rafmacalaba/datause-encoder-data huggingface dataset:
Urdal & Hoelscher: Urban Youth Bulges and Social Disorder levels of both lethal and nonlethal events. This difference between level and change may suggest that while pressures associated with large urban youth bulges may be associated with higher levels of lethal disturbance in Sub-Sahara African cities, young people in SSA generally migrate towards the urban centers that provide opportunities. Hence, growth in urban youth populations may primarily reflect where economic opportunities are most promising. Income levels, economic growth, democracy, armed conflict and prior disorder have similar effects for the SSA countries as for the entire sample.

**<u>Table 2 Sub-Saharan Africa</u>**

|**Explanatory**<br>**Variables**|**Model 5**|**Model 6**|**Model 7**|**Model 8**|
|---|---|---|---|---|
||**Lethal**<br>**events**|**Nonlethal**<br>**events**|**Lethal**<br>**events**|**Nonlethal**<br>**events**|
|Urban male β<br>youthbulgesz|0.088**<br>(2.06)|-0.027<br>(0.96)|||
|Urban male<br>youthgrowth|||-1.425**<br>(-2.12)|-1.319**<br>(-2.13)|
|Urban male<br>youthbias|0.434<br>(0.53)|-0.083<br>(-0.11)|1.209<br>(1.42)|0.233<br>(0.31)|
|City pop|0.004<br>(0.65)|-0.001<br>(-0.13)|0.007<br>(1.08)|-0.002<br>(-0.33)|
|Real gdp pc|0.020<br>(0.21)|0.191**<br>(1.98)|-0.099<br>(-1.14)|0.210**<br>(2.31)|
|Real gdp per<br>capita growth|-0.023***<br>(-2.71)|-0.014*<br>(-1.65)|-0.022***<br>(-2.60)|-0.013<br>(-1.59)|
|Regime type|0.023<br>(1.34)|-0.010<br>(-0.55)|0.013<br>(0.72)|-0.012<br>(-0.73)|
|Regime squared|-0.013***<br>(-3.86)|-0.011***<br>(-3.70)|-0.013***<br>(-3.85)|-0.010***<br>(-3.38)|
|Missing regime<br>data|-0.038<br>(-0.05)|-0.733<br>(-0.78)|-0.736<br>(-0.83)|-0.832<br>(-0.86)|
|Ongoing armed<br>conflict|0.438***<br>(2.67)|0.261*<br>(1.67)|0.432***<br>(2.60)|0.246<br>(1.60)|
|Lagged<br>dependent|0.096***<br>(3.08)|0.115***<br>(3.53)|0.092***<br>(2.90)|0.110***<br>(3.34)|
|Constant|-3.748**<br>(-2.15)|0.571<br>(0.46)|0.602<br>(0.53)|0.889<br>(0.88)|
|N<br>No. of cities<br>LogLikelihood|872<br>23<br>-615.67|872<br>23<br>-732.24|872<br>23<br>-615.56|872<br>23<br>-730.30|

* Sign at 0.1 ** Sign at 0.05 ***Sign at 0.01.

The first three interaction models are presented in Table 3. Neither secondary educational attainment, expansion in tertiary education, nor high levels of informal employment interact with large urban male youth bulges to increase the level of social disturbance. The closest in terms of statistical significance levels, is that the interaction between urban youth and expansion in tertiary education is positively associated with higher levels of nonlethal events (Model 12). Interestingly, higher levels of secondary educational attainment are clearly associated with lower 14
both child and parent characteristics in the regression. Nevertheless, selection based on unobservable individual characertisitcs is still likely.

