rafmacalaba/data-use-mentions-extended huggingface dataset:
and land and possibly other (non-water) natural resources should be accounted for. Empirical observations of land market transactions and more elaborate hedonic pricing using farm sales data and econometric techniques show that typical residual imputation studies yield higher valuations than do market transaction-based studies. If, for example, in a long-run context of analyzing FDB the contributions of some of these non-water owned inputs are neglected in calculating the residual claimant for water, then the value assigned to water is erroneously large because it includes returns not just to water, but to the ignored owned inputs. Results from such analyses would yield exaggerated estimates of FDB from decreased water supplies.

51. Similarly, the studies that used the value-added measure from regional input-output models to estimate FDB also produced overstated FDB—because changes in value-added consist not only in the 15
who draw income from farm sources as well was 69.5 percent 2000, 81.5 percent in 20005, and 82.0 percent in 2010. In this section, we estimate the net contribution of microenterprise in income generation and poverty reduction using the three rounds of HIES survey data. Table 7 presents the relationships between microenterprise participation and household welfare (measured in terms of per capita income and expenditure as well as moderate and extreme poverty) over time.<sup>6</sup> As Table 7 shows, the percentage of households engaged in microenterprise activities besides farm and other activities has declined from 25.6 percent in 2000 to 21.6 percent in 2010. Yet we find consistently higher growth in per capita income and expenditure among the households engaged in microenterprises, besides farming and other nonfarm activities. For example, in 2010, households with microenterprises as additional sources of income had 36 percent higher per capita income and 12 percent higher per capita expenditure than those without a microenterprise activity as an additional source of income and their differences are statistically significant at more than the 5 percent level.

We also find that both the moderate and the extreme poverty rates are substantially and significantly lower for households with microenterprises than those for households without a microenterprise activity. For example, as Table 7 suggests, in 2010 moderate poverty is 26.5 percent for households with microenterprises compared to 35.1 percent for those who do not have a microenterprise activity. Extreme poverty follows the same trend.

This leads us to ask whether participation in a microenterprise activity indeed causes income and expenditure to rise and poverty to fall. The relationships reported in Table 7 are not causal in the sense that it is not clear whether income or expenditure have increased because of

> 6 The calculation of moderate poverty is based on the official poverty line, which includes the food poverty line and an allowance for nonfood expenditures. The food poverty line is calculated by estimating the cost of a food basket needed to maintain the per capita daily caloric requirement
<!-- Start of picture text --> Gas Telecom Electricity<br>Trade Transportation Finance<br>2000 2002 2004 2006 2008<br>Other services Water<br>2000 2002 2004 2006 2008 2000 2002 2004 2006 2008<br>4<br>3<br>2<br>1<br>4<br>3<br>2<br>1<br>4<br>3<br>2<br>Indices of infrastructure and services reforms<br>1<br><!-- End of picture text --> Notes: The progress of reforms in infrastructure and services is based on EBRD indeces of infrastructure and transition indicators. Mapping from EBRD indices to services sub-sectors is dicussed in Appendix. Progress of reforms in Gas sub-sector is based on the index for Gas sector developed by Institute of Economic Research which is compatible with EBRD index by methodology and scale. Other services category includes business services, hotels and restaurants, real estate, rent, information technologies, research and development Figure 2: Services sub-sectors liberalization in Ukraine in 2000-2009 9
Policy Research Working Paper 10620

# **Abstract**

The lack of comparable urban definitions across countries has presented a significant challenge in effectively addressing poverty in both urban and rural areas. This study aims to tackle this issue by comparing subnational poverty statistics across countries, integrating internationally consistent definitions of urban areas into the World Bank’s official global poverty measurement framework. Focusing primarily on 16 Sub-Saharan African countries, the analysis reveals that poverty rates tend to be lower in densely populated urban areas. However, the findings also highlight that urban areas have a higher concentration of impoverished populations than previously estimated. These results underscore the importance of employing consistent urban definitions in cross-country poverty analysis and call for a reevaluation of geographically targeted policies to expedite poverty reduction efforts.

This paper is a product of the Urban, Disaster Risk Management, Resilience and Land Global Practice and the Poverty and Equity Global Practice.. 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 snakamura@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
markets through advised bans on share tenancy and limits on cash rental fees. From a theoretical point of view, the expected impact would be ambiguous. On the one hand, there is a negative direct effect as prohibition of tenant eviction precludes the landlord from using the threat of eviction as a device to elicit higher effort by the tenant and would therefore be expected to reduce productivity. On the other hand, the reallocation of bargaining power in favor of the tenant would increase incentives to supply effort and thus productivity. While one would expect the adverse incentive effect to dominate at low wealth levels, the positive effect would be dominant for farmers with intermediate wealth(Banerjeeand Ghatak, 1997).

