Economic development is often held to be beneficial for gender equality. However, there is good reason to believe that persistent institutions such as religion, legal traditions, and family practices, also matter. This article provides an empirical assessment of the relative importance of development and historical determinants of gender equality at the cross-national level. To capture this long-term relationship, a new index of gender equality that stretches back to 1950 is introduced. The determinants of this index are analysed using data on development and religious, legal, and family traditions. We find that variables measuring the long-lasting institutions of countries can be as important as economic development in determining gender equality outcomes. Thus, our study highlights the importance of considering the historical context of a country when analysing the determinants of gender equality gaps. (JEL codes: J160, N000, Z130, J120)

1 Introduction

Achieving gender equality, a situation in which the social and cultural environment recognizes both men and women as being of equal value, is a desirable goal from a social justice perspective.1 Moreover, it has also come to be seen as smart economics and not without cause. Equalling the playing field of women vis-à-vis men has been shown to have a positive effect on development outcomes such as children’s educational attainment and health (Strauss and Thomas 1995; Currie and Moretti 2003), agricultural productivity (FAO 2011), economic growth (Klasen 2002; Klasen and Lamanna 2009), and the quality of government, particularly by reducing corruption (Dollar et al. 2001).

However, much of the world is still characterized by gender inequality. Especially in developing countries, many women face limits to their freedom in terms of movement, but also when it comes to access to resources and political voice. They are discriminated against not just in the workplace and the political arena, but also within the household. This negatively affects women’s decision-making powers and sometimes even their survival chances. Besides the intrinsic importance of women’s well-being (Sen 2001), women gaining an equal position to men also has instrumental importance for attaining other development goals (World Bank 2011). This article seeks to provide an empirical assessment of the relative importance of economic development on the one hand, and the persistent institutions of a country on the other, in determining gender equality. To achieve this, the article will introduce new, long-term data on gender equality.

Broadly speaking, the literature offers two sets of explanations for cross-national disparities in gender equality: modernization (development) and institutions (especially the informal institutions that shape norms and values). The modernization view argues that as countries become more economically developed, industrialized, democratic, and their populations more educated, the resources available to women increase and give them a better bargaining position (Inglehart and Baker 2000). An alternative mechanism through which modernization is expected to lead to gender equality is that it brings about shifts in the norms and values of societies, which promote more gender egalitarian attitudes (Norris and Inglehart 2003).

The cross-sectional correlation between income and gender equality in 2011 illustrated in Figure 1 broadly supports the modernization view. However, this figure also highlights some clear outliers. Most prominent are wealthy countries such as Qatar and Saudi-Arabia which nevertheless perform poorly on measures of gender equality (UNDP 2011). Even among highly developed European countries, there are substantial differences in matters related to gender equality such as parental leave and labour force participation (Bruning and Plantenga 1999).

Figure 1

Gender equality and economic development in 2011.

Figure 1

Gender equality and economic development in 2011.

One explanation for these counterexamples and the lack of an automatic link between gender equality and economic development lies in the role of long-lasting, historical institutions such as religion, family practices, and legal traditions that may disadvantage women. From this perspective, contrary to the predictions of modernization theory, the norms and values of a society are persistent and rooted in long-lasting institutions, rather than merely lagging behind the development process (Alesina et al. 2013; Branisa et al. 2013). For instance, the historical and cultural legacy of Islamic countries may partly explain what is observed in Saudi Arabia and Qatar (Spierings et al. 2009). Women are strongly disadvantaged by Islamic customs and laws concerning marital and inheritance practices (Htun and Weldon 2011). Likewise, polygamy is a persistent practice in sub-Saharan Africa and associated with greater gender inequality (Tertilt 2006; Bove and Valeggia, 2009).

Another example where economic development does not always translate to gender equality is that of ‘missing women’ (Sen 1992). Although Klasen and Wink (2002) observed improvements in this respect in some countries as their income and education levels increase, they also found that China and India have experienced worsening sex ratios despite rapid economic growth. Part of this results from the availability of sex-selective abortion combined with a strong son preference (Hu and Schlosser 2012), in turn associated with long-standing family systems (Dyson and Moore 1983). Similarly, the historical record suggests that gender equality is not solely determined by the level of development. In North-Western Europe, women had access to labour markets well before the Industrial Revolution, when the region was still poor by current international standards (Horrell and Humphries 1995; De Moor and Van Zanden 2010). Taken together, these examples point to the fact that practices exist within countries or regions, which disadvantage women and are unique and long-standing. These practices will not necessarily change as a result of economic development.

This article will show that, while the development process betters the condition of women, long-lasting institutions are at least equal determinants of cross-national variation in gender equality. Furthermore, our results show that the relation between long-lasting institutions and gender equality is dependent on the level of development of a country.

The article is organized as follows: Section 2 will discuss the literature on the relationship between gender equality and development, history, and culture. In section 3, we will introduce new, long-term data on gender equality. Section 4 discusses the methodology and data. Section 5 presents the results, and the final section concludes.

2 Literature

Much of the literature on gender inequality suggests that as countries develop economically, gender equality will increase. In a recent review of the literature on women’s empowerment and development, Esther Duflo (2012) concludes that the two are closely, though not automatically, related. In an example of a study that examines links from development to gender equality, Doepke et al. (2012) present a model where women’s rights are determined by their returns to education, in turn largely driven by technological progress. Similarly, Goldin (2006) argues that the growth in women’s labour force participation in the US between 1930 and 1950 was due to the increase in service-sector jobs. The decline of footbinding in China provides another example of women’s status improving with economic development. Bossen et al. (2011) claim that as mass-produced textiles replaced domestic production, women’s household confinement was questioned, and with it the practice of footbinding.

A related idea is that over the course of the development process, the relationship between gender equality and economic progress may change. Claudia Goldin (1995) posits a U-shaped relation between married women’s labour force participation and economic development. In the initial stages of growth, men move into higher productivity jobs outside family enterprises, and this income effect depresses women’s labour force participation. However, eventually a tipping point is reached where women’s wage-earning opportunities in the service sector outweigh the family income effect. Alternatively, initial gains in women’s empowerment may temporarily reinforce norms that preclude the inclusion of women in life outside the household (Eastin and Prakash 2013). Das and Desai (2003) find that as economic development in India leads to improvements in a family’s status, women from these families are less likely to work, as women working outside the household is viewed as a taint on family honour.

The idea that economic development will lead to gender equality fits with modernization theory. Proponents of this view argue that economic development leads to occupational specialization, rising educational and income levels, bringing about changes in gender roles, and declining fertility rates. In combination this leads to increased gender equality (Inglehart and Baker 2000). Higher income and education as well as greater control over reproduction provided by modern medicine is associated with lower fertility. Therefore, women spend less of their lifetime bearing and rearing children (Christy 1987; Inglehart and Norris 2003). Another argument is that modernization is associated with more general cultural change. Cavalli (1983), for instance, observes that industrialization encourages egalitarian ideals, such as aspirations for more equality between the two sexes and the idea that society should provide more egalitarian educational and occupational opportunities. Overall, we expect that as countries are more socio-economically developed, they will have higher gender equality (H1).

Although the modernization view suggests that development will bring about gender equality and cultural change, a growing body of literature claims that persistent norms, beliefs, and values matter. Inglehart and Baker (2000, p. 19) highlight that cultural change depends on the heritages of societies and these heritages have autonomous and enduring effects. Hence, besides economic development, the norms of a country are also likely to matter for gender equality. Therefore, to fully understand gender outcomes these long-lasting institutions also have to be studied.

Examples in the literature confirming that norms matter are plentiful. This applies to development outcomes in general, as well as to those related to gender equality. Nunn (2012) argues the importance of taking into account values and beliefs when trying to explain the economic performance of countries. Spolaore and Wacziarg (2013) provide a review of literature showing that development outcomes are influenced by persistent traits that are culturally and genetically transmitted across generation.

Turning to gender outcomes, Branisa et al. (2013) find significant associations of (gendered) development outcomes with long-lasting norms, values, and codes of conduct related to gender equality. Another example is Almond et al. (2013) study of missing women which shows that gender bias continues to exist among immigrants to Canada and can only be explained by taking into account their cultural background. Furthermore, Alesina et al. (2013) demonstrate a relationship between traditional agricultural practices and present-day gender outcomes. By analysing the children of immigrants, they identify culture as a transmission mechanism of attitudes to gender roles.

From a historical perspective, three types of institutions seem particularly important. First, religion is a cultural institution likely to affect gender equality. The religious traditions of the world vary strongly in their prescriptions on the proper role for women. For instance, controlling for the level of economic development, Donno and Russett (2004) found that the position of women is significantly worse in Islamic countries. Catholicism too is associated with less gender equality. Catholic cantons in Switzerland have been shown to have invested substantially less in the education of girls between 1860 and 1930 (Praz 2006).

The second long-lasting cultural institutions likely to affect gender outcomes are the traditions and practices regulating family life. These near-universal institutions hold great weight for communities because they regulate their membership and transmit their values from generation to generation (Shachar 2001). One scholar who has looked at the importance of family ties is David Reher (1998). He considers family ties persistent, historical systems, and observes their impact on policy issues such as old-age care on a European-wide scale. Likewise, Galasso and Profeta (2011) used a family system classification scheme devised by Emmanuel Todd (1985) to explain current day pension system differences within Europe. Duranton et al. (2009) also suggest that family systems have a lasting impact on regional disparities in many social and economic indicators in Europe. Alesina and Giuliano (2010) find that respondents in the World Value Surveys indicating strong family ties have significantly lower female labour force participation and more traditional views on gender roles. Finally, by using Italian data at the regional level, Bertocchi and Bozzano (in press) find that historical family structure matters for gender education gaps.