To deal with such individual-level selections, we use local norm of parental matchmaking as the instrumental variable for one's own matchmaking choice. The social norm of parental matchmaking is constructed as the share of males getting married via parental matchmaking in the same province-urban cell with the same age or being older by up to three years.<sup>18</sup> We have tried alternative measures of social norms such as relying on the sample of the same age only, or the sample of respondents that of the same age or older no more than one (two) year and so on. The results are qualitatively similar. If a region has a stronger norm of parental involvement in their children's spousal selection, parents have a larger network of potential marriage partners for their sons. This would alter their search benets and costs, thus directly aecting individual-level reliance on parental matchmaking. On the other hand, after controlling for the son's characteristics and family background, it is unlikely that the local social norm would directly aect marriage outcomes. To the extent that matchmaking norm is correlated with unobserved local culture and tradition that cannot be explained by average income or schooling dierences across townships, such variations in local culture and tradition are absorbed in matchmaking norm, and the eect of parent matchmaking should be viewed as those induced by local parent matchmaking norms and related culture and tradition. Given the likely prevalence of individual-level selection in parental matchmaking, we shall mainly rely on the instrumental variable regression results below.

Our baseline results are contained in Table 4. In the rst 3 columns, we report the results for Harmony. Column (1) reports the OLS result with a base set of controls; column (2) adds religion and ethnic dummies; column (3) is the 2SLS result corresponding to column (2). The next three columns repeat the same structure with the dependent variable being the logarithm of joint couple income. All standard errors are White-corrected and clustered at the district / township level since we have local income and schooling controls at this level. First-stage Cragg-Donald Wald F statistics and Kleibergen-Paap Walk Rank F statistics are reported at the bottom of Columns (3) and (6). The complete rst-stage regressions are reported in Appendix B.

Parental matchmaking is robustly correlated with lower marital harmony. The coecient of Parent Matched is consistently negative and signicant from the two OLS regressions, with no signicant dierence between urban and rural areas. The instrumental variable estimate is again negative, more pronounced in magnitude, and statistically signicant. According to the 2SLS estimate, increasing Parent Matched by one standard deviation (0.47) would lead

> 18In computing the average, we exclude the self to avoid articial correlation between the instrument and the endogenous variable.

22
# NOTES

1. See, for example, Theodore Shultz (editor), Economics of the Family (Chicago: Chicago University Press, 1974).

2. Lee Benham, "Benefits of Women's Education within Marriage", Journal of Political Economy, (March-April 1974).

3. See G.S. Becker, "A Theory of Marriage", Journal of Political Economy (July-August 1973).

4. The theory of the benefits of association can be extended to include other dimensions of the effects of wife's attributes and marriage on husband's earnings: see A. Grossbard-Shechtman and S. Neuman, "Men's Earnings, Marriage, and Culture" Mimeo 1988. This paper confirms the applicability of Benham's approach to Israel.

5. Benham, p 376.

6. See Yue-chim Wong, "Entrepreneurship, Marriage and Earnings," Review of Economics and Statistics, 1986. These particular findings, however, may be suspect, because of data inadequacies: see A. Ziderman, "Testing for cross productivity effects of education among entrepreneur families," Mimeo 1989.

7. S. Neuman and A. Ziderman, "Testing the Dual Market Hypothesis: Evidence from the Israel Labor Mobility Survey," Journal of Human Resources (21, 1986). The classic presentation of the dual labor market viewpoint is given in Peter Doeringer and Michael Poire, Internal Labor Markets and Manpower Analysis, (Lexington, Mass: D. C. Heath, 1971).

8. Robert McNabb and George Psacharopoulos, "Further Evidence of the Relevence of the Dual Labor Market Hypothesis for the UK", Journal of Human Resources (16, 1981).

9. Tyree's occupational prestege ratings for Israel were used; see Andrea Tyree, "Occupational Socioeconometric Status, Ethnicity,and Sex in Israel: Considerations in Scale Construction" (Hebrew) Megamot. (September 1981). Workers were assigned to primary or secondary labor markets on the basis of occupational prestige scores, rather than earnings as is the case in many other studies, in order to avoid problems of truncation bias, as discussed in G. Cain, "The Challenge of Segmented Labor Market Theories to Orthodox Theory: A Survey," Journal of Economic Literature, (14, 1976). The correlation between earnings and prestige scores is not high. See Neuman and Ziderman for an account of, and justification for, the method used.

