rafmacalaba/datause-encoder-data huggingface dataset:
# **1. Introduction**

In an effort to improve the effectiveness of efforts at reducing poverty, programs that fall under the broad rubric of “community driven development” (CDD) have recently seen tremendous expansion. The amount of World Bank loans under this category alone is estimated to have increased from US$ 0.3 billion per year in the late 1990s to some US$ 7 billion annually in 2006 (Mansuri and Rao 2004, Mansuri and Rao 2007). As a result, CDD is now applied in areas ranging from delivery of agricultural technology and inputs to health care, education, micro-finance, and insurance. The motive for such expansion is a belief in local actors’ informational advantages regarding local needs and their ability to monitor outcomes at lower cost. However, especially in stratified societies with few countervailing institutional arrangements, local groups’ informational advantages may be more than compensated by the dangers of elite capture. This implies that empirical assessment of the impact of such programs and the factors conducive to attaining outcomes will be desirable.

This paper focuses on a large CDD program in the Indian state of Andhra Pradesh (AP) that is innovative in combining social empowerment with micro-finance intervention. The program focuses exclusively on women and draws on self-help groups (SHGs) as the primary channel for delivering interventions. To do so, it builds on a large infrastructure of pre-existing SHGs that largely focused on micro-credit that was established in the state during the 1990s. To expand coverage of the poor and generate synergies between social and economic development, SHGs’ traditional focus on micro-credit is complemented by an emphasis on empowering women socially and economically. The first step in doing so, which is a focus of the evaluation in this paper, is to foster formation of SHGs by targeting the “leftover poor”. This is to be followed by efforts to build the capacity of existing SHGs, and establishment of second tier institutions at the village and mandal (county) levels to capitalize on economies of scale in capacity building, credit and insurance, and to ensure that public programs reach the poor.

We aim to evaluate the impact of the program at the household level. To do justice to program objectives, we consider economic and non-economic outcomes. We draw on a 2004 survey of more than 6,000 households in program districts where the program became available in 2001 and control districts where it became available in late 2003. Our data provide rich information on female empowerment, nutritional status, consumption, income, and assets that can be used as measures of the economic and social impacts of the program.

Methodologically, we combine three elements, namely (i) a pipeline setting to create groups that are arguably comparable in unobservables; (ii) propensity score matching on observables over an appropriate 1
Policy Research Working Paper 10871

# Measuring Poverty in Tanzania

Comparison of Diary and Recall Approaches to Food Consumption Data Collection _Akuffo Amankwah Darcey Jeanne Genou Johnson Josephine Ofori Adofo Maryam Gul Amparo Palacios-Lopez_ Development Economics Development Data Group August 2024 A verified reproducibility package for this paper is available at http://reproducibility.worldbank.org, click **here** for direct access.
# **1. Introduction**

Afghanistan, like many countries affected by fragility, conflict and violence (FCV), represents an extreme case where firms face a plethora of business risks in a deeply uncertain environment together with largely undeveloped financial markets. Still, the state of investment in Afghanistan stands out among the fragile situations. According to the World Bank Enterprise Surveys, only 27.5 percent of the firms in the country reported undertaking any investment projects compared to 40 percent in Burundi, 43 percent in the Democratic Republic of Congo (DRC) and 36.5 percent in West Bank and Gaza (WBG).<sup>3</sup> Concurrently, the standard of financial development in Afghanistan remains weak with humble financial intermediation. In 2015, only 3.7 percent of GDP was intermediated as loans from banks to the private sector. The weakness of the financial system is reflected in the fact that out of every five firms undertaking any investment, four rely exclusively on internal funds or retained earnings for any investment related expenditure. A paltry 3 percent of firms use bank loans to finance their investment. The almost complete reliance of firms on internal resources is remarkable even across fragile situations. In contrast, around 40 percent of firms report using bank loans for the median country in the broad FCV sample (figure 1). In addition to being burdened by the weak financial situation, firms in Afghanistan also navigate through a sea of business risks emanating from macroeconomic (for example price and exchange rate volatility), political and security-related uncertainties.

**Figure 1: Share of Investing Firms Using Bank Loans: Fragile Situations**<sup>**4**</sup>

<!-- Start of picture text --> 45<br>40<br>35<br>30<br>25<br>20<br>15<br>10<br>5<br>Bank Loans (%) 0<br>Share of Investing Firms using<br>AFG (2014) MMR (2014) SSD (2014) COD (2013) IRQ (2011) ZWE (2011) MDG (2013) CAF (2011) SLB (2015) KOS (2013) BDI (2014) PNG (2015)<br><!-- End of picture text -->

> 3 The aggregates correspond to 2014 for Afghanistan and Burundi, whereas in case of DRC and WBG they are computed using the 2013 data.

