rafmacalaba/datause-encoder-data huggingface dataset:
# Bridging Bangladesh and India: Cross-Border Trade and the Motor Vehicles Agreement<sup>_∗_</sup>

Mat ́ıas Herrera Dappe<sup>_†_</sup> Mathilde Lebrand<sup>_‡_</sup> Diana Van Patten<sup>_§_</sup> World Bank World Bank Princeton University March 2021 _Keywords:_ Agglomeration economies, economic integration, spatial general equilibrium, trade and geography, transport corridors.

_JEL Classification:_ F12, F15, O18, R11, R12, R13.

> _∗_ This work is a product of the staff of the World Bank with external contributions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of the World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on maps in this work do not imply any judgment on the part of the World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries.

> _†_ mdappe@worldbank.org.

> _‡_ mlebrand@worldbank.org.

> _§_ vanpatten@princeton.edu.
transaction costs are equalized.

There are other potential explanations for our findings. Nutritional deprivation leading to very high marginal utility of consumption of food could explain the low levels of temptation spending observed, but in our study very little of the transfer is spent on food. This is consistent with the behavior of very poor households studied by Banerjee & Duflo (2007), who report considerable non-food expenditures despite very low incomes, and with recent findings that income earned through Malawi’s public works program (PWP) does not improve nutrition (Beegle, Galasso & Goldberg 2015).

We study a one-time transfer, which limits the opportunity for habit formation. Somville & Vandewalle (2015) study recurring transfers by paying Indian survey participants the equivalent of a daily wage for 7 to 13 weeks. They vary whether payments are in cash or through individual accounts with local banks, and find lower food consumption and nearly-equivalent higher savings for those paid through bank accounts. However, the effect dissipates as soon as payments are switched to cash. This works against the hypothesis that habit formation or learning is an important mechanism or a reason that our results would underestimate the impact of recurring direct deposits.

The transfers in our study are unearned and unanticipated. Previous work in Malawi shows that direct deposit of earned agricultural income does affect savings, investment, and consumption in the following year (Brune et al. 2016). In other studies of access to bank accounts, deposits come from the subjects’ own assets or income (Dupas & Robinson 2013 _a_ ). Mental accounting could lead to different use of earned and unearned income, and to different effects of payment structure on earned income than what we measure, for unearned income. Blumenstock, Callen & Ghani (2015) find imprecise increases in spending six to eight months after wage payments for Afghani workers are converted to mobile money instead of in cash.

Similarly, payment delay does not affect the level nor composition of expenditures in our study, but it may in other contexts. While there is evidence that direct deposit does affect spending and investment for earned income, the evidence on payment frequency or delay is less conclusive. In Malawi, paying public works beneficiaries every three days compared to every week does not affect consumption (Beegle, Galasso & Goldberg 2015), but paying participants in an NGO’s livelihood program monthly instead of weekly reduces total short-run spending and increases take up of a high yield short term investment opportunity (Brune & Kerwin 2014). In Indonesia, unanticipated delays to planned disbursements of a governmentsponsored unconditional cash transfer reduced consumption growth of beneficiaries relative to non-beneficiaries as well as to those who received payments on schedule (Bazzi, Sumatro & Suryahadi Forthcoming).

Previous studies have established that financial access and savings defaults can change savings and investments, and our results do not contradict those findings. Rather, they 22
# **3. Simulations**

## _Simulation Design_

The baseline scenario from 1998-2005 is constructed by utilizing the recursive dynamic version of the model. The baseline scenario establishes a plausible growth trajectory for the Chinese economy, which takes into account events such as China's WTO accession and its recent dramatic surge in exports, which have doubled in the last four years. We then utilize the updated 2005 data base as the new benchmark equilibrium from which we employ the comparative steady-state model to conduct the policy simulations. A series of trade reform scenarios are then considered, followed by a final scenario that is designed to capture the added impact of rural education reform.

