rafmacalaba/data-use-mentions-extended huggingface dataset:
14 sponsored funds, the NPF, local and foreign strategic investors. We also continue to include the Herfindahl index to control for ownership concentration effects.

Table 2, regression iii reports the results for the panel regressions. There continues to be evidence for a signaling value from general bank-sponsored fund ownership as the coefficient for bank-sponsored fund ownership remains significantly positive for the Tobin's Q regression. The coefficient for local strategic ownership (profitability-regression) remains also significantly positive. We find no support for the conflicts of interest hypothesis as the coefficient for the main-bank ownership dummy is not negative, but rather significantly positive for the Tobin's Q regression and insignificantly positive for the profitability regression. 1<sup>7</sup> Minority shareholders appear thus to value the role of banks. There is therefore evidence of both signaling valuethrough bank-sponsored funds owning part of a firm-and of a useful monitoring role by main banks. While there may be conflicts of interest, they are not strong enough to cause ownership by a main bank-sponsored-fund to be associated with lower Tobin's Q or profitability; quite the opposite, the coefficients are (significantly) positive. The year-by-year cross-section regressions (not reported) suggest that these positive effects are increasing over time as the coefficients increase in value and significance. This increasing effect corroborates Claessens (1997) who finds that, while voucher prices in the Czech and Slovak Republics were relatively lower when a bank-sponsored fund had a relatively large equity stake, this effect was not found for the later secondary market prices in the Czech Republic.

To further test the importance of general monitoring benefits versus conflicts of interest costs, we also ran regressions where included a dummy when any ownership stake was more than 20% (ratios between 15% and 30% led to similar results) as all types of blockholders can presumably monitor firms (not reported). This general blockholder dummy is highly correlated with the Herfindahl index-but not with the main-bank ownership dummy-and is in general not significant in either the valuation or profitability regression. Including it
.

In Nigeria, schooling attendance does not necessarily translate into increased learning, and educational indicators for the north substantially lag behind the national average. According to the Reading and Access Research Activity report (2019), in northern Nigeria, less than 3 percent of second grade pupils in government primary schools could read a text in Hausa with 80 percent comprehension or greater (Kano: 2% girls and 3% boys; Jigawa: 0% girls and 3%). One factor that may contribute to lower school enrollment and learning outcomes in the north is the inter-generational persistence of low rates of educational attainment. Overall, in the North West of the country, only 29% of 15-49 year-old women and 59% of men are literate (NPC and ICF 2019). A number of analyses show that parental educational attainment is a strong determinant of educational outcomes among 5
). Stochastic job matching means that changes in labor taxes, subsidized health or prices may shift the relationship between vacancies and unemployment, and that the effect of a change in the relevant policy parameter on _u_ via job offers is mitigated, since there are additional effects that offset this demand-side effect.

> 50This is more or less consistent with the empirical fact that the formal sector is skilled labor intensive while the informal sector is unskilled labor intensive in Colombia: average years of schooling for a FS worker is 12.14 , while for an IS worker it is 9.12 years (Source: Author’s calculations based on ECH, second quarter of 2003).

21
Table 6: Simulation Results Using SRHS Approach and World Bank Measure of GW Volume

||GW<br>Depth|Extraction<br>Recharge<br>Ratio|Aquifer<br>Productivity|Grids<br>Satisfying<br>Constraints|Grids with<br>Production|Median<br>Gains in<br>Production|Mean<br>Gains in<br>Production|
|---|---|---|---|---|---|---|---|
|Crop|Constraint|Constraint|Constraint|(%)|Gains (%)|(%)|(%)|
|(1)|(2)|(3)|(4)|(5)|(6)|(7)|(8)|
|Barley<br>|7_._00<br>|0_._70<br>|0_._05|5_._47<br>|4_._68<br>|33_._28|65_._23|
|Barley|7_._00|0_._70||5_._47|4_._68|33_._28|65_._23|
|Barley|7_._00||0_._05|5_._48|4_._67|33_._28|65_._23|
|Barley||0_._70|0_._05|20_._98|4_._33|41_._85|68_._83|
|Barley|7_._00|||5_._48|4_._67|33_._28|65_._23|
|Barley||0_._70||20_._98|4_._33|41_._87|68_._89|
|Barley|||0_._05|24_._91|3_._64|41_._85|68_._83|
|Barley||||24_._91
||institutional investors||region|
|---|---|---|---|
|Comoros 1/||34.9|2011|
|Swaziland|Commercial banks|30.4|2011|
|Gabon 1/||22.1|2011|

1/These countries had no recent domestic issuance when DeMPA was conducted. Source: DeMPA reports, WDI, IMF staff reports and staff calculation based on ECCU statistics.