Empirically, district level data from West Bengal suggest that effective implementation of tenancy registration which protected tenants from being evicted and fixed an upper ceiling for rent yielded significant productivity gains of about 40% - larger than the static loss estimated by Shaban (Banerjee and Ghatak, 1997). While this suggests that tenancy reforms can be effective, one should not forget that the study area is thie only state in India where regulation of tenancy was actually implemented, that costs of implementation need to be considered in making an assessment of the economic benefits from such a measure, and that tenancy reform may not have been the only alternative available.

Regulatory interventions such as tenancy regulation lead to reduced investment incentives on the part of the landlord, while tenants may not perceive sufficient security to invest at what would be a socially optimal level. The trade-off between the positive effect of greater security to tenants and the investment incentives of owners is not easily balanced. Therefore, scarce financial and administrative resources might be better spent in efforts to foster general pro-poor development (e.g. education, infrastructure, credit and insurance, markets, and off-farm employment opportunities) that improve the bargaining position of would-be tenants, and that facilitate more fixed rent contracts, than in trying to enforce tenancy regulations. The difficulty of striking such a balance is illustrated by the fact that,
realities of agricultural production and a sound suspicion against the ability of small-scale cultivators to manage on their own. let alone to be able to increase productivity (Barraclough 1970).

- '° The importance of political factors is also evident from a number of Eastern European countries where political constraints generally led to a relatively "inefficienf' way of implementing land reform -through physical restitution of plots rather than compensation of former owners through fungible cash payments (Swinnen, 1997).

- " Despite attempts to limit beneficiary desertion through imposition of legal restrictions and severe punishment in case of contravention, there is considerable anecdotal evidence on land sales by reform beneficiaries in Nicaragua, Colombia, and El Salvador. In a recent Census of Brazilian land reform settlements, only about 60% of land reform beneficiaries were actually found tilling their land.

6
ANGOLA’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE Rosnes, Orvika, and Haakon Vennemo. 2009. ―Powering Up: Costing Power Infrastructure Spending Needs in Sub-Saharan Africa.‖ AICD Background Paper 5, Africa Region, World Bank, Washington, DC.

- Briceño-Garmendia, Cecilia and Shkaratan, Maria. 2010. ―Power Tariffs: Caught between Cost-Recovery and Affordability.‖  Policy Research Working Paper forthcoming, World Bank, Washington DC

- World Bank. 2010a. _Angola: Electricity Dialogue_ . Back to the Office Report, World Bank, Washington, DC,  March 15–26.

# ———. 2010b. _Angola Enterprise Surveys 2010_ .

- www.enterprisesurveys.org/ExploreEconomies/?economyid=142&year=2009.

- ———. 2010c. ―Getting Electricity: A Pilot Indicator Set from the Doing Business Project.‖ <u>http://doingbusiness.org/data/exploretopics/getting-electricity.</u>

# Transport

- Bofinger, Heinrich C. 2009. ―An Unsteady Course: Growth and Challenges in Africa’s Air Transport Industry.‖ AICD Background Paper 16, Africa Region, World Bank, Washington, DC.

- Bullock, Richard. 2009. ―Off Track: Sub-Saharan African Railways.‖ AICD Background Paper 17, Africa Region, World Bank, Washington, DC.

- Carruthers, Robin, Ranga Rajan Krishnamani, and Siobhan Murray. 2009. ―Improving Connectivity: Investing in Transport Infrastructure in Sub-Saharan Africa.‖ AICD Background Paper 7, Africa Region, World Bank, Washington, DC.

- Curtis, Barney. 2009. ―The Chirundu Border Post: Detailed Monitoring of Transit Times.‖ SSATP Discussion Paper No. 10, Regional Integration and Transport—RIT Series, Africa Region, World Bank, Washington, DC.

- Gwilliam, Ken, Vivien Foster, Rodrigo Archondo-Callao, Cecilia Briceño-Garmendia, Alberto Nogales, and Kavita Sethi. 2008. ―The Burden of Maintenance: Roads in Sub-Saharan Africa.‖ AICD Background Paper 14, Africa
. We use three measures as proxies for trade exposure. First, firms located close to ports may have been more exposed to trade competition prior to the reforms, or may have been more affected by trade liberalization. We create a dummy variable that is equal to one if a stateindustry group is located in a state with a port, zero otherwise. We also develop measures of the extent to which particular industries might have been more or less exposed to competition from imports, or to foreign markets through exports. To so do, we use data from the COMTRADE database to estimate total exports and total imports for each industry in 1990. We then calculate

> 20The samples we use are restricted to states for which we have data on labor regulations, and are therefore smaller than the baseline sample.

25
and type of address (house, apartment or other) for addresses owned by the survey’s respondents. The estimated coefficients were applied to the same variables of the PNAD-C for the group of homeowners.

