rafmacalaba/data-use-mentions-extended huggingface dataset:
56% increase). Although the point estimates are positive, we do not observe statistically significant impacts on the engagement with the child’s teacher in columns (3) and (4). We also explored whether parents in the treatment group and other household members were more likely to be part of the school committee. Here, column (5) shows a positive but statistically insignificant impact.

Third, DICIPE causes a small reduction in the labor supply of parents in a context with almost universal labor market participation. For example, 98.6% of mothers in control communities work and that fraction is only reduced by 1.3 percentage points for mothers of children in treated areas. While most in the literature show that eligible papers preschool or childcare programs can increase the labor market participation of (mostly female) caregivers (Berlinski and Galiani, 2007; Berlinski et al., 2011; Halim et al., 2022; Hojman and Boo, 2022; Donald and Vaillant, 2023; Halim et al., 2023; Mata, 2024),<sup>16</sup> these results on the reduction in the household labor supply of mothers are consistent with those of Krafft and Lassassi (2023), who find that pre-primary education may have decreased women’s employment.<sup>17</sup> Taken we together, find evidence that DICIPE increases parental time investments in children through stimulation, home play, and engagement with school principals and induces reductions in the likelihood of working.

Our qualitative analysis from the caregivers survey hints at the possibility that two mechanisms in treated communities are that potential why parental practices improved the program induced parents to be significantly involved in the preschool activities and that parents perceive positive changes in their children’s skills that may facilitate parentchild quality engagements. Despite the low compliance with the parenting education activities (instead of monthly sessions, they were held every three months), the families

> 16In a recent evidence review (Halim et al., 2023),
erent kinds of data. In the context of intergenerational educational mobility, there are two issues relevant here. First, whether data on educational attainment refer to years of schooling or education categories (primary, secondary etc.). The DHS data we use have information on years of schooling for both the parents (father) and children. Second, in many household surveys used for intergenerational mobility analysis in developing countries, data on parental

> 27We take the information from the household roster which is the same in all DHS surveys.

15
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# **_Legal and regulatory environment_**

The literature generally finds laws, regulations, and policies relating to FDI (e.g., foreign ownership restrictions, investment approval mechanisms, regulations governing operations) to be crucial for attracting new investment and retaining existing investors. Part of North’s (1990) conceptualization of institutions as “rules of the game”, the legal and regulatory environment for FDI shapes investment performance in host countries. Once investments are made, FDI is partially ‘sunk’, rendering it particularly sensitive to regulatory uncertainty (Saggi, 2002). In addition to uncertainty, a suboptimal business environment increases transaction costs, effectively constituting a tax on business activity (Buchanan, Le, & Rishi 2012).

A sizable body of research suggests that improvements in the quality of a country’s legal and regulatory environment are associated with higher FDI inflows. Mistura and Roulet (2019) find that legal restrictions on FDI decrease FDI inflows to both developed and developing countries. The quality of institutions governing the business environment—measured in terms of bureaucratic efficiency, corruption levels, and property rights protections—also has a statistically significant effect on FDI (Ali, Fiess, & MacDonald, 2010; Bénassy-Quéré, Coupet & Mayer, 2007; Bevan, Estrin & Meyer, 2004; Egger & Winner, 2005; Fung et al. 2005; Globerman & Shapiro 2002; Kinda 2010; Richards & Nwankwo, 2005; Staats and Biglaiser, 2012). Evidence from surveys of investors and foreign businesses reinforces empirical evidence that a supportive business climate is among the top priorities for foreign investors (A. T. Kearney 2019; Asiedu, 2006, Campos, Lien, & Pradhan, 1999; Gastanaga, Nugent & Pashamova, 1998; Kusek and Silva 2018; Smarzynska 1999; Wei 2000).

# **_Political risk and investor protection_**

Foreign businesses in host countries are exposed to the risk of disruption by political and government actions. Such political risks emanate from host country governments’ failure to
number of Syrians in Turkey were also not available until starting in 2012. Overall, in 2013, Syrians were still very concentrated in only a few regions. Out of 26 regions, Syrians comprised more than 1 percent of the population in only 7 regions. Estimations cannot be conducted at the household-level data since the survey-to-survey imputation methods used to compute poverty rates yield only group level estimates of poverty rates, not household level poverty rates.

The ideal methodology would be to measure the causal effects of the influx (shock) of Syrians under temporary protection as a proportion of the population onto the poverty rates of the host community. However, there are some concerns regarding endogeneity. The foreign-born in Turkey have freedom of movement and it is very likely that households prefer to settle in locations that are more welcoming or offer better economic opportunities. Regional differences in social and economic conditions can influence their decisions to locate. Del Carpio and Wagner (2015) discuss these concerns and propose an instrumental variable approach. Two different, but complementary IVs are proposed: distance and time from Syrian regions to Turkish regions. In this paper, regional aggregation and time dimension of the data limits the data to only 52 data points. There are not enough rank conditions and IV is not feasible.