Lastly, the legal system of a country may influence gender equality. Htun and Weldon (2011) claim that family law ‘shapes virtually every aspect of a woman’s life’, including property rights, the ability to work outside the home, and freedom in marriage. They furthermore illustrate that family law and state-building histories have a substantial influence on present-day gender equality outcomes. For example, in many former British colonies, gender-biased family practices were codified. Moreover, countries where the state-building process required accommodating tribal and religious authorities could result in family law systems that disadvantaged women (Weldon and Htun 2012). Hallward-Driemeier et al. (2013) also look at women’s legal rights over the past fifty years and show that the rights women hold are relevant for women’s labour force participation, education, health condition, and representation in parliament.

Related to this point is the work on legal origins (La Porta et al. 1999, 2008). Although their work has been criticized for being too Europe-centric (Siems 2007), their concept of legal origins as an historically determined ‘style of social control of economic life’ is relevant for gender equality. Legal equality of men and women was an important step towards gender equality, while educational reform, labour market access, and health care priorities all required the active government styles that are associated with civil and socialist law countries (see also Hallward-Driemeier et al. 2013). A stronger legal position of women regarding divorce and property rights is also associated with better outcomes such as higher labour force participation and investment in daughters’ human capital (Gray 1998; Deininger et al. 2013).

Thus, we expect that in societies that are characterized by historical institutions related to religion, family, and legal traditions that are more supportive of the position of women, gender equality will be higher (H2).

Overall, the literature suggests that both development as well as the historical and cultural legacy of a country matter for achieving gender equality. However, it should be noted that the interpretation of our results is limited by the fact that these two sets of relationships can suffer from endogeneity issues. There is the possibility that gender equality is both a cause and a consequence of economic development (Duflo 2012). Such reverse causality issues may also hold for the historical institutions, for instance in a situation where increasing gender equality influences family practices. However, because we are looking at slowly changing historical legacies, reverse causality issues are less of a concern for the latter set of variables (Nunn 2012). The next sections will discuss the data and our method for testing these explanations empirically.

3 Historical Development of Gender Equality

In this section, we present our measure of gender equality from 1950 to 2003 and describe the trends observed in gender equality over time.

3.1 Construction of the gender equality measure

Previous studies seeking to measure gender equality highlight the multidimensionality of the concept. Since the 1990s, measures that capture different aspects of gender equality have become available such as the UNDP’s Gender Empowerment Measure (GEM) and the Gender Inequality Index (GII), and the OECD’s Social Institutions and Gender Index (SIGI).

Most of these measures are limited to the recent time period, focusing on gender equality developments from the 1990s onwards. However, reaching a situation where women have equal rights is generally a long-term process. Major improvements in human capital formation, labour force participation, and longevity can only be observed in the long run (Dorius and Firebaugh 2010). The impact of China’s one-child policy on ‘missing girls’ in China becomes apparent only if sex ratios are compared before and after 1980 (World Bank 2011). Moreover, a historical perspective is not only required to better grasp changes in gender equality over time (Giuliano in press), but also to understand the long-term relationship between gender equality and development.

To provide such a long-term perspective on gender equality, Carmichael et al. (2014) collected historical data on different aspects of gender equality. Information on these measures is provided in Table 1 below. The selection of these indicators is mostly based on the availability of data.

Table 1

Overview of the measures in the Historical Gender Equality Index

Subindex Indicator Range Mean (sd) Countries Years Source 
Health Life exp. ratio 0.73–1.5 0.99 (0.05) 130 1900–2003 UN (2013), lifetable.de, Human Mortality Database, Preston (1975) 
Sex ratio 0.83–1.23 0.97 (0.02) 130 1900–2003 Mitchell (2007), UN (2013) 
Household Marriage age ratio 0.61–0.98 0.85 (0.07) 129 1900–2003 Carmichael (2011) 
Political Parliament seats ratio 0–0.95 0.06 (0.1) 130 1900–2003 Paxton et al. (2008) 
Socio- economic Av. years schooling ratio 0.03–1.46 0.73 (0.26) 130 1950–2000 Barro and Lee (2013) 
Lab. force part. ratio 0.02–1.29 0.6 (0.24) 130 1945–2003 ILO (2010) 
Subindex Indicator Range Mean (sd) Countries Years Source 
Health Life exp. ratio 0.73–1.5 0.99 (0.05) 130 1900–2003 UN (2013), lifetable.de, Human Mortality Database, Preston (1975) 
Sex ratio 0.83–1.23 0.97 (0.02) 130 1900–2003 Mitchell (2007), UN (2013) 
Household Marriage age ratio 0.61–0.98 0.85 (0.07) 129 1900–2003 Carmichael (2011) 
Political Parliament seats ratio 0–0.95 0.06 (0.1) 130 1900–2003 Paxton et al. (2008) 
Socio- economic Av. years schooling ratio 0.03–1.46 0.73 (0.26) 130 1950–2000 Barro and Lee (2013) 
Lab. force part. ratio 0.02–1.29 0.6 (0.24) 130 1945–2003 ILO (2010) 

For the main empirical analysis, these measures are combined in one composite gender equality index: the Historical Gender Equality Index (HGEI). Although the overview in Table 1 is based on non-imputed data, missing data have been imputed to maximize the index’s coverage. Imputations were made only for countries that had at least one observation for each variable, which limits our data coverage to 130 countries. Because the data coverage on the other indicators becomes substantially better after 1950, the HGEI is limited to the period between 1950 and 2003. Nonetheless, this represents a substantial improvement over previous composite indices of gender equality.

To construct the HGEI, we follow a similar strategy to that of the Global Gender Gap (GGG) Index (Hausmann et al. 2012). First, the ratio of women to men for all measures has been taken to capture the gap between women and men. A number below one indicates inequality biased against women, one reflects perfect equality, and a value above one is inequality biased against men. To reflect innate biological differences, the equality benchmark for sex ratio is set to 0.944 and female life expectancy has been corrected by five years.2 The second step is to truncate the ratios above one. Doing so assigns the same score to a country that has reached parity between men and women and one where women have surpassed men. As a third step, we carried out a principal component analysis to see whether our indicators measured the same latent variable, in our case gender equality. The results of the principal component analysis showed that all variables capture one underlying latent variable (eigenvalue 2.18) and Cronbach’s alpha was 0.56, meaning our composite index is moderately reliable.

As a fourth step, the weighted average for the two sub-indices consisting of multiple measures (health and socio-economic status) has been calculated to avoid a single measure driving all variation in our index. Following the strategy of the GGG index, we then normalize the variables in the socio-economic status and health sub-indexes by computing a one percentage point change in terms of standard deviations (by dividing 0.01 by the standard deviation of each variable). These values are then used to determine the weight each variable gets in the sub-index.

Finally the equally weighted arithmetic mean of the four sub-indexes is calculated and multiplied by 100. Thus, our measure ranges between 0 and 100 where zero is complete gender inequality and 100 an equal or better position for women. However, no country in our dataset achieves a score of 100. Between the period 1950 and 2003, Sweden is the most gender egalitarian country with a mean score of 77.30 and achieves the highest score of 93.59 in 2002, while Niger has the lowest mean score of 50.96 and gets the lowest value of 40.23 on the index in 1951.

3.2 Trends in gender equality

Figure 2 presents the overall results of the index as a population-weighted global average of country scores from 1950 to 2003. The good news is that after a slow start in the 1950s and 1960s, the gender equality measure exhibits a steady upward trend. However, it should also be noted that global progress was limited. At a global average of 68 in 2003, gender equality was still well short of the maximum score of 100 on the index. Looking at regional averages reveals further failings in achieving gender equality. Figure 3 shows that the highest gender equality scores are found in Europe, its offshoots, and East Asia. Gender equality in other regions, particularly the Middle East and North Africa (MENA), Latin America, and Southern Asia, was substantially lower. Sub-Saharan Africa is in the middle of the pack, a reflection of the fact that we are measuring equality between genders, rather than their absolute performance.

Figure 2

Population-weighted world average HGEI, 1950–2003.

Figure 2

Population-weighted world average HGEI, 1950–2003.

Figure 3

Regional population-weighted averages of the HGEI, 1950–2000.

Figure 3

Regional population-weighted averages of the HGEI, 1950–2000.

Figure 3 also shows that while there was progress in terms of gender equality everywhere, important regional differences remained. Between-region inequality was persistent, with only Latin America and the Caribbean closing the gap with Europe and North America. Because the measure has an asymptotic limit of one hundred, the lack of convergence is remarkable. The MENA remains the region furthest removed from gender equality throughout the 1950–2003 period. Strikingly, though South Asia and Sub-Saharan Africa are seen to make absolute progress towards gender equality over the period, the gap with the leading regions remains, as countries like India were deteriorating between 1961–1972.

What does the picture look like when we look at individual variables? The past century has seen marked progress in the female to male ratio of life expectancy and decreasing the gender gap in terms of education. To take one example at country level, in 1960 the ratio of female to male life expectancy in India was around 0.87 whereas by 2010 Indian women had achieved near parity in terms of life expectancy with their male peers. Similarly, on a global level, the ratio of female to male education has risen to 0.9.

However, in other areas, progress has been less marked or stagnation has occurred. In terms of the ratios of marriage ages, the number of girls to boys, and political participation, there has been less of a move towards equality. Looking at the sex ratios at ages 0–5 reveals a less rosy picture for Indian women than life expectancy ratios do. The ratio of boys to girls in India declined from 1.04 in 1930 to a current day level of 0.925. China has also experienced falling sex ratios due to sex-selective abortions. Other countries have seen progress towards gender equality in terms of sex ratios, for instance, Brazil which experienced progress starting from the 1870s onwards, from a ratio of 0.89 reaching equality by 1930. Overall, however, the progress in sex ratios was limited, with the world average declining from close to one to 0.97 by 2010. Similar trends are observed in the stagnation of the ratio of marriage ages, and the world average of women in parliament has not managed to reach a level of higher than 23%, with only Rwanda and Sweden making significant progress towards closing this particular gap.