**_Instrument_** : Although the preference may be for a wide array of instruments, it is better to maintain a degree of simplicity and standardization. For example issuing zero coupon bills at shorter maturities and bonds carrying semiannual coupons for longer maturities, makes it easier to lay the foundation of a yield curve and attract retail investors. Among the small states in the sample group the vast majority of instruments used were Treasury bills, with maturity ranging from one month to one year. For example, of the 223 securities issued via the Regional Government Security Market (RGSM) of the ECCU since its establishment in 2002 up to February 2011, 189, or 85 percent of total issuance, were Treasury bills with maturity of 91-, 180- or 365- days, Treasury bonds of 5-year, 7-year and 10-years have also been issued in the ECCU but in small states outside of those in the sample group<sup>27</sup> . The gross value of Treasury bills amounted to EC$ 3,388 million, and Treasury bonds EC$1,222 million. In 2012, 42 auctions had taken place up to end-October and 9 were scheduled for the rest of the year. Out of these 51 issues, 44 (86 percent) are Treasury bills, and 2 (4 percent) 4-year Treasury notes and 5 (10 percent) Treasury bonds. In some countries **,** such as Guyana and Samoa, longer term securities were issued in the past but the operation was discontinued due to
<mark>WPS3573</mark>

# **The Effects of Migration on Child Health in Mexico**<sup>#</sup>

## **Nicole Hildebrandt and David J. McKenzie**<sup>*****</sup>

_Department of Economics, Stanford University_

### **Abstract**

This paper investigates the impact of international migration on child health outcomes in rural Mexico using a nationally representative demographic survey. Historic migration networks are employed as instruments for current household migration to the United States in order to correct for the possible endogeneity of migrant status. Children in migrant households are found to have lower rates of infant mortality and higher birthweights. We study the channels through which migration may affect health outcomes and find evidence that migration raises health knowledge in addition to the direct effect on wealth. However we also find that preventative health care, such as breastfeeding and vaccinations, is less likely for children in migrant households. These results provide a broader and more nuanced view of the health consequences of migration than is offered by the existing literature.

_Keywords:_ migration; child health; infant mortality; health knowledge _JEL codes:_ O15, I12, F22

### World Bank Policy Research Working Paper 3573, April 2005

_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._

> # Thanks to Gerardo Esquivel, Ernesto Schargrodsky, Miguel Urquiola, and participants at the Economia meeting in
Multivariate regression results with country fixed effects reported in Table 2, columns 1-2, for the sample of developing countries confirm these findings.<sup>5</sup> They show that unbanked adults in these countries are significantly more likely to belong to typically underserved groups, such as women, poor adults, less educated adults, and young adults.<sup>6</sup> They also show that women with less formal education are significantly more likely to be unbanked.

> 5 The regression results remain robust when using logit instead of ordinary least squares. Furthermore, the regressions in Table 2 exclude China due to missing data on employment status, but the results are robust if we exclude employment status as a determinant of being unbanked.

> 6 This regression is consistent with an analysis of 2011 Global Findex data in Allen, et al., 2016.

13
.82)|(13.16)|
|Political stability *|-0.367***|1.42***|-0.117***|
|fuel exporters<br>dummy|(-7.98)|(4.59)|(-6.48)|
|Time trend|0.289***|0.0189|0.0334*|
|(=0 in 2000)|(6.04)|(0.82)|(1.65)|
|n|1,286|1,232|1,128|
|R-squared|0.305|0.098|0.121|
|RMSE|7.59|3.87|3.02|

_Note:_ Figures in parentheses are robust t-statistics. *, **, ***: significant at 10, 5, and 1 percent respectively. Annual data from 1996–2013 for low- and middle-income countries. RMSE = root mean square error, or sample standard deviation.

16
the phrasing of both proxies, clearly differentiating planted area losses from productivity reductions

- Providing (visual) aid in handling percentages more accurately and consistently

- Directly asking for losses by merging both proxies into a single question eliciting the loss benchmarked against what farmers believe could have been their attainable harvest