10. The economic sectors are: Industry (mining and ianufacturing) - IND; Electricity and water ELECT; Construction (building and - public works) CONSTR: Commerce, restaurants and hotels COMM; Transport, storage and communications TRANS; Financing and 13
Consider the fertility-mortality-breastfeeding system as consisting of the relationships among three events that may follow a live birth: the termination of breastfeeding (i.e., the weaning of the child); the death of the child; the birth of the next child (Marcotte, 1988). Clearly the latter two events need not occur for every birth; indeed, death of the child is a relatively rare event in most human populations. Breastfeeding eventually ends for all children; but in those cases where the child is breastfed until death, death effectively censors breastfeeding and the child is never weaned. Any one of the three events may not have occurred as of the time of data collection, i.e. they may be censored by the interview. A final point is that, where the data allow, it is preferable to use the onset of the next pregnancy (live or non-live outcome) rather than the next live birth as the fertility event, as most of the hypothesized effects concern pregnancy. (That is, weaning and mortality responses to the next pregnancy can occur during the pregnancy, prior to the next live birth).

Hence, we have three events to model jointly: weaning, death, next pregnancy. These three events are the basic drivers of demographic change. Particularly in societies where deliberate contraceptive behavior is rare - a situation typifying much of Africa (North and sub-Saharan) - to a considerable extent population dynamics (size, rate of growth, age structure) can be accounted for by simple aggregation of the risk of these three events occurring (singly and jointly). The contraceptive prevalence rate in Egypt at the time of the Egyptian Fertility Survey (the data used in this study) was roughly sixteen per cent, rather high by African standards but still indicative of the largescale absence of modern contraceptive efforts.

6
even larger for droughts that occur the year after a child’s birth. The impact of a drought during the birth season is more muted for a child’s weight (measured at the time of the survey), but it is still statistically significant. Being underweight is likely to be influenced by more contemporaneous factors, while impacts on stunting are more lasting.

This method also allows us to estimate the impacts on a child being born during the lean season. The impact, on stunting, of a child born during the lean season (3 percentage points) is as consequential as the difference in a child being born into a household in the poorest quintile instead of the second poorest quintile. Once again, the likelihood of being underweight, if a child is born during the lean season, is muted (but still statistically significant).

Table 5, comparable to Table 3, uses a full set of controls, but employs province and survey year fixed effects (equation 4 below).

Once again, it is clear that the height of a child’s mother is a major influence on the likelihood of a child being stunted, even after controlling for factors correlated with household wealth and income. The magnitudes of the drought impacts are substantial, when compared to the other factors. A child has a 4 percentage point greater likelihood of being stunted if born a harvest than a normal harvest. This is double the during poor magnitude of the impact associated with having a mother that is not literate. A child born to a partially literate or illiterate mother has a 2 percentage point greater likelihood of being stunted (controlling for other wealth correlates). Similarly, other important deprivations — such as not owning livestock and not treating drinking water — are comparable to drought impacts.

Having established that average drought impacts are causal and significant, both in terms of magnitudes and p-values, it is worth examining how these impacts may vary across countries. This is possible because we can use variation in birth years. If we were trying to understand drought impacts on the diversity of a child’s diet, for example, the available data would limit us to exploiting cross-section variation.<sup>24</sup> Given that weather anomalies are spatially correlated, at different spatial scales, this would necessitate combining data from several countries and regions.

# **3.2 Impacts across Countries**

Droughts may exert differing stunting impacts in different countries, even in the case in which all the countries are in the same region. First, countries have very different so-

> 24The DHS reports nutrition intake for children between 6 and 24 months at the time of the survey.

14
force participation, but it increases with time, as more years from the initial enactment of legal reforms pass.

Overall, our results suggest that gendered laws matter, but they matter more for some labor market outcomes than others. The effect of legal reforms is relatively small, but this is to be expected, given that legal discrimination is only one among many sources of gender imbalances and that the passing of better laws does not guarantee that these laws will be enforced, especially in countries with social norms disadvantaging women’s participation in the formal economy. But laws are actionable in the short run – in contrast to norms and attitudes, which may take longer time to change. In future research, it would be interesting to link the measures of women’s legal treatment in the WBL database to measures that capture women’s actual economic agency and investigate the relationship between _de jure_ and _de facto_ female empowerment.