4 Methodology

Global data were collected covering the period 1950 to 2003 to test the possible determinants of the gender equality measure outlined above. Our independent variables consist of two groups: the long-lasting (informal and formal) institutional factors and the political and economic characteristics of countries. The descriptive statistics of the variables are shown in Table 2.

Table 2

Descriptive statistics (N = 117, n = 5237)

Variable Minimum Maximum Mean sd 
HGEI 43.83 93.58 64.23 7.53 
African fam. 0.13 0.34 
Anomic fam. 0.14 0.35 
Stem fam. 0.11 0.32 
Egal. nucl. fam. 0.24 0.43 
Endo. com. fam. 0.23 0.42 
Exo. com. fam. 0.14 0.35 
% Protestant 0.99 0.17 0.19 
% Catholic 0.99 0.37 0.30 
% Islam 0.30 0.29 
Scandinavian/German C. code 0.09 0.29 
English Common Law 0.28 0.45 
French C. Code 0.49 0.50 
Socialist/Communist Laws 0.13 0.34 
log GDPPC 5.31 10.67 8.03 1.06 
Polity IV −10 10 0.32 7.55 
% Education expenditures 0.4 13.04 4.10 1.80 
Inst. international women movement 7.19 33.89 17.24 8.63 
Variable Minimum Maximum Mean sd 
HGEI 43.83 93.58 64.23 7.53 
African fam. 0.13 0.34 
Anomic fam. 0.14 0.35 
Stem fam. 0.11 0.32 
Egal. nucl. fam. 0.24 0.43 
Endo. com. fam. 0.23 0.42 
Exo. com. fam. 0.14 0.35 
% Protestant 0.99 0.17 0.19 
% Catholic 0.99 0.37 0.30 
% Islam 0.30 0.29 
Scandinavian/German C. code 0.09 0.29 
English Common Law 0.28 0.45 
French C. Code 0.49 0.50 
Socialist/Communist Laws 0.13 0.34 
log GDPPC 5.31 10.67 8.03 1.06 
Polity IV −10 10 0.32 7.55 
% Education expenditures 0.4 13.04 4.10 1.80 
Inst. international women movement 7.19 33.89 17.24 8.63 

To measure the long-lasting institutions of societies, we focus on religion (Maoz and Henderson 2013), legal origins (Teorell et al. 2013), and family systems (Todd 1985). While our measure of family systems is time invariant, data on religion and legal origins are available in panel data form from 1946 onwards. Our first variable, religion, is the percentage of the population that identifies as Muslim, Protestant, or Catholic and is taken from the World Religion Dataset (WRD). This dataset provides detailed information about religious adherence worldwide for every 5-year period since 1945.3 As a measure of long-lasting formal institutions determining the style of governance, we include the legal origins of the countries from the Quality of Government dataset available annually from 1946 onwards. The legal origins variable has four categories: (i) common (reference category), (ii) French civil, (iii) Socialist, and (iv) Scandinavian/German civil law.4 Family system is a categorical variable which classifies countries according to their egalitarianism in inheritance practices, the freedom they allow children in terms of spousal selection, and co-residence practices. Rijpma and Carmichael (2013) scrutinise Todd’s classification of family systems by comparing Todd’s classification of countries to a classification created based on the measures from Murdock’s (1967)Ethnographic Atlas. We use six categories: (i) egalitarian nuclear (reference category), (ii) stem, (iii) endogamous community, (iv) exogamous community, (v) anomic, and (vi) African families.5

To capture the effect of economic characteristics and development on gender equality, we include log GDP per capita (Maddison 2008) and total public spending on education as a percentage of GDP (Wejnert 2007).6 The Polity IV index (Marshall et al. 2011) is used to control for level of democracy, as democracy and gender equality have been shown to be related (Inglehart et al. 2002). The Polity IV index scores countries on the quality of their democratic institutions. It is based on three criteria: competitiveness of political participation, competitiveness of executive recruitment, and constraints on chief executive. The scale ranges from −10 (hereditary monarchy) to +10 (consolidated democracy). For ease of interpretation, the Polity IV index has been standardized to range between zero and one in which a higher score is a higher level of democracy.

We also include a global measure on the institutionalization of women’s equality (Paxton et al. 2006). It is measured based on three world-level indicators: (i) cumulative foundings of WINGOs; (ii) the cumulative count of international conferences, treaties, and groups related to women; and (iii) the cumulative count of countries ratifying the 1919 Maternity Protection Convention. Finally, we use a time trend and add regional fixed effects to control for the effect of omitted global and regional characteristics. The regional dummies are—(i) East Asia and the Pacific, (ii) Europe and the former Soviet Union, (iii) the Americas, (iv) the MENA, (v) South Asia, and (vi) Sub-Saharan Africa (reference category).7

As alternative dependent variables, two other gender equality measures are used. First, we used the GII from the UNDP (2011) for 2000, giving an indication of the inequality between men and women in health, empowerment, and labour market participation. It is designed to measure the shortfall in human development due to gender inequality. The index ranges between 0 and 1 and was rescaled so that a higher score on the index implies higher gender equality. The second alternative gender equality measure is the World Economic Forum’s GGG (Hausmann et al. 2012). Although its data only start in 2006, it is conceptually closer to our index, as it measures the extent to which women have achieved equality to men in economic participation, economic opportunity, political empowerment, educational attainment, and health and well-being. Its earliest set of scores (2006) are therefore compared with our measure for the year 2000. Our measure has a correlation of 0.76 and 0.86 points with the GII and GGG, respectively.

4.1 Estimation strategy

The bivariate relation between the independent variables and our HGEI is provided in the Spearman’s correlation matrix in Table A2 in the appendix.

The effect of institutions and development on gender equality is studied using the following panel data specification:  

(1)
Git=a+βkZi+βlKit+βmXit+βnϑt+ɛit

G is gender equality at time t for country i, α is the constant, Z represents the time-invariant institutional characteristics, namely, family systems, for country i, whereas K represents time-varying institutional characteristics, religion and legal institutions for country i, at time t. X represents the time-varying economic and political characteristics for country i at time t. ϑ represents the year variable which is included to capture long-term growth in gender equality, and ɛ is the error term. Because a number of variables of interest are either time-invariant or hardly change over time (i.e. religion and legal institutions), pooled OLS is used (clustering standard errors at the country level). Equation (1) is estimated in three separate models (Table 3). The first model includes only historical institutional variables, the second model takes into account time-varying economic and political characteristics, and the third model includes regional dummies and a variable measuring the global institutionalization of women’s equality. Additional model specifications and robustness checks are discussed in the following section.

Table 3

Results for OLS regressions of gender equality, 1950–2003

 (1) (2) (3) 
African fam. −3.16*** −0.18 −0.01 
1.11 1.23 1.7 
Anomic fam. −1.49** −0.65 0.08 
0.72 0.69 0.76 
Stem fam. 0.8 0.83 0.38 
1.59 1.27 1.55 
Endo. com. fam. −6.90*** −5.41*** −3.56** 
1.08 1.15 1.39 
Exo. com. fam. −0.15 0.08 0.41 
1.72 1.39 1.16 
% Protestant 8.75*** 5.34*** 4.45*** 
1.34 1.13 1.11 
% Catholic 0.89 0.15 −0.38 
0.81 0.71 0.71 
% Islam −3.47*** −3.92*** −3.54*** 
1.07 1.09 0.79 
Scandinavian/German C. code 1.9 2.63* 1.2 
1.83 1.45 1.63 
French C. Code −0.66 −0.15 −0.73 
0.74 0.69 0.74 
Socialist/Communist Laws 5.51*** 6.74*** 4.59*** 
1.65 1.35 1.23 
Year 0.17*** 0.13*** 0.03 
0.01 0.01 0.03 
log GDPPC  1.49*** 1.51*** 
 0.34 0.37 
Polity IV  0.06 −0.01 
 0.04 0.04 
% Education expenditures  0.38*** 0.46*** 
 0.1 0.1 
Inst. international women movement   0.19*** 
  0.05 
East Asia & Pacific   0.89 
  1.83 
Europe & Central Asia   1.94 
  1.62 
Americas   0.33 
  1.56 
Middle East and North Africa   −3.05** 
  1.26 
South Asia   −2.77** 
  1.32 
Constant 59.85*** 47.26*** 46.56*** 
1.09 2.95 3.31 
Observations 5237 5237 5237 
Adjusted R2 0.62 0.66 0.68 
 (1) (2) (3) 
African fam. −3.16*** −0.18 −0.01 
1.11 1.23 1.7 
Anomic fam. −1.49** −0.65 0.08 
0.72 0.69 0.76 
Stem fam. 0.8 0.83 0.38 
1.59 1.27 1.55 
Endo. com. fam. −6.90*** −5.41*** −3.56** 
1.08 1.15 1.39 
Exo. com. fam. −0.15 0.08 0.41 
1.72 1.39 1.16 
% Protestant 8.75*** 5.34*** 4.45*** 
1.34 1.13 1.11 
% Catholic 0.89 0.15 −0.38 
0.81 0.71 0.71 
% Islam −3.47*** −3.92*** −3.54*** 
1.07 1.09 0.79 
Scandinavian/German C. code 1.9 2.63* 1.2 
1.83 1.45 1.63 
French C. Code −0.66 −0.15 −0.73 
0.74 0.69 0.74 
Socialist/Communist Laws 5.51*** 6.74*** 4.59*** 
1.65 1.35 1.23 
Year 0.17*** 0.13*** 0.03 
0.01 0.01 0.03 
log GDPPC  1.49*** 1.51*** 
 0.34 0.37 
Polity IV  0.06 −0.01 
 0.04 0.04 
% Education expenditures  0.38*** 0.46*** 
 0.1 0.1 
Inst. international women movement   0.19*** 
  0.05 
East Asia & Pacific   0.89 
  1.83 
Europe & Central Asia   1.94 
  1.62 
Americas   0.33 
  1.56 
Middle East and North Africa   −3.05** 
  1.26 
South Asia   −2.77** 
  1.32 
Constant 59.85*** 47.26*** 46.56*** 
1.09 2.95 3.31 
Observations 5237 5237 5237 
Adjusted R2 0.62 0.66 0.68 

Standard errors (clustered at country level) reported below coefficients.

