rafmacalaba/datause-encoder-data huggingface dataset:
Intelligence Scale for Children (WISC), Calderon et al. demonstrate impairments in long-term memory and linguistic abstraction in Mexican children aged six to nine years old. Wasserman et al. (2004) and (2007) show similar neurologic consequences in Bangladeshi children. In a cross-sectional study of 10-year old children in Arhaizar, Bangladesh, it was found that those children exposed to arsenic levels greater than 50 ppb in drinking water tested worse on the WISC in Performance raw scores compared to those children exposed to less than 5.5 ppb arsenic in drinking water. Children in the highest quartile of arsenic exposure scored on average 10 points lower in Performance raw scores compared to the lowest quartile. The Performance score measured accuracy in picture completing, coding, block design, and maze tests, while arsenic exposure was measured by testing household water sources (Wasserman, et al., 2004). Later in 2007, a second study by Wasserman et al. implemented comparable intellectual functioning tests to a younger subset of children at age six. Although not as strong of an association as seen among 10-year old children, the authors saw a significant decline in raw scores dependent on a child’s exposure to arsenic in well water (Wasserman, et al., 2007). These results complement an earlier study in Taiwan, China, which found strong negative correlations between wellwater arsenic and similar Performance-type tests for older children (Tsai et al, 2003).

Additionally, Rosado et al. (2007) found a negative impact on memory and the ability to focus and solve problems among children aged 6-8, while Asadullah and Chaudhury (2008) showed that adolescent male Bangladeshi children who were exposed to arsenic at home had lower mathematics scores in school compared to those who had no contact with arsenic (Asadullah & Chaudhury, 2008). Most studies observing links between arsenic and cognitive function in children only examine children’s current exposure status to arsenic. However, von Ehrenstein et al. consider in-utero arsenic exposure as well as present arsenic concentration exposure in children aged 5-15 years old in West Bengal. Again, using the WISC, the authors found a negative correlation between raw scores and current arsenic exposure status; however, they did not find a significant association between raw scores and arsenic exposure during pregnancy as hypothesized (von Ehrenstein et al., 2007).

Aside from intellectual functioning, there is strong evidence asserting other arsenic-related neurological impairments including motor disabilities. In a cross-sectional study of children aged 8-11 years old in rural Bangladesh, Parvez et al. observed impairments particularly in fine manual control and body coordination skills (Parvez et al., 2011), while Tseng et al. (2006) found impairments in motor and sensory nerve peripheral conduction. However, unlike this paper, these studies do not examine young children to observe effects in early childhood development.

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disaggregating the nonpoor group into two groups: the vulnerable (those that are nonpoor but still face a significant risk of falling into poverty) and the secure (or “middle class”). A common, but rather ad-hoc, approach is to arbitrarily scale up the poverty line by a certain factor to obtain the vulnerability line. In India, vulnerability has in the past been proposed to occur within a fixed income range between 1.25 times and twice the national poverty line in India (NCEUS 2007). Other countries similarly define the vulnerability line as twice (Pakistan; Lopex-Calix et al, 2014) or 30% above (Vietnam; World Bank, 2012) the national poverty line. This approach has the advantage of being simple and easy to understand, but it appears to be based on no underlying welfare theoretical framework.

The recent approach proposed in Dang and Lanjouw (2017) instead derives the vulnerability line from a specified vulnerability index in the spirit of vulnerability to poverty. While sharing a similar conceptual approach and motivation with existing studies of vulnerability (e.g. Pritchett, Suryahadi, and Sumarto, 2000; Chaudhuri, 2003; Christiaensen and Subbarao, 2005), this approach differs from them in several important respects. First, it explicitly provides a framework to estimate a vulnerability line which is associated with a vulnerability index that can be derived in various ways, including budgetary planning, (ideal or desirable) social welfare objectives, or relative concepts of well-being. Second, unlike in Pritchett et al. (2000) and Chaudhuri (2003), the target population consists of the currently nonpoor households rather than all households. Finally, the Dang and Lanjouw (2017) approach employs simpler nonparametric estimation methods to estimate vulnerability as a function of consumption alone. It works with either actual panel data or synthetic panel data that can be constructed from cross-sections. We employ a vulnerability index of 20% and the associated vulnerability line for our welfare analysis in the next sections. The dividing line (vulnerability line), _j_ = 1 or 2, that separates these groups can be derived ii from the following equality vv 15
this was intended to avoid bias towards finding growth of impacts on household consumption per unit of transfer over time in the presence of inflation.

# **2.3 Descriptive statistics**

Descriptive statistics on the UCT and TUP interventions, and on the estimated impacts on consumption of these interventions, are reported in Table 1. As much of our analysis focuses on impacts of UCT, we begin our discussion of these interventions. The average transfers in these studies are quite large, representing 0.62 years of consumption on average, but there is meaningful variation in transfer size across interventions. Transfers last 8 months on average, so any increase in consumption during those 8 months caused by the UCT will not typically be accounted for in our results. The transfers in UCT are relatively low cost to deliver, with the average UCT in our sample reporting 18% overhead. The 14 interventions from 7 RCTs comprising our sample represents a large base of evidence compared to many other categories — of interventions in development economics Vivalt (2020) identifies more estimates only for micronutrient supplementation, conditional cash transfers, and deworming, while using less strict inclusion criteria.