<u>Question 2: How do farmer reports compare to crop losses based on expert assessments and can we establish an objective, reliable benchmark (‘gold standard’) for crop losses?</u> Eliciting losses directly from farmers may be unbureaucratic and easily scalable, however, the previous analysis has indicated that it comes with a number of potential drawbacks. In order to better assess the accuracy of farmers’ self-reports, there is a need to understand the way in which farmers form their estimates and compare them to a credible benchmark or ‘gold standard’. For example, methodological research comparing self-reports to an objective measure uncovered systematic measurement error in farmers’ reports of plot size and harvest quantity (Carletto, Savastano and Zezza, 2013; Carletto, Gourlay and Winters, 2015; Gourlay, Kilic and Lobell, 2019). Using data from the Uganda MAPS experiment, we can compare farmers’ loss reports to 19
likely other, unobserved factors inducing this rural-urban wage differential, in which case estimation of the labor market distortion via subtraction of known factors is biased in the direction of overstating the _hukou_ -related distortion. Therefore, it is useful to also estimate the direct impact of household registration status on the observed wage difference among households. Shi (2002) takes this approach to the problem, using the same CHNS data set. He finds that only 28% of the ruralurban wage difference can be explained directly via the coefficient on the _hukou_ registration variable. This is quite a bit less than the 48% left unexplained via the subtraction approach of Shi, Sicular and Zhao (2002).

> 5 See Hertel and Zhai (2004) for a detailed description of how this _ad valorem_ distortion is obtained.

6
*|-2.34***|0.44|
|50th Percentile|3.06***|-6.39***|-2.11***|0.49|
|75th Percentile|3.28***|-6.47***|-1.73***|0.58|
|90thpercentile|3.50***|-6.54*|-1.36***|0.67|
|||**2018-2019 Rec**|**ession**||
|Large City|-1.09|-40.19***|-5.27***|-4.58***|
|25th Percentile|-3.19***|-38.46***|-4.45***|-3.85***|
|50th Percentile|-4.85***|-37.11***|-3.81***|-3.29***|
|75th Percentile|-7.61***|-34.84***|-2.74***|-3.24***|
|90thpercentile|-10.38***|-32.59***|-1.67*|-1.39*|

Notes: F-stat significance based on robust standard errors (clustered by province) in parenthesis *** p<0.01, ** p<0.05, * p<0.1. Coefficients estimated combining major city (which corresponds to the main effect) and distance parameters (for each sector and time period separately) estimated in Table 3a. All regressions use data on all 81 provinces and employ province fixed effects.

Distance to major city is computed as
a new category that has not been emphasized in the literature, but recent papers find it important for explaining firm performance across the world (Clarke, Li and Xu 2017). It incorporates whether or not a firm is located in a large city, the extent to which a firm is surrounded by “capable firms”, measured as the share of firms whose number of employees exceeds 50 (capacity agglomeration), and whether the firm competes with firms in the informal sector (informal competition).

When looking at air pollution, we focus on measures of particulate matter. Even though many pollutants contribute to contaminate the air, particulate matter is the one that affects human health the most. In particular, small particles, those with a diameter of 2.5 microns or less, are the most dangerous because they can travel in the blood stream and sit in the lungs, producing long lasting health consequences.<sup>7</sup> We use remote sensing data (van Donkelaar, 2016) and assign pollution measures to each particular firm.

Finally, in order to measure firm performance, we use the same two variables as Reyes et al. (2017): employment growth and labor productivity growth. Employment growth corresponds to the one-year employment change, and labor productivity is measured as sales over the number of permanent employees.

Our findings can be summarized in two main points. Frist, among the business environment variables, capacity agglomeration is the only variable that shows a different effect for African firms. Capacity agglomeration (the share of firms with at least 50 employees) has a stronger positive effect in this region, increasing labor productivity growth. Second, concentration levels of PM 2.5 also have a distinct effect for African firms. The relationship between pollution and firm performance goes through three stages: negative, positive, and negative again (cubic relationship between PM 2.5 and labor productivity growth). Although, as expected, we find a range of pollution levels where the correlation with productivity is
countries. In the Philippines, the legislators appear to file an inordinate number of bills despite the historically low enactment rates. Based on interviews of some legislators, it is evident that a primary reason why they file bills despite the near-zero probability of having them enacted into laws is political posturing before their constituents. Some legislators prepare “accomplishment reports” which, among other items, list all the bills they have sponsored. Voters have few reasons why they should care about most of these bills because even though most bills filed, especially in the Lower House, address local matters, few of them touch constituents’ lives directly. Following the long-established tradition of clientelism, it is faster for voters to approach local politicians for specific help when they are in need than waiting for some national legislation to be enacted and begin to have policy effects on their daily lives. Once filed, the bills require aggressive lobbying efforts by the sponsoring legislators to move up the deliberation processes of each chamber. Certain officers of both chambers, such as the chairman of the relevant legislative committee and the Speaker of the House/the President of the Senate yield considerable powers over the fate of individual bills. Individual legislators will have to exert significant personal efforts to follow up with these officers and others if they truly seek to have their bills passed into legislation, a high transaction cost as well as use of political capital vis-à-vis fellow legislators, which no one can absorb very frequently, especially given limited pressure from their constituents makes such efforts less electorally worthwhile.

