Abstract
This paper evaluates the impacts of education on women’s relational empowerment, within a context of 70 developing countries across the world. Exploiting the variation in educational attainment between biological sisters, we find that education is positively associated with women’s intra-household decision making authority in both financial and non-financial domains. Moreover, education reduces relational friction, especially women’s exposure to psychological abuse. Our mechanism analyses provide suggestive evidence that these improvements could be attributed to increased access to information, assortative matching, and better labor market outcome.
Appendix A
Correlation test.
| (1) | (2) | (3) | |
|---|---|---|---|
| Deviation of female education from pair mean | |||
| Birth order | −0.250 | ||
| (0.394) | |||
| City as childhood place of residence | −0.380 | ||
| (0.674) | |||
| Marriage to first birth of interval (months) | −0.005 | ||
| (0.006) | |||
| Observations | 23,901 | 23,901 | 16,933 |
NOTE: Dependent variable is the deviation from (sister) pair mean of the woman’s years of education. Explanatory variables are the deviation from (sister) pair mean of the woman’s prior characteristics. These characteristics include birth order, childhood place of residence (an indicator for a city), and the time interval between marriage and first birth. All regressions control for statistical area-by-wave-by-birth year fixed effects. Standard errors are provided in the parentheses. *p < 0.1, **p < 0.05, ***p < 0.01.
Additional heterogeneity analyses.
| (1) | (2) | |
|---|---|---|
| Own earnings | Husband/Partner earnings | |
| Panel A: African women | ||
| Female education | 0.003 | 0.006 |
| (0.003) | (0.005) | |
| Observations | 6594 | 4567 |
| Panel B: Non-African women | ||
| Female education | −0.001 | −0.004 |
| (0.003) | (0.006) | |
| Observations | 6823 | 5501 |
| Panel C: Rural women | ||
| Female education | 0.002 | 0.001 |
| (0.006) | (0.006) | |
| Observations | 4360 | 4446 |
| Panel D: Urban women | ||
| Female education | 0.002 | 0.000 |
| (0.002) | (0.007) | |
| Observations | 8211 | 4953 |
| Panel E: Married women | ||
| Female education | 0.004 | 0.003 |
| (0.004) | (0.002) | |
| Observations | 5038 | 6714 |
| Panel F: Unmarried women | ||
| Female education | 0.001 | 0.004 |
| (0.002) | (0.007) | |
| Observations | 8379 | 3354 |
| Panel G: Employed women | ||
| Female education | 0.002 | 0.002 |
| (0.002) | (0.005) | |
| Observations | 11,365 | 5283 |
| Panel H: Unemployed women | ||
| Female education | 0.006 | −0.001 |
| (0.005) | (0.009) | |
| Observations | 1978 | 4768 |
NOTE: Each cell reports the coefficient β1 in equation (2). The panel headings indicate dimensions of heterogeneity. All regressions control for age, the age difference between the woman and her sister, sister fixed effects, as well as the country-specific birth cohort trend. Standard errors are provided in the parentheses. *p < 0.1, **p < 0.05, ***p < 0.01.
The list of countries.