*p < 0.10, **p < 0.05, ***p < 0.01”.

Multiple imputation specifically designed for panel data was used to address missing-data issues (Honaker and King 2010). Imputations are especially important here because calculating the composite index requires all underlying variables to be present. Linear interpolation has also been tried as an imputation strategy. Generally, this gave similar results, though some of the results considering developing countries separately are sensitive to the imputation strategy, as missing data are most problematic for developing countries.8

5 Results

Looking at religion, the results of the first model show countries that have a higher percentage of Protestants among its population have significantly higher gender equality, whereas a higher percentage of Muslims is associated with significantly lower gender equality. The percentage Catholics does not have a significant impact on gender equality. However, the effect of endogamous community persists even when we control for the effect of Islam on gender equality. This finding implies that the disadvantageous position of women in the Middle East may be the result of family structure as well as Islam, which provides empirical evidence for the discussion in the literature related to the position of women in Islam (see for instance al-Hibri 1997).

Countries characterized by family systems that are thought to be unfavourable to women and promote traditional gender roles indeed have lower gender equality, even after taking into account the differences in legal structure and religion. Compared with egalitarian nuclear families, we find lower gender equality in countries with African family systems, characterized by a tradition of polygamy; in countries with endogamous community family systems emphasizing large households and fraternal bonds; and in countries with anomic family systems. To illustrate, a country which is characterized by endogamous community family structures, mostly found in the MENA, is expected to score 6.9 points less on the HGEI compared with a country characterized by egalitarian nuclear family systems—a substantial difference on our index where about 90% of the countries score between 50 and 75. Furthermore, countries characterized by anomic family and African family structures score 1.5 and 3.1 points less, respectively. No significant differences emerge between stem and egalitarian nuclear family structures. This contradicts Todd (1985) who argues that maternal authority in stem families is stronger than in the egalitarian nuclear family. In line with what has been presented above, there is a significant improvement in gender equality, as the time trend is positively significant.

Among the legal origins variables, countries with socialist legal origins score 5.5 points higher on the HGEI. This is not surprising considering the experience of Soviet countries where gender equality was achieved in various dimensions by active policy implementation (Schalkwyk and Woroniuk 1999; Htun and Weldon 2011). Other legal origin measures do not seem to have a significant impact on explaining gender equality.

The second model also includes the development indicators. Religion and legal origins are still meaningful sources of explanation for gender equality even after accounting for differences in the level of development. The relation between gender equality with endogamous community families and Protestantism becomes weaker after taking into account the level of development in a country while the impact of socialism has strengthened. These findings are investigated further in Table 5. Regarding the development characteristics themselves, a 10% increase in GDP per capita leads to a 0.15-point increase on the HGEI (a 1.5-point increase for each doubling of per capita GDP), whereas a one percentage point increase in the percentage of GDP spent on education leads to a 0.4-point increase on the HGEI.

In the third model, regional fixed effects are included as additional controls to account for omitted regional characteristics. Doing so has no substantial impact on the conclusions drawn from previous model.9 We also include a measure that captures the international institutionalization of women’s equality in the world.10 While including this variable does not change the interpretation of our main interest variables, the institutionalization of women’s equality on a global level is positively and significantly related to gender equality.

Table A3 in the appendix provides cross-sectional specifications of other non-historical gender equality indices (the GII and the GGG).11 Generally, the models are similar, though the effects of educational expenses are no longer significant in the cross-sectional specifications. The most important difference between the cross-sectional models is that per capita GDP seems to have little predictive power for the GGG index. A further difference is related to the effect of religion. Unlike our index and the GGG, a larger share of Catholics is associated with higher gender equality according to the GII. The African family system also has a stronger impact on the contemporary indices. Furthermore, socialist legal origins are significantly related to our long-run gender equality index where they do not have an explanatory power regarding the cross-sectional results for the other indices. The lack of importance of socialist systems is probably due to the lack of long-term data in the contemporary indices. Many formerly socialist countries experienced a reversal in the trend towards gender equality after 1991, meaning current indices cannot pick up their achievements.

To judge the relative impact of the variables, we need standardized coefficients. Table 4 reports these coefficients for the most complete model (3) and shows that institutional variables clearly matter for gender equality. Socialist legal origins followed by religion, Protestantism, and Islam in particular, have large effects among the explanatory variables. However, we emphasize that the development level of countries is as important for gender equality outcomes as institutional characteristics are. For instance, a one standard deviation increase in log GDP per capita is associated with a 0.21 standard deviation increase in the HGEI. The international institutionalization of equality also has a large positive impact on gender equality (β = 0.21).

Table 4

Standardized coefficients based on model 3

 Standardized coefficients 
African fam. −0.000 
Anomic fam. 0.004 
Stem fam. −0.016 
Endo. com. fam. −0.196 
Exo. com. fam. 0.019 
% Protestant 0.110 
% Catholic −0.015 
% Islam −0.135 
Scandinavian/German C. code 0.046 
French C. Code −0.048 
Socialist/Communist Laws 0.206 
log GDPPC 0.211 
Polity IV −0.014 
% Education expenditures 0.110 
Inst. international women movement 0.214 
East Asia & Pacific 0.039 
Europe & Central Asia 0.112 
Americas 0.018 
Middle East and North Africa −0.141 
South Asia −0.085 
Year 0.069 
Observations 5237 
 Standardized coefficients 
African fam. −0.000 
Anomic fam. 0.004 
Stem fam. −0.016 
Endo. com. fam. −0.196 
Exo. com. fam. 0.019 
% Protestant 0.110 
% Catholic −0.015 
% Islam −0.135 
Scandinavian/German C. code 0.046 
French C. Code −0.048 
Socialist/Communist Laws 0.206 
log GDPPC 0.211 
Polity IV −0.014 
% Education expenditures 0.110 
Inst. international women movement 0.214 
East Asia & Pacific 0.039 
Europe & Central Asia 0.112 
Americas 0.018 
Middle East and North Africa −0.141 
South Asia −0.085 
Year 0.069 
Observations 5237 

To test whether the effect of our explanatory variables differs depending on the stage of development, we split our data into developed versus developing countries. For this classification, we adopt the World Bank definition of countries with a Gross National Income (GNI) less than $4,085 classified as developing versus the developed countries with a higher GNI. Table 5 shows that some of our indicators do seem to matter in different ways for gender equality in the two stages of development. For instance among our family systems measures, endogamous community family is detrimental for gender equality only in developed countries. Another interesting finding is that socialist legal origin only matters significantly for developed countries. These results underline the conclusions drawn from Table 4 that both institutional conditions and economic development are important drivers of gender equality and that they can work for or against gender equality together.

Table 5

Results for OLS regressions of gender equality, 1950–2003 by level of development

 Developing countries Developed countries 
African fam. 1.46  
1.9  
Anomic fam. 1.88 −1.43 
1.04 0.78 
Stem fam.  −0.57 
 1.51 
Endo. com. fam. −1.37 −5.19* 
1.86 2.26 
Exo. com. fam. 3.59 −0.59 
2.38 1.01 
% Protestant 1.76 4.82*** 
1.78 1.13 
% Catholic 0.71 −1.07 
0.89 0.91 
% Islam −3.81** −2.83* 
0.99 1.12 
Scandinavian/German C. code  1.35 
 1.55 
French C. Code −0.35 −1.23 
1.12 0.93 
Socialist/Communist Laws 1.71 4.45*** 
1.55 1.22 
log GDPPC 0.92 1.13* 
0.88 0.46 
Polity IV 0.02 −0.05 
0.04 0.05 
% Education expenditures 0.46* 0.40*** 
0.16 0.11 
Inst. international women movement 0.18* 0.20*** 
0.07 0.06 
East Asia & Pacific 4.69* −2.32 
1.72 1.25 
Europe & Central Asia 0.73 0.63 
2.49 1.38 
Americas −0.21 −0.11 
1.6 1.24 
Middle East and North Africa −3.19* −4.27 
1.46 2.6 
South Asia −3.30*  
1.37  
Year 0.03 0.06 
0.05 0.03 
Constant 49.35*** 51.66*** 
6.75 3.39 
Observations 2129 3108 
Adjusted R2 0.57 0.71 
 Developing countries Developed countries 
African fam. 1.46  
1.9  
Anomic fam. 1.88 −1.43 
1.04 0.78 
Stem fam.  −0.57 
 1.51 
Endo. com. fam. −1.37 −5.19* 
1.86 2.26 
Exo. com. fam. 3.59 −0.59 
2.38 1.01 
% Protestant 1.76 4.82*** 
1.78 1.13 
% Catholic 0.71 −1.07 
0.89 0.91 
% Islam −3.81** −2.83* 
0.99 1.12 
Scandinavian/German C. code  1.35 
 1.55 
French C. Code −0.35 −1.23 
1.12 0.93 
Socialist/Communist Laws 1.71 4.45*** 
1.55 1.22 
log GDPPC 0.92 1.13* 
0.88 0.46 
Polity IV 0.02 −0.05 
0.04 0.05 
% Education expenditures 0.46* 0.40*** 
0.16 0.11 
Inst. international women movement 0.18* 0.20*** 
0.07 0.06 
East Asia & Pacific 4.69* −2.32 
1.72 1.25 
Europe & Central Asia 0.73 0.63 
2.49 1.38 
Americas −0.21 −0.11 
1.6 1.24 
Middle East and North Africa −3.19* −4.27 
1.46 2.6 
South Asia −3.30*  
1.37  
Year 0.03 0.06 
0.05 0.03 
Constant 49.35*** 51.66*** 
6.75 3.39 
Observations 2129 3108 
Adjusted R2 0.57 0.71 

Standard errors (clustered at country level) reported below coefficients.

