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- (2013) data set available from http://www.humanrightsdata.com/. We use the three following variables: Women’s Political Rights: takes into account women’s rights to vote, to run for political office, to hold elected and appointed government positions, to join political parties, and to petition government officials. This variable takes discrete values between 0 and 3, with 3 representing high rights and 0 representing low rights. This variable is available for the period of 1981–2011 for approximately 139 (in 1990) to 195 (in 2011) countries.
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- (d) Imputing 19901994 with 1995 -1 0 1 2 3 Health Expenditure (% of GDP) -1 0 + Y e a r s -8 -6 -4 -2 0 2 4 6 8 1 0 + Y e a r s Time to Reform Point Estimate 95% CI 90% CI Estimates based on 3933 observations, with dependent variable mean of 6.126. (e) Proportion of Aid to Maternal Health -.1 -.05 0 .05 .1 .15 Maternal Aid as a Proportion of DAH -1 0 + Y e a r s -8 -6 -4 -2 0 2 4 6 8 1 0 + Y e a r s Time to Reform Point Estimate 95% CI 90% CI Estimates based on 4335 observations, with dependent variable mean of 0.069. (f) Maternal Health Aid p.c. -6 -4 -2 0 2 4
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- (h) ln(Gov’t Health Spend) Imputing 1990‘99 with 2000 -.5 0 .5 1 log(Government Domestic Health Spending p.c.) -1 0 + Y e a r s -8 -6 -4 -2 0 2 4 6 8 1 0 + Y e a r s Time to Reform Point Estimate 95% CI 90% CI Estimates based on 4270 observations, with dependent variable mean of 5.098.
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- ‡Men’s Schooling, Average 15–19 (Barro and Lee (2013)) As above. Teen Pregnancy (World Bank) The adolescent fertility rate expressed as the number of births per 1,000 women aged 15–19 is provided by the World Bank, WDI database, indicator SP.ADO.TFRT.
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- ‡Women’s Schooling, Average 15–19 (Barro and Lee (2013)) Women’s schooling measures are taken from the BarroLee dataset (Barro and Lee, 2013) which gives average years of schooling for women aged 15–19 years. BarroLee is only available quinquennially from 1950 to 2015. We use the sample from 1990–2015, and linearly interpolate by country between 5 year periods.
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- Development assistance for health (IHME) Development assistance for health (DAH) data are based on the Institute for Health Metrics and Evaluation (IHME) Development Assistance for Health Database (1990– 2017). These data are available at the source country × receiver country × year level.
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- edu/dataset.xhtml?persistentId=doi:10.7910/DVN/4JQRCL). The dataset is available for the years 1945–2013.
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Elías, J. J., N. Lacetera, M. Macis, and P. Salardi (2017, May). Economic development and the regulation of morally contentious activities. American Economic Review 107(5), 76–80.
- Event Lags 95% Honest CI Coverage (h) Abortion (Save Mother’s Life) 0 2 4 6 8 10 −0.015 −0.010 −0.005 0.000 0.005 0.010 Event Lags 95% Honest CI Coverage (i) Abortion (Fetal Impairment) 0 2 4 6 8 10 −0.02 −0.01 0.00 0.01 0.02 Event Lags 95% Honest CI Coverage Notes: Refer to Figure A5. Here models based on identical outcome variables are estimated, however in this case, each postquota coefficient from event study 1 is documented, along with valid inference under Rambachan and Roth (2020)’s “Honest DiD” methods. Additional notes are available in Figure 5. Figure A14: Gender quotas and schooling (15–19 yearolds) (a) Women (Event Study) -1 0 1 2 Women's Years of Schooling (15-19) -1 0 + Y e a r s -8 -6 -4 -2 0 2 4 6 8 1 0 + Y e a r s
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- Event Lags 95% Honest CI Coverage (h) Dev. assistance for maternal health 0 2 4 6 8 10 −0.05 0.00 0.05 0.10 Event Lags 95% Honest CI Coverage (i) ln(GDP per capital) 0 2 4 6 8 10 −0.2 −0.1 0.0 0.1 0.2 Event Leads 95% Honest CI Coverage Notes: Each postquota coefficient from event study 1 is documented, along with valid inference under Rambachan and Roth (2020)’s “Honest DiD” methods. In each case, these correspond to models conditioning on ln(GDP p.c.) and democracy fixed effects. Here, in place of assuming parallel trends in quota and nonquota countries, valid 95% confidence intervals are constructed under the assumption that postquota trends in quota countries relative to nonadopters would have followed their prevailing path from the prequota period, permitting violations of standard parallel trend assumptions.
