rafmacalaba/data-use-mentions-extended huggingface dataset:
Policy Research Working Paper 10071

# **Abstract**

Using fine-grained spatial data and a dynamic spatial general equilibrium model, this paper assesses the magnitude of mobility frictions in Latin America as well as the effects of their reduction on spatial development in the region. The results suggest that in most Latin American countries, migration frictions calibrated based on spatially differentiated initial utility are on average smaller and less dispersed than those obtained assuming uniform within-country initial utility. A reduction in trade costs due to optimal investments in road infrastructure in most Latin American countries increases the present discounted value of real per capita income on average in the region by 15.1 percent. This effect is larger than the effects obtained with static quantitative trade models because of substantial dynamic gains. By contrast, a reduction in migration entry costs in the most productive and more populous locations in the Latin American countries has a negligible effect on the present discounted value of the region’s real per capita income, reflecting the relatively small dispersion in domestic migration frictions and their relatively low levels in top locations. In both counterfactuals, the welfare increases are significantly larger than the increases in real per capita output because the reductions in mobility frictions allow people to relocate to areas with better amenities and therefore derive higher utility. These results suggest that trade costs, not migration barriers, represent a major constraint to the efficient spatial distribution of economic activity and growth in Latin America.

This paper is a product of the Office of the Chief Economist, Latin America and the Caribbean Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at b.conte@unibo.it or eianchovichina@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues.
been more successful than FSU countries at designing tax systems, tax administrations, and government structures in which taxpayers can put their trust. Hence, our results suggest that CEE countries have been more successful than FSU countries at designing tax systems, tax administrations, and government structures in which taxpayers can place their trust. Such institutional improvements and observable changes may help to explain the higher willingness to cooperate in CEE countries, some of which exhibit higher values of tax morale than some Western European countries.

Torgler (2007) explores the differences between CEE and FSU in different stages, namely in 1989-1993, 1995-1998 and 1999-2001 across 22 transition countries. Using a multivariate analysis, the study finds that that in most of the three time periods there is a statistically significant difference between CEE and FSU countries; interestingly, the difference between CEE and FSU is statistically significant in all specifications. The marginal effects are much higher in the years 1995-1998, indicating a higher divergence between the regions. The study also indicates that the respondents originating from a CEE rather than from a FSU country, increases the probability of stating that ―tax evasion is never justified‖ by around 13 percentage points (compared to around 2 percentage points in 1989-1993). Looking at the 1999-2001 data, FSU countries have still significantly lower tax morale than the CEE countries. However, the marginal effects have not increased as in the previous years and some are even observed to be lower (close to 9 percentage points).

What are the driving forces that shape tax morale in Central Eastern and Former Soviet Union countries? Trust in the government and the legal system seemed to be key factors. Governments fulfill a leading role in the transition process; institutional changes are connected to uncertainty. Institutions provide a reduction of uncertainty by designing the provided structure of interaction. As a consequence, greater certainty in the political process is gained. Ensley and Munger (2001) argue that ―if rules are not formalized, the players may spend too much time arguing over the rules and less time competing
ographic coverage, the extent of low-lit areas, and sensor recalibrations. Temporal variations unrelated to economic activity give rise to large noise in nighttime light data, but year fixed effects in regression analyses can control for such noise if it is common across countries. We found that the quarterly correlation between VIIRS nighttime light growth and GDP growth is stronger for EMDEs than for advanced economies.

Different from annual DMSP nighttime light data, monthly VIIRS nighttime light data can be used to study economic short-term impacts of different shocks. Efforts in this direction are already leading to very interesting new insights. Among others, studies have looked into the impact natural disasters like the 2017 earthquakes in Nepal (Beyer, Chhabra, Galdo, and Rama, 2018), domestic policy measures like the demonetization in India (Chodorow-Reich, Gopinath, Mishra, and Narayanan, 2020) or lockdown measures during the COVID-19 pandemic (Beyer, Jain, and Sinha, 2020), and trade shocks like the recent tariff war between China and the United States (Chor and Li, 2021). Other possible applications are too numerous to list. For all of them, it is necessary to translate changes in nighttime lights measured in nanowatts into changes in economic activity measured in US dollars (or any other currency).