Not only are Filipino legislators relatively poor at having their bills passed, those bills they file appear to be extensions of local constituency work rather than attempts to craft national policies. The data in Table 8 show that, except for the 12<sup>th</sup> Congress, far more local application bills (i.e., those intended to address matters specific to certain localities without nationwide implications) were filed and hence approved in absolute terms, indicating the legislators’ tendency to use national
their land but econometric analysis is needed to confirm this and explore sources that could underlie such differences.

# **3. Conceptual framework and empirical strategy**

Use of partner data allows us to take a three-pronged approach to assess productivity implications of land rental, each with different samples. To assess existence and magnitude of Marshallian inefficiency, we compare productivity on owner-cum-tenants‟ owned and sharecropped plots. If such inefficiency were outweighed by differences in farming ability, rental transactions could still contribute to higher levels of productive efficiency. The tenant and landlord sample is thus used to compare productivity on owneroperated plots by tenants and their landlords to estimate differences in ability differences or equivalently the maximum potential productivity gain from land rental. Comparing productivity between landlords‟ owned and cultivated and leased out plots provides an estimate of the actual productivity impact of land rental, i.e., the extent to which potential productivity gains are realized in practice.

> 12 In line with what emerged at the household level, comparing plots in our two samples (table 3 for the entire sample and appendix table 2 for plots with matching partner information), points towards very few significant differences, suggesting that the latter are representative of the overall population.

6
program. These estimates are therefore conservative if the impacts observed are positive; they are therefore a lower bound of the effect of the program among those who attended training sessions and participated in program activities. Thus, if the program increased employability and achieved other desired outcomes, the effect would be larger among those who actually participated in the program than among those reported in this paper.

# a. Attrition

At endline, Statistics Sierra Leone was able to track 2,782 of the 3,319 individuals surveyed at baseline, putting the overall survey attrition rate at 16 percent (Appendix C).<sup>12</sup> Over 80 percent of individuals were successfully interviewed at both baseline and endline. To check for bias resulting from attrition, Appendix C presents t‐tests of differences in means between individuals who left the sample (attritors) and individuals who stayed (nonattritors). Most of the differences between attritors and nonattritors arise from variables with zero or a low number of observations among attritors or nonattritors and thus constitute a small share of the sample.

> 11 Conditional regressions do not control for outcomes at baseline for two main reasons: (a) the loss in sample size beyond the loss from conditioning based on employment or on engagement in a household enterprise, particularly because of a labor market weakened by Ebola, and (b) key measurement changes to the endline survey after the first national labor force survey was conducted in 2014. Regressions using consumption and business practices as outcome variables do not control for outcomes at baseline because the relevant data were not collected at baseline.

12 McKenzie and Woodruff (2014) examine survey attrition rates in studies on business training. They find a range of between 5.3 percent and 28.0 percent; the rate in about half the studies is higher than the rate in this evaluation.

10
share of intermediate goods that the country of "origin" exports to the country of "destination". The variable _share_ 1 accounts for a country’s importance in Global Value Chains as an exporter. The second variable, denoted _share_ 2, is the share of intermediate inputs that the country of "origin" is importing from other countries that are part of the same regional trade agreement. The variable _share_ 2 accounts for the importance of the regional component of GVC to the imports of a given country.

As we will discuss in the next section on our empirical approach, trade policy is endogenous. Countries that are natural trade partners may be more inclined to sign a trade agreement (Krugman (1991)). Figure 3 provides empirical support to this hypothesis by showing that on average, upon signing an agreement, a country-pair that just signed an agreement trades roughly twice as much as a country-pair where only one country only joined the trade agreement. More precisely: for each country and agreement, we normalized to 100 the trade flows between two countries signing a trade agreement, on the year the agreement is put into force. We can then compare this number (for the same year) to the trade flows between a member country to a non-member country. On average across all countries and trade agreements, we find that trade with non members is only 55.94% of trade between members, on the first year of the agreement.<sup>5</sup>

# **3 Regional trade agreements and trade flows**

Difference-in-differences is the natural identification strategy for a panel setting in which a policy affects groups. Our identification of the effects of trade agreements comes from comparing trade flows, for the relevant country-pairs, before and after a trade agreement comes into effect, for the 227 trade agreements that were signed between 1958 and 2015. Importantly, our specification controls for country-pair and country-time fixed effects.<sup>6</sup> The country pair fixed effects not only accounts for standard