> 4Sample contains 12 countries that feature in the World Bank's <u>List of Fragile Situations FY17 (World Bank (2017)) and for whom</u> the Enterprise Survey data are available for any year beginning 2011. Our broad classification of all fragile situations under a common umbrella masks significant variation in level of fragility across this group. Many development measures, including economic development, vary across this group and can partially account for the variation in financial development observed within this group.

2
Labor market integration studies follow the product and capital market integration literature in the sense that studies use three similar metrics. Differences in absolute levels of wages, covariation of wages over time, and the convergence of wages back to equilibrium differentials all appear as metrics of labor market integration. Rothenberg (1988) connects labor market integration with wage rate dispersion. Rosenbloom (1989, 1995) uses the differences in wage levels when measuring the labor market integration. Allen (1990) uses real wage convergence to analyze how tightly integrated labor markets were between regions that sent and received migrants. O’Rourke (1993) uses both the co-variation of wages in different countries over time and the convergence of wage levels. Robertson (2000) uses both the co-variation and convergence of wages and finds that U.S. and Mexican labor markets were integrated even before the North American Free Trade Agreement (NAFTA).

# **B. Theoretical Framework**

Three measures have emerged as the main measures of labor market integration. The first is the difference in absolute wage levels. The second is the co-movement of wages over time. The third is the rate of convergence back to an equilibrium differential. All of these measures focus on the wage differential between two countries for similar workers. Although it is well-known that the trade-theoretic prediction of Factor Price Equalization rarely holds, we present measures of the size of differentials between countries to illustrate and motivate the additional two measures. We posit that the difference in absolute wage levels differential is a function of labor-market integration following Robertson (2000).

Consider an economy composed of two countries (“A” and “B”). We assume that labor in the two countries are price substitutes, such that an increase in the wages of “A” workers increases 7 | P a g e
# _3.2 Descriptive statistics, shocks, and balance_

Table 1 presents baseline descriptive statistics for some key variables in control and treatment villages for the full sample (column 1 and 2), and for the sample of households with predicted (baseline) PMT scores below the program selection threshold (column 4 and 5). Both the full sample and the sample below the (predicted) PMT threshold are very poor, with per capita consumption below 332 CFA per day (0.57 USD). Average livestock herd size is also relatively small (1.58 Tropical Livestock Units, TLU, in the control group). Virtually all households engage in agriculture, with an average land area of 3.75 ha in the control group. Renting or renting out land is rare (0.17 ha and 0.11 ha on average respectively, in the control group). _Tontine_ (ROSCA) participation rates are relatively low (12%) but involvement in household enterprises is widespread (68% in control group). Households are large (average of 8.5 members) and household heads have less than one year of education on average.

Column 3 and 6 show the result of balance tests for the respective samples. Overall, there are few significant differences across groups. The treatment and control groups are well balanced, including below the predicted PMT threshold.

We define drought shocks based on rainfall in June 2014, i.e. at the start of the main planting season the year preceding the follow-up survey. Using the AFDM data, we compute for each village the historical average rainfall in June (for years 1970-2011) as well as the rainfall deficit in June 2014 (the difference between the June 2014 rainfall and the historical average). We define our main shock variable as rainfall below the 20<sup>th</sup> percentile of the historical distribution. We define shocks similarly for years 2011, 2012 and 2013. Shocks in 2014 (prior to our followup survey) are not correlated with shocks the previous years (2011-2013) defined in a similar manner. Shocks are spatially dispersed across and within regions, although more frequent in the Maradi region.<sup>22</sup> 794 households (20.9%) and 111 villages-hamlets (21.7%) are categorized as exposed to a shock during the main agricultural season before the follow-up survey. We also define alternative measures of shocks based on each percentile of rainfall deficits. We focus on

> 22 There is no heterogeneity in our results across region (available upon request), so that regional effects are not driving our results.