In the first trade reform scenario ( _ROW_ ) we consider the impacts of global trade liberalization excluding China. In particular, this entails elimination of all import tariffs in the rest of the world. In addition, agricultural export subsidies are eliminated, as are subsidies for domestic agricultural production in the OECD. The second scenario ( _Uni_ ) focuses on China's unilateral liberalization. All import tariffs and non-tariff barriers of China are eliminated in this scenario. The third scenario ( _Full-Lib_ ) considers the impact of global free trade by combining the first and the second scenarios. The fourth scenario is the standard _Doha_ scenario.

To reflect the impacts of multilateral trade liberalization in the single country model, we incorporate external market impacts into the Chinese CGE model through exogenous shifts in import prices and export demand schedules. The sizes of these exogenous trade shocks are obtained from global simulations. The tariff reduction in China is excluded in this GTAP simulation but is included in the simulation of the single country model.

14
indicate signi...cance of geographical di¤erences, they do not directly provide a measure of how important those di¤erences are or how those di¤erences evolve over time. The second approach utilizes the local area estimation technique to estimate Theil inequality coe¢ cients at local levels from census data and decompose the inequality index into within and between community indices (Elbers, Lanjouw, Mistiaen, Ozler and Simler (2004)). This approach however cannot be directly used to explore the factors that may lead to spatial di¤erences in welfare, as can be done in the ...rst approach.

This paper constructs a simple measure of spatial disparity in welfare. This measure, termed as "spatial disparity index", estimates the proportion of total variations in welfare that can be attributed to common area characteristics faced by households living an area/community. Our “spatial disparity index" can be thought of as a spatial analog of the "neighborhood correlations" proposed by Solon, Page and Duncan (2000). The neighborhood correlations are widely used to study the in‡uence of common neighborhood factors on the adult outcomes (e.g. education, income) of children growing up in the same neighborhood (Solon, Page and Duncan (2000), Page and Solon (2003), Raaum, Salvanes and Sorensen (2006)). To the best of our knowledge, no study has yet used this measure to study spatial inequality in welfare.

In a spatial equilibrium model, households are sorted into communities/areas in terms of income opportunities and amenities (Roy(1951), Roback(1984)). Such sorting means that households of similar attributes and hence similar welfare status tend to live in the same community, resulting in a positive correlation in income and welfare among households. At the one extreme of complete segregation or perfect sorting, all households living in a community will look similar, producing a spatial disparity index estimate of unity. In this case, all of the inequality in welfare is due to inter-community di¤erences. In contrast, if there is no sorting, then a randomly selected sample of households from a community will be indistinguishable from a random sample of households from any other community. The di¤erence in welfare in this case is entirely due to within 2
_Figure 12: Sector Export Shares in Cooperative Scenarios_ <!-- Start of picture text --> GCC countries Russian Federation<br>100 100<br>90 90<br>80 80<br>70 70<br>60 60<br>50 50<br>40 40<br>30 30<br>20 20<br>10 10<br>0 0<br>2020 2030 2040 2050 2020 2030 2040 2050 2020 2030 2040 2050 2020 2030 2040 2050<br>Traditional Diversification Asset Diversification Traditional Diversification Asset Diversification<br>Middle-income coal exporters Low-income countries with large reserves<br>100 100<br>90 90<br>80 80<br>70 70<br>60 60<br>50 50<br>40 40<br>30 30<br>20 20<br>10 10<br>0 0<br>2020 2030 2040 2050 2020 2030 2040 2050 2020 2030 2040 2050 2020 2030 2040 2050<br>Traditional Diversification Asset Diversification Traditional Diversification Asset Diversification<br>% of total exports % of total exports<br>% of total exports % of total exports<br><!-- End of picture text --> _Source: World Bank and Purdue University (ENVISAGE)_

