rafmacalaba/data-use-mentions-extended huggingface dataset:
**Figure 2: Patterns in intermediate input sourcing at the aggregate level**

<!-- Start of picture text --> Share of VA + domestic inputs Breakdown of imported inputs in<br>manufacturing<br>1.00 0.50<br>0.95 0.40<br>0.90 0.30<br>0.85 0.20<br>0.80 0.10<br>0.75 0.00<br>1995 2005 2015 EU ROW SSA CHINA OAF USA<br>Manufacturing Agriculture 1995 2005<br>Aggregate Aggregate 2015 Aggregate (2015)<br><!-- End of picture text --> Notes: Own calculations based on the EORA data.

Perhaps surprising is the small and declining share of parts sourced from the United States, which in 2015 only accounted for 2.3% of imported inputs and 0.3% of the full output value. However, this is very much in line with its low importance for the majority of countries in the region. Other African countries (OAF) are much less important for Rwanda than for the average country in the region, but that is intuitive given its relatively large distance from both South Africa and the Northern African countries.

From the information in the rows of the country-specific input-output table for Rwanda, we can learn where its firms sell their output. In Figure 3 we show the results for manufacturing products. On the left, we see that domestic sales in the form of intermediate inputs to other sectors is the most important category, but its importance has gone down over time. The second most important category are domestic sales to final demand, which has picked up the share lost by domestic intermediate input use. In 2015, these two components absorb 57% and 41% of manufacturing output, while only a paltry 2% is exported.

The panel on the right shows exports, but note that the scale of this graph
of households that had their outstanding balance cancelled entirely declined by between Rs 24,000 (US$ 470) and Rs 26,000 (US$ 508), or approximately 30% of the pre-treatment mean of overall household debt.<sup>18</sup> These estimates remain stable and statistically significant in alternative samples and are robust to the inclusion of additional controls and bank and district fixed effects. Given that households were surveyed approximately one and a-half years, or two

> 18Note that if there is measurement error in recall data, this would likely lead to downward bias in estimates of the change of overall indebtedness, so that the true effect of debt relief may be larger than the reported point estimates.

18
, 1985.

- **Kleven, Henrik Jacobsen, Martin B. Knudsen, Claus Thustrup Kreiner, Søren Pedersen, and Emmanuel Saez** , “Unwilling or Unable to Cheat? Evidence From a Tax Audit Experiment in Denmark,” _Econometrica_ , 05 2011, _79_ (3), 651–692.

- **Lovics, G ́abor, Katalin Szoke, Csaba G. T ́oth, and B ́alint V ́an** , “The effect of the introduction of online cash registers on reported turnover in Hungary,” Working Paper, Ministry of Finance Hungary 2019.

- **Medina, Leandro and Friedrich Schneider** , “Shadow economies around the world: what did we learn over the last 20 years?,” _IMF Working Papers_ , 2018.

24
points of production and consumption can be large. Marketing costs also vary depending on whether the product is imported, exported, or domestically produced and marketed.

Almost all Mozambican households have some money income, either from goods sales or from factor remunerations. This income is used for purchases of essential goods that cannot be produced by the households themselves. Nevertheless, the possibility of home consumption enables households to bypass the market in so far as they can produce consumption goods themselves. The presence of high marketing margins implies the existence of significant differences between farm gate (and factory gate) sales prices, on the one hand, and prices in the commercial markets on the other hand. Rather than sell at a low price and purchase at a high price, households—particularly rural agricultural households—often opt to consume at least some of what they produce. In some cases these marketing margins are so large as to isolate the household from commercial markets altogether. Therefore, explicit modeling of the interaction between marketing costs and home consumption becomes essential for assessing important aspects of the economy. Home-consumed and market consumption of all commodities are captured in the linear expenditure system (LES) formulation mentioned above. Appropriate modeling of home consumption and marketing margins has been shown to be important (Arndt, Jensen, Robinson, and Tarp 2000).

# **2.2 The Mozambique Micro-simulation Model**

A micro-simulation model in the spirit of Chen and Ravallion (2004) is developed to examine the poverty implications of the trade liberalization scenarios analyzed. The model relies upon data from the 2002-03 Mozambican Household survey, known as IAF 2002-03 (INE 2004). The survey provides detailed information on consumption patterns 9
tropical typhoon directly passes over or nearby. The estimated wind speeds are merged to the household FIES survey at the barangay level and consumption expenditures are regressed against windspeed (or a related damage index) and socioeconomic household characteristics. The paper shows that different specifications of typhoon effects have negative impacts on consumption levels, especially food. The estimated coefficients from the regression model are then used to estimate _ex-ante_ household vulnerability to poverty in the event of future natural disasters of different intensity.