| Code | Name | Survey year and wave | Avg. Education | Avg. Age |
|---|---|---|---|---|
| AL | Albania | [09]5, [17]7 | 11.3 | 27.8 |
| AO | Angola | [15,16]7 | 6.7 | 25.433 |
| AM | Armenia | [00, 05]4, [10]6, [16]7 | 10.593 | 30.093 |
| AZ | Azerbaijan | [06]5 | 10.0 | 27.963 |
| BD | Bangladesh | [93, 94, 96, 97], [04]4, [07]5, [11, 14]6 | 5.2 | 27.056 |
| BJ | Benin | [96]3, [01]4, [06]5, [11, 12]6, [17, 18]7 | 4.920 | 27.095 |
| BO | Bolivia | [93, 94, 98]3, [03, 04]4, [08]5 | 10.441 | 25.471 |
| BR | Brazil | [96]3 | 6.635 | 25.442 |
| BF | Burkina Faso | [03]4, [10]6 | 5.558 | 26.236 |
| BU | Burundi | [10, 11]6, [16, 17]6 | 5.354 | 25.539 |
| KH | Cambodia | [00], [05, 06, 10, 11]5, [14]6 | 5.503 | 27.716 |
| CM | Cameroon | [04]4, [11]6 | 7.590 | 28.536 |
| CF | Central African Republic | [94, 95]3 | 3.610 | 27.992 |
| TD | Chad | [96, 97]3, [04]4, [14, 15]6 | 2.145 | 28.443 |
| CO | Colombia | [95]3, [00, 04, 05]4, [09, 10]5, [15, 16]7 | 9.245 | 26.958 |
| KM | Comoros | [96]3, [12]6 | 6.364 | 25.921 |
| CG | Congo | [05]5, [11, 12]6 | 7.537 | 27.983 |
| CD | Congo democratic Republic | [07]5, [13, 14]6 | 7.743 | 27.595 |
| CI | Cote d’Ivoire | [11, 12]6 | 4.100 | 28.866 |
| DR | Dominican Republic | [96, 99]3, [02]4, [07]5, [13]6 | 9.783 | 26.926 |
| EG | Egypt | [95]3, [00, 05]4, [08]5, [14]6 | 6.624 | 31 |
| ET | Ethiopia | [92, 97]4, [03]6, [08]7 | 5.353 | 25.460 |
| GA | Gabon | 00, 01, 12 | 7.533 | 27.459 |
| GM | Gambia | [13]6 | 7.989 | 27.240 |
| GH | Ghana | [93, 98]3, [03]4, [08]5, [14]6 | 7.574 | 25.896 |
| GU | Guatemala | [95, 98, 99]3, [14, 15]6 | 6.564 | 25.794 |
| GN | Guinea | [05]4, [12]6 | 5.246 | 27.616 |
| GY | Guyana | [09]5 | 10.905 | 27.551 |
| HT | Haiti | [00]4, [05, 06]5, [12]6, [16, 17]7 | 6.378 | 27.248 |
| HN | Honduras | [05, 06]5, [11, 12]6 | 7.735 | 25.813 |
| IA | India | [98, 99]3, [05, 06]5, [15, 16]6 | 7.677 | 26.569 |
| ID | Indonesia | [94, 97]3, [02, 03]4, [07]5, [12]6, [17]7 | 10.152 | 29.693 |
| JO | Jordan | [02]4, [07]5, [12]6, [17, 18]7 | 9.7 | 31.44 |
| KK | Kazakhstan | [95, 99]3 | 10.5 | 25.214 |
| KE | Kenya | [98]3, [03]4, [08, 09]5, [14]6 | 8.427 | 25.509 |
| KY | Kyrgyz Republic | [97]3, [12]6 | 11.7 | 27.234 |
| LS | Lesotho | [04, 05]4, [09, 10]5, [14]6 | 8.442 | 25.79 |
| LB | Liberia | [06, 07]5, [13]6 | 5.531 | 27.609 |
| MD | Madagascar | [97]3, [03, 04]4, [08, 09]5 | 5.237 | 26.065 |
| MW | Malawi | [00, 04, 05]4, [10]5, [15, 16]7 | 7.1 | 25.706 |
| MV | Maldives | [09]5, [16, 17]7 | 8.851 | 29.089 |
| ML | Mali | [95, 96]3, [01]4, [06]5, [12, 13]6, [18]7 | 3.261 | 27.389 |
| MB | Moldova | [05]4 | 10.846 | 22.577 |
| MA | Morocco | [03, 04]4 | 5.133 | 28.523 |
| MZ | Mozambique | [97]3, [03]4, [11, 15]6 | 5.902 | 26.595 |
| MM | Myanmar | [15, 16]7 | 6.255 | 32.26 |
| NM | Namibia | [00]4, [06, 07]5, [13]6 | 8.215 | 27.817 |
| NP | Nepal | [96]3, [01]4, [06]5, [11]6, [16]7 | 6.004 | 25.140 |
| NC | Nicaragua | [97, 98]3, [01]4 | 7.381 | 26.129 |
| NI | Niger | [98]3, [06]5, [12]6 | 3.755 | 27.545 |