14
<!-- Start of picture text --> Impact of floods on the family in 2010 and after (% Impact of floods on the assets in 2010 and after (% of<br>of HHs) HHs)<br>ho impact SS ho impact a<br><!-- End of picture text --> <!-- Start of picture text -->
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Policy Research Working Paper 9130

# **Abstract**

This paper analyzes the welfare and distributional impacts of increasing taxes on cigarettes in Georgia. Increasing taxes on tobacco is an effective measure to reduce smoking. According to some estimates, increasing tobacco taxes could save more than GEL 3.6 billion and 53 thousand lives over a 15-year period. However, concerns over potentially regressive effects on the poor are often raised. An Extended Cost Benefit Analysis (ECBA) is applied to simulate the welfare and distributional impacts of raising prices on cigarettes. Decile-specific price elasticities of demand are estimated to account for heterogenous behavioral responses of different income groups. Empirical estimations confirm that poorer households in Georgia tend to reduce consumption more intensely when faced with higher tobacco prices. The estimated magnitude and distribution of elasticities are comparable to peer countries. The simulations based on household survey data suggest that the long-term net distributional effects of increasing taxes on cigarettes in Georgia are likely progressive. Incorporating the indirect benefits of reduced smoking—reductions in medical expenses and earnings from adverted premature deaths—could bring small, albeit positive, income gains for large sectors of the population. The magnitude of those benefits is most significant among lower-income households, potentially contributing to lift them out of poverty.

This paper is a product of 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 afuchs@worldbank.org and mgonzalezicaza@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
<!-- Start of picture text --> Real Credit Growth<br>100.0%<br>80.0%<br>P Stanbic<br>60.0%<br>E<br>R 40.0%<br>UCB<br>C<br>20.0%<br>E<br>N 0.0% UCB+Stanbic<br>T -20.0%1 996 1998 2000 2002 20 04 (Virtual)<br>Sector<br>-40.0%<br>-60.0%<br>-80.0%<br><!-- End of picture text -->

**Figure 4**

Regression models in Table 5 also indicate some credit growth since the privatization to Stanbic. Model 1 indicates that UCB’s real credit growth was significantly slower than that of other banks, whereas Stanbic’s credit growth was not significantly different from other banks before or after the acquisition. The insignificant coefficient for Stanbic after the acquisition could be seen as a sign of improvement in that UCB’s sluggish preprivatization lending had been overcome. Recall however that UCB’s sluggish lending was largely due to BOU restrictions. These results, therefore, could be seen as a return to normal operations for the UCB portion of the merged entity.

Model 3, which describes the lending behavior of the composite bank, reinforces conclusions drawn from Model 1. Prior to the acquisition, the composite bank had significantly slower credit growth than other Ugandan banks. In the year of the privatization, that changed. Although the “Stanbic at Privatization” coefficient is insignificant, it is positive and similar in magnitude to that of the “UCB+Stanbic” coefficient. To assess Stanbic’s postprivatization credit growth relative to other banks, those two coefficients must be evaluated jointly. When summed, they are not significantly different from zero, which indicates that Stanbic credit growth improved to the sector average (ceteris paribus). The quarters since privatization coefficient is near zero and insignificant, indicating that the improvement in credit growth has been 16
- 9 -

m is a dummy variable that takes a value of unity if an NTB is applied to the item in year m and zero otherwise. 9/ If N and m are zero the index is based on current trade values, otherwise it is expressed in a base year trade weights. Holding n constant and varying m will measure the effects of changes in protection with constant trade weights. In the present analysis, however, _-_ we employ current year trade weights (i.e., m N) given the major structural changes that occurred in the developed countries over 1966-1986.

Before turning to the empirical results, it would be useful to consider some of the ways pressures for protection differed between the 1960a and 19809. In the 19609, rapid market penetration by "newly industrialized" developing countries was a problem in the textile and clothing sector, but was not yet a major factor in most other labor intensive industries. 10/ Pressures for protection in the 1970s and 1980s would be heightened by a rapid

- 2/ This measure suffers from the familiar problem of any "own" trade weighted index in that products facing very restrictive NTBs will enter the calculation with zero or low weights. There have been attempts to reduce this source of bias in aggregate data through the use of "world" trade weights, but factors such as demand differences or A high degree of sectorial correlation in OECD protection make this approach suspect. Also, equation (2) tells nothing about the "restrictiveness" of NTBs, but merely how much actual trade encounters these measures. While recent applications of equation (2) are based on tariff line level records of NTBs and trade data, we have utilized Walter's concept of "affected" products for the empirical analysis in this study. That is, the coverage ratios in this report show the value of trade in "affected" four-digit SITC products as a percentage of total imports.

