rafmacalaba/data-use-mentions-extended huggingface dataset:
# Two Sides of Gender: Sex, Power, and Adolescence<sup>∗</sup>

Manisha Shah Jennifer Seager University of California, Los Angeles & NBER George Washington University

> ∗We would like to thank participants at UC Berkeley, NYU, Columbia, U of Michigan, BREAD, NBER Health, UCSD, UT Austin, UCLA, UC Riverside, WADES, OU, Rice University, Tinbergen, Erasmus University, Georgetown, George Washington University, and the World Bank for their valuable comments and feedback. We thank Debraj Ray, Lori Heise, and Michael Frese for helpful conversations. Gabriela Rubio for excellent research assistance. We gratefully acknowledge funding for this project from the Hewlett Foundation and the Africa Gender Innovation Lab (GIL) at the World Bank. Empirical analysis is pre-registered through the AEA RCT registry (RCT ID: AEARCTR-0001305). 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. For questions or comments please contact Manisha Shah at `ManishaShah@ ucla.edu` .
# **Concluding Remarks**

This paper is the first to explore the emergence of gender differences in the labor market in Azerbaijan. A further novelty of the paper is the focus on early career, made possible by the ILO’s SWT survey, a unique source of information both for the size of the sample and the wealth of information on young people’s individual and demographic characteristics and labor market activity.

We address the question of whether gender wage differences appear from the beginning of the careers of young men and women or whether they emerge later in their careers. The analysis suggests that at the point of entry into the labor market, differences between men and women are marginal. However, measurable differences emerge as workers begin making choices between family formation and work. The Oaxaca and Blinder decomposition analysis shows that women have better productivity-related characteristics than their male counterparts but are paid less for the same characteristics. This points to a sizeable unexplained component of the gap. The Juhn, Murphy and Pierce decomposition confirms these results at different quantiles of the earnings distribution. In fact, quantity effects – differences by gender in productivity characteristics – are almost invariably irrelevant. Overall, both the Oaxacha and Blinder and the Juhn, Murphy and Pierce decomposition analyses suggest that differences in pay may be due to the way the labor market rewards the same characteristics depending on whether it is a man or a woman who possesses them. This case is generally associated with the phenomenon referred to as “sticky floor and glass ceiling”, namely the tendency of men and women to be paid differently especially at the bottom and at the higher end of the earnings distribution, where differences in pay are more striking. This hypothesis is strongly confirmed by Machado and Mata decomposition analysis at each percentile of the earnings distribution.

One surprising result is the selection into employment of young men and women. Contrary to expectations, it is the men, rather than the women, who experience more self-selection based on skill and motivation. The selection is based on civil
women with children working.

All treatment groups receive information on the extent of women’s support for women with children working; treatment group 2 also receives information on the extent of men’s support for shared child care; and treatment group 3 receives all three types of information listed above.

> 3Bursztyn et al. (2023) examine misperceptions of social norms using nationally representative datasets from 60 countries, including Indonesia. They find that Indonesia has one of the lowest shares of support for women having the right to work outside the home (supported by 59% of men and 73% of women). These figures are very similar to the levels of support found in our study - 62% and 76% for men and women respectively. They further find that Indonesians underestimate the level of support for women having the right to work outside the home. The underestimation of women’s support for women working outside the home is 7.9 percentage points (very similar to the average underestimation of 9.4 percentage points in our sample); and of men’s support is 6 percentage points (slightly larger than the 2.5 percentage point underestimate in our sample).

> 4Changing men’s behavior in relation to participating in home production and childcare goes hand-inhand with increasing female labor force participation. Since childcare is still largely a gendered task, changing this norm has the potential to increase women’s ability to search for employment opportunities outside the home.

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More importantly, FDI can push up wage levels for skilled workers and elevate the overall returns to education in local labor market. FDI also raises household income in host locations. Table 9 already demonstrated a strong income effect. As parents’ income rises, they are more likely to send their children to high school and college. Unfortunately, we are unable to test whether cities that received more manufacturing FDI inflows experienced higher increase in skill premium because we only have income data in 2005.