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- Exclusion by Gender Index (v2xpe_exlgender): “The index is formed by taking the point estimates from a Bayesian factor analysis model of the indicators power distributed by gender (v2pepwgen), equality in respect for civil liberties by gender (v2clgencl), access to public services by gender (v2peapsgen), access to state jobs by gender (v2peasjgen), and access to state business opportu nities by gender (v2peasbgen)” (Coppedge et al., 2020). Relative Freedom of Movement for Women: Ratio of freedom of domestic movement for women (v2cldmovew) freedom of domestic movement for women (v2cldmovem) .
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- Female Labor Force Participation: This is modelled by the International Labour Organization (pro vided in the ILOSTAT database) as the percent of women aged 15 and above who are economically active. It is available from 1990 to 2015.
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- Figure A2: Reserved seat quota timing: 1990–2012 1990 1995 2000 2005 2010 Year 0 5 10 15 20 25 Total Number of Countries with a Gender Quota East Asia & Pacific Latin America Middle East & N Africa South Asia Sub-Saharan Africa Notes: Timing of the implementation of reserved seats is documented by geographic region. Additional notes related to quota adoption are provided in Figure A1.
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Fitzsimons, E., B. Malde, A. Mesnard, and M. VeraHernández (2016). Nutrition, information and household behavior: Experimental evidence from Malawi. Journal of Development Economics 122, 113–126.
Folbre, N. (2012). Should Women Care Less? Intrinsic Motivation and Gender Inequality. British Journal of Industrial Relations 50(4), 597–619.
- Freedom from forced labor for women(v2clslavef): measures whether adult women free from servi tude and other kinds of forced labor. “Involuntary servitude occurs when an adult is unable to quit a job s/he desires to leave — not by reason of economic necessity but rather by reason of employer’s co ercion. This includes labor camps but not work or service which forms part of normal civic obligations such as conscription or employment in command economies” (Coppedge et al., 2020).
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- Gagliarducci, S. and M. D. Paserman (2016, August). Gender Differences in Cooperative Environments? Evi dence from the U.S. Congress. Working Paper 22488, National Bureau of Economic Research.
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- GDP (World Bank) The log of GDP per capita is PPP adjusted and measured in 2011 international dollars. This is taken from the World Bank WDI database, indicator NY.GDP.PCAP.PP.KD.
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- Girum, T. and A. Wasie (2017). Correlates of maternal mortality in developing countries: an ecological study in 82 countries. Maternal health, neonatology and perinatology 3(1), 1–6.
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GoodmanBacon, A. (2021). DifferenceinDifferences with Variation in Treatment Timing. Journal of Econo metrics (forthcoming).
- Grépin, K. A. and J. Klugman (2013). Maternal health: a missed opportunity for development. The Lancet 381(9879), 1691–1693.
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- Here models based on identical outcome variables are estimated, however using the de Chaisemartin and D’Haultfœuille (2020) DID M estimator. Lead (placebo) and lag (dynamic) effects are estimated for each variable. Figure A8: Event studies: reserved seat quotas and predictors from political science literature (a) Overseas Development Assistance p.c. -100 -50 0 50 Overseas Development Assistance (per capita) -1 0 + Y e a r s -8 -6 -4 -2 0 2 4 6 8 1 0 + Y e a r s Time to Reform Point Estimate 95% CI 90% CI Estimates based on 4335 observations, with dependent variable mean of 52.223.