**Indirect taxes.** To estimate indirect taxes, we use the estimates from Lara Ibarra et al. (2021) based on the POF survey. To impute the results in PNAD-C, we create a tax burden share (tax burden/consumption) in POF and calculate different measures of the average tax burden shares. These average shares were then smoothed using a _lowess_ estimation. Different options were evaluated: using percentiles of disposable income, percentiles of disposable income by urban and rural, percentiles of tax burden for each group by urban and rural population, and percentiles of tax burden statewide. We opted for using the tax share burden by disposable income per capita percentile in urban and rural zones because it offers a better estimation than the national percentile. The results were comparable to alternative options and, importantly, alternative imputations yield qualitatively similar results. 20F<sup>21</sup> The smoothed tax burden shares were then multiplied by disposable income in PNAD-C. 21F<sup>22</sup>

It should be noted that the range of indirect tax burden is wide. For example, for the tax burden as a ratio to disposable income, the interquartile range is nine, and the difference between the max and minimum is around 39 percentage points. This broad range results from estimating the tax burden from a composite measure of different indirect taxes, with distinct tax bases, rates, and disparate patterns of taxable consumptions according to income. However, the average by decile and urban/rural resulted in a share of outliers (outside the range of the mean +/- two standard deviations) that corresponds to less than 5 percent of the observations.

Table 1 presents the set of taxes and contributions in Brazil in 2019 and indicates whether each of them was included in the analysis. Most policies
BURKINA FASO’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE

# Roads

## **Achievements**

Burkina’s 15,202 km of classified road network length seems, in general, adequately designed given the level of traffic and the connectivity it provides; it is also, for the most part, in good condition. Even if Burkina Faso’s classified road density indicators look relatively low by some standards, the classified network provides basic regional, national, and international connectivity, linking Ouagadougou to international border crossings and provincial capitals in the interior (table 5).

**Table 5. Burkina Faso’s road indicators benchmarked against Africa’s low- and middle-income countries**

||Unit|Low-<br>income<br>countries|**Burkina**<br>**Faso**|Middle-<br>income<br>countries|
|---|---|---|---|---|
|Total road density|km/1,000 km<sup>2</sup>of arable land|132.1|**81.5**|318.4|
|Classified road density|km/1,000 km<sup>2</sup>of arable land|88.2|**55.6**|278.4|
|Rural accessibility index—household<br>survey|% of rural population within 2 km of all-season road|34.1|**25.0**|62.7|
|GIS rural accessibility|% of rural population within 2 km of all-season road|23.1|**23.7**|31.5|
|Paved road traffic|Average annual daily traffic|1,341.1|**867.7**|3,797.7|
|Unpaved road traffic|Average annual daily traffic|38.5|
# **4. DATA**

# **4.1. EXPORT DATA**

The principal trade data source is the BACI World trade database developed by CEPII, created using COMTRADE. BACI data from 1995 to 2009 are used for this exercise. In total, 20 MENA countries and 136 countries from other regions are covered (see Table 6 for a list of MENA countries). One advantage of the BACI to the COMTRADE is that exporter and importer declarations have been checked for gross inconsistencies. The version used is aggregated at the country-sector level, where sectors are defined by the ISIC 2-digit level. It is important to be clear that there is no information on exporter characteristics in this database such as age, legal status, ownership, share of exports over total sales, or employment levels. Moreover, this study cannot answer why some firms export and others do not, or what are the determinants of becoming an exporter.

The World Bank’s Export Dynamics Database (EDD) is also used as a second source of customs data. The EDD includes exporting data from 1997-2011, but analysis is limited to 2005-2010 since data are available for the majority of countries during this period only. All agricultural and extractive industries are excluded. The EDD’s country coverage is narrower than BACI’s, however EDD comprises additional information in terms of mean and median export value per exporter, which allows consideration of the intensive margin of trade. The full EDD data set comprises 43 countries, 7 of which are in the MENA region. Kuwait is the only high-income MENA country in the EDD. Egypt, Morocco, and Yemen are lower-middle-income, and Iran, Jordan, and Lebanon are upper-middle-income. Depending on our level of analysis and availability of control or business climate variables, MENA coverage ranges from three countries to seven countries.

# **4.2. DEPENDENT VARIABLES**

The share of total exports in a given sector is calculated per industry for every country and every sector using the BACI. Trade
A recent paper by Berlinski and Galiani (2005) analyzes the impact of a large program to construct pre-school facilities in Argentina in the 1990s on pre-primary school attendance and maternal labor supply. The intensity of the program varied by region, and Berlinski and Galiani use a differences in differences framework to identify program impact. The estimation also includes cohort and region dummies to control for nationwide trends and level differences across regions. The identifying assumption is therefore that regions that received more preschool facilities would not have had different growth rates in enrollment in the absence of the construction program. (Berlinski and Galiani provide evidence that this is a reasonable assumption.) Berlinski and Galiani conclude that the program had a large, positive impact on preschool enrollment—indeed, they cannot reject the null hypothesis that all new preprimary school slots were taken up by children who would otherwise not have been in school. The authors take this as strong evidence for a supply constraint on preschool enrollment in Argentina.