14
report to have arrived in the U.S. within one year (and hence are unlikely to have already returned home), this share stands at 52.9 pecent, and it is relatively stable over the years since migration (58.3 percent after nine years or more).<sup>21</sup> Figure 4 then examines how sensitive our Figure 2 results on the likelihood of a change in marital status after migration are to accounting for return migration. It displays both the probabilities of changes conditional on staying in the U.S., and our lower bounds on the unconditional changes, assuming no change in marital status after return migration. For migrant men who were unmarried before migration, the probability to get married nine

> 20Due to sampling noise, we obtain a slightly negative rate of return migration for some years. When we examine immigrants from all origin countries, we obtain an overall rate of return migration of 23 percent nine years after migration, consistent with previous studies’ estimates (OECD, 2008; Borjas and Bratsberg, 1996).

> 21These figures are obtained using the 2017-2021 ACS data (as in Table 1). Using the 2008-2021 ACS data and focusing on the 2007-2012 cohort, we obtain a share of unmarried migrants of 57.8 percent for migrants arrived one year ago or less and of 60.6 percent for migrants arrived since nine years.

21
Terrain roughness|2.87|2.56|3.01|2.03|4.44|3.11|1.45|1.16|
|Average 12-month total|1375.9|428.8|929.4|336.5|1246.4|154.5|1770.4|261.7|
|rainfall (mm) for Jan.–Dec.|||||||||
|Observations|2125||516||825||784||

_Note:_ Description of the variables is given in table A.2. sd = standard deviation.

iii
|**Dietary intake**<br>**variables**|**Indicator definition**|**Data source**|**Year**|**Data**<br>**availability**<sup>**1**</sup>|**Notes**|
|---|---|---|---|---|---|
||sugar, salt, total and saturated fat, and red<br>and processed meat.||||The score ranges from zero to<br>nine expressed as an average<br>score.|
|**All-5**|% of adults ≥ 15 years who consumed all<br>five food groups typically recommended<br>for daily consumption in food-based<br>dietary guidelines around the world|World Gallup Poll<br>(Global Diet Quality<br>Project)|2021-2022|N=55<br>countries|Proportion of the population<br>who consumed all five food<br>groups [_as well as each one_<br>_individually_] at least one<br>**vegetable**, at least one**fruit**,<br>at least one**pulse, nut or**<br>**seed**, at least one**animal-**<br>**source food**, and at least one<br>**starchy staple**in the previous<br>day or night.|
|**Zero vegetable or fruit**<br>**consumption**|Proportion of the population who<br>consumed no vegetables or fruits during<br>the previous day or night.|World Gallup Poll<br>(Global Diet Quality<br>Project)|2021-2022|N=55<br>
Review_ 104(1): 183-223 Kadapakkam, Palani-Rajan, P. C. Kumar, P. C., and Leigh A Riddick (2998) “The Impact of Cash Flows and Firm Size on Investment: The International Evidence.” _Journal Banking and Finance_ 22(3): 293–320.

Liu, Qing, and Yi Li (2015) “Firm investment and exporting: Evidence from China's value-added tax reform” _Journal of International Economics_ 97(2): 392–403 Levine, Ross, Normal Loayza, and Thorsten Beck (2000) "Financial intermediation and growth: causality and causes" _Journal of Monetary Economic_ 46 (2000): 31-77 Modigliani F. and Miller, Merton H.(1958) "The cost of capital, corporation finance and the theory of investment." _The American Economic Review_ 48(3): 261-297 Morawczynski, Olga, and Mark Pickens (2009) “Poor people using mobile financial services: Observations on customer usage and impact from M-PESA.” World Bank, Washington, DC.

Munyegera, G.K and Tomoya Matsumoto (2016). “Mobile Money, Remittances, and Household Welfare: Panel Evidence from Rural Uganda”. _World Development_ Vol. 79, pp. 127–137, 2016 17
/sup>|0.54|0.59|-0.05<sup>***</sup>|
|Early marriage|0.13|0.59|-0.46<sup>***</sup>|0.10|0.53|-0.43<sup>***</sup>|
|_MPI poor households_|||||||
|Years of schooling|0.81|0.86|-0.05|0.85|0.88|-0.03|
|School attendance|0.64|0.71|-0.06<sup>*</sup>|0.68|0.62|0.06|
|Unemployment|0.10|0.21|-0.11<sup>***</sup>|0.14|0.16|-0.02|
|Legal identification|0.87|0.89|-0.01|0.83|0.86|-0.03|
|Early marriage|0.21|0.67|-0.46<sup>***</sup>|0.22|0.64|-0.42<sup>***</sup>|

Source: Authors’ calculations using the Nigeria IDP Survey (2018). Significance at 1% ***, 5% **, and 10% * levels.