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- Hogan, M. C., K. J. Foreman, M. Naghavi, S. Y. Ahn, M. Wang, S. M. Makela, A. D. Lopez, R. Lozano, and C. J. Murray (2010). Maternal mortality for 181 countries, 1980–2008: a systematic analysis of progress towards Millennium Development Goal 5. The Lancet 375(9726), 1609–1623.
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- Infant Mortality Rates (DHS) We use male and female infant mortality rates based on the DHS data. Infant mortality is defined as the death of a child before reaching the age one. (continued on next page) A45 Variable (Source) Description Quota Predictors (IPI, World Bank, Beck et al. (2001) ) We examined quota predictors as laid out in Krook (2010): Peacekeepers: the number of peacekeepers in a country from The International Peace Institute, IPI Peacekeeping Database.
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- INSTITUT DE RECHERCHE ÉCONOMIQUES ET SOCIALES Place Montesquieu 3 1348 Louvain-la-Neuve ISSN 1379-244X D/2021/3082/10
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- InterParliamentary Union (2015). Women in Parliament: 20 years in review. Technical report, IPU, Geneva.
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Iyer, L., A. Mani, P. Mishra, and P. Topalova (2012, July). The Power of Political Voice: Women’s Political Representation and Crime in India. American Economic Journal: Applied Economics 4(4), 165–93.
Jayachandran, S. and A. LlerasMuney (2009). Life Expectancy and Human Capital Investments: Evidence from Maternal Mortality Declines. The Quarterly Journal of Economics 124(1), 349–397.
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- Kassebaum, N. J., A. BertozziVilla, M. S. Coggeshall, K. A. Shackelford, C. Steiner, K. R. Heuton, D. GonzalezMedina, R. Barber, C. Huynh, D. Dicker, et al. (2014). Global, regional, and national levels and causes of maternal mortality during 1990–2013: a systematic analysis for the global burden of disease study 2013. The Lancet.
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- Kassebaum, N. J., R. M. Barber, Z. A. Bhutta, L. Dandona, P. W. Gething, S. I. Hay, Y. Kinfu, H. J. Larson, X. Liang, S. S. Lim, et al. (2016). Global, regional, and national levels of maternal mortality, 1990–2015: a systematic analysis for the global burden of disease study 2015. The Lancet 388(10053), 1775–1812.
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- Koblinsky, M., M. E. Chowdhury, A. Moran, and C. Ronsmans (2012). Maternal morbidity and disability and their consequences: neglected agenda in maternal health. Journal of health, population, and nutrition 30(2), 124.
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- Krook, M. L. (2010). Quotas for Women in Politics: Gender and Candidate Selection Reform Worldwide. Oxford: Oxford University Press.
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- Kruk, M. E., S. Kujawski, C. A. Moyer, R. M. Adanu, K. Afsana, J. Cohen, A. Glassman, A. Labrique, K. S. Reddy, and G. Yamey (2016). Next generation maternal health: external shocks and healthsystem innova tions. The Lancet 388(10057), 2296–2306.
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Kudamatsu, M. (2012, 12). Has Democratization Reduced Infant Mortality in SubSaharan Africa? Evidence from Micro Data. Journal of the European Economic Association 10(6), 1294–1317.
- Lippmann, Q. (2020, August). Gender and Lawmaking in Times of Quotas. Available at SSRN.
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- ln(MMR) -3-2 -1 0 1 2 3 4 5 Periods to State Gender Quota Point Estimate 95% CI Notes: Event studies are conducted using all available statelevel estimates of maternal mortality in India, which are generated provided in the Office of the Registrar General & Census Commissioner’s Sample Registration System (SRS) Bulletins. State level reforms refer to the reservation of seats for women in local councils, as described in Iyer et al. (2012). All standard errors are based on wild bootstrapped clustered standard errors (clustered by state), given the relatively low number of states.
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Lorentzen, P., J. McMillan, and R. Wacziarg (2008). Death and development. Journal of Economic Growth 13(2), 81–124.
