WPS6617 Policy Research Working Paper 6617 Women’s Legal Rights over 50 Years What Is the Impact of Reform? Mary Hallward-Driemeier Tazeen Hasan Anca Bogdana Rusu The World Bank Development Research Group Finance and Private Sector Development Team September 2013 Policy Research Working Paper 6617 Abstract This study uses a newly compiled database of women’s rights, including 28 countries that had eliminated all property rights and legal capacity covering 100 countries of the constraints monitored here. In the cross-section over 50 years to test for the impact of legal reforms and within countries over time, the removal of gender on employment, health, and education outcomes gaps in rights is associated with greater participation for women and girls. The database demonstrates of women in the labor force, greater movement out of gender gaps in the ability to access and own property, agricultural employment, higher rates of women in wage sign legal documents in one’s own name, and have employment, lower adolescent fertility, lower maternal equality or non-discrimination as a guiding principle and infant mortality, and higher female educational of the country’s constitution. In the initial period, 75 enrollment. This paper provides evidence on how the countries had gender gaps in at least one of these areas strengthening of women’s legal rights is associated with and often multiple ones. By 2010, 57 countries had important development outcomes. made reforms that strengthened women’s economic This paper is a product of the Finance and Private Sector Development Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at mhallward@worldbank.org. The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Produced by the Research Support Team Women’s Legal Rights over 50 Years: What Is the Impact of Reform? Mary Hallward-Driemeier, Tazeen Hasan and Anca Bogdana Rusu 1 JEL Codes: K37; N40; O1 Key terms: Law; gender; property rights; legal capacity; employment; health; education; empowerment. 1 World Bank, Development Research Department. The authors gratefully recognize financial support from the UK’s Department For International Development (DFID). The opinions expressed here do not necessarily reflect the position of the World Bank, its Board of Executive Directors or the member countries they represent. Special thanks go to Sarah Iqbal who, along with Tazeen Hasan, supervised the data collection effort, and to the team members from the Women, Business and the Law who contributed to the database: Garam Dexter, Khrystyna Kushnir, Lourdes Lizarraga Ortega, Nayda Almodovar Reteguis, Paula Tavares, Thibault Meilland and Yasmin Klaudia bin Humam. In addition, Abhinav Goel, Ashley S. Zohar, Erin F. Rogers, Lindsey Scannell, Sarah Knapp, Shazia Akhter, Tatyana Chursova, Yulia Dovgaya and Zachary Walter conducted research for the database as part of their internships with the World Bank Group. Comments can be sent to mhallward@worldbank.org. Introduction Rights matter. They matter in themselves. The question here is what is the evidence that they matter for other outcomes of interest – namely the ability to pursue economic opportunities, and health and education outcomes? Existing research shows that strengthening women’s economic and legal rights has a real and positive impact on women’s labor force participation, investment and agricultural productivity. However, most of the literature focuses on a particular country, examining differences in property rights across groups of individuals or looking at a particular reform episode. The “50 Years of Women’s Legal Rights Database” offers an opportunity to expand the analysis – with comparable indicators across 100 countries and covering 50 years. The legal rights focused on here can be grouped into three broad categories. The first regards the ability to access and own property. This can mean land, but it also means other types of assets more generally. The second is legal capacity, whether women have the same ability as men to enter into legal agreements in their own name. The last is the approach to principles of equality and non-discrimination within the constitution. Such principles can be recognized in general, or with enumerated groups (e.g. non-discrimination based on gender or sex). But in some countries laws governing property, marriage and inheritance can be explicitly exempt from these principles in the constitution. The database highlights the extent to which gender gaps in these three areas have been widespread, recognized in all regions and across all income groups. But the time dimension also shows that there has been change. Not only countries, but entire regions have eliminated the constraints examined here. Today’s rich countries of the OECD had their share of gender gaps in the 1960s and 1970s. However, today, they have removed all of the ones covered in this 2 study. In the countries of Eastern Europe and Central Asia, only Turkey had some gender gaps in these laws; it no longer does. In Latin America, there are now only two exceptions to the laws on legal capacity and property rights. And Sub-Saharan Africa, the region with the highest rates of gender gaps in the initial period, has removed more than half of them by 2010. Progress towards women’s equal rights is possible (see companion paper for a more detailed discussion of legal reforms and the factors that help trigger reforms). At the same time, there are still countries with gender gaps in these rights. And some countries have increased the number of constraints since the 1960s. On net, both in South Asia and the Middle East & North Africa, the net number of constraints has remained fairly stable, with both some reforms and some new constraints being introduced. Given the variation in the legal rights both across countries and over time, how are they correlated with outcomes? We focus on employment, health and education as these are traditionally areas where women and girls have not enjoyed the same benefits and access as men and boys. They are also key indicators of well-being. The paper begins by looking at comparisons across countries. This has the advantage of allowing a wider range of outcome variables to be examined. Unfortunately, gender disaggregated data are not available for many of the indicators except in recent years. However, there are indicators for employment that go back 30 years, and there are some health and education indicators that cover the entire 50 years. For those indicators for which we have sufficient time variation that straddle reform episodes, we look at the impacts of the law within countries over time. Finally, we examine whether the effects of legal reforms vary either by level of development or by the strength of the rule of law. Is it that having formal recognition of rights is only important once countries reach a 3 certain level of development, or do de jure rights have little benefit in a society that does not uphold the law? This is important in understanding where reforms are likely to have the greatest impact and where the lack of reform can be the most costly. The following section reviews the literature on rights and women’s empowerment outcomes. The next section describes the data in more detail. The methodology is explained and then the results are discussed. The final section concludes. Review of the Literature Interest in the importance of property rights stretches back centuries. Adam Smith was one of the first to argue forcefully about the economic benefits that come from securing people’s incentive to invest and exert effort. The extent to which it is formal rights that matter, however, is still a matter of debate, particularly in countries with larger rural populations, lower levels of education and pluralist systems for resolving disputes. However, what laws are on the books does determine the rules and whose interests will be protected. They send important signals as to what is acceptable or not, even if parties never make it to a court. And as arms-length transactions become more common, the formal legal system plays a larger role. Many cross-country studies aimed at analyzing how laws and regulations affect employment, including entrepreneurship, look at business regulations. Botero et al. 2004, Klapper et al. 2006 and Djankov et al. 2003 point to the importance of these regulations in explaining cross-country patterns of employment, firm start-ups and use of courts. But they do not look at gender disaggregated results. Indeed, legislation to register property, enforce contracts or access credit is largely gender neutral. However, these laws presuppose one can own property or enter contracts in the first 4 place. The law that determines who has control over assets and thus affects the types of economic opportunities that are available is family law. Family law covers issues of marriage, but also of marital property and who can control it – within the marriage and at its end, whether through divorce or inheritance. And it is here that gender gaps can be—and still too often are— explicit. There are also several country specific studies that find significant impacts of the reforms to family law. In studies that analyze the impact of the Hindu Succession Act Amendment of 2005, equal inheritance rights for girls and women are shown to be correlated with increased educational attainment, higher household investment in girls as well as higher age at marriage (Deininger, Goyal, and Nagarajan, 2010). Equal inheritance rights for women are also associated with higher women’s autonomy (Roy 2008). Assessments of changes in divorce laws in the Unites States show that women were more likely to initiate a divorce in states where women’s position was strengthened. Also the changes in divorce laws were correlated with a fall in domestic violence in these states. As illustrated by Gray (1998) and Stevenson and Wolfers (2006), part of the effect may come from shifts in intra- household bargaining power. Similarly, changes in the family law in Ethiopia were associated with a substantial shift in women’s economic activities (Hallward-Driemeier and Gajigo, 2013). As of 2000, Ethiopia requires both spouses’ consent in managing marital property, enabled women to work outside the home without needing permission from their spouse and raised the minimum marriage age