| NG | Nigeria | [03]4, [08]5, [13] | 9.482 | 26.168 |
| PK | Pakistan | [12, 13]6, [17, 18]7 | 3.417 | 29.667 |
| PE | Peru | [96]3, [00]4, [03–12]5 [09–12]6 | 10.703 | 26.921 |
| PH | Philippines | [98]3, [03]4, [08]5, [13]6, [17]7 | 11.351 | 27.593 |
| RW | Rwanda | [00, 05]4, [10, 11, 14, 15]6 | 5.061 | 26.98 |
| ST | Sao Tome and Principe | [08]5 | 6.186 | 26.644 |
| SN | Senegal | [05]4, [10–13, 15]6, [17]7 | 4.70 | 28.576 |
| SL | Sierra Leone | [08]5, [13]6 | 5.36 | 27.771 |
| ZA | South Africa | [98]3, [16]7 | 9.789 | 27.420 |
| SZ | Swaziland | [06, 07] | 9.014 | 24.958 |
| TJ | Tajikistan | [12]6, [17]7 | 9.595 | 27.812 |
| TZ | Tanzania | [96]3, [04, 05]4, [09, 10]5, [15, 16]7 | 6.743 | 26.962 |
| TL | Timor-Leste | [09, 10]5, [16]17 | 9.468 | 26.268 |
| TG | Togo | [98]3, [13, 14]6 | 5.994 | 26.959 |
| TR | Turkey | [98]3, [03, 04]4 | 5.176 | 26.235 |
| UG | Uganda | [95]3, [00, 01]4, [06]5, [11]5, [16]7 | 7.144 | 26.852 |
| UA | Ukraine | [07]5 | 12.706 | 25.647 |
| UZ | Yemen | [96]3 | 10.632 | 27.211 |
| ZM | Zambia | [96]3, [01, 02]4, [07]5, [13, 14]6 | 7.471 | 26.701 |
| ZW | Zimbabwe | [94]3, [99]4, [05, 06]5, [10, 11]6, [15]7 | 9.336 | 26.425 |
Column 1 and 2 display country code and name. Column 3 shows [survey year]survey wave. For example, [99, 01–0.3]4 means that the respondents of survey wave 4 in the sample are interviewed in 1999, 2001, 2002, and 2003. Besides, Columns 4 and 5 also provide the average years of education and age for the sampled women.
Additional summary statistics.
| Mean (SD) | |||
|---|---|---|---|
| Intra-household decision making | Relational friction | ||
| Large purchases | 0.411 | Being pushed | 0.241 |
| (0.404) | (0.428) | ||
| Daily purchases | 0.454 | Being slapped | 0.257 |
| (0.444) | (0.437) | ||
| Own earnings | 0.861 | Being punched | 0.118 |
| (0.286) | (0.323) | ||
| Husband/Partner earnings | 0.411 | Being kicked | 0.123 |
| (0.360) | (0.328) | ||
| Women’s health care | 0.584 | Being strangled | 0.052 |
| (0.431) | (0.221) | ||
| Food cooked | 0.455 | Being twisted | 0.091 |
| (0.444) | (0.287) | ||
| Family visits | 0.546 | Being humiliated | 0.17 |
| (0.407) | (0.383) | ||
| Being threatened with harm | 0.110 | ||
| (0.313) | |||
| Being insulted | 0.226 | ||
| (0.418) | |||
NOTE: The seven items that constitute the intra-household decision making indices include Large Purchases, Daily Purchases, Own Earnings, Husband/Partner Earnings, Women’s Health Care, Food Cooked, Family Visits. Each takes the value of 1 if the woman is the sole decision maker, 0.5 if she is partially involved in the decision, 0 if she has no say in the decision. The items that form the relational friction indices include Being Pushed, Being Slapped, Being Punched, Being Kicked, Being Strangled, Being Twisted Being Humiliated, Being Threatened with Harm, and Being Insulted. Each is a dummy indicating whether the husband/partner ever uses a particular type of violence against his wife.
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