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- Maternal Aid Funding p.c. (1000s of USD) -1 0 + Y e a r s -8 -6 -4 -2 0 2 4 6 8 1 0 + Y e a r s Time to Reform Point Estimate 95% CI 90% CI Estimates based on 4306 observations, with dependent variable mean of 1.381. (g) ln(Government Health Spending p.c.) -.5 0 .5 1 log(Government Domestic Health Spending p.c.) -1 0 + Y e a r s -8 -6 -4 -2 0 2 4 6 8 1 0 + Y e a r s
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- Maternal Mortality, Indian states (SRS) Statelevel estimates of maternal mortality in India are gleaned from the Office of the Registrar Gen eral & Census Commissioner’s Sample Registration System (SRS) Bulletins (RGI, 2006). These data are available for the 15 large states – Andhra Pradesh, Assam, Bihar (including Jharkhand), Gujarat, Haryana, Karnataka, Kerala, Madhya Pradesh (including Chattisgarh), Maharashtra, Odisha, Punjab, Rajasthan, Tamil Nadu, Uttar Pradesh (Uttarakhand), and West Bengal – for the period of 1997–2003.
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- Miller, G. (2008). Women’s Suffrage, Political Responsiveness, and Child Survival in American History. The Quarterly Journal of Economics 123(3), 1287–1327.
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Miller, G. and C. Valente (2016, August). Population Policy: Abortion and Modern Contraception Are Substi tutes. Demography 53(4), 979–1009.
- Net Overseas Development Assistance: World Bank Indicator DT.ODA.ODAT.CD Political Competition: a series of measures of political competition and landscape from (Beck et al., 2001) Democracy (Polity IV) Our measure of democracy was gleaned from the Polity IV project database. This database records in formation on the political regime in 167 countries, between 1800 and 2014. The democracy indicator is available annually, and is a 0–10 scale based on measures of competitiveness of political participation, openness and competitiveness of executive recruitment and constraints on executive powers. Higher values reflect more open, democratic societies.
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Niederle, M. (2016). Gender. In J. H. Kagel and A. E. Roth (Eds.), The Handbook of Experimental Economics, Volume 2: The Handbook of Experimental Economics, second edition, pp. 481–553. Princeton: Princeton university press.
- Notes: Each panel plots event study estimates of the impact of quota passage on women in parliament (lefthand column) or maternal mortality (righthand column), based on alternative samples or modeling decisions. The top panel estimates standard errors with double clustering (by country and year). The second row removes high income countries from the control group. A static (2015) measure of high income is used to ensure consistency of the sample across years. The third row provides estimates using country population weights, where India and China are removed given that their population (weight) is an order of magnitude larger than most other countries. Estimates for the same unweighted sample are available in the final row. A12 Figure B14: Characteristics of births and mothers: DHS birth pseudopanel (a) log(Fertility Rates) -.4 -.2 0 .2 .4 log(DHS Fertility Rate) -1 0 + Y e a r s -8 -6 -4 -2 0 2 4 6 8 1 0 + Y e a r s
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- Notes: Eventstudy estimates examine the variation of measures of women’s rights and measures of relative social standing based on data collected in the Variety of Democracy dataset (Coppedge et al., 2020). When generating ratios of women to male outcomes (in panels (d)(f)) these are Winsorized at the 1 st and 99 th percentiles to avoid outliers in cases where the denominator is very small.
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- Notes: Eventstudy estimates of potential quota predictors suggested in the political science literature are displayed. All estimation details follow those described in notes to Figure 2. Overseas Development Assistance (ODA) is measured as per capita net inflows in current US dollars, and is generated from the World Bank Data Bank. Peacekeepers (measured in 1000s) are from the IPI Peacekeeping Database, and political measures including the orientation of leader’s party, the leader’s time in power, Herfindahl Index of parties, vote shares and regime types and changes are recorded by the Database of Political Institutions. Indicators for the executive’s political leaning are coded from the Database of Political Institutions, based on a classification of leaders into left (31.4%), right (22.8%), center (7.4%) or notapplicable (38.4%).