# 6. Heterogeneity

## 6.1 FDI shock by export intensity

A main channel for manufacturing FDI to increase labor demand is through export expansion. Better knowledge about foreign markets and established global production networks allow foreign-owned firms to account for a disproportionately high share of exports in many host locations. By supplying to the global market, export-oriented FDI raises labor demand much more than domestic market-seeking FDI does. How does the effect of FDI shock on structural transformation and human capital accumulation vary by export intensity of FDI? We first calculate foreign manufacturing firms’ export intensity across 3-digit industries using 1998-2005 ASIF dataset. Export intensity of FDI is calculated as below: The numerator is total exports of all foreign firms in industry i during 1998-2005. The denominator is total sales of all foreign firms in industry i during the same period. Essentially, the export intensity of FDI is the share of total foreign exports in total foreign sales in each industry. Ideally, we would use 1990-2005 firm data to calculate FDI export intensity, but ASIF data is only available from 1998. Foreign firms’ export intensity in each industry remains highly stable over time, so we calculate this time-invariant indicator and divide manufacturing industries into two groups: high export intensity industries (above median export intensity) and low export intensity industries (below median export industry). Using a similar Bartik approach, we define change in high and low export intensity FDI: ∆FDI_export_H and ∆FDI_export_L as below: ∆FDI_export_H is the interaction between initial industry employment share in city c, province p and
# **_5.2 Firm Financing Patterns (Capital Structure Choice)_**

An extensive theoretical literature in corporate finance shows that an optimal choice of securities and contracts can be used to mitigate agency conflicts<sup>20</sup> Further, this optimal choice depends on the information available to investors and their ability to monitor the firm and enforce their legal rights.<sup>21</sup> Since accounting standards and information available to investors and investor protection rights vary across countries and, one should expect firms‟ financial structures to differ systematically across countries as well. The first generation of papers on capital structure choices across developing countries relied mainly on large publicly traded firms and was focused on explaining a firm‟s leverage choices. With the availability of firm-level survey data across small, medium, and large firms in developing countries on their financing choices, the second generation literature was able to study firm financing patterns more broadly. We review both streams of literature below.

Demirguc-Kunt and Maksimovic (1999) were the first to establish systematic differences in debt maturity choices of firms in developed versus developing countries. Examining 30 countries between 1980-1991, they find that firms in developed countries had more long term debt, regardless of firm size. They then explore whether these differences can be accounted for by firm and institutional characteristics.<sup>22</sup> They find that large firms in countries with effective legal systems substitute long-term debt for short-term debt while small firms do not. As for institutional factors, they find limited evidence that both large and small firms in countries with a common-law tradition use less long-term debt, relative to their assets, than firms in countries with a civil-law tradition. They also find that stock market activity influences the debt levels of large firms but not small firms (large firms have more long-term debt in countries with active stock markets) whereas size of the banking sector influences debt levels of small firms but not large firms (small firms have less short term debt and more long
SOEs accounted for most of the recent rise in corporate leverage, and the fastest-growing component of SOE debt was for local government financing vehicles (LGFVs). SOE debt rose from 73 to 103 percent of GDP in 2012–15 (Figure 20). Accelerated debt accumulation by LGFVs explains the rapid increase in the share of SOE debt (Bai et al., 2016). Based on the Wind database sample of firms in China that issue bonds, the liabilities of LGFVs that issue bonds grew by more than 20 percent a year during 2012–16 if the effect of the local government debt swap program is netted out (Figure 21).<sup>18</sup> In contrast, the liabilities of other enterprises increased by 13 percent a year in 2015–16. While the headline growth in LGFV liabilities declined in 2015 and 2016, this can be attributed to the bond swap scheme that transformed part of their debt into government bonds.

**Figure 20 Estimated composition of debt**

(percent of GDP)

**Figure 21 Growth in liabilities of LGFVs and other corporations**

(annual growth in total liabilities, percent) <!-- Start of picture text --> LGFVs SOEs (Non-LGFVs) All corporates<br>300 Private General government Non-LGFVs<br>Household 30 LGFVs<br>250 LGFVs (adjusted for bond swaps)<br>44.4<br>38.8 25<br>35.7<br>200<br>33.1<br>29.7 41.7 44.5 20<br>40.2<br>37.2<br>150 34.4<br>66.8 63.6 15<br>65.4<br>62.4<br>100 57.7<br>10<br>47.8 52.9<br>42.9<br>50 42.0 42.0<br
- McKenzie, D., Stillman, S., Gibson, J., 2010. How important is selection? Experimental vs. nonexperimental measures of the income gains from migration. _Journal of the European Economic Association_ , _8_ (4), 913-945.

- Mitchell, M., Favara, M., Porter, C., Sánchez, A., 2020. Human capital development: New evidence on the production of socioemotional skills (Discussion Paper No. 13804), _Discussion Paper Series. Institute of Labor Economics (IZA), Bonn, Germany._

- Montenegro, C.E., Patrinos, H.A., 2021. A data set of comparable estimates of the private rate of return to schooling in the world, 1970–2014. _International Journal of Manpower ahead-of-print_ .

- Muralidharan, K., 2019. Reforming the Indian School Education System, in: _What the Economy Needs Now, edited by Abhijit Banerjee, Gita Gopinath, Raghuram Rajan, and Mihir Sharma, Juggernaut_ .

