funding to expand access to affordable, reliable, high-speed internet across the country.

Core to the success of the President’s plan is the Affordable Connectivity Program (ACP), which provides qualifying households with up to $30 per month (or $75 per month for households on qualifying Tribal Lands) off their internet bill. The ACP is the largest and most successful internet affordability program in our nation’s history, with over 23 million households enrolled—one in every six households. Because the Administration worked with internet providers to offer high-speed internet plans that are fully covered by the Affordable Connectivity Program, most of these 23 million households have received high-speed internet for free.

Without further funding from Congress, the Affordable Connectivity Program will expire today. This expiration would increase the price of internet for the more than 23 million households enrolled in the program with significant economic implications. That 23 million includes nearly 11.5 million military families, 4 million seniors, 5.75 million African American households, 5.75 million Latino households, and 320,000 households on Tribal lands. Many families would lose internet all together—a recent FCC survey found that more than three-quarters of respondents would have their service disrupted by losing their ACP benefit. Depriving these families of this funding would leave them without money to spend on other necessities like groceries, education, or healthcare. In some states like Kentucky, Ohio, and Nevada, one in four households are enrolled.

That’s why, since last October, President Biden has called on Congress to extend this benefit through 2024. Democratic Members and Senators have joined him in this effort. But Republican leaders in Congress have failed to act. President Biden is once again calling on Republicans in Congress to join their Democratic colleagues in support of extending funding for the Affordable Connectivity Program, so tens of millions of Americans can continue to access this essential benefit.

This blog describes the economic benefits of access to affordable high-speed internet and the consequences of letting the ACP expire, with a particular focus on the role of internet access in supporting small business creation and economic growth.

The significance of access to high-speed internet in the U.S. economy

The COVID-19 pandemic brought into sharp focus the importance of affordable, reliable, high-speed internet for American businesses and families in the 21 st century economy. Even pre-pandemic, an extensive literature pointed to the significance of access to affordable, reliable, high-speed internet for an array of economic outcomes, including small business formation and economic growth. Small businesses, in particular, are a crucial part of local economies and communities—they are responsible for more than 40% of America’s economic output and two-thirds of net new jobs.

Access to internet is now a must-have for creating and running businesses in the U.S. economy. Businesses engage with customers, suppliers, and services (such as banking and accounting) online; online sales account for 15.9 percent of total retail sales, nearly nine percent more than a year ago; and most job seekers now look for jobs online. Several recent papers have found causal links between expansions of broadband (high-speed internet) access and the creation of new businesses, as well as the growth of existing businesses, in urban and near-urban areas. The literature indicates that rural broadband expansion also likely affects business growth and formation, particularly in knowledge-intensive industries.

These results may stem from increased access to new ideas, supply chains, and customers. Additionally, some researchers have described the effects of the internet as allowing businesses in smaller cities or more rural areas to “ borrow size ”—to take advantage of the benefits of larger cities without the costs associated with physically locating in those cities.

The economic benefits of access to high-speed internet extend beyond small business formation to health and education. Researchers have found that virtual visits with trained medical professionals can improve patient outcomes at a lower cost and lower risk of infection than traditional care provided in-person. Unfortunately, a survey of community-based health centers found that, among those not using telehealth, lack of access to broadband was a barrier to adoption, especially for those living in rural areas. In education, survey data show that students in rural school districts with high-speed internet at home had higher grades and standardized test scores than their peers without access, with ensuing economic effects.

These effects and others mean that affordable high-speed internet supports a stronger and more resilient economy. One study comparing countries that belonged to the Organization for Economic Cooperation and Development between 1996 and 2007 found that a 10-percentage-point increase in broadband penetration was associated with a 0.9 to 1.5 percentage point increase in per capita economic growth. Another study focused on the United States estimated that counties gaining broadband access in the early 2000s experienced a 1.8 percentage point increase in employment rates. More generally, a number of studies support benefits of broadband internet for employment , labor productivity , and economic resilience .