In this paper, we presented a novel framework to estimate the elasticity between nighttime lights and GDP, which is fundamental for this translation. Our framework uses varying degrees of measurement errors in nighttime light data across countries to identify the elasticity. We estimate it to be 1.55 for EMDEs and find only small differences across model specifications and country groups. This elasticity can now be used to translate changes in nighttime lights into changes in economic activity. For example, if the economic impact of a shock is studied with a difference-in-differences approach, a 10 percent decline of nighttime lights in the treated group with respect to the control group reflects an economic impact of 6.5 percent of GDP.<sup>30</sup> We concluded the paper
falling to just 8 percent of all primary schools in 2003. At the same time, the expansion of the non-public sector has increased education access. The primary completion rate grew from 35 percent for Haitians born 1950-1954 to 88 percent for those born a generation later (1980-1984). Despite this progress, as of the most recent (2005) survey data, severe gaps between rich and poor remained. Primary attendance and completion rates for those in the wealthiest quintile are comparable to those of middle income countries in the region, while the rates for the poorest quintile are similar to those of the poorest countries in Africa. Another key feature of the Haitian education system is that many students are over the prescribed age for their grades. Multivariate analysis presented in this paper indicates that parents’ education, household composition, and

> 1 See World Bank (2006) for estimates of returns to schooling in Haiti based on 2001 survey data. Overall, the estimates for the marginal return from an additional year of education are 15.6-19.7 percent for wage earnings and 14.0-17.2 percent for total earnings (including wages and self-employment earnings).

> 2 In Haiti, all non-state providers of education are collectively referred to as the “non-public” sector. In this paper, the terms “private” and “non-public” are used interchangeably.

2
11 countries are considered to have ”high-quality” measures of income inequality by the World Inequality Database project, due to the lack of available tax records.<sup>2</sup> Recent research on top income inequality in the region includes Alvaredo & Londo ̃no Velez (2014) on Colombia, Zu ̃niga Cordero (2022) on Costa Rica, Alvaredo _et al._ (2017) on Mexico, Burd ́ın _et al._ (2022) on Uruguay, Morgan (2018) on Brazil and Flores _et al._ (2020) on Chile. As an illustration, the current level of top 1% income share in Honduras in the WID is 18.3%, obtained by ”regional imputation”.<sup>3</sup> As with other recent studies in the region, we show that new estimates using detailed tax records might provide a very different perspective on the levels and trends of top income shares in Latin America.

# **2 Context**

Honduras is a lower-middle-income country in Central America with approximately 9.8 million inhabitants. Economic activity is linked to low value-added agricultural

> 1The existing literature in Honduras exclusively exploits survey data (see for instance Ham (2011), World Bank (2016) and S ́anchez & Urrea (2019))

> 2Still, this figure includes countries where there is no micro-data but tax-tabulations e.g., Brazil, and interpolation techniques are used to estimate incomes at the top.

> 3Both values, the number of countries identified as with ’high-quality’ data, and the Honduran top income share, are obtained from the WID website (October 2023).

3
Policy Research Working Paper 8622

# **Abstract**

Inequalities in the opportunity to obtain a good education in low-income countries are widely understood to be related to household resources and schooling quality. Yet, to date, most researchers have investigated the contributions of these two factors separately. This paper considers them jointly, paying special attention to their covariation, which indicates whether schools exacerbate or compensate for existing household-based inequalities. The paper develops a new variance decomposition framework and applies it to data on more than one million children in three low-income East African countries. The empirical results show that although household factors account for a significant share of total test score variation, variation in school quality and positive sorting between households and schools are, together, no less important. The analysis also finds evidence of substantial geographical heterogeneity in schooling quality. The paper concludes that promoting equity in education in East Africa requires policies that go beyond raising average school quality and should attend to the distribution of school quality as well as assortative matching between households and schools.

This paper is a product of the Development Research Group, Development Economics. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/research. The authors may be contacted at hdang@worldbank.org and jones@wider.unu.edu.

_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
8We assume that depreciation is a linear function of the book value of the firm’s capital stock : Dept = π ∗ Kt.

> 9Bartel (1991) uses a survey conducted by the Columbia Business School with a 6% response rate. Black and Lynch (1997) use data on the Educational Quality of the Worforce National Employers survey, which is a telephone conducted survey with a 64% ”complete” response rate. Barrett and O’Connell (2001) expand an EU survey and obtain a 33% response rate.