# 3.4. **Helping Those Who Are Less Able to Diversify and Cooperate**

Additional nudges to cooperate may be needed for the two country groups that have low incentives to implement domestic carbon taxes even under the threat of Nordhaus import duties, namely (i) lower-middle income countries with large proven, but not yet extracted, fossil fuel reserves; and (ii) the middle-income coal-exporting countries (see figure 8). In order to bridge the gap between consumption in cooperative and non-cooperative scenarios, the LCT pioneers can provide strategic financial, technology, and knowledge transfers worth $663 billion until 2050 (approximately $22 billion per year). This is one-eighth of the $5.5 trillion savings they would derive if all FFDCs cooperated (avoided incremental costs of unilateral climate action). These transfers would allow these vulnerable countries to implement domestic cooperative carbon prices. The former ones could use international assistance to overcome shortage of capital needed to invest in asset diversification. The latter, to address social challenges of transition away from coal in the mining regions. The key challenge of financial transfers is political feasibility, where historically it has been difficult to ensure credible international climate finance transfers (OECD et al. 2015, CPI 2019).

21
assessed as rural in practice. But there are no substantial differences for most villages, whose rural status is confirmed by the subjective assessments.

**Table 4. Classification based on human judgments versus administrative classification**

|Administrative classification|Assessed urban<br>(percent)|Assessed rural<br>(percent)|Total<br>(percent)|
|---|---|---|---|
|Statutory towns|23.1|8.6|31.7|
|Census towns|20.0|23.6|43.6|
|Villages|0.2|24.5|24.7|
|Total|43.3|56.7|100.0|

# **4. Machine learning**

The urban status of places derived from human judgments can be used to infer the urban status of the other places in the universe. Doing this requires first learning from the sample and then using the results to make out-of-sample predictions. A first question is which indicators to consider for this exercise. Official measures of urbanization are based on traditional data sources, such as population censuses, whereas more recent studies rely on modern data, and especially on satellite imageries. A second question refers to the statistical approach to be used. A specific data generation process is assumed in the classical statistical tradition, but supervised machine learning is becoming increasingly popular. Our methodology brings together traditional and modern data, and compares the outcomes depending on whether classical econometric models or machine learning are used for the prediction.

## _Traditional and modern data_

We chose as key covariates for the prediction a set of indicators which appear recurrently in the urban literature and are observable for all administrative units in India.

Traditional data were from the 2011 Census of India. These data were georeferenced to the digitized boundaries of administrative units as part of the Spatial Database for South Asia project. The range of georeferenced indicators available for all places in the country as of 2011 is wide (Li et al. 2015). Following the practice of national governments and international organizations, we selected _population_ and _population density_ at the town and village level as the key indicators. This choice is consistent with that of studies relying on high-quality microdata from the ground for more advanced economies (Michaels, Rauch and Redding 2012; Rozenfeld et al. 2011). Population density was computed as the ratio between the population of the administrative unit and the size of the area within the corresponding boundary.

Modern data were obtained from open-source products built on satellite imagery. Following more recent global products, built-up cover and nighttime lights are the preferred data in this respect. For built-up cover, we selected the Landsat-based product provided by the Global Human Settlement Layer, hereafter referred to as GHSL (Pesaresi et al. 2016). The product is derived from images taken by sensors aboard Landsat 7 and Landsat 8 satellites. As one of the first civilian satellite programs on land cover, Landsat has produced the longest continuous space-based record of the Earth’s land surface. Landcover products 16
2 statistical **analysis** of this issue, both in the case of Chile and in industrial countries may htve underestimated the negative impact of MWs because they do not correct for selectivity bias.