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- Okuyama, Y. (2018). The Consequences of Increased Women’s Representation in Politics: Evidence from Japan. Technical report, Mimeo.
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Oster, E. (2009). Does increased access increase equality? Gender and child health investments in India. Journal of development Economics 89(1), 62–76.
- Pande, R. and D. Ford (2012). Gender Quotas and Female Leadership. In World Development Report 2012 (Ed.), Gender Equality and Development, Background Paper. World Bank.
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Parthasarathy, R., V. Rao, and N. Palaniswamy (2019). Deliberative Democracy in an Unequal World: A Text AsData Study of South India’s Village Assemblies. American Political Science Review 113, 623 – 640.
- Paxton, P., J. Green, and M. Hughes (2008). Women in parliament, 19452003: Crossnational dataset. ICPSR24340v1. Ann Arbor, MI: Interuniversity Consortium for Political and Social Research [distribu tor], http://doi.org/10.3886/ICPSR24340.v1.
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- Pemstein, D., K. L. Marquardt, E. Tzelgov, Y.t. Wang, J. Medzihorsky, J. Krusell, F. Miri, and J. von Römer (2020). The vdem measurement model: Latent variable analysis for crossnational and crosstemporal expertcoded data. Varieties of Democracy Institute Working Paper 21(5th Ed).
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- PetterssonLidbom, P. (2014). Midwives and maternal mortality: Evidence from a midwifery policy experiment in Sweden in the 19th century. Technical report, mimeo.
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- Political Gender Quota Data, CrossCountry (IDEA) We collated measures for each country of whether the country has a legislated and binding reserved seat quota for women, its year of implementation, and the size of the quota measured as number of seats divided by all seats in the uni or bicameral chamber. To create the database, we started with measures provided by Dahlerup (2005) and completed the most recent years from Global Database of Quotas for Women database (available online at quotaproject.org), which is a repository developed and maintained by the International Institute for Democracy and Electoral Assistance (IDEA), the Inter Parliamentary Union, and Stockholm University.
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- Political Gender Quota Data, India (Iyer et al. (2012)) Statelevel data on the reservation of seats for women in local councils come from Iyer et al. (2012) who provide a timevarying statelevel indicator for when women were given political representation.
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- Powley, E. (2007). Rwanda: The impact of women legislators on policy outcomes affecting children and fami lies. Background Paper, State of the World’s Children.
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- Property rights for women (v2clprptyw): measures whether women enjoy the right to private prop erty. “Private property includes the right to acquire, possess, inherit, and sell private property, including land. Limits on property rights may come from the state (which may legally limit rights or fail to en force them); customary laws and practices; or religious or social norms. This question concerns the right to private property, not actual ownership of property.” (Coppedge et al., 2020). Women, Business and the Law Index (World Bank) The WBL index is a recently released index covering 170 countries between 19702020, providing a measures of women’s equality in development outcomes, labor force participation, vulnerable employ ment and political participation where scores are based on the average of each economy’s scores for 8 distinct topics listed below. A higher score indicates more gender equal laws.
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Propper, C. and J. Van Reenen (2010). Can pay regulation kill? panel data evidence on the effect of labor markets on hospital performance. Journal of Political Economy 118(2), 222–273.
- Ram, F., U. Ram, and A. Singh (2006). Maternal mortality: Is Indian programme prepared to meet the chal lenges? Health & Development 2(1&2), 67–80.
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- Rambachan, A. and J. Roth (2020, November). An Honest Approach to Parallel Trends. mimeo, Harvard University.
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- Relative Access to Justice for Women: Ratio of Access to justice for women (v2clacjstw) Access to justice for men (v2clacjstm) . Access to justice “specifies the extent to which women/men can bring cases before the courts without risk to their per sonal safety, trials are fair, and women have effective ability to seek redress if public authorities violate their rights, including the rights to counsel, defense, and appeal” (Coppedge et al., 2020).