7
39 Table A2.4: Shares of total household expenditure on LPG for all households and for purchasing households in Guatemala (%)

|**Quintile**|**Rural**|**All households**<br>**Urban**|**Total**|<br>**Rural**|**User households**<br>**Urban**|**Total**|
|---|---|---|---|---|---|---|
|**1**|0.1|0.8|0.2|6.2|6.8|6.6|
|**2**|0.3|1.7|0.8|4.1|4.4|4.3|
|**3**|0.8|2.5|1.6|3.8|3.6|3.7|
|**4**|1.3|2.3|1.9|2.8|2.7|2.8|
|**5**|1.0|1.4|1.3|1.6|1.6|1.6|
|**All**|0.6|1.8|1.3|2.7|2.5|2.5|

_Source:_ Authors’ calculations.

# **India (National Sample Survey, 2004–05)**

The data are taken from the 61<sup>st</sup> round of the National Sample Survey of India administered by the government’s National Sample Survey Organization. The fieldwork for the survey was carried out between July 2004 and June 2005.

The value of all non-purchased items was about 14
**Table 2: Regression Results for Step 1**

**Pass Through from International to Domestic Food Price Inflation**

||Full long-term pass-<br>through|R-squared<br>adjusted|
|---|---|---|
|_Using FAO food index_|0.16|0.25|
|_Using FAO cereals sub-index_|0.13|0.28|

These results are in line with the 0.16 weighted average pass-through of the IMF 2008a country-bycountry estimate, and the 0.19% estimate of El-Sakka and Ghali (2005). Yet, these results may seem much lower than the 0.34 median long-term pass-through of international food price shock in EMEs, (IMF, 2011). This may be due to expressing international prices in local currency in IMF, 2011, blending thus together changes in the exchange rate and changes in international food prices. Yet, our results remain unexpected given the large size of the food basket in Egypt‟s CPI.

The estimation of the second-step equation showed that the long-term the spill-over from domestic food prices to other domestic prices is sensitive to the variables used both in step 1, the international price index being (either the FAO food index or the FAO cereals sub-index), and step 2, the domestic price index (core versus non-food inflation) and the economic activity proxy variable (output gap versus output growth gap). In fact, the eight equations that were estimated showed that the long-term spill-over effects ranged between 0.15 (from domestic food prices impacted by FAO cereals price changes to core inflation) and 1 (complete spill-over of the shock to domestic food price inflation to non-food price inflation when the FAO food index is used) (table 3).

To solve the inconclusiveness of the results of the spill-over estimates, the authors resorted to an out-ofsample forecasting method to compare the forecasting power of various models. As shown in table 3, ceteris paribus, having a lower RMSE
we cannot cleanly isolate the minimum wage channel. We also acknowledge that allowing a triple difference to vary by both gender and time period is demanding on the data, and the estimates are accordingly noisy, so they should be viewed as suggestive. We further caution that, as discussed in the introduction, the more time that passed after Rana Plaza, the greater the likelihood of a shock to garment workers in treated districts that would violate the parallel trends assumption needed for a causal interpretation of the triple difference in equation 1. So the medium-term results should be viewed as somewhat more suggestive, though it’s broadly reassuring for policy-makers interested in improving the welfare of garment workers that positive point estimates for wages do not dissipate completely in the medium term.

The stated objective of much of the international scrutiny post Rana Plaza reforms was to improve safety and working conditions inside garment factories. In column 2 of Table 2, we report estimates of the effects of the Rana Plaza reforms on the index of working conditions described in section 3.1. Overall, we find that Rana Plaza increased the working conditions faced by garment workers by 0.80 standard deviations, with similar orders of magnitude between men and women. From Figure 5, we see that the effects are particularly strong in 2016 (especially for women), though again the estimates are fairly noisy and this pattern should be viewed as suggestive. By contrast, we do not find qualitatively large or statistically significant effects on hours of work or the probability of receiving a contract.

Table 3 examines other sources of potential heterogeneity behind the average effects given in panel A of Table 2. Specifically, we consider four binary dimensions of heterogeneity: at or below median age and education in estimation sample (7 years of education and 28 years of age), whether the respondent is married, and whether there is at least one child in the respondent’s house<sup>7</sup> . These variables were chosen because they either reflect human capital (lacking direct
In this study, we augmented an existing rich household panel of households (pre- and postprogram) with a new follow-up survey round. With the new round of data, we use a dynamic panel data approach estimated by GMM (Arellano and Bond 1991; Jalan and Ravaliion 1998) to test for impacts, which allow us to account for time-varying unobserved heterogeneity.