- 10/ It could be argued that conditions for a trade liberalization were more favorable in the 1960s then they are at present. Many restraints were starting to be lifted in the late 1950s and early 1960s as world economic growth and low rates of unemployment lent a sense of prosperity to the scene. The Kennedy Round, concluded in 1966, was the most extensive multilateral trade negotiation since the inception of CATT and had achieved a major reduction in tariffs. Exchange rates were fixed and currencies were convertible. Countries like the United Kingdom had to resort to import surcharges for balance of payment (BOP) reasons but by and large the widespread use of post-war nontariff barriers for BOP reasons and exchange controls had largely ceased in the industrial countries.
**Table 6: Changes in agricultural income: fixed effects**

||All|Bottom 40|All|Bottom 40|
|---|---|---|---|---|
||households|percent|households|percent|
|**Farming practices**|||||
|Total area planted self-reported, in Ha|0.00734**|0.00846|||
||(0.00313)|(0.00674)|||
|Renter (land)|0.0682|-0.0343|||
||(0.126)|(0.189)|||
|Used of fertilizer|0.0846|0.217**|||
||(0.0523)|(0.0904)|||
|Use of pesticides|0.149***|0.147**|||
||(0.0479)|(0.0695)|||
|Used improved seeds/seedlings|<br>0.0238|<br>0.0407|||
||(0.0549)|(0.0760)|||
|Hired labor used|0.148***|0.209***|||
||(0.0475)|(0.0653)|||
|Log of number of days of family labor|0.173***|0.231***|||
||(0.0343)|(0.0476)|||
|**Access to markets and services**|||||
|Distance to output market (km)|-0.00613|-0.00747|||
||(0.0194)|(0.0304)|||
|Any extension in village in past 12 months|0.0600|-0.00359|||
||(0.0457)|(0.0726)|||
|**External environment**|||||
|Log of rainfall (percent of needs measured by WRSI)|0.986***<br>(0.196)|1.356***<br>(0.280)|1.886***<br>(0.343)|2.417***<br>(0.506)|
|Log of maize price|0.446***|0.544***|0.492***|0.715***|
||(0.0674)|(0.0970)|(0.0840)|(0.113)|
|Log of beans price|0.922***|1.295***|1.091***|1.247***|
||(0.143)|(0.213)|(0.155)|(0.214)|
|Log of number of fatalities|<br>0.00849|<br>0.0406|<br>-0.146***|<br>-0.187***|
||(0.0413)|(0.0577)|(0.0515)|(0.0662)|
|Constant|<br>-2.048|<br>-7.283***|<br>-6.619***|<br>-11.48***|
||(1.521)|(2.252)|(2.010)|(2.818)|
|Observations|5,145|2,501|6,852|3,334|
|Number of HHID<br>Source: Staff calculations using UNPS 2006-2012. Note:<br>income. Robust standard errors in parentheses*** p<0.01,|1,806<br>Dependent va<br>** p<0.05, *|871<br>riables is log<br>p<0.1|2,044<br>of real per ca|966<br>pita crop|

19
**Figure 2. Structure of Budget Revenue in Mali and Niger, 2014**

<!-- Start of picture text --> 31.2<br>26.4<br>24.4 23.7<br>15.5 16 16.3<br>9 8.7<br>5 4.4 7.2 6.5 5.7<br>Wages and Other direct Taxes on Goods Other indirect<br>Salary Taxes taxes and Services taxes<br>Personal and corporate taxes Indirect taxes Other taxes Non taxes Grants and<br>revenue others<br>Mali Niger<br>Source : Authors<br><!-- End of picture text --> The analysis of spending begins with measurement of the incidence of public spending on education, health, and targeted social programs. It also includes the effects of specific subsidies for electricity and liquefied petroleum gas (in Mali) and agricultural subsidies (in both countries). The social spending considered accounted for approximately 30 percent of total government expenditures in 2014 in Mali and 27 percent in Niger (Appendix B). The method for analyzing public expenditure generally comprises three stages. First, the value of the unit costs of the public expenditure or subsidy is estimated. Second, coverage of the spending or subsidies is identified and allocated to users or beneficiaries. Third, the results are aggregated and presented, showing the magnitude of public spending relative to household spending and income broken down according to quantile.

# **3. Distribution of Taxes and Transfers**

# _Direct Taxes: WST_

Direct taxes included in this analysis are the WST, a monthly tax on gross salaries of people employed in the formal sector. A person is working in the formal sector if he or she is entitled to annual paid leave, sick leave, or a retirement pension as an employment benefit. In Mali, wage earners who are employed by private and public organizations pay the WST, whereas in Niger, international organizations and family employees are exempted from the WST.

The richest individuals pay most of the direct taxes in both countries. The share of direct taxes increases with market income decile (figure 3.a). The richest individuals in Mali and Niger pay nearly all the direct taxes collected (figure 3.b). The richest decile pays more than 75 percent of total direct taxes in Mali and 95 percent in Niger, whereas the three bottom deciles pay less than 2 percent of total direct taxes (0.54 percent in Mali, 0.09 percent in Niger). These findings indicate 5