*p < 0.1, **p < 0.05, ***p < 0.01.

Table A4 in the appendix provides further robustness checks on the development variables. First, in the literature, the relation between economic development and gender equality is argued to vary by level of economic development (Eastin and Prakash 2013). This U-shaped link has been tested by separately considering developing and developed countries (Table 5), and through a quadratic GDP per capita term. The joint significance of per capita GDP and its quadratic term provides some evidence for a U-shaped relationship. However, for the entire range of per capita GDP the effect of income is positive. To control for endogeneity due to unobserved time-invariant country characteristics, random and fixed effects model were estimated. Both are very similar to the pooled OLS specification, though the time-invariant family systems and legal origins cannot be estimated in the FE model. Finally, an instrumental variable model was used to assess reverse causality running from gender equality to economic development. Lagged GDP per capita and latitude were used as instruments (Gallup et al. 1999). This specification shows a minor diminution of coefficient on the per capita GDP variable, but it remains a statistically significant predictor of gender equality.

To see whether our explanatory variables have different explanatory power for different dimensions of gender equality, we regress our full set of explanatory variables on single components of the HGEI (see Tables A5 and A6). There are a few interesting results for the explanatory variables that had a robust relation with gender equality in the previous models. For instance, Protestantism seems to be particularly relevant for closing the gender gap in education and parliament, whereas Islam is especially associated with gender inequality in labour force participation and parliamentary activity. This finding is in line with the World Bank’s MENA 2013 report finding that despite significant improvements both in overall human development and closing the gender gap in various aspects (e.g. life expectancy, education) in the MENA region, women’s participation in the public sphere, both for labour force and political participation remains one of the main challenges in achieving gender equality. Furthermore, socialist legal systems, which had a robust relation with gender equality seems to matter most for labour force participation, education, and participation in parliament. Thus, one can conclude that the institutional structure of countries seems to be particularly relevant for the gender gap in the public sphere. Economic development measured by GDP per capita seem to matter particularly for closing the gender gap in life expectancy and education. Moreover, estimating the models for the single components using non-imputed data does not change the interpretation of the results.

6 Conclusion

Over the past decades the idea that gender equality matters has steadily gained credence. The reasons for this are many, ranging from the intrinsic importance of treating women as equal to men, to ‘smart economics’—the idea that improving gender equality is beneficial for development outcomes such as children’s health, or for increased economic growth due to higher female labour force participation (World Bank 2011). Given the importance of achieving gender equality, this article explores the determinants of cross-national differences in gender equality outcomes over a fifty-year period (1950–2003).

The literature suggests that both development (modernization) and long-term, (in)formal institutions could matter for gender equality. To analyse these from a long-term perspective, we have constructed a new index of gender equality spanning five decades. We find that long-term institutions, especially religion and legal systems, are almost as important for gender equality outcomes as economic development.

These results illustrate how gender equality is determined by a range of different factors. Furthermore, institutional factors continue to matter in different stages of development. This provides a better understanding of why countries that achieve economic development, such as China and India, still struggle to achieve gender equality. This is key to keep in mind when designing policy geared towards tackling gender inequality. The specific historical and cultural legacy of countries will mean that, when it comes to reducing gender gaps, there is no one size fits all policy. Even when simply trying to understand why gender gaps persist, a multifaceted approach is required.

Our results also suggest avenues for future research on the determinants of gender equality. For one, there should be a closer inspection of the relative role of institutions and development at different levels of income. Simply breaking our sample in two sets of countries already revealed differences and it would be useful to analyse in-depth the interaction with development levels. Second, the dominant norms and values in a country can also be measured directly through surveys and this can sharpen our view of how long-term legacies matter. Finally, an even longer-term view on gender equality might be warranted. Progress towards gender equality and the development process go back to at least the nineteenth century. Data on these issues have been collected (Van Zanden et al. 2014), though much work remains, and with this contribution we hope to have inspired scholars to take up this gauntlet in future research.

Acknowledgements

For their comments and suggestions, we thank Maarten Prak, Jan Luiten van Zanden, Lotte van der Vleuten, Jan Kok, and seminar participants at the Groningen Political Economy, Growth and Development seminar, the CESifo Venice summer Institute workshop ‘The Determinants of Gender Gaps: Institutional Design and Historical Factors’, and two anonymous referees for their useful comments.

Funding

This work is part of the research programme ‘Agency, gender, and economic development in the world economy 1850–2000’ [nr. 360-53-150], which is financed by the Netherlands Organisation for Scientific Research (NWO). Attendance of the Venice summer Institute workshop was made possible by CESifo.

1 Gender is generally used to emphasize the social and cultural, as opposed to the biological distinctions, between the sexes (OED).
2 See Klasen and Wink (2003) for a discussion on the ‘missing girls’. Furthermore, the UN’s gender related development index assumes that due to biological advantages women will live on average five years longer than men, which we take into account before taking the ratio of women to men in life expectancy.
3 The results are similar when religion is included in the analysis as a time-invariant categorical measure classifying countries as Muslim, Catholic, and Protestant.
4 Besides the institutional variables, the effect of colonial origin on gender equality has been tested. As the effect of colonial origin on gender equality is not significant, this variable was dropped from the final analysis.
5 More information on the operationalization of family systems can be found in Table A1 in the appendix.
6 We also tested for the effect of urbanization and the size of the workforce employed in the industrial and service sectors. Because these variables are highly correlated with GDP, their inclusion did not provide additional information on the role of socio-economic development on gender equality. The effect of oil rents as a percentage of GDP was also tested and turned out to be insignificant.
7 Although Sub-Saharan Africa largely coincides with the African family system, we keep this regional control in the analysis, as inclusion of this variable does not change the interpretation of the other variables in the regression analysis.
8 The results using interpolation can be found in the working paper version (Dilli, Rijpma and Carmichael 2013).
9 As a geographical control, we tested whether inclusion of latitude and longitude influences the interpretation of our results, which was not the case and the results are therefore not presented.
10 Since the 1975 declaration of the Decade of Women by the United Nations, achieving gender equality has become an issue on the international agenda, creating common interests and strategies for action in gender equality the world over (World Bank 2011).
11 The GII was inverted so the interpretation on the signs of the coefficients is the same as for our own index.

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Appendix A

Table A1

Todd’s family systems

Family type Attitudes to liberty (defined by co-residence and type of spouse selection) Attitudes to symmetry (defined by inheritance) Country examples 
Egalitarian nuclear family Free, with obligatory exogamy Symmetry France, Switzerland, Poland, Romania, Italy, Greece, Spain, Portugal, partly Latin America 
Exogamous community family Parents Symmetry Russia, Yugoslavia, Slovakia, Bulgaria, Hungary, Albania, China, India and Cuba 
Endogamous community family Custom Symmetry Arab world, Turkey, Afghanistan, Iran, Pakistan, Azerbaijan, Turkmenistan, and Uzbekistan 
Anomic Family Free, without obligatory exogamy Indifference Burma, Thailand, Laos, Philippines, Cambodia, Malaysia, Indonesia, Madagascar, Sri Lanka 
Stem family Parents Asymmetry Germany, Austria, Belgium, Norway, Sweden, Israel, Japan, and Korea 
African family Indifference, generally strong prohibitions of consanguinity Indifference All Africa except Northern African countries and South Africa 
Family type Attitudes to liberty (defined by co-residence and type of spouse selection) Attitudes to symmetry (defined by inheritance) Country examples 
Egalitarian nuclear family Free, with obligatory exogamy Symmetry France, Switzerland, Poland, Romania, Italy, Greece, Spain, Portugal, partly Latin America 
Exogamous community family Parents Symmetry Russia, Yugoslavia, Slovakia, Bulgaria, Hungary, Albania, China, India and Cuba 
Endogamous community family Custom Symmetry Arab world, Turkey, Afghanistan, Iran, Pakistan, Azerbaijan, Turkmenistan, and Uzbekistan 
Anomic Family Free, without obligatory exogamy Indifference Burma, Thailand, Laos, Philippines, Cambodia, Malaysia, Indonesia, Madagascar, Sri Lanka 
Stem family Parents Asymmetry Germany, Austria, Belgium, Norway, Sweden, Israel, Japan, and Korea 
African family Indifference, generally strong prohibitions of consanguinity Indifference All Africa except Northern African countries and South Africa 
Table A2