We find that most of the effects on household per capita expenditure, schooling enrollment, and transport costs, have indeed attenuated over time. Households in villages that received the project between 2001 and 2005, for example, experience stronger impacts for these outcomes compared to households that received the project earlier. However, attenuation in project effects is not across the board; for example, non-agricultural wage employment has risen more for households in areas targeted before 2001. This suggests a feedback effect between off-farm work and rural road development, where road improvements foster markets that become increasingly diversified across sectors. Alternatively, improved school enrollment, likely associated with better access to schools, could generate higher demand for labor in the long run. Ultimately, understanding these trends requires an analysis of other community-level changes in other infrastructure, such as electricity, and market growth to better understand how roads interact with other policy changes to affect households’ economic opportunities.

Distributional impacts of rural road investments are also an important policy concern. We examine these effects through (i) access, using data on distance to the project road and new data on quality of road paving and (ii) quantile regressions examining the effect of the road project by households’ initial position in the outcome distribution. We find that much of the overall project impact, including asset accumulation, is explained by road quality. The quantile results indicate that the initially poorest households have not shared in the benefits of rural roads; at most, households between the 25<sup>th</sup> and 50<sup>th</sup> percentile of per capita food expenditure have experienced positive gains. Households in this
delivery possibilities of other classes of wheat, the CBOT contract is considered more reflective of global wheat conditions. In addition, the class of wheat traded at the CBOT most closely resembles the type of wheat grown in Poland. For these reasons, the CBOT contract was chosen as the price to be used in this analysis. Outside the US, the most liquid wheat futures contract is the LIFFE wheat futures. This futures contract was also included in the analysis.<sup>8</sup> The analysis was carried out over a period of 6 years, i.e., from 1990 to 1995. This period represents the time during which Poland experienced a liberalized economic structure. Despite the beginnings of a free market system, finding a representative price series in Poland to compare against futures prices is somewhat problematic. While several grain exchanges exist where physical cash wheat is traded, the volume of trade is erratic and quoted prices might not be representative of the overall market. In addition, most of these exchanges were created only recently, thereby limiting the time frame available for analysis. The Polish price series chosen for the analysis was average monthly wheat prices for Poland as reported by the Central Statistical Office (GUS). This price represents prices paid to farmers by commercial enterprises. Price analysis was conducted on both a calendar year and crop year (August-September) basis as both have some merit in terms of looking at impacts of various factors.

# 2. Wheat Price Variation in Poland in **Years 1990-95**

The first analytical task chosen was to gain insight into the price variation in Poland with respect to variation over time and spatially within Poland. The primary objective of examining variation over time was to gain insight into the degree of Polish price volatility. The basic methodology used was to quantify the spread of minimum and maximum prices and the coefficient of variation (standard deviation divided by average prices for each year).

The purpose of the spatial variation analysis was to determine if prices within Poland showed any significant
These conclusions hold in each of the follow-up rounds, suggesting that this is not a case of training taking time to show impact.

In contrast, the combination of training and the cash grant does have positive and significant impacts on capital stock, which hold across survey rounds. Truncated capital stock increases by an ITT of 10,000 Rs, with the TOT for the pooled rounds of 15,357. Thus capital stock appears to have increased by the same amount as the grant for those who completed the training and received the 15,000 Rs. There is a significant increase in profits when using the pooled sample with truncated or log profits. This effect comes from the round 2 and 3 data. However, it appears that this increase in profits is only temporary; the point estimate on profits is much smaller by the rounds 4 and 5 surveys.<sup>16</sup> This is seen also in Figure 4B, where the CDF of profits in round 5 almost on top of that of the other two groups. The sales data are noisier than the profits data, and we generally see a positive, but not significant, impact on sales. Hours worked are higher in the round 2 survey, but not significantly different from hours worked in the control group in subsequent rounds.

The combination of training and a grant therefore have immediate effects which appear to dissipate a year later. Since we wanted to be able to compare the impact of training and cash to that of training alone, cash grants are only given to those who completed training. Ex ante it was not possible to tell who would complete training, precluding the inclusion of a treatment group receiving only cash conditional on being the sort of person who would complete training if offered it. To learn whether the short-term impact on profits is due just to the cash grants, or to the combination of the cash and training, we therefore re-estimate the impact on profits, controlling directly for capital stock. The control for capital stock nets out both