for women. The reform, which is now applicable across the country, was initially rolled out in select regions and cities. Using two nationally representative household surveys, one in 2000 just before the reform and one five years later, Hallward-Driemeier and Gajigo (2013) find that 5 women’s participation in occupations which require work outside the home, full-time hours, and higher skills rose more where the reform had been enacted (controlling for time and location effects). Property rights can be set out in family law as well as in land law. Here too the literature has found significant gender impacts from differences in the strength of rights to land. Secure property rights to land are fundamental to agriculture and rural economic activity. Without secure rights, the incentive to invest is diminished, as it is not clear the rewards of the investment can be enjoyed. In addition, the lack of such rights undermines the land owner’s ability to use it as collateral, leading to credit constraints. Besley (1995) demonstrates that individuals in Ghana vary their investment across plots depending on the security of their rights. Goldstein and Udry (2008) show that in a society where land rights are not secure, it is those at the top of the local hierarchy—those with the more tenured rights—that benefit the most. A number of other empirical studies point to increased agricultural productivity as a result of women controlling larger shares of resources (Saito, Mekonnen, and Spurling 1994; Udry and others 1995; Quisumbing 1996; Besley and Ghatak 2009). More resources in women’s hands is also associated with a decline in poverty (World Bank 2001). And the benefits can transfer across generations. Duflo’s work in South Africa showed that when women received additional resources, the spending on education and food, particularly for girls, went up (Duflo 2003). Indeed, many of the conditional cash transfer programs, inspired by the results of Progresa in Mexico, now specifically target women as recipients (Skoufias and McClafferty 2001). Beyond general principles that give everyone equal access to own property, how property rights are implemented can be important. Even when a household has secure property rights, 6 titling has too often been under a single name, that of the male head of household. As a consequence, many women have been excluded from ownership. Some countries, such as Ethiopia, have tried to address this unbalance by mandating joint titling of land, thus increasing women’s control over land. (Deininger et al. 2008). The benefit of such policies is apparent from Field’s (2007) study of a titling program in the slums of Peru, where she finds a strong impact on labor supply, especially for women. Without the need to physically protect plots and dwellings, women have more time to work away from their home. Thus the literature shows that economic rights can affect women’s employment, health and education outcomes in particular countries and for particular reforms. This paper contributes to the literature by expanding both the country coverage and time dimension of legal indicators available for analysis. It also broadens the set of outcome variables analyzed. It provides further evidence of the scope for legal reforms to expand women’s wellbeing and empowerment. But it also shows that benefits are not automatic. This is true both as rising country incomes is not necessarily associated with closing gender gaps in these economic rights, and because the impact of giving women and girls equal rights is shown to vary by level of development and rule of law. Ensuring women and girls obtain and benefit from stronger protections of the property rights and legal capacity is an active agenda. Data and Methodology The paper uses the newly compiled “50 Years of Women’s Legal Rights” database. The methodology is explained in more detail in the appendix. It draws on the constitutions as well as family, succession and land laws to look at three sets of legal rights for women. The indicators are based on an assessment of de jure rights based on the reading of the constitutions and 7 statutes. There may well be a gap between what is on the books and what happens in practice, but this database focuses on the former as the measures are objective and provide an easy way to benchmark countries across issues, countries and time. The indicators are generally 0-1 measures of whether women and men have the same right. They do not attempt the measure the degree of the inequality, nor are the indicators weighted or aggregated into an index. Access to and control of assets is examined between unmarried men and women and between married men and women. In addition, indicators include whether sons and daughters are treated equally in inheritance, and another whether wives and husbands are treated the same in determining their inheritance shares when the other spouse dies. 2 A second set of indicators concerns legal capacity. These largely stem around ‘head of household’ statutes, both in terms of recognizing a head and who the head can be, and the rights the head can exercise. Gender gaps include the inability of women to be recognized as the head of household. And statutes can give the husband, as head of household, the right to deny permission to his wife to work or pursue a trade or profession. His signature may be required for her to open a bank account, to sign a contract or to initiate legal proceedings. A third set looks at the approach to equality before the law. By 2010 all the countries with a constitution have this principle enshrined in it. Many further have a non-discrimination clause that explicitly enumerates discrimination based on gender or sex as something that is protected against. 3 However, the principle is not universally applied across all areas of the law in some countries. The two most common exceptions come from the formal recognition of 2 Additional measures of the default marital property regime and whether joint titling is allowed are included in the database. As these indicators remain almost unchanged for countries, they are not included in the time series analysis. 3 It should be noted that it is not necessary to enumerate gender or sex if the constitution already has an equality provision. In fact, its presence can sometimes be an indicator of perceived weakness of women’s rights that such a clause was deemed necessary. 8 religious and customary law as prevailing in matters of marriage, property, inheritance – and explicitly exempting religious or customary law from the non-discrimination requirement in the constitution. One lesson that comes out clearly is that ‘women’ are not a homogenous group. In particular, marital status matters. Many of the gender constraints come upon marriage, with the head of household rules the most common example. The formal status of the marriage matters too (e.g. whether it is registered with the state or is a customary marriage) in determining whether statutes, customary or religious law applies to any dispute within that marriage. Another lesson is that there are strong patterns by legal tradition. Those with civil law traditions are more likely to have the head of household rules codified on their books. While those with common law traditions tend not to have those rules, but rather are more likely to recognize customary law and exempt it from constitutional principles of non-discrimination. There can also be differences by religious affiliation, particularly with regard to the formal recognition of religious law, with implications for property statutes too. Figure 1 shows each of the indicators and how it has evolved over time. The indicators are grouped by theme. The height of the line indicates the share of countries that do not have a gender gap on this dimension; the higher the line the more countries treat men and women equally. 9 Figure 1A. One pattern that is striking is that the rights of unmarried women to immoveable property were recognized before those of married women. The difference is also there, but only mildly, for inheritance. The bottom line covers whether joint titling is the default (i.e. whether it automatically applies) in marriage. This has benefits for both spouses. It is more commonly a feature of civil law traditions and not something that changes much over time. It is displayed here, but is not considered in the analysis of reforms. There has been progress in closing gender gaps with regard to legal capacity (figure 1B). Restrictions on women being the head of household are still the most common, with almost one in four countries not recognizing women in this role. On the other hand, restrictions to initiate legal proceedings, or the need for permission to open bank accounts or to enter contracts are now only on the books in 5-10% of the countries in our sample. The ability of a husband to deny his wife permission to work outside the home was in 1960 and still is more common. And progress in the last decade has flattened off. 10 Figure 1B. Figure 1C. 11 The constitutional principle of equality is now recognized everywhere, except for the countries in our sample that do not have a constitution (e.g. UK and Jamaica). The principle of non-discrimination has climbed to over 60% (figure 1C). The interpretation of this latter variable, however, is not always straightforward. Some legal scholars argue it is not necessary if a constitution already has an equality clause; many high-income countries do not have a non- discrimination clause. Indeed, the need to enumerate gender could even be interpreted as a sign of weakness; that doubts about the strength of the equality provisions in safeguarding women’s rights are what led to its inclusion. On the other hand, having this principle included provides additional legal tools to argue against statutes seen as potentially discriminatory. The last figure (figure 1D) depicts countries’ approaches to legal pluralism. Recognition of customary law has been growing since 1960 and to a lesser extent so has recognition of religious law. Some of this reflects the inclusion of new countries post-1960 that included such a provision in their constitution at the time of independence. However, the emphasis here is whether customary and/or religious law – recognized as prevailing over issues of property, marriage and inheritance – is exempt from non-discrimination protections. 