Spearman’s Correlation Matrix between Variables

HGEI                      
African fam. −0.037                     
Anomic fam. −0.015 −0.156                    
Stem fam. 0.249 −0.139 −0.146                   
Endo. com. fam. −0.571 −0.21 −0.22 −0.195                  
Exo. com. fam. 0.279 −0.157 −0.165 −0.147 −0.221                 
% Protestant 0.28 0.156 −0.107 0.198 −0.23 −0.062                
% Catholic 0.165 −0.051 0.33 −0.017 −0.365 −0.13 0.035               
% Islam −0.443 −0.088 −0.155 −0.171 0.609 −0.044 −0.156 −0.343              
Scand./German C. code 0.252 −0.123 −0.129 0.772 −0.173 −0.027 0.314 −0.109 −0.172             
French C. Code −0.347 −0.09 0.252 −0.291 0.196 −0.3 −0.246 0.31 0.147 −0.315            
Socialist/ Communist Laws 0.383 −0.152 −0.079 −0.123 −0.214 0.612 −0.091 −0.065 −0.111 −0.126 −0.39           
log GDPPC 0.449 −0.422 −0.043 0.392 −0.198 0.015 0.225 0.152 −0.165 0.355 −0.091 −0.051          
Polity IV 0.431 −0.147 0.065 0.42 −0.36 −0.135 0.314 0.182 −0.342 0.365 −0.189 −0.155 0.502         
% Education expenditures 0.28 0.006 −0.134 0.24 −0.016 0.041 0.238 −0.067 −0.006 0.196 −0.208 −0.01 0.413 0.266        
Inst. internat. women mov. 0.334 0.097 −0.047 −0.04 0.031 0.049 0.08 −0.017 0.008 −0.043 −0.041 0.072 0.168 0.158 0.18       
East Asia & Pacific 0.131 −0.147 0.082 0.058 −0.207 0.077 0.008 −0.166 −0.074 0.094 −0.252 0.161 −0.037 0.024 −0.155 −0.028      
Europe & Central Asia 0.471 −0.229 −0.241 0.384 −0.267 0.311 0.171 0.049 −0.183 0.373 −0.234 0.36 0.477 0.372 0.212 −0.004 −0.226     
Americas 0.032 −0.203 0.507 −0.189 −0.286 −0.142 −0.049 0.545 −0.268 −0.167 0.382 −0.134 0.101 0.095 −0.115 −0.079 −0.2 −0.313    
MENA −0.4 −0.159 −0.167 −0.056 0.622 −0.087 −0.197 −0.299 0.504 −0.131 0.187 −0.163 0.1 −0.362 0.208 0.004 −0.157 −0.245 −0.217   
South Asia −0.262 −0.095 0.027 −0.089 0.245 0.026 −0.121 −0.173 0.104 −0.079 −0.156 −0.098 −0.285 −0.005 −0.207 −0.018 −0.094 −0.147 −0.13 −0.102  
Year 0.334 0.097 −0.047 −0.04 0.031 0.049 0.082 −0.016 0.009 −0.043 −0.041 0.072 0.169 0.158 0.18 −0.028 −0.004 −0.079 0.004 −0.018 
HGEI                      
African fam. −0.037                     
Anomic fam. −0.015 −0.156                    
Stem fam. 0.249 −0.139 −0.146                   
Endo. com. fam. −0.571 −0.21 −0.22 −0.195                  
Exo. com. fam. 0.279 −0.157 −0.165 −0.147 −0.221                 
% Protestant 0.28 0.156 −0.107 0.198 −0.23 −0.062                
% Catholic 0.165 −0.051 0.33 −0.017 −0.365 −0.13 0.035               
% Islam −0.443 −0.088 −0.155 −0.171 0.609 −0.044 −0.156 −0.343              
Scand./German C. code 0.252 −0.123 −0.129 0.772 −0.173 −0.027 0.314 −0.109 −0.172             
French C. Code −0.347 −0.09 0.252 −0.291 0.196 −0.3 −0.246 0.31 0.147 −0.315            
Socialist/ Communist Laws 0.383 −0.152 −0.079 −0.123 −0.214 0.612 −0.091 −0.065 −0.111 −0.126 −0.39           
log GDPPC 0.449 −0.422 −0.043 0.392 −0.198 0.015 0.225 0.152 −0.165 0.355 −0.091 −0.051          
Polity IV 0.431 −0.147 0.065 0.42 −0.36 −0.135 0.314 0.182 −0.342 0.365 −0.189 −0.155 0.502         
% Education expenditures 0.28 0.006 −0.134 0.24 −0.016 0.041 0.238 −0.067 −0.006 0.196 −0.208 −0.01 0.413 0.266        
Inst. internat. women mov. 0.334 0.097 −0.047 −0.04 0.031 0.049 0.08 −0.017 0.008 −0.043 −0.041 0.072 0.168 0.158 0.18       
East Asia & Pacific 0.131 −0.147 0.082 0.058 −0.207 0.077 0.008 −0.166 −0.074 0.094 −0.252 0.161 −0.037 0.024 −0.155 −0.028      
Europe & Central Asia 0.471 −0.229 −0.241 0.384 −0.267 0.311 0.171 0.049 −0.183 0.373 −0.234 0.36 0.477 0.372 0.212 −0.004 −0.226     
Americas 0.032 −0.203 0.507 −0.189 −0.286 −0.142 −0.049 0.545 −0.268 −0.167 0.382 −0.134 0.101 0.095 −0.115 −0.079 −0.2 −0.313    
MENA −0.4 −0.159 −0.167 −0.056 0.622 −0.087 −0.197 −0.299 0.504 −0.131 0.187 −0.163 0.1 −0.362 0.208 0.004 −0.157 −0.245 −0.217   
South Asia −0.262 −0.095 0.027 −0.089 0.245 0.026 −0.121 −0.173 0.104 −0.079 −0.156 −0.098 −0.285 −0.005 −0.207 −0.018 −0.094 −0.147 −0.13 −0.102  
Year 0.334 0.097 −0.047 −0.04 0.031 0.049 0.082 −0.016 0.009 −0.043 −0.041 0.072 0.169 0.158 0.18 −0.028 −0.004 −0.079 0.004 −0.018 
Table A3

Results for cross-sectional OLS regressions of historical gender equality index compared to present-day indices in 1995/2000

Variable HGEI GII GGG 
African fam. −5.91 −0.19*** −27.32*** 
3.54 0.04 8.84 
Anomic fam. −0.75 −0.05* 4.08 
1.58 0.03 3.26 
Stem fam. 0.33 0.02 0.79 
2.03 0.03 3.46 
Endo. com. fam. −5.65** −0.16*** −23.11*** 
2.67 0.05 5.13 
Exo. com. fam. −0.69 0.02 5.38 
1.73 0.03 3.79 
% Protestant 14.85*** 0.12* 41.52*** 
3.46 0.06 8.92 
% Catholic −0.14 0.06* 6.76 
2.06 0.03 4.89 
% Islam −3.02 −0.05 −3.99 
3.1 0.06 5.72 
Scandinavian/German C. code −1.19 0.04 −8.48 
2.67 0.03 5.58 
French C. Code 0.68 0.03 −3.8 
1.8 0.04 3.91 
Socialist/Communist Laws 3.52 0.06 −6.93 
2.41 0.04 5.48 
log GDPPC 1.94* 0.12*** 1.98 
0.94 0.02 2.41 
Polity IV 0.08 0.36 
0.17 0.35 
% Education expenditures 0.13 −1.22 
0.49 0.01 1.4 
East Asia & Pacific −4.09 −0.06 −17.17** 
 3.07 0.05 7.41 
Europe & Central Asia −3.8 −0.09* −12.10* 
3.03 0.05 6.96 
Americas −5.57 −0.22*** −22.42*** 
3.27 0.05 6.51 
Middle East and North Africa −5.03 −0.06 −4.42 
3.14 0.05 7.1 
South Asia −5.44 −0.02 −8.35 
3.87 0.05 7.59 
Constant 56.42*** −0.32*** 62.12*** 
7.25 0.12 18.76 
Observations 89 89 89 
Adjusted R2 0.75 0.84 0.66 
Variable HGEI GII GGG 
African fam. −5.91 −0.19*** −27.32*** 
3.54 0.04 8.84 
Anomic fam. −0.75 −0.05* 4.08 
1.58 0.03 3.26 
Stem fam. 0.33 0.02 0.79 
2.03 0.03 3.46 
Endo. com. fam. −5.65** −0.16*** −23.11*** 
2.67 0.05 5.13 
Exo. com. fam. −0.69 0.02 5.38 
1.73 0.03 3.79 
% Protestant 14.85*** 0.12* 41.52*** 
3.46 0.06 8.92 
% Catholic −0.14 0.06* 6.76 
2.06 0.03 4.89 
% Islam −3.02 −0.05 −3.99 
3.1 0.06 5.72 
Scandinavian/German C. code −1.19 0.04 −8.48 
2.67 0.03 5.58 
French C. Code 0.68 0.03 −3.8 
1.8 0.04 3.91 
Socialist/Communist Laws 3.52 0.06 −6.93 
2.41 0.04 5.48 
log GDPPC 1.94* 0.12*** 1.98 
0.94 0.02 2.41 
Polity IV 0.08 0.36 
0.17 0.35 
% Education expenditures 0.13 −1.22 
0.49 0.01 1.4 
East Asia & Pacific −4.09 −0.06 −17.17** 
 3.07 0.05 7.41 
Europe & Central Asia −3.8 −0.09* −12.10* 
3.03 0.05 6.96 
Americas −5.57 −0.22*** −22.42*** 
3.27 0.05 6.51 
Middle East and North Africa −5.03 −0.06 −4.42 
3.14 0.05 7.1 
South Asia −5.44 −0.02 −8.35 
3.87 0.05 7.59 
Constant 56.42*** −0.32*** 62.12*** 
7.25 0.12 18.76 
Observations 89 89 89 
Adjusted R2 0.75 0.84 0.66 

Standard errors (clustered at country level) reported below coefficients.

*p < 0.10, **p < 0.05, ***p < 0.01.