Expanding access to reliable, high-speed internet

Despite the importance of affordable, reliable, high-speed internet for economic equity and growth, in 2022, only 75.9 percent of U.S households had wired high-speed internet service at home according to the American Community Survey with adoption varying by income, race, and the density of their community (Figure 1).

This variation means that expanded access to and adoption of broadband is important for reducing economic disparities. Additionally, it points to two separate challenges for broadband adoption. First, some households—particularly those in rural communities—do not have access to broadband internet because it is not offered in their community. According to the latest data by the Federal Communications Commission, 7.2 million physical locations—either homes or small businesses—are unable to access broadband internet due to a lack of the necessary infrastructure. A second challenge is that some households are unable to afford it; in the beginning of 2021, 15 percent of home broadband users reported having trouble paying for high-speed internet service, including 34 percent of users in households with less than $30,000 in income.

Through its Investing in America agenda, the Biden-Harris administration is making targeted investments in addressing both of those challenges and thereby gaining the benefits of widespread high-speed internet adoption for business formation, employment, health, education, and economic growth. The Broadband Equity Access and Deployment program, created by the Bipartisan Infrastructure Law, invests over $40 billion in building out high-speed internet infrastructure in every U.S. state and territory. In addition, $2.75 billion is included for the Digital Equity Act , which provides grants for communities to take advantage of high-speed internet connections. At the same time, the Affordable Connectivity Program reduces the price of internet for eligible households.

Over time, these investments will connect every American with affordable, reliable, high-speed internet. But connectivity is not enough, it’s essential that Americans can afford the service. The Biden Harris-Administration is asking Congress to extend funding the Affordable Connectivity Program, so that millions of households do not lose the connections that enable them to run their own business, access telehealth, and participate in remote and virtual education.

Without action from Republican leaders, funding for the ACP will soon lapse. This means that families will see their internet bills increase by $30 or more, and communities across the country will lose out on the economic benefits of connectivity. When accounting for lost economic opportunities, education, and telehealth services, one study found that vulnerable communities are projected to lose over $20 billion annually in economic benefits. Furthermore, the first two years of the Biden-Harris Administration were the two highest years of applications to start businesses on record—the third year is on track to surpass both. The loss of ACP subsidies could threaten to slow this pace because many of these businesses rely on access to high-speed internet to succeed.

The economic benefits of programs that expand access to high-speed internet, like the Affordable Connectivity Program, are well-established. Continued funding for the Affordable Connectivity Program would not only benefit the 23 million households that are able to afford high-speed internet through the program, but also all Americans who benefit from thriving small businesses and strong, stable, equitable economic growth.

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Twenty years of gender equality research: A scoping review based on a new semantic indicator

Introduction

Data collection

Text processing and keyword extraction

Classification of research topics

Evaluation of semantic importance

Overview of main topics

Compensation.

Decision-making.

Career progression.

Performance.

Organization.

Human capital.

Emerging topics: Leadership and entrepreneurship

Research gaps and conclusions

Supporting information

Acknowledgments

Twenty years of gender equality research: A scoping review based on a new semantic indicator

Filippo Chiarello

Paola Rovelli

Associated Data

Introduction

Data collection

Text processing and keyword extraction

Classification of research topics

Evaluation of semantic importance

Overview of main topics

Compensation

Decision-making

Career progression

Performance

Organization

Human capital

Emerging topics: Leadership and entrepreneurship

Research gaps and conclusions

Supporting information

Funding Statement

Data Availability

The intellectual structure of gender equality research in the business economics literature

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Women’s entrepreneurship and culture: gender role expectations and identities, societal culture, and the entrepreneurial environment

1 Introduction

2 Methodology

2.1 Assembling

2.2 Arranging

2.3 Assessing

3.1 Main lines of research

3.2 Connection between lines of research: turning points

4 Research agenda

4.1 Beyond women on board and TMT: the middle management

4.2 Human resources and people management

4.3 Organisational behaviour

4.4 What about customers?

4.5 Wage gap reasons

4.6 Tangible and intangible assets

4.7 Gender in corporate governance and business ethics

4.8 Size and geography matter

5 Conclusions

Acknowledgements

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