12 Figure 1D. Country Coverage One hundred countries were selected to ensure a good regional and income representation. Table 1 shows the distribution across regions, divided into initial income quartiles. In terms of 2010 income categories set by threshold levels of income, there is a disproportionate number of low-income countries included, in part because these are countries where some of the legal constraints for women remain more prevalent and where progress is still needed on employment, health and education outcomes. But there is a good representation of higher-income countries too. This allows for comparisons across the income distribution and to test how the role of income affects the probability of reform (the relationship is very weak; Hallward-Driemeier, Hasan and Rusu 2013) and whether the impact of having a certain protection on the books varies with development. One selection issue did arise. Certain countries had to be excluded as it was not possible to find the relevant statutes, not only historically but even today – itself a powerful indicator of 13 the state of rights in those countries. Of the 100 countries that are included, there are some gaps in early years or pre-independence. However, by 2010, only Niger’s laws regarding property rights to unmarried men and women could not be located. Table 1 : Regional and Income Representation of Countries (1960) Number of Quartiles of Initial Income Levels Region Countries Lowest Lower Middle Upper Middle Upper EAP 12 5 3 3 1 ECA 10 0 4 6 0 LAC 15 0 1 11 3 MENA 8 0 5 3 0 OECD 17 0 0 2 15 SAR 5 5 0 0 0 SSA 33 16 14 2 1 Total 100 26 27 27 20 Approach The legal indicators cover the period 1960-2010. The aim is to look at how changes in these indicators affect outcomes in women’s and girls’ economic opportunities, education, health, and empowerment. However, before analyzing the time dimension, we first start with the cross-country relationships between a large set of outcomes and each of the legal indicators. Table 2 presents the cross-country variation in the legal indicators and their association with outcomes. In each regression, each country appears once, generally in the year of its most recent household survey. Each of the legal indicators is entered in a separate regression, so each cell in Table 2 represents the results of different estimations. A number of country characteristics are controlled for, including GDP per capita and the sectoral composition of the economy. The size of the agricultural, industry or service sectors can 14 have an independent impact on the prevalence of employment categories (e.g. wage employment tends to rise as the service sector expands; natural resource sectors often do not employ as many workers), and may also indicate the range of opportunities that are available in an economy. 4 Another control used is whether a country was in a recent conflict and the intensity of the conflict. Conflicts disrupt economic, health and education outcomes, particularly if they are on a large scale. However, the post-conflict era could mark an opportunity for reforms if there is a new constitution or as statutes are reformed. Whether this opportunity is taken by reformers to address gender gaps is an empirical question. The measures of conflict also have the benefit of covering the entire sample period. The rule of law is another control used, but not in all specifications as it is only available since 1985. 5 It is recognized that the probability of reform itself is not necessarily exogenous from all the outcomes of interest. Greater participation of women in paid employment may contribute to political pressures to reform laws, which then may further enable more women to pursue employment opportunities. More women in parliament may be associated with reforming statutes that give women greater property rights and legal capacity. The specification thus lags country characteristics; they are thus predetermined. We examined different lag structures of one, five and ten years. The five-year lag is our preferred specification; all the legal indicators and country characteristics in the regression tables are lagged by five years. Some reforms are unlikely to lead to immediate large-scale responses. In many cases it may take a few years – for the information to become widely known and for 4 These measures of sectoral composition are available for all countries but Switzerland and Niger since 1994. In the 1960s coverage is not complete as some of the countries had not yet gained independence. By 1970, almost 85% of the countries have the data available. 5 There are two sources for ‘rule of law’ indicators. The one from ICRG goes back to 1985, but only covers up to 84 of the countries in our sample. There is another source, the Global Governance Indicators, that covers all the countries, but only back until 1996. In the cross-section results, we use the GGI version to maximize coverage, but with the longer time series we use both to test for the importance of either greater time or country coverage. 15 people to then change their behavior. At the same time, too long a lag is likely to dilute the findings, particularly if other changes are also happening. Given many gender disaggregated outcome variables are only available in the 1990s and onwards, such a long lag structure would also restrict the ability to construct a meaningful panel for the analysis. We then turn to the impact of changes in the legal indicators over time. Our preferred specification is a panel regression with country fixed effects that looks at how reforms within a country are associated with changes in the various outcomes. This approach holds all time- invarying characteristics constant, decreasing the concern about omitted variable bias. We also include additional controls for country characteristics that do change over time, such as GDP per capita and whether the country is in a conflict, and we include a trend variable. Each of the legal indicators are then entered one at a time to test for the significance of strengthening women’s legal rights in that area on each of the outcomes. With the country fixed effect, the coefficient on the legal indicator is identified by changes in its value, i.e. by reforms, rather than by differences across countries. This provides the strongest test of the importance of these legal rights. Yit = α + β1Legal_indicatori,t-5 + β2GDPper_capitai,t-5 + β3agri_GDPi,t-5 + β4services_GDPi,t-5 + β5conflicti,t-5 + β6conflict_intensityi,t-5 + β7trend + β8Country_dummies + vi,t-5 (1) This approach is taken for at least one key variable in each of the outcome categories. For economic opportunities, we look at women’s labor force participation. For education, we look at the ratio of girls to boys in primary, secondary and tertiary education. For health, we look at infant mortality and women’s life expectancy. And for empowerment, we look at the age of first marriage and adolescent fertility. 16 There are other outcome measures that can also be examined over time. However, the time-series coverage of these variables is not as extensive. Data may only be available for the last 20 years rather than closer to 50 years. This restricts the ability to identify some of the reforms, particularly with country fixed effects, as there are simply fewer reform episodes covered in 20 years versus 50 years. So, for the wider set of outcome variables we look at shorter panels using random effects. We also aggregate the legal indicators. We combine the individual legal indicators according to their group, resulting in three measures: property rights, legal capacity and constitutional rights. These measures capture more reform episodes, making it easier to identify impacts – although the results cannot tell which sub-component is driving the results. It is also possible that the effectiveness of legal reforms varies across countries. It may be that the benefit of having equal property rights or legal capacity is only realized if a country is already reasonably developed, or where the rule of law is sufficiently established. Alternatively, it may be that having some rights formally recognized is particularly important when the rule of law is otherwise weak. We explore if the impact of legal reforms is non-linear, whether the strength of the rule of law or a country’s level of development affects how the legal rights translate into outcomes. Results Cross-country analysis Table 2 provides the basic cross-country results for each of the legal variables separately, for each of 25 outcome variables. The outcome variables are grouped by theme, with the definitions and sources used listed in the appendix. Looking at the first category, ‘employment’ it 17 is striking the association between equal property rights, particularly with regard to inheritance and joint titling, with increased labor force participation, greater employment outside of agriculture and into wage work. Particularly in low-income countries, women are disproportionately underrepresented in wage employment, a gap that tends to close with income. Stronger property rights appear to reinforce this transition into wage employment. Measures of greater legal capacity are also associated with improved employment outcomes, both for labor force participation more generally and for wage work more specifically. The correlations for the self-employed are generally the same but of the opposite sign than for wage employment. As these are two largest categories of the employed, it is natural that there is some substitution between the two types of work. On the other hand, somewhat surprisingly, unmarried and married property rights are negatively associated with women being employers. However, with a small number of countries in the cross-section that do not recognize equal rights to immovable property for unmarried men and women, the result is not necessarily generalizable to historical relationships. Regarding constitutional principles, non-discrimination (as a clause in the constitution, and for limiting religious law) is associated with higher labor force participation, non- agricultural employment and being an employer. The second category includes the education outcomes. There are fewer significant associations here; not needing