Table A4

Results for OLS regressions of gender equality, 1950−2003: specification with random effects, fixed effects, quadratic GDP per capita term, and instrumental variables

 Non−linear RE FE IV IV 
First stage Second stage 
African fam. −0.96 −0.71  −0.15** −0.4 
1.82 1.82  0.06 1.56 
Anomic fam. 0.07 −0.15  −0.02 
0.91 0.91  0.05 0.89 
Stem fam. −1.57 −1.45  −0.04 −1.53 
1.65 1.67  0.03 1.4 
Endo. com. fam. −4.98*** −4.87***  −0.16*** −3.77*** 
1.49 1.51  0.05 1.29 
Exo. com. fam. −0.21 −0.19  −0.09* 0.99 
1.34 1.39  0.05 1.03 
% Protestant 0.58 0.6 0.51 −0.20*** 1.24** 
0.65 0.66 0.59 0.05 0.52 
% Catholic −0.04 −0.06 −0.01 −0.03 0.14 
0.44 0.44 0.32 0.03 0.31 
% Islam −1.25** −1.24** −0.86** −0.03 −2.80*** 
0.43 0.43 0.37 0.03 0.34 
Scand./German C. code 1.96 2.04  0.03 2.21 
1.83 1.9  0.04 1.45 
French C. Code −2.86*** −2.85***  −0.07** −2.46*** 
0.84 0.91  0.03 0.56 
Socialist/Communist Laws 1.04 0.81  −0.21*** −0.32 
1.15 1.23  0.07 0.82 
log GDPPC −5.76 1.26** 1.53***  1.25*** 
4.38 0.44 0.4  0.27 
gdp 2 0.43     
0.27     
Polity IV −0.04 −0.04 −0.02 0.01** −0.08*** 
0.03 0.03 0.03 0.01 
% Education expenditures 0.32*** 0.31*** 0.29*** 0.02*** 0.45*** 
0.06 0.07 0.06 0.05 
Inst. internat. women move. 0.22*** 0.23*** 0.25*** −0.01*** 0.24*** 
0.04 0.05 0.04 0.03 
East Asia & Pacific 0.73 0.77  0.23*** 1.83 
1.97 2.01  0.06 1.57 
Europe & Central Asia 3.20* 2.99  0.21*** 3.71** 
1.77 1.77  0.07 1.49 
Americas 1.21 0.94  0.11 0.93 
1.7 1.7  0.07 1.53 
Middle East and North Africa −2.75 −3.17*  0.21*** −3.21*** 
1.57 1.47  0.05 1.17 
South Asia −4.40** −4.15**  −0.04 −3.81*** 
1.61 1.58  0.06 1.4 
Year 0.04 0.04 0.01** 0.03 
0.03 0.03 0.02 0.02 
log GDPPC (10y lag)    0.85***  
   0.02  
lat    0.00***  
    
Constant 78.31*** 50.03*** 46.63*** 1.29*** 49.16*** 
17.84 3.88 3.11 0.2 2.45 
Observations 5237 5237 6563 4338 4338 
Adjusted R2 0.68 0.65 0.77 0.95 0.69 
 Non−linear RE FE IV IV 
First stage Second stage 
African fam. −0.96 −0.71  −0.15** −0.4 
1.82 1.82  0.06 1.56 
Anomic fam. 0.07 −0.15  −0.02 
0.91 0.91  0.05 0.89 
Stem fam. −1.57 −1.45  −0.04 −1.53 
1.65 1.67  0.03 1.4 
Endo. com. fam. −4.98*** −4.87***  −0.16*** −3.77*** 
1.49 1.51  0.05 1.29 
Exo. com. fam. −0.21 −0.19  −0.09* 0.99 
1.34 1.39  0.05 1.03 
% Protestant 0.58 0.6 0.51 −0.20*** 1.24** 
0.65 0.66 0.59 0.05 0.52 
% Catholic −0.04 −0.06 −0.01 −0.03 0.14 
0.44 0.44 0.32 0.03 0.31 
% Islam −1.25** −1.24** −0.86** −0.03 −2.80*** 
0.43 0.43 0.37 0.03 0.34 
Scand./German C. code 1.96 2.04  0.03 2.21 
1.83 1.9  0.04 1.45 
French C. Code −2.86*** −2.85***  −0.07** −2.46*** 
0.84 0.91  0.03 0.56 
Socialist/Communist Laws 1.04 0.81  −0.21*** −0.32 
1.15 1.23  0.07 0.82 
log GDPPC −5.76 1.26** 1.53***  1.25*** 
4.38 0.44 0.4  0.27 
gdp 2 0.43     
0.27     
Polity IV −0.04 −0.04 −0.02 0.01** −0.08*** 
0.03 0.03 0.03 0.01 
% Education expenditures 0.32*** 0.31*** 0.29*** 0.02*** 0.45*** 
0.06 0.07 0.06 0.05 
Inst. internat. women move. 0.22*** 0.23*** 0.25*** −0.01*** 0.24*** 
0.04 0.05 0.04 0.03 
East Asia & Pacific 0.73 0.77  0.23*** 1.83 
1.97 2.01  0.06 1.57 
Europe & Central Asia 3.20* 2.99  0.21*** 3.71** 
1.77 1.77  0.07 1.49 
Americas 1.21 0.94  0.11 0.93 
1.7 1.7  0.07 1.53 
Middle East and North Africa −2.75 −3.17*  0.21*** −3.21*** 
1.57 1.47  0.05 1.17 
South Asia −4.40** −4.15**  −0.04 −3.81*** 
1.61 1.58  0.06 1.4 
Year 0.04 0.04 0.01** 0.03 
0.03 0.03 0.02 0.02 
log GDPPC (10y lag)    0.85***  
   0.02  
lat    0.00***  
    
Constant 78.31*** 50.03*** 46.63*** 1.29*** 49.16*** 
17.84 3.88 3.11 0.2 2.45 
Observations 5237 5237 6563 4338 4338 
Adjusted R2 0.68 0.65 0.77 0.95 0.69 

Standard errors (clustered at country level) reported below coefficients. Note: R2 for RE model based on single imputation.

*p < 0.10, **p < 0.05, ***p < 0.01.

Table A5

Results for OLS regressions of gender equality, 1950–2003 by component of the historical gender equality index (with imputations)

 Sex ratio Life exp. ratio Marriage age ratio Labour force part. ratio Av. years schooling ratio Parl. seats ratio 
African fam. 0.01 0.03** 0.01 0.01 0.02 
0.01 0.01 0.01 0.07 0.06 0.02 
Anomic fam. −0.01 −0.06 0.07** 0.01 
0.01 0.01 0.04 0.03 0.01 
Stem fam. −0.01** −0.02*** −0.01 −0.01 0.03 0.01 
0.01 0.01 0.01 0.06 0.03 0.03 
Endo. com. fam. −0.01 −0.02* −0.12** −0.04 
0.01 0.01 0.01 0.05 0.05 0.02 
Exo. com. fam. −0.01** 0.01 −0.01 −0.01 −0.02 0.05** 
0.01 0.01 0.01 0.04 0.03 0.03 
% Protestant −0.02** 0.02** 0.01 0.11*** 0.13*** 
0.01 0.01 0.03 0.04 0.03 
% Catholic 0.02*** 0.09*** 0.08*** 0.02 
0.01 0.01 0.03 0.03 0.01 
% Islam −0.01* −0.03*** −0.16*** −0.08*** −0.03** 
0.01 0.01 0.03 0.03 0.02 
Scand./German C. code 0.02** 0.01 0.02 −0.09** 0.06* 
0.01 0.01 0.01 0.06 0.04 0.03 
French C. Code −0.02 −0.05* 0.02 
0.01 0.01 0.03 0.03 0.01 
Socialist Laws 0.02* 0.02** 0.14** 0.09** 0.06** 
0.01 0.01 0.01 0.06 0.04 0.02 
log GDPPC 0.00*** 0.02*** 0.02*** 0.02 0.09*** 0.01 
0.02 0.01 0.01 
Polity IV 0.00** 0.00* −0.00*** 
% Edu. expenditures 0.00** 0.01** 0.01*** 0.01*** 
Inst. women move. 0.00** 0.00** 0.01*** 0.00*** 0.00** 
East Asia & Pacific −0.02** 0.03** 0.05*** −0.05 0.08 −0.01 
0.01 0.01 0.01 0.07 0.06 0.03 
Europe & Central Asia −0.02* 0.03*** 0.03** −0.03 0.06 0.02 
0.01 0.01 0.01 0.07 0.06 −0.03 
Americas −0.01 0.02* 0.02* −0.13* 0.1 
0.01 0.01 0.01 0.07 0.06 0.03 
MENA −0.01 0.02* 0.05*** −0.21*** −0.01 −0.06*** 
0.01 0.01 0.01 0.06 0.05 0.02 
South Asia −0.03** −0.02* 0.03*** −0.16** −0.08 0.01 
0.01 0.01 0.01 0.07 0.05 0.02 
Year 0.00*** 
Constant 1.03*** 0.80*** 0.63*** 0.74*** −0.13 −0.1 
0.02 0.03 0.02 0.15 0.11 0.07 
Observations 5237 5237 5237 5237 5237 5237 
Adjusted R2 0.49 0.38 0.38 0.50 0.53 0.42 
 Sex ratio Life exp. ratio Marriage age ratio Labour force part. ratio Av. years schooling ratio Parl. seats ratio 
African fam. 0.01 0.03** 0.01 0.01 0.02 
0.01 0.01 0.01 0.07 0.06 0.02 
Anomic fam. −0.01 −0.06 0.07** 0.01 
0.01 0.01 0.04 0.03 0.01 
Stem fam. −0.01** −0.02*** −0.01 −0.01 0.03 0.01 
0.01 0.01 0.01 0.06 0.03 0.03 
Endo. com. fam. −0.01 −0.02* −0.12** −0.04 
0.01 0.01 0.01 0.05 0.05 0.02 
Exo. com. fam. −0.01** 0.01 −0.01 −0.01 −0.02 0.05** 
0.01 0.01 0.01 0.04 0.03 0.03 
% Protestant −0.02** 0.02** 0.01 0.11*** 0.13*** 
0.01 0.01 0.03 0.04 0.03 
% Catholic 0.02*** 0.09*** 0.08*** 0.02 
0.01 0.01 0.03 0.03 0.01 
% Islam −0.01* −0.03*** −0.16*** −0.08*** −0.03** 
0.01 0.01 0.03 0.03 0.02 
Scand./German C. code 0.02** 0.01 0.02 −0.09** 0.06* 
0.01 0.01 0.01 0.06 0.04 0.03 
French C. Code −0.02 −0.05* 0.02 
0.01 0.01 0.03 0.03 0.01 
Socialist Laws 0.02* 0.02** 0.14** 0.09** 0.06** 
0.01 0.01 0.01 0.06 0.04 0.02 
log GDPPC 0.00*** 0.02*** 0.02*** 0.02 0.09*** 0.01 
0.02 0.01 0.01 
Polity IV 0.00** 0.00* −0.00*** 
% Edu. expenditures 0.00** 0.01** 0.01*** 0.01*** 
Inst. women move. 0.00** 0.00** 0.01*** 0.00*** 0.00** 
East Asia & Pacific −0.02** 0.03** 0.05*** −0.05 0.08 −0.01 
0.01 0.01 0.01 0.07 0.06 0.03 
Europe & Central Asia −0.02* 0.03*** 0.03** −0.03 0.06 0.02 
0.01 0.01 0.01 0.07 0.06 −0.03 
Americas −0.01 0.02* 0.02* −0.13* 0.1 
0.01 0.01 0.01 0.07 0.06 0.03 
MENA −0.01 0.02* 0.05*** −0.21*** −0.01 −0.06*** 
0.01 0.01 0.01 0.06 0.05 0.02 
South Asia −0.03** −0.02* 0.03*** −0.16** −0.08 0.01 
0.01 0.01 0.01 0.07 0.05 0.02 
Year 0.00*** 
Constant 1.03*** 0.80*** 0.63*** 0.74*** −0.13 −0.1 
0.02 0.03 0.02 0.15 0.11 0.07 
Observations 5237 5237 5237 5237 5237 5237 
Adjusted R2 0.49 0.38 0.38 0.50 0.53 0.42 