Among the wider population, women are more likely to be deprived in employment regardless of their displacement status, but among the poor, this gender gap only holds for displaced women. Women are more deprived in legal identification only among the wider population, although it is a serious issue among the poor, too, with eight in ten individuals lacking identification across the board. Furthermore, women report being married
# **4. Discussion**

The empirical results found in the previous section merit some further discussion. As a general observation and as visible in Figure 3, a large part of total trade costs in services appears to be driven by the non-discriminatory aspect of trade policy which form part of the TFiS agenda. True, even though the categories of Regulatory transparency and Barriers of competition as part of the OECD STRI cannot be distinguished from discriminatory Market Access measures, the fact that two additional TFiS measures provide clear significance in the empirical estimations points out that many so-called non-discriminatory behind-the-border measures determine trade costs in services and therefore facilitate trade in services. This result confirms empirical findings in previous works that also assess trade cost policies in relation to services trade (e.g. Miroudot and Shepherd, 2014; Nordås and Rouzet, 2015).

However, our findings suggest not only that behind-the-border measures are important, but that the bulk of that these non-discriminatory trade costs factors must be found in the governance structure of a country. Our results show that the strongest cost variable explaining services trade is captured by the two World Bank governance indicators, and not so much behind-the-border measures covered by the World Bank’s Doing Business and Regulatory Governance indicators. The two governance indicators typically measure a country’s institutional capacity regarding policy frameworks and as such, when viewed from the perspective of services, are in our view more related to the regulatory institutional capacity of a country. Hence, to the extent that key words such as effective and meaningful market access, transparency and regulatory certainty matter for TFiS, our results show that they mainly appear to matter with respect to the institutional strength of governments and regulators dealing with behindthe-border policies in services.

Moreover, the institutional regulatory governance in services matters comparatively more for countries with lower levels of development when put in comparison with their market access policies. In other words, at any given the level of market access restrictions in services, the institutional component of the regulatory framework in which governments and regulators operate
.5). Data source: household survey. Dependent variables come from credit bureau data.

treatment arm (see Online Appendix E). Having established that there was no switching away from MFI borrowing, we can further check whether households might have switched between loans offered by our implementing partner. If this was going on, we would expect a significant increase in sanitation loan amounts borrowed accompanied by a decrease in borrowing of other loan products. Results are presented in Table 12. We first confirm with administrative data from our implementing partner that amounts borrowed for sanitation increased significantly, in line with the impact on loan uptake. This is shown in column (1) of Table 12. Impact estimates on loan amounts taken for other loan products (columns (2) to (5)) are considerably smaller, insignificant, and - except for education loans - positive. The finding is robust to multiple hypothesis testing as indicated by the Romano-Wolf p-values.

These results confirm that the average client did not shift away from other loan products offered by our implementing partner, at least on average, following the introduction of sanitation loans.<sup>50</sup> This evidence is also in line with that presented in Section 6.1 which indicated that most households did not substitute away from the more expensive business loan to the cheaper sanitation loan, which would have been the case if the interest rate, but not the loan label, was the main driver of the observed intervention impacts.

> 50 Though we do not observe any impacts of the intervention on overall borrowing or borrowing composition, at least on average, this does not mean that overall borrowing could not have increased, and/or borrowing composition changed for some sub-groups. Indeed, the model indicates different effects for households by whether or not they are credit constrained and/or sensitive to loan labels. In line with this, Augsburg et al. [2019] find evidence of heterogeneous impacts on overall borrowing and borrowing composition by households’ eligibility for the SBM
NIGER’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE Banerjee, Sudeshna, Heather Skilling, Vivien Foster, Cecilia Briceño-Garmendia, Elvira Morella, and Tarik Chfadi. 2008b. ―Ebbing Water, Surging Deficits: Urban Water Supply in Sub-Saharan Africa.‖ AICD Background Paper 12, Africa Region, World Bank, Washington, DC.

- Fall, Matar, Philipped Marin, Alain Locussol, and Richard Verspyck. 2009. ―Reforming Urban Water Utilities in Western and Central Africa: Experiences with Public-Private Partnerships.‖ Volume 2: Case Studies, Water Sector Board Discussion Paper Series, Paper 13, Africa Region, World Bank, Washington, DC. June.

- Gulyani, Sumila, Debabrata Talukdar, and Darby Jack. 2009. ―Poverty, Living Conditions, and Infrastructure Access: A Comparison of Slums in Dakar, Johannesburg, and Nairobi.‖ AICD Working Paper 10, Africa Region, World Bank, Washington, DC.

- IBNET (The International Benchmarking Network for Water and Sanitation Utilities). 2009. http://www.ib-net.org/.