permission to work is positively associated with three of the four outcomes and property rights with two. Limiting religious law to conform to non-discrimination principles is associated with higher primary school enrollment, but lower tertiary enrollment. This is due in part from the contribution of countries in the Middle East and North Africa that 18 have very high rates of women in tertiary education and are more likely to recognize religious law without restricting it. There are many beneficial health outcomes that are significantly associated with smaller gaps in gender rights. Measures of women’s life expectancy – as a level and relative to men – are significantly related to all three categories of rights. The negative associations are where either customary or religious law is formally recognized. Another outcome strongly associated with women’s legal rights is access to contraceptives. As much as any particular reform may contribute, this is likely reflects a more open view of women’s roles in society. Among the outcomes where lower values indicate better outcomes (i.e. the shaded columns), both maternal and infant mortality fall with better property rights and greater legal capacity. Recognition of customary law, however, has a positive sign, indicating that mortality rates are higher where customary law prevails. Recall, the results cannot be interpreted as causal; they are associations in the data, controlling for a number of other explanatory variables. The fourth set of outcomes provides additional measures of women’s empowerment. Indicators from all three sets of legal rights are significantly associated with higher rates of women in parliament. Similar patterns hold for the share women among senior officials and managers, although there are some negative associations with some of the legal capacity indicators, driven again by the smaller number of countries with this outcome variable that also have these constraints on the books. Again, the variables that come in strongly negative are ones represented in the cross section by very few countries. In terms of women’s access to finance, whether simply to a bank account or to a loan, legal capacity matters, as do measures of property rights. 19 The final column is shaded, to indicate that for this outcome, lower values reflect better outcomes. Thus negative signs should be interpreted as reforms helping improve the outcome. The indicator is drawn from DHS surveys regarding domestic violence and the share of women who could face a beating for arguing, refusing sex or burning the food. The country coverage is low, but both equal inheritance and non-exemption of customary law are associated with lower rates of women fearing being beaten. Time series analysis For the series with the longest time series dimension, Table 3 looks at the effect of reforms of each legal indicator. 6 The same set of controls is again included. We also allowed for non-linear effects by income. It should be noted that some of the coefficients are quite large, with offsetting interaction effects. This reflects that there is a sizeable variation in the outcome variables across countries – including those with and without reforms. The claim is not that strengthening women’s rights on its own will automatically lead to large improvements in outcomes; but there are significant differences on average between countries with and without gender gaps in rights, controlling for a number of time-varying and non-varying country characteristics. In terms of women’s labor force participation, there are differential effects by level of income; the effect of the reforms in raising labor force participation is almost always stronger in middle- and upper-level-income countries. The inflection point comes in close to the median of the sample; so the beneficial impacts are relevant for a large number of countries. At the median 6 There is no time series dimension available on the variables measuring women’s access to bank accounts or loans; the coverage of the share of women as senior officials and managers is likewise thin and there is no repeating information on the measure of domestic violence. The coverage of female infant mortality is less extensive than of infant mortality overall, so we look at the latter measure in the panel analysis. The same is true of ‘the age of first marriage’ compared to ‘the share of 18 year olds who are married.’ 20 income, an increase of income of one standard deviation would raise women’s labor force participation 2.1% percentage points higher for countries with equal inheritance for wives and husbands than countries where wives do not have the same inheritance rights. Or, for countries at the 75% percentile of income, those that do not require permission for wives to open bank accounts on average have women’s labor force participation that is 2.62% higher. For employment in the non-agricultural sector, the more limited time dimension means that only the regressions on inheritance spanned a sufficient number of reforms. For both indicators, the impact of closing the gender gap in inheritance is associated with an increase in the share of women working outside of agriculture. The effect is positive, with only a very small interaction term that would reduce the effect only at the very upper end of the income distribution. For education, the effects are strongest for primary enrollment, particularly regarding property and inheritance rights. The effects of reform are generally positive, with a negative interaction term indicating the effect is lower as incomes rise. Expanding women’s legal capacity and protecting non-discrimination principles are also generally associated with higher ratios of girls enrolled; again with the effect the strongest in lower-income countries. For example, at the 25th percentile of income, countries that give sons and daughters equal inheritance rights on average have a 6.4 percentage point higher ratio of girls to boys in primary enrollment. The pattern for secondary enrollment is similar, although not always statistically significant. However, for tertiary education the interaction terms with income often flip signs. Whereas legal reforms tend to have the most impact in raising primary education in lower- income countries, they tend to contribute to higher rates of women in tertiary education in higher-income countries. For the age of first marriage, the effect of legal reforms in raising the age of marriage is greater in higher-income countries. This is true for property rights and legal 21 capacity, as well as safeguards that invalidate customary and/or religious law that discriminate based on gender. For health, we look at infant mortality (overall, not gender disaggregated). The impacts of reforms helping lower infant mortality are most significant with indicators of property rights and inheritance. And the effects of closing the legal gender gaps are more beneficial at lower levels of income. At the 25th percentile of income, recognizing women as the head of household is associated on average with a decline in infant mortality of 9.3 deaths per 1000 live births; at the 10th percentile the decline is 12.3. Table 4 then looks at whether there are also differential impacts of reforms by the strength of the rule of law. As this measure is only available for 83 of the 100 countries, it reduces the sample and thus the potential number of reforms spanned by the data. As a result, the list of outcomes is shorter, as is the number of legal indicators with sufficient changes in the time period covered. For women’s labor force participation, the variables that have non-linear impacts by rule of law are unmarried women and men’s property rights, and the recognition and limitations on customary and religious law. In all three cases, the greater equality of rights appears to have a stronger association with women’s labor force participation where the rule of law is otherwise weak. For education, the non-linear effects are most apparent in secondary school. Property rights measures are associated with higher girls’ enrolment where the rule of law is stronger; but the effect is the opposite for inheritance rights where the effect of reforms seems stronger where the rule of law is stronger. The signs are often the same for primary and tertiary education, but the coefficients are not significant. For infant mortality, the effects are also most beneficial where the rule of law is stronger. The same pattern also holds for life expectancy (note: the signs are actually opposite as improvements in infant mortality imply 22 declining rates, while improvements in life expectancy imply rising rates), although often not at statistically significant levels. Table 5 then looks at additional outcome variables that have a sufficient time dimension to span legal reform periods. One of the challenges here is that the data on the outcomes of interest are not always available going back more than 10-20 years, depending on the series, and some, e.g. infant mortality, are not gender disaggregated until relatively recently. For those series with a relatively short time span, they often span an insufficient number of reforms to be able to identify an effect. As a solution, we group the legal indicators into the three categories of property rights, legal capacity and constitutional principles of non-discrimination. Each outcome is again run separately on each of the three sets of legal rights. The same controls (lagged 5 years) are included, GDP per capita, the sectoral composition of the economy, whether it had been in a conflict and the conflict’s intensity, and a year dummy as the same indicator is not necessarily available for all countries in the same year. As the lengths of the panels vary by outcome variable, the regressions will cover differ numbers of reforms, so the comparisons across outcomes should take into account the length of reform periods being examined. For employment, equal property rights are associated with more women working outside of agriculture. However, it is the measure of stronger legal capacity that is most associated with a higher share of women in wage work, and lower shares of women in vulnerable and self- employment. As one of the sub-indicators within legal capacity is whether a husband can deny his wife permission to work, this correlation makes sense. However, the results on non- discrimination are more surprising, being associated with lower wage work and more vulnerable employment and self-employment. 