# II. The Issue

Two distinct methodologies have prevailed in analyzing the impact of MWs in the economy.<sup>1</sup> In cross-sectional studies different MW levels prevailing across regions (states) **are** correlated with other observed labor market outcomes, thus providing some policy implications on the basis of specifli labor force groups being affected. Studies by Osterman (1979), Cunningham (; and Lang (1982) **are very** much in this vein; also those by Freeman (1979) and Mvyer and Wise (1981) for the specific case of the young. A variant in the application of this methodolog7 is offered by Linneman (1982) who uses crosssectional regressions to assess the adult wage structure prevailing prior to the establishment of MWs, identifying the subminimum wage population. A second type of methodology is based upon time series analyses that, in principle, would produce more robust results, for they allow a more direct observation of the effect of MWs on certain market outcomes. Cotterman (1981) discusses the issues involved in the specification of a system of econometric relationships; Fels and Vaa Boa (1981), and Paldam **and** Riveros (1987) apply full and partial causality tests between MVe, average wages and other macroeconomic outcomes.

Surprisingly, econometric research on the role played by MWs in LDCs is all but abundant.<sup>2</sup> At the same time, most of the available studies on the role of MWs in industrial economies have been based on the observation of aggregate relationships, usually estimated on the basis of some reduced-form model. These results surround much of the current empirical wisdom, which in turn support many policy recommendations (see, for instance, Drabick and Takayama (1982)).
24 Fiscal incidence studies are quantitative studies which measure revenue burdens and expenditure benefits by different income groups. At best they estimate the effective incidence (the ultimate tax or expenditure effect) rather than the statuatory incidence, which is based on the letter of the law. 23 The effect of a change in fiscal expenditure is then measured by mechanical calculations based on the accessibility to government services by socioeconomic groups. Behavioural responses are not incorporated and as such, the utilization of incidence studies is not of a general equilibrium nature.<sup>2 4</sup> Furthermore, the incidence studies focus on secondary incomes, or transfers of taxes, subsidies, remittances; the effect of fiscal actions on the primary distribution of income, through changes in the demand aid supply of factors and goods, are generally not included.

# d. Macro Output - Micro Input

A fourth method starts with a country poverty profile and links it to a macromodel that provides output on intermediate variables such as wages, employment, and prices. This would be a partial equilibrium analysis because it measures the impact of the intermediate variables on poverty, but would not incorporate the feedback from the poverty to the macromodel. A study by Youngblood, et al (1989), commissioned by USAID on El Salvador, u.cs this methodology. They develop a three sector macromodel (importables, exportables, and nontradables) and estimate three econometric equations for the value added of each sector. The economic reforms are represented as changes in the relative 23See Catsambas (1988) for a discussion on the issues and problems in fiscal incidence studies.

24However, current research by Emmanuel JimeLnez at the World Bank is examining behavioural responses to social expenditure programs and the implications for policy.
**Figure 3.1: Literacy Rate of People of Age 10 and Older by Gender and Rural and Urban Living, Paraíba, 2000**

<!-- Start of picture text --> 90.00%<br>total urban rural<br>79.87%<br>80.00% 77.73% 75.30% 76.18%<br>72.44%<br>70.00% 68.38%<br>65.98%<br>58.97%<br>60.00%<br>52.24%<br>50.00%<br>40.00%<br>30.00%<br>20.00%<br>10.00%<br>0.00%<br>Total Men Women<br>Source: Based on Census 2000.<br><!-- End of picture text -->

**_School Enrollment._** In Paraíba, school enrollment has improved enormously in the last two decades. During 1980-99, enrollment in primary schools increased by 15 and 17 percentage point to 95 and 93 percent, for Brazil as a whole and Paraíba respectively (Figure 3.2). In 2000, a number of 889.003 children and adolescents were enrolled in primary school in Paraíba. Figure 3.3 shows that Paraíba’s school-enrollment catch up occurred mainly after 1994. These gains arose from changes in policy, in particular among federal initiatives to boost enrollment and guarantee funding per child, such as _FUNDESCOLA_ and _FUNDEF_ (see below), combined with effective decentralization to states and municipalities.