- WHO (World Health Organization), Joint Monitoring Program (JMP). 2010a. ―Niger Estimates for the use of Improved Drinking-Water Sources.‖ Updated March 2010. http://www.wssinfo.org/resources/documents.html.

- ———. 2010b. ―Niger Estimates for the useof Improved Sanitation Facilities.‖ Updated March 2010. http://www.wssinfo.org/resources/documents.html.

- Keener, Sarah, Manuel Luengo, and Sudeshna Banerjee. 2009. ―Provision of Water to the Poor in Africa: Experience with Water Standposts and the Informal Water Sector.‖ AICD Working Paper 13, Africa Region, World Bank, Washington, DC.

- Morella, Elvira, Vivien Foster, and Sudeshna Ghosh Banerjee. 2008. ―Climbing the Ladder: The State of Sanitation in Sub-Saharan Africa.‖ AICD Background Paper 13, Africa Region, World Bank, Washington, DC.

- World
3 outlines our empirical strategy and Section 4 discusses the results. Robustness checks are provided in Section 5. Section 6 investigates the external validity of the results reported for India in other geographic settings such as Vietnam and Africa. Section 7 discusses the plausible mechanisms linking nitrogen pollution to height impacts, and Section 8 concludes.

# 2. Data

In this section, we describe the data sources that were used in the empirical analysis, and the construction of the main variables in the analysis.

# 2.1 Health Data

The data on our outcomes of interest come from the fourth round of the National Family and Health Surveys (NFHS) conducted in India. The NFHS is the Demographic and Health Survey (DHS) equivalent in India. The survey was conducted between January 2015 – December 2016 and covered all areas of the country. In a departure from the previous DHS surveys, the sample for this survey was designed to be representative at the district level. Close to 600,000 households were interviewed which included 0.7 million eligible women in the age group 15‐49.

4
very large and the estimated coefficients would otherwise not be very precise. As mentioned above, we use the first year a country introduced any of these reforms to create the ������ variable in our preferred specification.

As is the case with Rajan and Zingales’s (1998) measure of financial dependence, the measure of the sector’s ICT intensity should not be driven by the local demand and supply of Internet in the economy. Otherwise, this variable would be endogenous to the introduction of telecommunications reforms. Instead, the measure of ICT intensity should be independent of each country’s conditions. We assume that there is a technological reason to explain why some industries are more likely to adopt the Internet than others. For instance, the type of work carried out in certain industries may be more suitable to benefit from the use of the Internet at work. We measure the ICT intensity of a sector using data from a relatively frictionless environment. We argue that ICT use by firms in the United States is a relatively pure measure of their demand for this technology, because it is one of the first countries to have implemented telecommunications reforms to improve access and because its friendlier businesses environment may create more competitive pressures for firms to innovate and adopt new technologies.<sup>2</sup> As the measure of ICT intensity, therefore, we use data on ICT capital services per hour worked from EUKLEMS for the United States in the year 2007 (see **Table 2** ).<sup>3</sup> We estimate the dependent variables related to the labor market using the EU Labour Force Survey (EU‐ LFS) for the reference years 1995–2013. The EU‐LFS is the largest European household survey, with 1.8 million interviews conducted each quarter throughout the participating countries. The survey collects labor and demographic information for residents living in private households in the 28 member states of

> 2 There is a large literature on the effects of competition on
is et at the greater of $50 per capita or $150 million). Tax exemption is automatically granted to private activity bonds within that limit. However, exempt facility bonds are excluded from the volume limit and can be issued in tax exempt form in any amount. These exempt facility bonds include airports, docks and wharves, solid waste facility, etc, as well as qualified mortgage bonds, qualified small-issue industrial mortgage bonds, qualified student loan bonds, qualified redevelopment bonds, and qualified non-profit organization bonds (see Fortune 1992, op. cit.).

120. Tax exemption for municipal bonds is subject to three main criticisms. The first criticism is that tax exemption induces unnecessary volatility into municipal bond yields: it narrows the market for municipal bonds and makes it more sensitive to change in the distribution of investable funds between individuals and financial institutions, and to other factors affecting financial markets. Also, tax exemption introduces variability in the value of the capital-cost subsidy enjoyed by municipalities. Empirical evidence of the interest rate ratio for municipal bonds of various maturities in the US shows that municipal bond yields are more volatile than yields on US Treasury bonds (see Fortune, op. cit.). The second criticism is that tax exemption is economically inefficient, in that it encourages overproduction of public services and overuse of capital by the public sector. Estimates of the social cost of tax exemption based on 1980-85 US data shows t1he economic cost of tax exemption in terms of output foregone to be mild. The third criticism is that tax exemption is inequitable, because it erodes the vertical equity in t]he tax system by allowing the wealthy to avoid taxation in ways that are not available to the 32