23 For health outcomes, female wasting is lower where property rights are stronger. There are also some non-linear effects at work; both stronger property rights and legal capacity have a stronger association with lower female wasting in lower-income countries. The same is true for maternal mortality, with rates falling the most in lower-income countries with stronger rights for women across all three categories. For access to contraceptives, stronger property rights and legal capacity are associated with greater access, particularly in lower-income countries. However, for non-discrimination, the effect is greater in higher-income countries. All three sets of legal rights are highly significantly associated with the share of women in parliament. Greater legal rights can help empower women to run for office and to have more of the population recognize women as leaders. It is also true that the share of women in parliament is also associated with more reforms to close gender gaps. The relationship thus appears to run both ways, and there are no apparent non-linear effects by income. Conclusion Over the past 50 years, there has been tremendous progress made in closing many of the gender gaps in formal property rights and legal capacity. Change is possible. But it is not complete. And progress has been uneven – across countries and across types of legal constraints to give women equal legal capacity and property rights as men. Enshrining equal rights for women in the law is heralded as having intrinsic value. But there is also a case to be made that there is instrumental value too, that removing gender gaps in these rights will enable women to pursue greater opportunities thereby raising incomes and productivity. The paper examines the evidence on the strengthening of women’s economic legal rights on girls’ education, health outcomes, women’s employment (particularly in wage 24 employment and as employers), and women’s participation in elected office. While the effects cannot be interpreted as causal, the correlations are often strong – both across countries and within countries over time. The benefits of the reforms show signs of having differential effects by income and rule of law across different types of legal indicators. For raising girls’ primary and secondary education, and for lowering infant mortality, the benefits of reforms appear strongest for lower-income countries with relatively weaker rule of law. For employment outcomes, reforms are associated with greater women’s labor force participation and employment outside of agriculture in higher-income countries. 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Washington, DC: World Bank. 28 Appendix: Methodology for “50 Years of Women’s Legal Rights Database” The objective of the database is to track legal reforms affecting women’s property rights and legal status, starting with the law applicable in 2010 and tracking changes backwards in time to 1960 7. For economies that came into existence after 1960, the coding general begins with the economy’s independence in its current form. However, for countries that divide over time (e.g. countries of the former Soviet Union), the individual countries are included over the whole period, each with the laws that governed the initial single country for the relevant years, and then with the country-specific laws and constitutions after independence or separation. For economies that became re-united or unified (i.e. Yemen and Vietnam) within the period between 1960 and 2010, applicable legislation is analyzed and coding is done separately for the individual economies that eventually became one, covering that entire period. The process of data collection consists of desk research using written legislation, such as Constitutions, Personal Status laws, Civil Codes, Family Codes, and Inheritance laws, applicable in the main business city of the economies covered. Online sources of legislation such as the World Bank’s Gender Law Library8, Lexadin 9, the United Nations’ Human Rights Treaties database 10, the law library of the US Congress 11, ILO’s NATLEX database 12, the Notarius International Foreign law database 13, as well as legislation and secondary sources accessed through universities’ databases and virtual libraries such as Harvard Law School’s Law Library14, NYU Law’s Globalex 15, and HeinOnline 16, among others, are used. Also, hard copies of historical legislation not available online were obtained through the Library of Congress Georgetown Law Library and the Jacob Burns Law Library at George Washington University. The 50 Years of Women’s Legal Rights Database analyzes the evolution of gender parity within the legislation of the covered economies through a set of 17 questions in the following areas: 7 This data collection was performed with the guidance of Mary Hallward-Driemeier, Lead Economist Development Research Group, and carried out under the supervision of Sarah Iqbal, Program Officer of Women, Business and the Law, and Tazeen Hasan, Development Economics and PRMGE. Team members from the Women, Business and the Law who contributed are: Garam Dexter, Khrystyna Kushnir, Lourdes Lizarraga Ortega, Nayda Almodovar Reteguis, Paula Tavares, Thibault Meilland and Yasmin Klaudia bin Humam. In addition, Abhinav Goel, Ashley S. Zohar, Erin F. Rogers, Lindsey Scannell, Sarah Knapp, Shazia Akhter, Tatyana Chursova, Yulia Dovgaya and Zachary Walter conducted research for the database as part of their internships with the World Bank Group. 8 http://wbl.worldbank.org/WBLLibrary/elibrary.aspx?libid=17 9 http://www.lexadin.nl/wlg/legis/nofr/legis.php 10 http://www.bayefsky.com/ 11 http://www.loc.gov/law/ 12 http://www.ilo.org/dyn/natlex/natlex_browse.country?p_lang=en&p_country=COL 13 http://212.63.69.85/en/Links/links_international_en.htm 14 http://www.law.harvard.edu/library/research/guides/int_foreign/web-resources/foreign-law_c.html 15 http://www.law.nyu.edu/global/researchtools/globalex/index.htm 16 http://home.heinonline.org/ 29 property ownership, marital regimes, inheritance, property titling, status and capacity, access to the judicial system, and constitutional rights. For all questions concerning the ability of married women to carry out activities independently of their husbands, the key concern is reciprocity. Therefore, where a married man is unable to carry out the same activity without the permission of his wife, the question is not triggered because the provision is reciprocal. It is only triggered where a married man is able to carry out the activity and his wife cannot do so. To make the data comparable across economies, the following assumptions are being used 17: Assumptions about the woman • Resides in the main business city of the economy being examined; • Has reached the legal age of majority and is capable of making decisions as an adult. If there is no legal age of majority, please assume the woman is 30 years old; • Is sane, competent, in good health, and has no criminal record; • Is a lawful citizen of the economy being examined; • Where the question assumes the woman (or man) is married, the marriage is monogamous and registered with the authorities; • Where the question assumes the woman (or man) is married, the marital property regime she (or he) is married under is assumed to be the default marital property regime. • Where the question assumes the woman (or man) is unmarried, she (or he) has never been married. • Customary law is not being used to answer the questions. The only questions examining customary law are the ones that specifically address it. E.g. examining the place of customary law under the Constitution. • The year recorded in the “Year” column is the year the legislation or amendment was enacted, not the year in which it entered into force. • Where the answer differs according to the legal system applicable to the woman in question – as may be the case in economies were legal plurality exists – the answer used is the one applicable to the majority of the population. 17 For more details about the assumptions used to answer the particular questions under each sub-section, please refer to the Data Notes section of the 2012 Women Business and the Law report, pages 34 – 50, that can be accessed by visiting our website: wbl.worldbank.org. 30 List Of Questions Tracked From 1960 To 2010 Category Question Variable name Do unmarried men and unmarried women have equal ownership Unmarried property rights over immoveable property? Do married men and married women have equal ownership Married property rights over immoveable property? Access to Assets Do sons and daughters have equal inheritance rights over Sons-daughters inheritance immoveable property from their parents? Do female and male surviving spouses have equal inheritance Husband-wife inheritance rights over immoveable property? What is the default marital property regime? Default regime If joint titling exists for married couples, is it the default for Joint titling marital property? Can an adult married woman legally be designated as "head of Restrictions on Agency and Mobility for household" or "head of family" in the same way as an adult Head of household married man? Does an adult married woman legally need permission from her husband in order to get or keep a job or pursue a trade or Married Women Work without permission profession; or can a husband legally stop his wife from working? Can an adult married woman legally open a bank account in the Bank account without same way that an adult married man can? permission Are there any legal provisions that prevent an adult married Contract without woman from signing any type of contract in the same way that permission an adult married man would? Do adult married women need permission from their husbands Legal proceedings without in order to initiate legal proceedings in court in civil cases? permission Does the Constitution guarantee all citizens equality before the Gender Equality and Plural Constitutional Approach to Constitutional equality law? Is there a non-discrimination clause covering gender or sex in Constitutional non- Legal Systems the Constitution? discrimination