The remainder of the paper is structured as follows. Section 2 presents a brief description of the WBL database. Section 3 provides on overview of the literature on the impacts of gender discrimination under the law. Section 4 documents a series of stylized facts for the 190 countries and 50 years in our sample. Section 5 examines the causal impact of legal reforms on labor market outcomes. Section 6 concludes.

# **2. WBL Database: A Short Description**

The WBL data set focuses on legislation that may impact a woman’s access to employment and entrepreneurial activity; it does not cover legal gender discrimination across all aspects of a woman’s life. The information on the legal environment in each economy is collected through collaboration of legal experts based in the World Bank with local experts, including lawyers, judges, civil society representatives and public officials. In total, a network of more than 10,000 legal experts contribute to the WBL project.

The data set attempts to capture inequality in legislation throughout the duration of a woman’s working life, from the time she can enter the labor force through to retirement. Thirty‐five individual legislative issues are aggregated into the following eight indicators, with four or five binary questions in each: _Going Places_ examines constraints on freedom of movement; _Starting a Job_ analyzes laws affects a woman’s decision to work; _Getting Paid_ measures laws and regulations affecting women’s pay; _Getting Married_ assesses legal constraints related to marriage; _Having Children_ examines laws that affect women’s work after having children; _Running a Business_ analyzes constraints to women starting and running a business; _Managing Assets_ considers gender differences in property and inheritance; and, finally, _Getting a Pension_ 3
in this study. Our sample consists entirely of BDH-eligible households who are in the poorest two quintiles of Ecuador.

We find that random assignment of the BDH income is associated with less work for pay, less involvement in the family farm or business, increased schooling, and fewer children working in some way without attending school. Market work declines as schooling increases, but domestic work appears positively associated with the increase in income, although this increase is small and insignificant. These findings are consistent with a growing literature that has documented that cash and in-kind transfers can reduce child work and increase school enrollment (e.g. Attanasio et al. 2006; Edmonds 2006; Filmer and Schady 2008; Ravallion and Wodon 1998; Schultz 2004).

Our paper adds to this literature in a number of important ways. First, we provide a theoretical framework which predicts that there should be substantial heterogeneity in program effects. Using an adaptation of the Basu and Van (1998) model, we show in section 3 that the effect on child labor of the BDH transfer should be concentrated among children most vulnerable to transitioning between school and work. Specifically, our hypothesis is that for young children, for whom schooling is less expensive and the opportunity cost of time in school low, additional income is likely to have little effect on child time allocation. For older children, already withdrawn from school and working, the cash transfer is likely too small to affect their time allocation. However, for children in school and not working but facing the dramatic increase in schooling costs that comes with completing primary school in Ecuador and the rise in opportunity costs that comes with age, their time allocation is potentially substantially altered by small changes in non-child labor income.

The findings for work for pay are strongly consistent with this theory. The decline in work for pay associated with BDH receipt on average is concentrated in children most vulnerable to transitioning from work to school. Older children in poor households, especially girls and children in rural areas who are at the end of primary school or higher in the baseline survey are most likely to transition to work for pay and stop schooling in the control sample follow-up survey, taken 1.5 years later. It is this population of older children finishing primary or higher that experience the largest declines in work for pay and increases in schooling with the BDH transfer. These findings for work for pay and schooling are consistent with the results from the PROGRESA program in Mexico, which appears to have an impact on school enrollment 2
WPS3946

# Migration, Sex Bias, and Child Growth in Rural Pakistan

## Ghazala Mansuri*

### **Abstract**

Temporary economic migration is undertaken largely in response to resource constraints. This is evident in the volume of remittances sent back by migrants to their families of origin. In agricultural settings, where those left behind are likely to face considerable exposure to uninsured income risk, such resource flows should translate into better risk bearing capacity. In this paper we take up this question by asking whether economic migration allows households to avoid costly risk coping strategies. We focus on early child growth since there is considerable epidemiological evidence that very young children are particularly vulnerable to shocks that lead to growth faltering, with substantial long-term health consequences. The data come from rural Pakistan, where, as in the rest of Asia, son preference is substantial and there are large gender gaps in most developmental outcomes. As such, our interest is in examining also whether migration induced resource flows allow households to extend better nutrition and health care protection to girls. Recent work on the intra-household allocation of resources and risk has also shown that gender differences in the relative burden of risk may be important and that the allocation of resources to daughters is often one margin along which poor households adjust to uninsurable transitory income shocks. After accounting for selection into migration, the results indicate that migration has a substantially larger positive impact on growth outcomes for young girls. Moreover, the growth advantage is sustained among older girls, suggesting potential intergenerational benefits of averting nutritional and other health shocks for girls in early childhood. These results are further validated by restricting the sample to migrant households and comparing the growth outcomes of siblings before and after migration.