The average estimated effect of UCT is 0.58 per unit of transfer, with a standard deviation of estimates across studies of 0.57. This variation could be explained either by variation in true effects of UCT across contexts or by sampling error. The average standard error of estimates is 0.28, heuristically suggesting sampling error is responsible for a large share of the variation in estimated effects. We revisit this formally and interpret these magnitudes in Section 3.

As an alternative approach to understand variation in our estimates, we plot point estimates and 95% confidence intervals for UCT and TUP interventions in Figure 1.<sup>7</sup> The UCT estimates appear tightly clustered, with confidence intervals for only 6 of the 18 UCT estimates excluding 0.4. This is despite the heterogeneity across interventions in size and

> 7Figure 1 also contains posterior mean estimates and credible intervals for these estimates, which we discuss in Section 3.2.

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cyclicality of the current account for the two subgroups and test whether they are significantly different.<sup>24</sup> Figures 2(a)-2(d) present the results of this robustness check for various subsamples of the data. In each figure, the bold (solid) line plots the cyclicality of the current account in debtor (creditor) countries for the corresponding level of adjusted debt at which the sample is divided in two, indicated on the x-axis. The dashed line reports the p-value for a test of the null hypothesis that the cyclicality of the current account is equal in the two groups. Figure 2(a) uses data for all countries over the entire period from 1971 to 1993, and reveals that current accounts are clearly procyclical in creditor countries and countercyclical in debtors. Moreover, for a wide range of values of the threshold, this difference is significant at the 5-10 percent level. Figures 2(b),(c) and (d) present the same information for three subsamples of the data. Figures 2(b) and 2(c) restrict the sample to the 1971-81 and 1982-93 subperiods respectively, and reveal that the difference in current account cyclicality is much more pronounced in the latter period. However, if we drop the two years following the 1973 and 1979 oil shocks from the 1971-82 subperiod, as is done in Figure 2(d), the pattern we emphasize re-emerges.

In the theory developed above, output shocks are saved in both debtor and creditor countries, while the differential current account behavior in the two sets of countries arises from the the differential investment response to output shocks. In debtor countries, a fraction greater than one of these savings is allocated to domestic capital, while in creditor countries a this fraction is smaller than one. The 24 We remove country means from all variables before computing the correlations. We test for equality of current account cyclicality in the two groups as follows: First, we regress the current account on per capita income growth in the two subsamples. Under the assumption that the two point estimators are independent and asymptotically normal, we can construct the usual Wald statistic for the null hypotheses that the slope coefficients are equal in the two subsamples. A rejection of this null hypothesis constitutes evidence that the cyclicality of the current account differs in the two groups of countries.

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Policy ReseaRch WoRking PaPeR 4835

# **Abstract**

The authors use a sample of 147 countries to investigate the link between democracy and reforms. Democracy may be conducive to reforms, because politicians have the incentive to embrace growth-enhancing reforms to win elections. By contrast, authoritarian regimes do not have to worry as much about public opinion and may undertake reforms that are painful in the short run but bring future prosperity. This paper tests these hypotheses, using data on micro-economic reforms from the World Bank’s Doing Business database. These data do not suffer the endogeneity issues associated with other datasets on changes in economic institutions. The results provide robust support for the claim that democracy is good for growth-enhancing reforms.

This paper—a product of the Enterprise Analysis Unit, Financial and Private Sector Vice Presidency—is part of a larger effort in the department to better understand the functioning of the private sector. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at mamin@worldbank.org.

_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 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._ Produced by the Research Support Team
of land for agriculture, oil mining and gas mining is simply set fixed for all periods equal to the base year value.

Tax rates are set equal to those for 2010 derived from the SAM. These are summarized in Table A4. For the government deficit,  _G_ , we set it at the base year 1.69% of GDP initially, declining steadily towards zero in the long run. These deficits are cumulated into the stocks of domestic and foreign debt, _Bt G_ * and<sup>_B_</sup> _t_ , assuming a constant division between domestic and foreign borrowing. Data for the stock of debt and interest paid on it comes from the China Statistical Yearbook (NBS 2012, Table 8-13), IMF’s _World Economic Outlook 2012_ online database and the 2010 Social Accounting Matrix. Government transfers, _G_ transfer_ , are set to rise in proportion with population and average wage. The nontax fees paid by enterprises are set to be a fixed share of GDP equal to the base year’s share (Table A4).

The current account balance was in a huge surplus in the mid-2000s but has since declined. There is no consensus about the future evolution of this variable, for simplicity, after setting it as a share of GDP at the observed sample period values, we set it to decline rapidly to zero. This _CAt_ deficit is also the assumed rate of borrowing from the world. Import prices, _PM_<sup>_i*_</sup> , are assumed fixed at the base year value for every period with one important exception. World oil price forecasts are taken from the U.S. Energy Information Administration and shown in Figure A7.<sup>24</sup> The model also requires projections of the export share; while this has been rising rapidly in the past, it fell with during the 2008 Global Financial Crisis and never recovered. Given the aim to rebalance the economy away from exports and investment towards consumption, we simply project a constant value for the share parameter.