Standard errors (clustered at country level) reported below coefficient.

*p < 0.10, **p < 0.05, ***p < 0.01.

Table A6

Results for OLS regressions of gender equality, 1950−2003 by component of the historical gender equality index (without imputations)

 HGEI Sex ratio Life exp. ratio Marr. age ratio Lab. force part. ratio Av. years school. ratio Parl. seats ratio 
African fam. −0.05 0.01 0.01 −0.07 0.08 −0.01 
0.03 0.02 0.02 0.04 0.22 0.09 0.03 
Anomic fam. 0.01 −0.02 −0.05 0.08** 0.02 
0.01 0.01 0.02 0.04 0.04 0.02 
Stem fam. −0.09*** −0.01** −0.02*** 0.02 −0.02 −0.01 0.04 
0.02 0.01 0.01 0.02 0.07 0.04 0.03 
Endo. com. fam. −0.02 −0.01 −0.01 −0.01 −0.01 −0.05 0.02 
0.03 0.01 0.02 0.03 0.13 0.08 0.04 
Exo. com. fam. −0.04*** −0.01** 0.02 −0.03 −0.07 0.03 
0.01 0.01 0.01 0.01 0.06 0.05 0.03 
% Protestant 0.02 −0.03 0.01 −0.1 0.15** 0.22*** 
0.03 0.01 0.02 0.03 0.08 0.07 0.04 
% Catholic −0.05* 0.01 −0.24*** 0.11* −0.01 
0.03 0.01 0.01 0.03 0.08 0.06 0.03 
% Islam −0.08*** 0.01* −0.03 −0.25* −0.06 −0.07* 
0.02 0.01 0.01 0.03 0.13 0.07 0.04 
Scand./German C. code 0.06*** 0.03** −0.02 −0.11* 0.05 
0.02 0.01 0.01 0.02 0.07 0.06 0.04 
French C. Code 0.02* −0.01 0.01 −0.01 −0.10** 0.05*** 
0.01 0.01 0.01 0.01 0.05 0.05 0.01 
Socialist Laws 0.10*** 0.03* −0.03 0.13* 0.10* 0.11*** 
0.02 0.01 0.01 0.03 0.08 0.06 0.03 
log GDPPC 0.01 −0.00** 0.02*** −0.02 0.08*** 0.02* 
0.01 0.01 0.03 0.02 0.01 
Polity IV 0.00** −0.00*** 
% Educ. exp. 0.02* 
0.01 0.01 
Inst. women move. −0.00*** 0.01 0.01** 
East Asia & Pacific −0.04** 0.02 0.10*** −0.17 0.12 −0.03 
0.04 0.02 0.02 0.04 0.2 0.09 0.03 
Europe & Central Asia 0.01 −0.03* 0.03* 0.09** −0.13 0.1 −0.01 
0.03 0.01 0.02 0.04 0.21 0.09 0.03 
Americas −0.01 −0.02 0.03 0.07* −0.18 0.13 −0.02 
0.03 0.01 0.02 0.04 0.2 0.09 0.03 
MENA −0.04 −0.02* 0.02 0.07** −0.38** 0.08 -0.05* 
0.03 0.01 0.02 0.03 0.18 0.07 0.03 
South Asia  −0.04** −0.02 0.05 −0.44** −0.07 0.04 
 0.02 0.01 0.04 0.18 0.07 0.03 
Year 0.00*** 
Constant 0.53*** 1.03*** 0.83*** 0.77*** 0.79*** −0.11 −0.22*** 
0.07 0.03 0.03 0.07 0.26 0.16 0.08 
Observations 73 657 657 127 256 657 587 
Adjusted R2 0.743 0.553 0.442 0.392 0.667 0.667 0.501 
 HGEI Sex ratio Life exp. ratio Marr. age ratio Lab. force part. ratio Av. years school. ratio Parl. seats ratio 
African fam. −0.05 0.01 0.01 −0.07 0.08 −0.01 
0.03 0.02 0.02 0.04 0.22 0.09 0.03 
Anomic fam. 0.01 −0.02 −0.05 0.08** 0.02 
0.01 0.01 0.02 0.04 0.04 0.02 
Stem fam. −0.09*** −0.01** −0.02*** 0.02 −0.02 −0.01 0.04 
0.02 0.01 0.01 0.02 0.07 0.04 0.03 
Endo. com. fam. −0.02 −0.01 −0.01 −0.01 −0.01 −0.05 0.02 
0.03 0.01 0.02 0.03 0.13 0.08 0.04 
Exo. com. fam. −0.04*** −0.01** 0.02 −0.03 −0.07 0.03 
0.01 0.01 0.01 0.01 0.06 0.05 0.03 
% Protestant 0.02 −0.03 0.01 −0.1 0.15** 0.22*** 
0.03 0.01 0.02 0.03 0.08 0.07 0.04 
% Catholic −0.05* 0.01 −0.24*** 0.11* −0.01 
0.03 0.01 0.01 0.03 0.08 0.06 0.03 
% Islam −0.08*** 0.01* −0.03 −0.25* −0.06 −0.07* 
0.02 0.01 0.01 0.03 0.13 0.07 0.04 
Scand./German C. code 0.06*** 0.03** −0.02 −0.11* 0.05 
0.02 0.01 0.01 0.02 0.07 0.06 0.04 
French C. Code 0.02* −0.01 0.01 −0.01 −0.10** 0.05*** 
0.01 0.01 0.01 0.01 0.05 0.05 0.01 
Socialist Laws 0.10*** 0.03* −0.03 0.13* 0.10* 0.11*** 
0.02 0.01 0.01 0.03 0.08 0.06 0.03 
log GDPPC 0.01 −0.00** 0.02*** −0.02 0.08*** 0.02* 
0.01 0.01 0.03 0.02 0.01 
Polity IV 0.00** −0.00*** 
% Educ. exp. 0.02* 
0.01 0.01 
Inst. women move. −0.00*** 0.01 0.01** 
East Asia & Pacific −0.04** 0.02 0.10*** −0.17 0.12 −0.03 
0.04 0.02 0.02 0.04 0.2 0.09 0.03 
Europe & Central Asia 0.01 −0.03* 0.03* 0.09** −0.13 0.1 −0.01 
0.03 0.01 0.02 0.04 0.21 0.09 0.03 
Americas −0.01 −0.02 0.03 0.07* −0.18 0.13 −0.02 
0.03 0.01 0.02 0.04 0.2 0.09 0.03 
MENA −0.04 −0.02* 0.02 0.07** −0.38** 0.08 -0.05* 
0.03 0.01 0.02 0.03 0.18 0.07 0.03 
South Asia  −0.04** −0.02 0.05 −0.44** −0.07 0.04 
 0.02 0.01 0.04 0.18 0.07 0.03 
Year 0.00*** 
Constant 0.53*** 1.03*** 0.83*** 0.77*** 0.79*** −0.11 −0.22*** 
0.07 0.03 0.03 0.07 0.26 0.16 0.08 
Observations 73 657 657 127 256 657 587 
Adjusted R2 0.743 0.553 0.442 0.392 0.667 0.667 0.501 

Standard errors (clustered at country level) reported below coefficients.

*p < 0.10, **p < 0.05, ***p < 0.01.