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- Relative Freedom of Discussion for Women: Ratio of Freedom of discussion for women (v2cldiscw) Freedom of discussion for men (C) (v2cldiscm) . Freedom of discussion “specifies the extent to which men are able to engage in private discussions, particularly on political issues, in private homes and public spaces (restaurants, public transportation, sports events, work etc.) without fear of harassment by other members of the polity or the public authorities. We are interested in restrictions by the government and its agents but also cultural restrictions or customary laws that are enforced by other members of the polity, sometimes in informal ways” (Coppedge et al., 2020). Power distributed by gender (v2pepwrgen): Measures if political power distributed according to gender. Lower values indicate men have nearmonopoly on political power, while higher values indi cate more equality in power between women and men.
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- RestrepoMéndez, M. C. and C. G. Victora (2014). Maternal mortality by age: who is most at risk? The Lancet Global Health 2(3), e120–e121.
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- Ritchie, H. (2020). Exemplars in global health: Which countries are most successful in preventing maternal deaths? Our World in Data.
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Shastry, G. K. and D. N. Weil (2003). How much of crosscountry income variation is explained by health? Journal of the European Economic Association 1(23), 387–396.
Soares, R. R. (2005). Mortality reductions, educational attainment, and fertility choice. American Economic Review 95(3), 580–601.
Solon, G., S. J. Haider, and J. M. Wooldridge (2015). What are we weighting for? Journal of Human re sources 50(2), 301–316.
- Starrs, A. M. (2006). Safe motherhood initiative: 20 years and counting. The Lancet 368(9542), 1130–1132.
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- Swers, Michele, L. (2005). Connecting Descriptive and Substantive Representation: An Analysis of Sex Dif ferences in Cosponsorship Activity. Legislative Studies Quarterly 30(3), 407–433.
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- Table A3: Weights and Estimates from the GoodmanBacon (2021) decomposition Weight Estimate Panel A: Women in Parliament Earlier Treated vs. Later Control 0.024 9.337 Later Treated vs. Earlier Treated 0.015 6.614 Treated vs. Never Treated 0.954 5.739 Treated vs. Already Treated 0.007 0.614 Differenceindifference Estimate 5.799 Panel B: ln(MMR) Earlier Treated vs. Later Control 0.024 0.072 Later Treated vs. Earlier Treated 0.015 0.007 Treated vs. Never Treated 0.954 0.076 Treated vs. Already Treated 0.007 0.018 Differenceindifference Estimate 0.075 Notes: The GoodmanBacon (2021) decomposition above displays the weights and components making up the global “single coefficient” DD model. Decompositions are docu mented for the percent of women in parliament (panel A) and the natural logarithm of the MMR (panel B). Each compo nents’ weight is given along with the point estimate for this comparison. The global estimate is displayed at the foot of each panel.
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- TaylorRobinson, M. M. and R. M. Heath (2003). Do women legislators have different policy priorities than their male colleagues? A critical case test. Women & Politics 24(4), 77–101.
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- The indicators specify “the extent to which all women / men are able to move freely, in daytime and nighttime, in public thoroughfares, across regions within a country, and to establish permanent resi dency where they wish” (Coppedge et al., 2020).
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- These are complemented by an aggregate (statelevel) estimate from 1986, reported in Ram et al. (2006) covering the same large states. Ethnic Compostion (HIEF) Ethnic composition is measured by Ethnic Fractionalization (EF Index), which is the probability that two individuals who are chosen at random from a country belong to two different ethnic groups.
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- Tikkanen, R., M. Z. Gunja, M. FitzGerald, and L. Zephyrin (2020, November). Maternal Mortality and Ma ternity Care in the United States Compared to 10 Other Developed Countries. Issue briefs, Commonwealth Fund.