|**Table**<br>|**3.3: Age**<br>|**and Sch**<br>|**ool Enrol**<br>|**lment (1**<br>|**998)**<br>|||||
|---|---|---|---|---|---|---|---|---|---|
|**Age**|**Total**<br>**BR**|**Total**<br>**NE**|**Total**<br>**Paraíba**|**Urban**<br>**BR**|**Urban**<br>**NE**|**Urban**<br>**Paraíba**|**Rural**<br>**BR**|**Rural**<br>**NE**|**Rural**<br>**Paraíba**|
|**5-6 **|69.1|72.8|79.7|73.4|79.5|86.2|56.4|63.5|71.2|
|**7-14**|94.7|92.3|94.4|95.8|93.6|94.9|91.2|90.4|93.5|
|**15-17**|76.5|72.5|72.1|79.7|77.2|79.5|64.6|64.7|58.9|
|**18-19**|49.3|48.7|45.4|52.0|53.3|49.8|37.3|39.5|35.3|
|**20-24**|24.2|24.2|26.1|25.9|26.7|30.6|16.3|18.9|17.6|
|_Source_: Sí|ntese de Indic|adores Socia|is,1999 – IBG|E – Tabel 3.3||||||

The enrollment picture is not all rosy in Paraíba. In older age groups, Paraíba falls behind in enrollment rates. Enrollment for ages 15-17 is 72.1 percent, considerably below the national average of 76.5 percent (Table 3.3).

18
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Policy Research Working Paper 5302

# **Abstract**

Poor rural women in the developing world spend considerable time collecting water. How then do they respond to improved access to water infrastructure? Does it increase their participation in income earning market-based activities? Does it improve the health and education outcomes of their children? To help address these questions, a new approach for dealing with the endogeneity of infrastructure placement in cross-sectional surveys is proposed and implemented using data for nine developing countries. The paper does not find that access to water comes with greater off-farm work for women, although in countries where substantial gender gaps in schooling exist, both boys’ and girls’ enrollments improve with better access to water. There are also some signs of impacts on child health as measured by anthropometric z-scores.

This paper—a product of the Gender and Development Unit, Poverty Reduction and Economic Management Network— is part of a larger effort in the department to understand the constraints, including infrastructure-based, to women’s participation in market activities and the externalities for children. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at dvandewalle@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
business statistics on establishments, Canada reports Average Labor Units (ALU), while countries reporting to Eurostat and UNECE use various measures including legal (enterprises), geographical (local unit), and activity-based (kind of activity unit) for their business statistics.<sup>1</sup> As a result, the proposed unit of measurement must take into account the availability of the data, its consistency across countries, its relevance to entrepreneurship and focus on the formal sector. As such, we gather data only on corporations, which we define as _private companies with limited liability_ . Notably, this is the same definition used by the World Bank’s Doing Business report. It is also the most prevalent business form in most economies around the world (Doing Business, 2010).

“Limited liability” is a concept whereby financial liability of the members is limited to the value of their investment in the company. It is a separate legal entity which has its own privileges and liabilities. While the laws on business registration may vary greatly across countries, the approach to legal entities is largely uniform: any business with a unique legal entity (or “corporate personhood”) separate from its owners must be registered.<sup>2</sup>

# **_2.2 Sample Selection_**

As discussed in the last section, our data is not a comprehensive study of all registered firms. In order to provide harmonized, comparable data across countries, certain exclusions have been made, as described below:

> 1 US Census Bureau: <u>http://www.census.gov/econ/www. Also see Longitudinal Employment Analysis Program</u> (LEAP) of Statistics Canada: <u>http://strategis.gc.ca/epic/site/sbrp-rppe.nsf/en/rd00827e.html. Eurostat definition is</u> from council Regulation (EEC) No 696/93 of 15 March. UNECE terminology on Statistical Metadata is from United Nations Statistical Commission.

> 2 We collect information on all corporations regardless of their economic or employment size, since in many countries neither financial information nor the number of employees is collected, making it impossible to identify firm size.

5