The base year data for 2010 was constructed in 2013 since then, the macro variables for 2011-13 is now available; these include the GDP, investment and current account surplus. The current account surplus has fallen, and the unusually high share of investment in GDP has risen even more after 2010. We take these into account in setting the savings rate and current account balance as share of GDP for these years.

# _Parameters_

The rate of productivity growth is another factor that has a large effect on the base case growth rate of the economy but has little impact on the difference between cases. Total Factor Productivity growth at the industry level in the 1982-2000 period show a very wide range of performance as estimated by Cao et al. (2009), ranging from -10% to 5% per year. The Domar-weighted productivity growth for all industries was 2.7% for 1982-2000. To keep the base case as simple as possible we ignore this wide range of observed

> 24 The projections for crude oil prices are taken from the EIA’s _Annual Energy Outlook 2010_ , Table 12, which is available on their web page:  http://www.eia.gov/forecasts/aeo/.

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# **4.2 The Model under the Mean Dynamics Hypothesis**

It can be shown that the mean and mean performance hypotheses are algebraically similar in our framework, under certain conditions (Appendix A3.2). In addition, Goldin, Katz and Kuziemko (2006) argue that the relative increase in females’ scholastic performance in upper secondary school in the US was linked to a disproportionate increase in the returns to college education for women. This suggests that these two hypotheses are closely interlinked, and we therefore group them under the broader mean hypothesis in the context if this paper. In the remainder of the paper, we focus on the mean performance hypothesis as it is more straightforward to estimate empirically. The mean benefit hypothesis is however presented in more detail in Appendix A2.1.

A relative increase in females’ mean scholastic performance relative to males’ over time can generate a reversal in the gender gap in our framework. Such dynamics have been highlighted by Goldin, Katz and Kuziemko (2006), Cho (2007), Fortin, Oreopoulos and Phipps (2015) or Yamaguchi (2018) for the US, and suggested as a potential explanation for the reversal. Goldin, Katz and Kuziemko (2006) use samples of high school graduating seniors from three US longitudinal surveys in 1957, 1972, 1988, among which the last two are nationally representative. Looking at test scores, they find that girls reduced their disadvantage in math, and increased their advantage in reading between 1972 and 1992.

Using three nationally representative longitudinal datasets of high school students, Cho (2007) also looks at the evolution of females’ high school performance over time. He reports that females’ mean test scores in high school have increased more rapidly than males’ over the past three decades. Using a simple Oaxaca decomposition, he finds that women’s progress in high school scholastic performance can account for more than half of the change in the college enrollment gender gap over the past thirty years.

Fortin, Oreopoulos and Phipps (2015) use self-reported grades, rather than test scores, to look at the evolution of female high-school scholastic performance over time. Using a sample of 12th graders from the Monitoring the Future (MTF) study in 1976 and 1991, they report that the gender gap in the mean grades of high school seniors remained very stable since the 1970s. They find, 17
2007. In the long run we can expect much higher contributions to total exports from firm dynamics. In the case of Colombia, existing evidence indicates that the contribution of new firms to total export growth (of 7.6 percent) between 1996 and 2005 rose from 10 percent on an annual basis to 26 percent for the whole period (Eaton et al. 2007). The case of Chilean manufacturing exports is more dramatic: the contribution of entering firms to total export growth during 1991-2001 (which averaged 11.5 percent per year) rises from 23 percent on an annual basis to over 83 percent over the whole period (Alvarez and Fuentes 2009).

Table 9 provides calculations of the contribution of new firms, new products, and new combinations of firms and products, and new combinations of firms, products and destinations to Costa Rica’s total exports during the period under examination. The first column shows the share of total exports that was contributed by firms that did not conduct export activities in 1997 and 1998. The second column shows the same ratio but for new products (that did not exist in the PROCOMER data in 1997 and 1998). The third column focuses on new firm-products and the fourth column on new firm-product destinations.

As expected the contribution of entry rises over time, as a byproduct of the large rates of turn over discussed in previous sections. By 2007, new firms accounted for about 5.6 percent of total exports, and new products for about 7.5 percent of the total. The big contribution came from the entry of new firm-product combinations, with a contribution of 59.6 percent by 2007. The addition of new destinations to new firm-product combinations only adds about 6.5 percentage points to the contribution of new firm-product combinations, thus accounting for about 66.1 percent of aggregate exports in the (cleaned) PROCOMER data. That is, while it is expected that adding new dimensions to the definition of “entry” will tend to increase its contribution to exports from an accounting perspective, it is the contribution of new firm-products that contributes the lion’s share of exports.

Together with the previously mentioned evidence concerning the relatively high rates of product turnover among incumbent firms (recall Table 7), the evidence in Table 9 suggests that most of the action behind export growth in Costa Rica over the long run (or at least during 1997-2007) was due to product shifting by incumbent firms.

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