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- Time to Reform Point Estimate 95% CI 90% CI Estimates based on 1093 observations, with dependent variable mean of 4.414. (f) Female Infant Mortality -1.5 -1 -.5 0 .5 log(Female Infant Mortality Rate) DHS -1 0 + Y e a r s -8 -6 -4 -2 0 2 4 6 8 1 0 + Y e a r s
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- Time to Reform Point Estimate 95% CI 90% CI Estimates based on 1096 observations, with dependent variable mean of 4.345. (e) Male Infant Mortality -1.5 -1 -.5 0 .5 log(Male Infant Mortality Rate) DHS -1 0 + Y e a r s -8 -6 -4 -2 0 2 4 6 8 1 0 + Y e a r s
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- Time to Reform Point Estimate 95% CI 90% CI Estimates based on 2586 observations, with dependent variable mean of 6.132. (c) Extrapolating to cover 19901994 -2 -1 0 1 2 Health Expenditure (% of GDP) -1 0 + Y e a r s -8 -6 -4 -2 0 2 4 6 8 1 0 + Y e a r s Time to Reform Point Estimate 95% CI 90% CI Estimates based on 4283 observations, with dependent variable mean of 6.151.
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- Timevarying data on EF come from Historical Index of Ethnic Fractionalization Dataset (HIEF) V 2.0 (Dražanová, 2020), downloaded from the Harvard Dataverse (https://dataverse.harvard.
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- Tuberculosis Mortality (WHO) This is measured as the number of deaths due to Tuberculosis among HIV negative people, and is measured per 100,000 population. The data are from the WHO and were downloaded from: http: //apps.who.int/gho/data/view.main.57020ALL?lang=en, accessed on 17/03/2016. Women’s Rights (CIRI) Measures of women’s political, economic, and social rights data are based on the Cingranelli et al.
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- UNWomen (2013). Women make up more than onethird of Zimbabwe’s new parliament. Available at: https: //www.unwomen.org/en/news/stories/2013/9/zimbabwe-women-mps-sworn-in.
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Van der Windt, P., M. Humphreys, and R. S. de la Sierra (2018). Gender quotas in development programming: Null results from a field experiment in congo. Journal of Development Economics 133, 326–345.
Waldron, I. (1983). The role of genetic and biological factors in sex differences in mortality. In A. D. Lopez and L. T. Ruzicka (Eds.), Sex Differentials in Mortality: Trends, Determinants and Consequences. Canberra and New York, NY: Dept. of Demography, PB Consulting Service.
- We compute the proportion Development Assistance for Health to Maternal Health as: Development Assistance for Health to Maternal Health All Program Areas (constant 2017 US dollars) Development Assistance for Health disbursed from all channels (constant 2017 US dollars) .
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- We follow suggested practices in removing a small number of observations which are coded by 3 or fewer country experts (Coppedge et al., 2020) in “C” type variables from the VDEM data which are based on the opinions of country experts. Each specification follows equation 1. Figure A5: Women’s rights, empowerment, and women in politics (a) Women, Business & Law Index (WB) -5 0 5 10 Women, Business & the Law Index -1 0 + Y e a r s -8 -6 -4 -2 0 2 4 6 8 1 0 + Y e a r s Time to Reform Point Estimate 95% CI 90% CI Estimates based on 4257 observations, with dependent variable mean of 63.851. (b) Women Ministers -10 -5 0 5 10 15 Proportion of Women Ministers of State -1 0 + Y e a r s -8 -6 -4 -2 0 2 4 6 8 1 0 + Y e a r s
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- Weil, D. N. (2007). Accounting for the Effect Of Health on Economic Growth. The Quarterly Journal of Economics 122(3), 1265–1306.
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- WHO (2014). Maternal mortality, Fact sheet Number 348, Updated May 2014. World Health Organization, available at: http://www.who.int/mediacentre/factsheets/fs348/en/, Accessed on July 2014.
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- WHO (2019). Maternal Mortality, World Health Organization. Available at: https://www.who.int/ news-room/fact-sheets/detail/maternal-mortality (accessed March 2021).
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- Wilmoth, J. R., N. Mizoguchi, M. Z. Oestergaard, L. Say, C. D. Mathers, S. ZureickBrown, M. Inoue, and D. Chou (2012). A New Method for Deriving Global Estimates of Maternal Mortality. Statistics, Politics and Policy 3(2), 2151–7509.