The proposed approach applied to the case of typhoons is fully complementary to the proxymeans targeting (PMT) method used by _Listahanan_ and the 4Ps, in the sense that in addition to the chronic poor currently identified by the PMT method of the 4Ps program, it allows identification (or targeting) of the households that are likely to fall below the poverty line in the event of a natural disaster shock. The _ex-ante_ identification of those who are vulnerable to poverty combined with timely support for these households makes it possible to provide targeted support in a timely and cost-effective manner.

3
<mark>We apply the synthetic control method methodology on GDP per capita, poverty headcounts and a set of proxy variables for elements of multi-dimensional poverty indicators to measure if and by how much they are affected by sovereign defaults.</mark> <mark>We find that, on average, within three years of a sovereign default, the affected economies have fallen behind by a cumulative 8 percent of GDP p.c. relative to the synthetic counterfactual. Whereas growth slows down the year prior to default, a large part of the effect is driven by GDP p.c. growth of the defaulting country falling 3.6 (2.4) percentage-points behind the counterfactual in the year of default (one year after default). On average, sovereigns recover to the pre-default GDP p.c. peak four years after default.</mark> _<mark>Recovery</mark>_ <mark>defined in this manner, however, does not preclude serious scarring: Over the decade post default, the structural effect on growth leads to a deficit of around 1.5% per year. After one decade, defaulters’ economic output per capita is nearly 17% or one-sixth below the output reached by the non-defaulting counterfactual. We also show that the costs are larger for longer default episodes. To render a comparison with existing findings in the literature easier, we apply our methodology to the same sample used in leading prior works (namely Borenzstein and Panizza 2009). Allowing for time-variant effects leads to significantly larger and more long-lasting effects of default on GDP growth.</mark> <mark>Still, output has been criticized as a measure of welfare because, among other things, it can ignore the distribution of income (See e.g. Fleurbaey 2009; Stiglitz, Durand & Fitoussi 2018;</mark> <u><mark>Aitken 2020). This paper offers initial elucidation on</mark></u> _<mark>the
Before the intervention, I collected self-reported data on personal and family characteristics from enrolled students. Follow-up self-reported data included questions to measure the intervention’s impact on attitudes, violence, and crime as well as enrolled children’s exposure to risky spaces. I combined this self-reported information with neurophysiological evidence, particularly measures of stress and emotional regulation, from a random subsample of enrolled students. I used low-cost, portable electroencephalograms within an in-field lab setting. Finally, I also collected administrative records on grades, behavioral reports, and absenteeism data from the students. Schools provided these data before and after the intervention.

I report three sets of results. First, when I compare both types of group composition, integration is better than segregation. Results show that, on average, improvements in attitudes and misbehavior at school are larger when participants are in more diverse groups than when they are segregated. This is true for both high- and low-violence children. These results align with the evidence that interactions with diverse peers can generate differences in the learning experience (Lafortune et al., 2016).<sup>7</sup> In this sense, students in heterogeneous groups have the opportunity for exposure to both good behaviors they should follow and negative ones they should reject. These interactions are less available for students in the homogeneous group. In terms of neurophysiological outcomes, I find that students exposed to similar peers in terms of violence—that is, assigned to homogeneous groups—have stress levels greater than those of students placed in a heterogeneous setting. The increase in stress is particularly great for children treated in a homogeneous and highly violent group versus comparable children treated in heterogeneous groups.

Second, I studied tracking effects on marginal students, who are just above or below the median of the propensity distribution function within each stratum. By virtue of my design, very similar students around this cutoff were assigned either to homogeneous highly or less violent groups. By

> 7Alternatively, these results support the rainbow model of peer effects, whereby
bondholders accepted the offer.<sup>38</sup> The government then resumed payment on debt – except for the holdout debt—and sovereign spreads dropped from the astronomical levels (over 5000 basis points) that prevailed during the payment moratorium period.

During 2005, the government still faced financing constraints. In order to close a financing gap of $6.5 billion, the government resorted to extraordinary financing sources, “....including placing public-sector bonds with the tax collection agency ( _Administración Federal de Ingresos Públicos_ , AFIP), the social security system ( _Administración Nacional de la Seguridad Social_ , ANSES) and other public sector funds holding excess liquidity. The authorities also sold bonds to the government of the República Boliviariana de Venezuela and the province of Santa Cruz” (EIU Country Report March 2006). The use of ANSES for liquidity would foreshadow later events.