- Nunnally, J.C., 1978. Psychometric theory, 2nd edition. ed, McGraw-Hill series in _Psychology. McGraw-Hill, New York._

- Outes-Leon, I., Dercon, S., 2009. Survey attrition and attrition bias in Young Lives (Technical Note No.

- 5), _Young Lives Technical Notes. University of Oxford, Oxford, United Kingdom._

- Pierre, G., Sanchez Puerta, M.L., Valerio, A., Rajadel, T., 2014. STEP skills measurement surveys:

- Innovative tools for assessing skills (Discussion Paper No. 1421), _Social Protection and Labor Discussion Papers. World Bank, Washington, DC._

- Pritchett, L., 2013. The rebirth of education: Schooling ain’t learning. _CGD Books._

- Schultz, T. W., 1975. The value of the ability to deal with disequilibria. _Journal of Economic Literature_ , _13_ (3), 827-846.

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. The budget weights used for the two indices however, differ in two ways. First, in the year 2014, the official CPI base year was set at 2011 and CPI item weights were derived from EICV3 data. In contrast, item weights for the COLIs came from EICV4 data. Second, CPI item weights were computed using all survey households, while COLI used only the bottom 40 percent of households. Thus, both the year and the reference group used to obtain item weights for the two price indices are different.

The second major difference in CPI and COLI relates to the level of aggregation of the two indices. The CPI is estimated for national, rural and urban regions, while the COLI is estimated for 5 provinces.

> 12 Inequalities (12) and (12’) use a unique poverty line expressed in January 2014 prices. But as shown above, the global poverty line uses a poverty line expressed in prices of an average month of a household survey, i.e., IPL��� ��� �����  for EICV3 survey (2010/11) and IPL��� ��� ����� for EICV4 (2013/14). Appendix 2 shows how inequalities (12) and (12’) can be modified so that (i) poverty rates do not change but (ii) IPL��� ��� �����  and IPL��� ��� �����  are used as the poverty line for EICV3 and EICV4, respectively.

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for firms in the insourcing and outsourcing treatments. The second follow-up survey took place one year later (between February and June 2019), which corresponds to two years after interventions started and 14-21 months after interventions ended depending on treatment group.

The first follow-up survey had a response rate of 88.6%, and the second follow-up survey had a response rate of 86.1%. 93% of firms completed at least one of the follow-up surveys. In addition, we were able to collect data on business closure for many of the firms not answering the survey, so we have operating status for 96.4% of firms in the second follow-up survey. We cannot reject equality of attrition rates across the five experimental groups (Appendix Table 3.1). Further, the sample of survey non-attritors remains balanced on baseline observables (Appendix Table 3.2).

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imperfectly indicate the likelihood that a given child was vaccinated.<sup>11</sup> We interpret these results with caution as evidence of a causal effect of ITNs. However, it is possible that the changes the decomposition attributes to the increase in ITN ownership in high malaria risk zones are actually due to other anti-malarial interventions that are correlated with

> 10 In the Oaxaca-Blinder decomposition, the explained part of the overall difference is a sum of positive and negative contributions of all explanatory variables. Thus, the sum of positive contributions alone adds up to more than 100 percent of the overall change.

> 11 Vaccination rates are measured this way becase vaccination status is not available for deceased children.
be differential stock endowments across the two areas. This could explain our results for differential catch, but such an alternative explanation would have to take a particular form to capture both of our empirical results: specifically, the stock advantage of the Pacific side would have to be relatively larger for small scale species than for large scale species. Existing work suggests the presence of differences in ocean productivity in the Pacific versus Gulf sides of the Baja Peninsula; unfortunately, however, not much is known (as far as we are aware) about how these differences manifest differentially across small scale and large scale species. Therefore, this alternative explanation for our catch results may be plausible, and we do not have evidence to support or refute it at this time. Nevertheless, we believe our model is the most plausible explanation that captures all of the empirical patterns we have seen for price and catch in one unified framework.

# V CONCLUSION

In this paper, we set out to understand how cooperatives use property rights to control fishing effort, and how this use is shaped by key characteristics of the targeted fish populations: scale of individual movement and responses to large environmental fluctuations. Using rich logbook data from three cooperatives, including one that enjoys strong property rights, we find support for the implications of our theoretical model. The magnitude of the differences between the cooperative with property rights and the ones without rights—as well as the shrinking of these differences when resources have a large scale or when growth rates are high—are economically significant.