Keywords: Migration, Child Growth, Vulnerability, Sex-Bias

## World Bank Policy Research Working Paper 3946, June 2006

_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 view of the World Bank, its Executive Directors, or the countries they represent. Policy Research Working Papers are available online at http://econ.worldbank.org._

> *Development Research Group, World Bank, 1818 H St. NW, Washington DC 20433. Email: gmansuri@worldbank.org.
35

**Table 20. Impact of Decentralization on the Structure of Budget Expenditures**

|Regressors / Dependent Variable|Share of expenditures<br>on Education in the<br>consolidated regional<br>budget expenditures|Share of expenditures on<br>National Economy in the<br>consolidated regional<br>budget expenditures|
|---|---|---|
|Constant|4.80|43.07|
||(3.02)|(40.24)|
|Infant mortality in 1990|0.38<br>(4.43)||
|Percent of rural population in 1994|(6.22)|(-.37)|
|Local governments total revenues as<br>percent of the consolidated regional|0.12<br>_(5.96)_||
|budget revenues|||
|Local governments budget deficit as<br>f ll l|-0.10<br>|0.10*<br>|
|percent o oca governments tota<br>expenditures|(-3.62)|(2.17)|
|Real per capita income|-0.0003<br>(-4.36)||
|Dummy North Region|4.05|-7.17|
||(4.25)|_(-5.15)_|
|Dummy North Caucasus Region||-3.15<br>(-3.02)|
|Dummy Volgo-Vyatka Region||-4.97<br>(-4.62)|
|Dummy Ural Region|1.59|-3.54|
||(3.19)|(-4.61)|
|Dummy Eastern Siberia Region||-5.15<br>_(-2.75)_|
|Sample|1994 1996|1994 1996|
|Total Panel (Unbalanced) Observations|<br>243|255|
|Adjusted R-squared|0.46|0.36|
|<br>Durbin-Watson|0.89|0.90|
|White's Heteroskedasticity Test|85.91<br>(0.0O) **|62.69<br>(0.00) **|
|Standard Error of Regression|2.88|5.73|
|Root Mean Squared Residual 1994|2.14|4.88|
|Root Mean Squared Residual 1995|3.51|5.87|
|Root Mean Squared Residual 1996|2.65|6.07|

Notes: Unless otherwise indicated, numbers in parenthesis are t-statistics calculated with the White heteroskedasticity consistent standard errors of OLS coefficients Unless otherwise indicated, OLS coefficients are statistically significant at the 99% level of confidence

* Statistically significant at the 95% level of confidence

** P-value
**Figure 5: Impulse responses due to a 1 percentage point increase in growth in individual EM7 A. Aggregate spillovers B. Country spillovers**

<!-- Start of picture text --> Percentage point Percentage point<br>1.2 1.5<br>20-80 percentile range Average<br>0.8 1.0<br>0.4 0.5<br>0.0 0.0<br>-0.4 -0.5<br>China Russia India Brazil Mexico Indonesia Turkey China Russia India Brazil Mexico Indonesia Turkey<br><!-- End of picture text -->

# _Note:_

A. The graph shows cumulated impulse responses of growth in other EFM at the end of three years due to a 1 percentage point increase on impact in each of the EM7 growth. These results are from the aggregate VAR model. Solid bars represent medians, and the error bands represent 16-84 percent confidence bands.

B. The graph shows the cumulated impulse responses at the end of three years due to a 1 percentage point increase on impact in each of the EM7 growth. These results are from the country models. For each spillover source country, the bar denotes the 20-80 percentile range of the responses of other EFM economies and the red diamond denotes the cross-sectional average response.

19