A follow-up paper by Berlinski et al. (2005) analyzes the impact of the preschool construction program on test performance in Spanish and mathematics in third grade. The analysis provides compelling evidence of significant program impacts. Intent-to-treat estimates show that children in cohorts and regions exposed to the construction program have significantly higher test scores. Preschool participants also appear to perform better on noncognitive dimensions of development, including paying attention in class, being disciplined, and being participative, as reported by their third-grade teachers. Convincingly, Berlinski et al. provide evidence from a “placebo experiment” which shows that children in these same schools in other cohorts that were not affected by the preschool construction program do not appear to have higher test performance—an important check on their identification strategy.

Various papers by Grantham-McGregor and her co-authors use data from Jamaica to analyze the short- and medium-term impact of interventions in early childhood. In one study, a lottery was used to divide a sample of stunted children ages 9-24 months into four groups: The first study group received a food supplement of 1
to the ‘special category’ (Assam and HP) possess different fiscal arrangements with the central government and receive certain fiscal privileges such as 90% of expenditure covered by the central government on centrally sponsored schemes, preferential central funds, concessional excise duties, tax exemptions, a fund for infrastructure development. These fiscal supports are included in the corresponding variables, such as capital expenditure, investment, internal debt, and per capita income.

# **3.3. Data Sources, Model Specifications, and Econometric Methodology**

**Data Sources** : A balanced data set covering 18 major Indian states over the period 2005 to 2019 has been used for this study.<sup>7</sup> Data has been compiled from various official sources such as the Reserve Bank of India, Centre for Monitoring Indian Economy, different Central Government Ministries, and Census, 2011. A detailed list of variables, definitions, period of study, and sources are presented in Table 1.<sup>8</sup>

**Table 1: Variables Name, Definition, and Sources**

|**Index/Variable**|**Definition**|**Period of Study**|**Sources**|
|---|---|---|---|
|**_Physical Infrastructure_**||||
|Road density (sq. km (Road)|The ratio of the State’s total road<br>length to land area|2005 to 2019*|RBI|
|Rail density (sq. km (Rail)|The ratio of the State's<br>total rail network to the State’s land<br>area|2005 to 2019|RBI|
|Telecom Density (TEL)|_Telephone_(fixed-line plus mobile)<br>connections per 100 people|2005 to 2019|RBI|
|Per Capita Installed power<br>capacity (KW) (
spillovers in Morocco, which was attributed to possible adverse effects of increased competition offsetting positive spillovers from FDI.

Numerous studies on horizontal FDI spillovers have followed since, showing ambiguous effects of FDI on domestic productivity (see, for extensive literature reviews, Görg and Greenaway 2004; Lipsey and Sjöholm 2005; Smeets 2008, among others). In a review of 40 studies on horizontal productivity spillovers, Görg and Greenaway (2004), found that 20 studies reported statistically significant evidence of positive spillovers, while only 6 studies reported negative spillovers. However, they raised concerns over the robustness of the cross-sectional studies—almost all showed positive effects. By contrast to the 28 panel studies, only 6 studies reported positive spillovers, while 4 studies reported negative spillovers, and the large majority (18 studies) showed ambiguous results. Indeed, Paus and Gallagher (2008) concluded in their literature overview that regressions based on cross-sectional data tend to find positive spillovers, while those based on panel data are more likely to find negative spillovers.

In a seminal study using panel data for Lithuania, Javorcik (2004a) shifted the focus to vertical spillovers and introduced a measure of backward and forward spillovers based on input-output data, which has been widely used since. Besides finding positive horizontal spillovers, Javorcik (2004a) confirmed positive backward spillovers, but rejected the existence of forward spillovers. Since then, there has been a “virtual explosion of studies on vertical spillovers” (Havranek and Irsova 2011, p.1), including Blalock and Gertler’s (2008) widely cited study on Indonesian manufacturing firms that confirms the positive backward spillovers. In a comprehensive meta-analysis, Havranek and Irsova (2011) took into account 3,626 estimates from 55 studies on vertical spillovers, and found evidence of positive and economically important backward spillovers from multinationals to local suppliers in upstream sectors and smaller positive effects to local customers in downstream sectors. However, the authors rejected the existence of horizontal FDI spillovers. The findings suggest that a 10-percentage-point increase in foreign presence increases