These results highlight the value of linking theory with empirical analysis in order to examine the reciprocal interactions between natural resources and resource users. Our approach focuses on the economic mechanisms underlying these interactions and thereby complements more descriptive, existing analyses of fishery outcomes. Our results are also relevant beyond fisheries, as they illustrate how the decisions of resource users embedded in local institutions are mediated by characteristics of the resource and external dynamic factors. However, given that our logbook data are restricted to only three cooperatives, our
its estimates of irregular foreign workers are based on its ad hoc enforcement activities, suggesting that four out of ten foreign workers are irregular. Taking these two together leads to a foreign worker population of 2.93 million, including 1.3 million irregular workers, in 2018. The LFS captures some of the foreign worker population, including irregulars, estimating 2.43 million foreign workers in total in 2019, or about 15 percent of the total labor force. Population census-based data of the Department of Statistics Malaysia estimates 3.2 million foreigners residing in Malaysia, but this includes higher-skilled expatriates, their dependents, and all people who were not born in Malaysia.

**Foreign workers have become important to fill jobs.** LFS data depict the magnitude of the foreign workforce in Malaysia’s labor market, albeit imperfectly. Inflows of foreign workers have increased steadily since the 1990s, when the government introduced a system to manage the low-skilled foreign workforce. As shown in Figure 1, the share of foreign workers in total employment increased from 10 percent in 2006–08 to around 15 percent from 2013 onwards. The foreign worker share among the employed youth workforce has increased more rapidly: in 2016 about 26 percent of the total youth employed were foreign workers, compared to about 8 percent in 2006–08.  The share of male foreign workers has expanded faster than the female share: while the ratio of foreign to Malaysian employees remained at one to ten over the decade for females, it increased to two to ten for their male counterparts. This gender divide is likely attributable to the design of Malaysia’s foreign worker system, which has more vacancies for labor-intensive jobs traditionally held by men.

3
for developing countries through household surveys such as the DHS, and typically are infrequently collected.

The rest of Section 3 details the specific steps of this procedure for calibrating the effects of health on worker productivity. Section A3.2 discusses micro‐econometric estimates of the return to height, γ������ . Section A3.3 discusses estimates of the relationship between adult height and adult survival rates, β������,��� . Section A3.4 discusses how to calibrate estimates of the change in adult height attributable to reductions in stunting, β������,�������� .

# **A3.2  Estimates of the Return to Height**

Weil (2007) uses a baseline estimate of γ������ �0.034 , i.e. one additional centimeter of height raises earnings by 3.4 percent. This evidence is taken from two previous studies comparing height and earnings within twin pairs in the United States and in Norway. The main strength of these twin studies is their identification strategy of relying in random variations in birthweight between twins as a plausibly exogenous source of variation in their eventual adult heights. However, one might reasonably be concerned with the external validity of these findings, since these studies are based on pairs of twins in two advanced economies (Norway and the United States). To assess this concern, it is useful to briefly consider three other sets of estimates of returns to height from 19 other studies covering a range of developed and developing countries. All of these other estimates are based on instrumental variables regressions of log wages on height, with instruments of varying degrees of plausibility. Conditional on the validity of the instruments, these should all recover the effect of height on wages conditional on education, either because education is included in the regression, or because the instrument is uncorrelated with omitted education (under the null hypothesis that the exclusion restriction holds).

The
If underdeclaration does not respond at all to changes in tax rates, then revenues would rise or fall based entirely on the change in the tax rate; that is, a given percent change in the tax rate would give rise to a proportional change in stamp duty revenues. We examined historical data to test whether this hypothesis holds. Annex II provides a time series of historical stamp tax rates covering FY1980-1981 to FY2003-2004, collated for the purpose of this paper. Ideally, regression analysis could be used to test such a hypothesis. However, as perusal of Annex II shows, stamp duty rates, with the exception of West Bengal, have not changed often enough to get reliable estimates of regression coefficients for individual States.<sup>44</sup> Our analysis compared changes in stamp duty rates to revenue changes over the period in eleven major Indian States where duty rates have changed, as shown in Figures 1 to 11. Recall that Figures 1 to 11 show the trend analysis on a State by State basis. The pattern that emerges is quite clear: reductions in rates rarely result in a proportional decline in revenues. Indeed in several cases, revenues actually increase in response to a rate change. Likewise, rate increases (except in Kerala) tend to result in less than proportional revenue improvement, again indicating that underdeclaration tends to rise with rate increases. Figure 12 assembles all the instances of rate changes and associated revenue changes. All other factors held equal, if underdeclaration does not respond to tax rate changes, then we would expect these observations to be close to a 45-degree line, as a given percentage change in the tax rate feeds into a similar increase in taxes. However, the fitted line shows a slightly negative relationship between rate changes and revenue changes, although clearly there is a good deal of variability that is not explained by the rate changes alone. In statistical terms, the slope of the line is not significantly different from zero (the confidence level is about 65 percent). (See Annex