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 10.0% Djibouti 0 10 20 30 40 %
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 10.0% Niger 0 10 20 30 40 %
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 11.1% Jordan 0 10 20 30 40 %
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 13.0% Bangladesh 0 10 20 30 40 %
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 13.4% Kenya 0 10 20 30 40 %
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 15.2% Morocco 0 10 20 30 40 %
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 17.5% Pakistan 0 10 20 30 40 %
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 20.0% Algeria 0 10 20 30 40 %
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 20.0% Saudi Arabia 0 10 20 30 40 %
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 22.0% China 0 10 20 30 40 %
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 22.2% Zimbabwe Notes: In each panel, the vertical lines display the recorded date of the passage of a reserved seat quota for women in the national parliament, and the plots show the evolution of the percentage of women in parliament. Each figure shares a common yaxis for ease of comparison. A5 Figure B7: Impact of quotas on MMR by size of gender quota Panel A: By Quota Size (a) Quota Size: 015 -.4 -.2 0 .2 .4 log(Maternal Deaths) -1 0 + Y e a r s -8 -6 -4 -2 0 2 4 6 8 1 0 + Y e a r s
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 24.4% Uganda 0 10 20 30 40 %
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 25.0% Iraq 0 10 20 30 40 %
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 25.0% South Sudan 0 10 20 30 40 %
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 25.0% Sudan 0 10 20 30 40 %
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 27.3% Afghanistan 0 10 20 30 40 %
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 29.1% Tanzania 0 10 20 30 40 %
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 3.0% Haiti 0 10 20 30 40 %
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 30.0% Burundi 0 10 20 30 40 %
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 30.0% Eritrea 0 10 20 30 40 %
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 30.0% Rwanda 0 10 20 30 40 %
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- Women in Parliament 1990 1995 2000 2005 2010 2015 Year Quota: 5.3% Swaziland 0 10 20 30 40 %
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- Women Minister data is drawn from InterParliamentary Union (IPU) Women in Politics data, women’s protests as a share of all protests are calculated from data shared by Bell et al. (2019). Rights indexes are additionally defined by Cingranelli et al., and used in panels (d)(f).
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- Women’s Economic Rights: takes into account women’s rights to equal pay for equal work, free choice of profession or employment without the need to obtain a husband or male relative’s consent, the right to gainful employment without the need to obtain a husband or male relative’s consent, equality in hiring and promotion practices, job security (maternity leave, unemployment benefits, no arbitrary firing or layoffs, etc.), nondiscrimination by employers, be free from sexual harassment in the workplace, to work at night, to work in occupations classified as dangerous, to work in the military and the police force. This variable is available for the period of 1981–2011 for approximately 139 (in 1990) to 195 (in 2011) countries.
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- Women’s Political Participation Index (v2x_genpp): “The index is formed by taking the average of the indicators for lower chamber female legislators (v2lgfemleg, standardized) and power distributed by gender (v2pepwrgen)” (Coppedge et al., 2020).
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- Women’s Social Rights: takes into account women’s rights to equal inheritance; enter into marriage on a basis of equality with men; travel abroad; obtain a passport; confer citizenship to children or a hus band; initiate a divorce; own, acquire, manage, and retain property brought into marriage; participate in social, cultural, and community activities; education; and freedoms to choose a residence/domicile, and from female genital mutilation of children and of adults without their consent, and from forced sterilization. This variable is available for the period of 1981–2007 for approximately 139 (in 1990) to 193 (in 2007) countries.
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- Wong, Y. N. (2012). World development report 2012: Gender equality and development. In Forum for Devel opment Studies, Volume 39, pp. 435–444.
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- World Bank (2003). World Development Report 2004: Making services work for poor people.
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- World Health Organization (2015). Trends in Maternal Mortality: 1990 to 2015. Estimates by WHO, UNICEF, UNFPA, World Bank Group and the United Nations Population Division. Geneva: WHO.
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- ZureickBrown, S., H. Newby, D. Chou, N. Mizoguchi, L. Say, E. Suzuki, and J. Wilmoth (2013). Understanding global trends in maternal mortality. International perspectives on sexual and reproductive health 39(1).
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