Are customary law and/or religious law a valid source of law Customary law / under the Constitution? Religious law valid Customary law / Religious Are customary and/or religious law invalidated if they violate law invalidated by non- Constitutional provisions on equality and/or nondiscrimination? discrimination 31 Countries Covered in the Database EAP ECA LAC MENA OECD SAR SSA Banglades China Bulgaria Argentina Algeria Australia h Angola Fiji Belarus Bolivia Egypt, Arab Rep. Austria India Benin Indonesia Georgia Brazil Iran, Islamic Rep. Belgium Sri Lanka Burkina Faso Cambodia Kazakhstan Chile Jordan Switzerland Nepal Botswana Central African Lao PDR Kyrgyz Republic Colombia Morocco Germany Pakistan Republic Russian Syrian Arab Mongolia Federation Costa Rica Republic Spain Côte d'Ivoire Dominican Malaysia Tajikistan Republic Tunisia France Cameroon United Philippines Turkey Guatemala Yemen, Rep. Kingdom Ethiopia Papua New Guinea Ukraine Honduras Hungary Gabon Singapore Uzbekistan Jamaica Italy Ghana Thailand Mexico Japan Kenya Vietnam Nicaragua Korea, Rep. Liberia Peru Netherlands Lesotho Paraguay Norway Madagascar Venezuela, RB Portugal Mali Sweden Mozambique United States Mauritania Malawi Namibia Niger Nigeria Rwanda Sudan Senegal Sierra Leone Swaziland Togo Tanzania Uganda South Africa Congo, Dem. Rep. Zambia Zimbabwe 32 Source of outcome and explanatory variables • World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates. WDI was the source for indicators regarding GDP, GDP/capita, maternal and infant health, life expectancy, sectors value added to GDP and exports of natural resources. (databank.worldbank.org) • International Country Risk Guide (ICRG) - is generated by the PRS group. Updated monthly, ICRG monitors 140 countries. ICRG's statistical tables assign values to the 22 indicators underlying ICRG's business-oriented model for quantifying risk, examining such country-specific elements as currency risk, political leadership, the military and religion in politics, and corruption. The present study employs the Law and Order indicator. Law and Order are assessed separately, with each sub-component comprising zero to three points. The Law sub-component is an assessment of the strength and impartiality of the legal system, while the Order sub-component is an assessment of popular observance of the law. Thus, a country can enjoy a high rating – 3 – in terms of its judicial system, but a low rating – 1 – if it suffers from a very high crime rate of if the law is routinely ignored without effective sanction (for example, widespread illegal strikes). The maximum score is 6. (http://www.prsgroup.com/ICRG.aspx) • International Income Distribution Database (I2D2) – database of disaggregated labor market indicators derived from a large set of surveys from developing countries. The database presently includes more than 700 datasets from the period between 1984 and 2011. Ninety-one countries are covered by data from this source. • Gender Statistics includes data on key gender topics. Themes included are demographics, education, health, labor force, and political participation. The data was launched together with the World Bank’s World Development Report 2012 on Gender Equality and Development. Gender Statistics was the sources for indicators such as the ratio of female to male educational enrollment and young adult literacy. (databank.worldbank.org) • Inter-Parliamentary Union(IPU) - The data on percentage of women in parliament is compiled by the on the basis of information provided by National Parliaments by 1st May 2013. The percentages do not take into account the case of parliaments for which no data was available at that date. (www.ipu.org) • Armed Conflict Database - This dataset is a collaborative project between the Department of Peace and Conflict Research at Uppsala University and the Centre for the Study of Civil War at PRIO. The database includes armed conflicts, both internal and external, in the period 1946 to the present. (http://www.prio.no/Data/Armed-Conflict/UCDP-PRIO/) 33 Variables sources and definitions Source Definition Employment Women's labor force WDI Labor participation rate, female (% of female population ages 15+). Labor participation force participation rate is the proportion of the population ages 15 and older that is economically active: all people who supply labor for the production of goods and services during a specified period. Share of women in non- WDI Share of women employed in the nonagricultural sector (% of total agricultural employment nonagricultural employment). Share of women employed in the nonagricultural sector is the share of female workers in the nonagricultural sector (industry and services), expressed as a percentage of total employment in the nonagricultural sector. Share of women who are WDI Employers, female (% of employment). Employers refers are those workers employers who, working on their own account or with one or a few partners, hold the type of jobs defined as a "self-employment jobs" i.e. jobs where the remuneration is directly dependent upon the profits derived from the goods and services produced), and, in this capacity, have engaged, on a continuous basis, one or more persons to work for them as employee(s). Share of women who are WDI Wage and salaried workers, female (% of females employed) . Wage and wage workers salaried workers (employees) are those workers who hold the type of jobs defined as "paid employment jobs," where the incumbents hold explicit (written or oral) or implicit employment contracts that give them a basic remuneration that is not directly dependent upon the revenue of the unit for which they work. Share of women in WDI Vulnerable employment, female (% of female employment). Vulnerable vulnerable employment employment is unpaid family workers and own-account workers as a percentage of total employment. Share of women in self- WDI Self-employed, female (% of females employed). Self employed workers are employment those workers who, working on their own account or with one or a few partners or in cooperative, hold the type of jobs defined as a "self-employment jobs" (i.e. jobs where the remuneration is directly dependent upon the profits derived from the goods and services produced). Share of wage workers WDI / I2D2 Share of wage workers who are women calculated as a percentage of all wage who are women workers. Share of self-employed WDI/I2D2 Share of self-employed who are women calculated as a percentage of all self- who are women employed workers. Share of employers who WDI/I2D2 Share of employers who are women calculated as a percentage of all are women employers. 34 Education Ratio of girls to boys in Gender Statistics Ratio of female to male primary enrollment is the percentage of girls to boys primary education enrolled at primary level in public and private schools Ratio of girls to boys in Gender Statistics Ratio of female to male primary enrollment is the percentage of girls to boys secondary education enrolled at secondary level in public and private schools Ratio of girls to boys in Gender Statistics Ratio of female to male primary enrollment is the percentage of girls to boys tertiary education enrolled at tertiary level in public and private schools Ratio of young literate Gender Statistics Ratio of young literate females to males is the percentage of females to males females to young literate ages 15-24 who can, with understanding, read and write a short, simple males (% age 15-24) statement on their everyday life Health Life expectancy (female) WDI Life expectancy at birth indicates the number of years a newborn female infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life. Access to contraceptives Gender Statistics Contraceptive prevalence rate is the percentage of women who are practicing, or whose sexual partners are practicing, any form of contraception. It is usually measured for married women ages 15-49 only. Maternal mortality WDI Maternal mortality ratio is the number of women who die during pregnancy and childbirth, per 100,000 live births. Infant mortality WDI Infant mortality rate is the number of infants dying before reaching one year of age, per 1,000 live births in a given year. Infant mortality (female) WDI Female infant mortality rate is the number of female infants dying before reaching one year of age, per 1,000 live births in a given year. Malnutrition of children Gender Statistics Prevalence of child malnutrition is the percentage of children under age 5 0-5 (female) whose weight for age is more than two standard deviations below the median for the international reference population ages 0-59 months. The data are based on the WHO's new child growth standards released in 2006. Wasting (female) Gender Statistics Wasting prevalence is the proportion of children under five whose weight for height is more than two standard deviations below the median for the international reference population ages 0-59. Empowerment Age of first marriage Gender Statistics Mean age at first marriage shows the average length of single life expressed in years among those who marry before age 50 Share of 18 year olds who Gender Statistics Women who were first married by age 18 refers to the percentage of women are married ages 20-24 who were first married by age 18. Adolescent fertility Gender Statistics Adolescent fertility rate is the number of births per 1,000 women ages 15-19 35 Women in parliament IPU Women in parliaments are the percentage of parliamentary seats in a single or lower chamber held by women. Share senior officials and Gender Statistics Female legislators, senior officials and managers (% of total) refers to the managers who are women share of legislators, senior officials and managers who are female. Domestic Gender Statistics Proportion of women aged 15-49 subjected to physical or sexual violence in violence/Beating the last 12 months by an intimate partner (%) Share of women with FINDEX Percentage of women who have an account with a formal financial institution access to a bank account out of all women aged 15+ Share of women with FINDEX Percentage of women who have a loan from a formal financial institution out access to a bank loan of all women aged 15+ Control variables GDP per capita WDI GDP per capita is gross domestic product divided by midyear population. Industry, value added to WDI Industry corresponds to ISIC divisions 10-45 and includes manufacturing GDP (%) (ISIC divisions 15-37). It comprises value added in mining, manufacturing, construction, electricity, water, and gas. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. The origin of value added is determined by the ISIC revision 3. Services, value added to WDI Services correspond to ISIC divisions 50-99 and they include value added in GDP (%) wholesale and retail trade (including hotels and restaurants), transport, and government, financial, professional, and personal services such as education, health care, and real estate services. The industrial origin of value added is determined by the International Standard Industrial Classification (ISIC), revision 3. Conflict UCDP/PRIO UCDP defines conflict as: “a contested incompatibility that concerns Armed Conflict government and/or territory where the use of armed force between two parties, Dataset, version 4- of which at least one is the government of a state, results in at least 25 battle- 2009 related deaths. Conflict intensity UCDP/PRIO Takes into account the temporal dimension of the conflict. It is a dummy Armed Conflict variable that codes whether the conflict since the onset has exceeded 1,000 Dataset, version 4- battle-related deaths. A conflict is coded as 0 as long as it has not over time resulted in more than 1,000 battle-related deaths. Once a conflict reaches this 2009 threshold, it is coded as 1. Rule of law ICRG ICRG data: Law and Order are assessed separately, with each sub-component comprising zero to three points. The Law sub-component is an assessment of the strength and impartiality of the legal system, while the Order sub- component is an assessment of popular observance of the law. Thus, a country can enjoy a high rating – 3 – in terms of its judicial system, but a low rating – 1 – if it suffers from a very high crime rate of if the law is routinely ignored without effective sanction (for example, widespread illegal strikes). The maximum score is 6. 36 Table 1: Summary statistics Number First Last of Standard year year countries Average deviation Minimum Maximum available available Employment Women's labor force participation 100 40.55 9.33 11.00 56.00 1990 2010 Share of women in non-agricultural employment 100 38.06 11.49 6.00 56.00 1990 2010 Share of women who are employers 83 2.07 1.34 0.00 8.00 1980 2010 Share of women who are wage workers 90 67.38 24.66 0.00 96.00 1980 2010 Share of women in vulnerable employment 87 31.59 25.01 1.00 99.00 1980 2010 Share of women in self-employment 90 32.36 24.35 3.00 99.00 1980 2010 Share of wage workers who are women 91 37.37 10.14 6.76 55.12 1970 2010 Share of self-employed who are women 90 40.84 14.87 2.04 78.17 1970 2010 Share of employers who are women 84 23.53 10.03 0.58 81.24 1977 2010 Education Ratio of girls to boys in primary education 99 89.46 15.66 17.24 149.19 1970 2010 Ratio of girls to boys in secondary education 99 85.69 26.05 17.26 309.97 1970 2010 Ratio of girls to boys in tertiary education 99 75.54 41.36 4.07 228.77 1970 2010 Ratio of young literate females to young literate males 86 63.53 44.76 0.30 115.58 1975 2010 Health Life expectancy (female) 100 62.48 12.63 28.53 86.44 1960 2010 Ratio of women's life expectancy to men's 100 1.07 0.04 0.95 1.57 1960 2010 Access to contraceptives 100 47.89 23.81 0.80 96.00 1968 2010 Maternal mortality 96 215.01 286.15 1.00 1800.00 1961 2010 Infant mortality 100 66.99 49.21 2.00 273.00 1960 2010 Infant mortanlity (female) 67 43.24 37.79 1.00 232.00 1986 2009 Malnutrition of children 0-5 (female) 87 32.65 16.44 1.10 77.30 1968 2010 Wasting (female) 86 6.91 5.22 0.00 26.40 1968 2010 Empowerment Age of first marriage 99 23.15 3.33 14.40 33.20 1980 2010 Share of 18 year olds who are married 70 32.34 17.33 1.80 83.30 1986 2010 Adolescent fertility 100 68.56 51.34 2.20 242.04 1997 2010 Women in parliament 100 14.76 10.21 0.00 56.30 1990 2010 Share senior officials and managers who are women 64 27.20 10.12 2.10 64.23 1985 2010 Domestic violence/Beating 34 41.91 21.06 3.56 75.59 2003 2009 Share of women with access to a bank account 93 37.90 30.29 1.09 99.01 2010 2010 Share of women with access to a bank loan 93 8.48 5.99 0.49 30.28 2010 2010 Control variables GDP per capita 100 7.72 1.53 4.01 10.64 1960 2010 industry share of GDP 100 29.59 10.87 1.88 72.72 1960 2010 services share of GDP 99 48.04 12.25 4.14 79.34 1960 2009 conflict 100 0.19 0.39 0.00 1.00 1960 2010 conflict intensity 100 0.13 0.34 0.00 1.00 1960 2010 37 Cross-sectional results: Each column represents a different outcomes as the dependent variable Employment Education Table 2a Share of wage workers who are Ratio of girls to boys enrolled in Ratio of girls to boys enrolled in Ratio of girls to boys enrolled in Share of women who are wage Ratio of young literate females Non-agricultural employment Share of women who are self- Share of employers who are Share of women who are to males (% ages 15-24) Women's labor force secondary education primary education participation employers employed workers tertiary women women -** -** Access to and control of Unmarried property Married property * -* -** assets Sons-daughters *** *** * *** * inheritance Husband-wife *** *** *** ** ** inheritance Joint titling *** *** *** Head of household ** * ** -* *** * Work without ** * *** * ** * permission Legal capacity Bank account without -* permission Contract without permission Legal proceedings -*** without permission -*** ** -** * Constitutional principles and legal Constitutional equality Constitutional non- ** ** ** discrimination ** -* * *** pluralism Costomary law is valid Customary law invalidated by non- discrimination Religious law is valid -* ** -*** Religious law invalidated by non- *** *** ** ** -** discrimination Countries 98 98 81 88 88 89 90 96 96 95 85 *** p<0.01, ** p<0.05, * p<0.1 Note: Shaded columns indicate that lower numbers are desirable; so a "-" effect is a sign of improvement Each cell represents a separate regression. Country controls, lagged five years, were included (GDP per capita, the share of industry value added in GDP, the share of services value added in GDP, whether there was a conflict and its intensity.) 38 Cross-sectional results: Each column represents a different outcomes as the dependent variable Health Empowerment Malnutrition of children (age 0- Share of women reporting they Table 2b can be beaten for arguing, Access to a bank account Infant mortality - female Women - share of senior Access to contraceptives Life expectency - female officials and managers Women in parliament Access to a bank loan Age of first marriage Maternal mortality Adolescent fertility Share 18 married Wasting-females Infant mortality 5) -female Access to and control of ass Unmarried property *** -* -*** -* ** Married property *** *** -*** -*** -* -* -*** -* * ** Sons-daughters *** -* -*** ** ** * inheritance Husband-wife ** - -*** * *** ** -* inheritance Joint titling * -** ** Head of household * *** -** -*** -** * * ** Work without ** ** -*** -** ** ** permission Legal capacity Bank account without *** -** -* -* -* -*** permission Contract without *** *** -* -*** -*** permission Legal proceedings ** * ** -*** ** without permission * -** * -*** Constitutional principles and legal Constitutional equality *** Constitutional non- -* * ** discrimination -*** *** *** ** pluralism Costomary law is valid *** * Customary law invalidated by non- ** *** -*** -** discrimination Religious law is valid -** * ** Religious law invalidated by non- -* * ** *** discrimination Countries 97 97 94 98 65 87 86 97 98 70 97 63 91 91 33 *** p<0.01, ** p<0.05, * p<0.1 Note: Shaded columns indicate that lower numbers are desirable; so a "-" effect is a sign of improvement Each cell represents a separate regression. Country controls, lagged five years, were included (GDP per capita, the share of industry value added in GDP, the share of services value added in GDP, whether there was a conflict and its intensity.) 39 Table 3: Panel regressions: testing for non-linear effects by level of development (GDP per capita) Employment Education Health Empowerment (1) (2) (3) (4) (5) (6) (7) (8) Ratio of Ratio of Ratio of girls to girls to girls to Women's boys in boys in boys in Life Age of labor force primary secondary tertiary Infant expectancy Adolescent first participation school school education mortality (women) fertility marriage Unmarried -9.373*** -8.661 1.585 -27.81 -15.81 -9.498 -9.125 -7.533*** property rights (3.066) (28.30) (12.15) (22.50) (15.36) (11.62) (23.38) (1.411) Unmarried prop* 1.581*** 1.047 -0.475 4.842* 3.117 1.123 0.997 1.121*** GDPpc (0.483) (3.770) (1.820) (2.704) (2.302) (1.956) (3.225) (0.203) Property Rights, Access to and Control over Assets Married -3.225 17.31** 3.437 -41.55*** -25.63* -3.519 -34.62*** -5.762*** property rights (2.342) (8.066) (10.04) (10.69) (13.50) (5.222) (12.04) (1.654) Married PR* 0.575 -2.435** -1.650 5.182*** 3.635** 0.489 4.257*** 0.729*** GDPpc (0.372) (1.024) (1.479) (1.326) (1.709) (0.716) (1.597) (0.235) Sons-daughters -8.988** 35.01** 54.84*** 0.497 -72.58*** -3.964 -19.55 -4.148** inheritance (3.527) (14.27) (17.68) (20.72) (25.95) (9.500) (18.77) (1.715) Sons-daughters 1.332** -4.866** -7.863*** -1.997 11.89*** 0.246 2.352 0.538** inherit*GDPpc (0.575) (2.242) (2.861) (3.325) (4.058) (1.643) (2.882) (0.252) Husband-wive -8.644*** 33.34* 53.53*** 8.663 -76.33*** -4.913 -24.80 -2.897* inheritance (2.880) (17.41) (19.71) (19.64) (28.69) (9.755) (20.26) (1.554) Husband-wives 1.237** -5.271** -8.414** -2.678 12.51*** 0.234 3.184 0.353 inherit*GDPpc (0.480) (2.397) (3.232) (3.179) (4.364) (1.639) (3.165) (0.239) Joint titling -6.392** 7.812 12.16 -0.0991 1.499 1.178 -13.41 -4.927** (2.723) (10.57) (13.75) (27.58) (24.63) (6.603) (14.17) (2.093) Joint titling*GDPpc 1.022** -1.128 -1.281 -0.363 -0.428 -0.361 1.834 0.609** (0.422) (1.402) (2.237) (3.818) (3.412) (1.046) (2.049) (0.304) Women head of -3.764 22.95*** -0.714 -28.76** -46.87*** 0.827 -38.65*** -3.688** household (3.146) (8.647) (11.90) (14.39) (17.13) (5.007) (13.19) (1.477) Women head*GDPpc 0.566 -3.084*** -0.716 3.949** 6.394*** -0.186 5.008*** 0.445** (0.481) (1.074) (1.526) (1.821) (2.053) (0.612) (1.845) (0.221) No permission -6.515** -5.104 -1.390 -17.54 5.683 -9.316 -6.698 -1.196 needed to work (2.932) (18.85) (16.83) (22.89) (14.78) (7.281) (19.03) (2.407) No perm work 0.910** 0.347 -0.637 2.697 0.137 0.969 0.626 0.173 *GDPpc (0.432) (2.445) (2.662) (3.085) (2.116) (1.012) (2.469) (0.340) Legal Capacity No permission bank -8.700** 19.95** 7.524 -45.86*** -17.17 -4.950 -17.81 -4.611** account (3.406) (7.818) (7.427) (10.12) (13.10) (5.293) (13.80) (2.230) No perm bank*GDPpc 1.388*** -2.640** -1.267 5.206*** 2.981* 0.496 1.592 0.587* (0.517) (1.062) (0.940) (1.369) (1.754) (0.717) (1.795) (0.327) No permission to -8.795** 15.51 -4.834 -6.133 -20.21 -7.272 -18.65 -7.224** sign contracts (3.662) (9.992) (10.79) (20.47) (18.53) (5.692) (14.93) (3.004) No perm contract 1.347** -2.033 0.429 0.990 2.982 0.776 1.942 0.918** *GDPpc (0.557) (1.284) (1.437) (2.493) (2.286) (0.744) (2.036) (0.393) No permission for -2.136 8.847 -14.29 -3.455 -3.740 -4.281 -29.91* -1.838 legal proceedings (3.297) (9.494) (12.51) (20.07) (21.13) (6.642) (15.63) (3.132) No perm legal*GDPpc 0.371 -1.381 1.370 0.917 0.602 0.322 3.399 0.171 (0.504) (1.259) (1.690) (2.596) (2.867) (0.893) (2.154) (0.477) 40 Table 3 con't: Panel regressions: testing for non-linear effects by level of development (GDP per capita) Employment Education Health Empowerment (1) (2) (3) (4) (5) (6) (7) (8) Ratio of Ratio of Ratio of girls to girls to girls to Women's boys in boys in boys in Life Age of labor force primary secondary tertiary Infant expectancy Adolescent first participation school school education mortality (women) fertility marriage Constitutional -11.79*** -6.203 -31.88** -29.03 -30.49 2.789 -33.93*** 1.093 equality (2.615) (10.89) (15.34) (17.99) (20.88) (7.569) (10.21) (2.897) Constitutional Principles of Equality and Non-Discrimination Const equality 1.971*** 0.154 4.064* 4.359 4.949 -0.635 4.468*** -0.354 *GDPpc (0.436) (1.585) (2.302) (2.805) (3.060) (1.148) (1.588) (0.418) Constitutional non- -8.340*** 23.18*** 4.429 -12.48 -16.38 -2.356 19.58 -2.955** discrimination (2.570) (6.390) (13.27) (9.791) (15.52) (3.365) (16.80) (1.259) Const. non-disc 1.173*** -3.518*** -1.144 1.823 2.300 0.143 -2.499 0.310 *GDPpc (0.445) (0.830) (1.906) (1.402) (2.198) (0.505) (2.286) (0.199) Recognition of -6.174** 34.27*** 46.05* -1.783 -51.29** 9.796 0.592 customary law (2.632) (7.968) (24.02) (14.73) (20.00) (6.305) (1.390) Limits on -3.540 -12.38 13.60 79.48* -45.47 -12.30 -5.822 customary law (5.795) (27.98) (32.27) (43.43) (36.12) (12.74) (3.744) Customary law 1.151** -5.050*** -7.048* 0.0743 6.711** -1.482 -0.254 *GDPpc (0.451) (1.192) (3.979) (2.406) (3.016) (1.054) (0.191) Limits cust law 0.674 1.850 -2.621 -13.89** 5.057 2.364 1.175* *GDPpc (1.027) (4.856) (5.304) (6.991) (5.635) (2.289) (0.665) Recognition of 17.49** -18.03 -71.86*** 39.21 -8.551 1.755 -0.628 religious law (6.943) (20.98) (26.62) (32.91) (40.28) (8.018) (2.234) Limits on religious 14.98 31.34 -19.94 74.31 -52.83 8.443 -12.64*** law (11.61) (22.40) (35.43) (87.77) (45.53) (7.286) (3.247) Religious law*GDPpc -3.687** 4.489 11.29** -8.110 0.793 0.156 -0.0676 (1.450) (3.461) (4.629) (6.039) (7.423) (1.460) (0.467) Limits rel law*GDPpc -2.321 -5.297* 0.880 -12.59 10.40 -1.575 2.364*** (2.011) (3.116) (5.237) (13.82) (7.052) (1.206) (0.512) Observations 463 618 546 485 733 739 290 278 R-squared 0.301 0.327 0.356 0.723 0.726 0.592 0.648 0.587 Number of countries 99 98 98 97 99 99 99 96 Robust standard errors in parenthese; ***p<0.01, ** p<0.05, * p<0.1 Control variables are all lagged 5 years. They include GDP per capita, the share of industry in GDP, the share of services in GDP, conflict, conflict intensity, a trend and country fixed effects. Shaded columns indicate that lower numbers are desirable for these outcomes. 41 Table 4: Panel regressions: testing for non-linear effects by rule of law Employment Education Health (1) (2) (3) (4) (5) (6) Ratio of Ratio of Ratio of girls to girls to girls to Women's boys in boys in boys in Life labor force primary secondary tertiary Infant expectancy participation school school education mortality (women) Unmarried 6.832*** -1.356 -10.11** -26.18** 35.79*** -6.615 property rights (1.307) (3.385) (4.811) (10.28) (5.755) (16.89) Unmarried prop* -1.802*** -0.903 0.229 11.73*** -10.94*** 0.453 Property Rights, Access to and Control over Assets Rule_of_Law (0.441) (1.052) (1.691) (2.235) (2.197) (4.402) Married 1.148 -4.849 -13.51*** -1.823 7.757 -3.770 property rights (1.127) (3.717) (4.904) (15.08) (6.755) (3.388) Married PR* -0.0785 1.211 2.170* 1.333 -3.428** 0.635 Rule_of_Law (0.302) (0.861) (1.220) (3.745) (1.398) (0.653) Sons-daughters 0.00166 7.800 9.292 -1.877 11.15* -6.810** inheritance (1.119) (4.701) (7.848) (13.70) (6.386) (2.715) Sons-daughters -0.251 -1.100 -3.003** -1.445 -2.801* 0.460 inherit*Rule_of_Law (0.317) (1.028) (1.325) (3.945) (1.452) (0.390) Husband-wive -0.317 8.959** 15.68** -2.793 2.344 -5.385** inheritance (1.029) (4.033) (7.679) (13.66) (8.226) (2.385) Husband-wives -0.276 -1.512 -3.503*** -0.848 -2.485* 0.281 inherit*Rule_of_Law (0.312) (0.980) (1.259) (4.030) (1.377) (0.379) Joint titling 0.626 5.568 15.19* 22.15 7.143 -4.210 (1.081) (3.686) (9.073) (14.09) (4.859) (2.872) Joint titling*Rule_of_Law -0.0462 -1.437 -2.796** -6.656 -0.322 -0.00290 (0.276) (1.009) (1.146) (4.026) (1.342) (0.359) Women head of 1.894 1.888 0.118 6.645 1.259 -1.942 household (1.176) (4.035) (6.596) (13.71) (6.251) (2.574) Women head -0.439 -0.0132 -0.396 -2.405 -2.947** 0.540 *Rule_of_Law (0.307) (0.797) (1.347) (3.388) (1.258) (0.406) No permission 0.395 -2.761 -1.743 6.715 10.71** -1.594 needed to work (1.147) (3.710) (5.758) (11.71) (4.158) (1.905) No perm work -0.309 1.074 1.130 -0.177 -3.419*** 0.219 *Rule_of_Law (0.397) (0.877) (1.339) (2.305) (1.096) (0.334) Legal Capacity No permission bank -1.182 -2.404 -16.63** -4.237 2.655 -8.253* account (1.955) (6.386) (7.169) (13.78) (15.48) (4.939) No perm bank 0.734 0.378 5.224** 0.669 -2.632 1.748** *Rule_of_Law (0.525) (1.650) (2.020) (3.363) (3.304) (0.871) No permission to -0.263 2.414 -2.860 2.097 -3.429 -3.824 sign contracts (1.432) (5.710) (5.545) (15.35) (8.338) (3.804) No perm contract 0.223 -0.867 0.824 -0.169 -0.700 0.787 *Rule_of_Law (0.456) (0.957) (0.890) (3.366) (1.544) (0.698) No permission for 0.779 2.317 -5.920 6.604 -13.67 -3.369 legal proceedings (1.331) (3.901) (6.571) (10.02) (12.79) (4.734) No perm legal*Rule_of_L -0.0833 -1.528 1.214 -2.189 2.482 0.167 (0.279) (0.919) (1.278) (2.361) (2.903) (0.993) 42 Table 4: Panel regressions: testing for non-linear effects by rule of law Employment Education Health (1) (2) (3) (4) (5) (6) Ratio of Ratio of Ratio of girls to girls to girls to Women's boys in boys in boys in Life labor force primary secondary tertiary Infant expectancy participation school school education mortality (women) Constitutional 5.658** -9.509** -7.970** -2.604 4.375 -2.048 equality (2.278) (4.137) (3.405) (8.638) (8.470) (3.053) Constitutional Principles of Equality and Non-Discrimination Const equality -0.903 1.269 0.872 -0.538 -1.676 0.753 *Rule_of_Law (0.772) (0.954) (0.681) (2.050) (3.186) (1.028) Constitutional non- 0.843 -0.931 -2.007 -12.56 1.417 -2.679* discrimination (1.719) (4.234) (4.829) (15.26) (4.302) (1.388) Const. non-disc -0.494 0.356 -0.726 1.845 -2.196* 0.412 *Rule_of_Law (0.398) (1.123) (1.319) (4.124) (1.255) (0.367) Recognition of 2.960* -1.468 0.185 customary law (1.664) (5.265) (1.657) Limits on 2.896*** -4.204 0.838 customary law (1.008) (6.713) (1.925) Customary law -0.726* -2.578 0.114 *Rule_of_Law (0.433) (1.692) (0.407) Limits customary law -0.181 -1.896 0.0343 *Rule_of_Law (0.446) (2.559) (0.927) Recognition of 2.319** -13.63** 4.738*** religious law (1.123) (5.866) (1.674) Limits on religious 2.975*** 12.86*** 2.168** law (0.817) (3.080) (0.972) Religious law -0.629** -2.068 -0.00138 *Rule_of_Law (0.279) (1.549) (0.457) Limits religious law -1.118** -3.254** -0.488 *Rule_of_Law (0.458) (1.589) (0.408) Observations 377 327 292 251 377 377 R-squared 0.359 0.380 0.347 0.564 0.630 0.444 Number of countries 83 82 81 81 83 83 Robust standard errors in parenthese; ***p<0.01, ** p<0.05, * p<0.1 Control variables are all lagged 5 years. They include GDP per capita, the share of industry in GDP, the share of services in GDP, conflict, conflict intensity, a trend and country fixed effects. Shaded columns indicate that lower numbers are desirable for these outcomes. 43 Table 5a: Impact of legal reforms on additional outcomes (panel) Employment Health Empowerment Share of women in Share of Share of Share of non- women in women in women in Access to agricultural wage vulnerable self- Wasting contra- Women in employment employment employment employment (female) ceptives parliament Property rights 0.783** 1.452 0.234 -1.201 -0.920*** 3.630*** 1.955*** (0.392) (1.139) (1.263) (1.153) (0.260) (0.902) (0.632) Legal capacity 0.00872 2.644*** -2.127** -2.537*** -0.109 1.970*** 0.762** (0.158) (0.676) (0.899) (0.626) (0.240) (0.644) (0.377) Non- 0.544 -7.266** 6.416*** 6.836*** -1.191 0.918 3.512*** discrimination (1.091) (2.825) (2.448) (2.379) (0.726) (1.616) (0.868) Observations 294 265 234 265 213 383 356 R-squared 98 88 85 88 86 99 99 Robust standard errors in parenthese; ***p<0.01, ** p<0.05, * p<0.1 Control variables are all lagged 5 years. They include GDP per capita, the share of industry in GDP, the share of services in GDP, conflict, conflict intensity and a trend. Note: Shaded columns indicate that lower numbers are desirable for these outcomes. Table 5b: Testing for non-linear impacts by GDP per capita Health Access to contra- Maternal Wasting ceptives mortality (female) Property right 10.46** -17.1* -3.288** (4.622) (9.41) (1.338) PropRghts*GDPpc -1.071 2.36* 0.377* (0.706) (1.30) (0.204) Legal capacity 8.675** -16.94** -2.451** (3.595) (7.21) (1.136) LegCap*GDPpc -0.957* 2.11** 0.364** (0.520) (1.16) (0.183) Non-discrimination -11.04 -64.9*** -3.244 (6.865) (21.5) (3.696) Non-discrim*GDPpc 1.806* 8.62*** 0.319 (1.062) (2.97) (0.524) Observations 383 174 213 R-squared 99 95 86 Robust standard errors in parenthese; ***p<0.01, ** p<0.05, * p<0.1 Control variables are all lagged 5 years. They include GDP per capita, the share of industry in GDP, the share of services in GDP, conflict, conflict intensity and a trend. Note: Shaded columns indicate that lower numbers are desirable for these outcomes. 44