In terms of international relations and macroeconomic policy, the government made an early payment of $9.6 billion to cancel its obligations to the IMF in January 2006. An Article IV Consultation was completed in July 2006, but the staff report was never published. Since then, there have been no Article IV consultations, and in this regard, Argentina is not in compliance with its membership agreement with the IMF.<sup>39</sup> Leading up to the presidential elections in October 2007, the economy was still growing at 8 percent. Inflation had been accelerating. In January, the government intervened in the national statistics agency (INDEC). Since then, there has been a credibility cloud over the official inflation data, and private agencies started publishing alternative data. With accelerating inflation, the government engaged in price control negotiations with major retailers and used export taxes to keep the supply at home of goods with rapidly rising prices.

Nestor Kirchner’s wife, Cristina Fernandez de Kirchner, won the 2007 presidential election with 45 percent of the vote, 20 percentage points ahead of the second-place candidate in a crowded field.
# **Statistical Matching for Combining the European Survey on Income and Living Conditions and the Household Budget Surveys: An Evaluation of Energy Expenditures in Bulgaria**<sup>**1**</sup>

Britta Rude Monica Robayo-April JEL classification: O13, P28, Q42, D12, C15, C52 Keywords: energy poverty, statistical matching, poverty, data fusion, imputation, EU-SILC, Bulgaria

> 1 This paper was prepared as part of the Poverty Program for Bulgaria in the World Bank's Global Poverty and Equity Practice. The study was carried out by a team composed of Mónica Robayo-Abril (Senior Economist, World Bank) and Britta Rude (Young Professional, World Bank). We thank the peer reviewer Paul Corral (Senior Economist, World Bank), for helpful comments and feedback.
and the NBS surveys starting in 2013, use residence in the household for six months of the year as the criterion for household membership.

When different criteria are applied to identify migrants, one finds different estimates related to migration. Even different waves of the same dataset cannot be used to establish migration trends if survey questions about migration, or available approaches to establishing migrant status or household membership, are not the same across survey waves (e.g., China Health and Nutrition Surveys and China Income Project Surveys). Using consistent definitions of migrant status is particularly important if the research objectives focus on estimating if and how the impacts of migration are changing over time.

Apart from residence in the household, sampling approaches for household surveys in China are also likely to have missed migrants in China’s cities until very recently. Most household surveys have used the sample frames developed by the rural and urban survey teams of the National Bureau of Statistics. A problem arises, particularly in urban areas, as sampling frames are constructed by residential structure 9
date and that there is a female learning premium. We also contribute conduct a development accounting exercise, providing a direct measure of school quality. We estimate that the role of human capital in explaining cross-country income differences ranges from a fifth to half – a middle ground in a wide-ranging literature. Moreover, we find that average estimates mask significant heterogeneity by country income status and region. This reveals the importance of including countries at all stages of economic development for understanding the role of human capital. Finally, we show that our learning database provides a measure of human capital that is more closely associated with economic growth than current education and human capital measures included in the Penn World Tables 9.0 and the Human Development Index.

This database comes at a moment when a series of global efforts have been launched to measure and track learning on a global scale. While recent modelling suggests the world is on track to achieve universal primary enrollment by 2030 (Friedman et al. 2020), if learning continues to stagnate this achievement will be partial. In recognition of this, the Sustainable Development Goals (SDGs) include a focus on learning whereas the Millennium Development Goals focused largely on schooling. In addition to the SDGs, another notable effort to measure and track learning on a global scale is the World Bank’s Human Capital Index which compares countries’ levels of human capital around the world (Kim 2018; Kraay 2019; World Bank 2019). This effort aims to disseminate a measure of human capital that will encourage countries to invest in the education of their people. The Human Capital Index includes learning outcomes from this database as one of its core ingredients. The database in this paper will be updated regularly and made public to enable these large-scale efforts, among others, and to advance our understanding and ability to track human capital formation and potential links to economic development.

15
Atlas provides aquifer productivity<sup>3</sup> and aquifer-type information from 51 African countries. Additionally, it has information on the recharge rates of groundwater, as well as groundwater depth maps across the African continent.

We merge the groundwater datasets with the Global Agro-Ecological Zones (GAEZ) dataset to impute water-supply information at the GAEZ grid level.

# **3.2 Agricultural Productivity**

We use the GAEZ dataset to measure agricultural productivity in SSA. The GAEZ dataset is curated by FAO and IIASA (2020) and provides information on agricultural productivity and estimates production gaps across the world for the years 2000 and 2010 at a granular level of approximately a 9x9 kilometer (km) grid. For our analysis, we consider the data for 2010 only, because they are the latest data.<sup>4</sup> The data are also disaggregated by crop type and irrigation type: rain-fed or irrigated using water from sources such as rivers, lakes, and/or groundwater. We have data on 291,798 GAEZ grids, and our subsequent analysis is conducted at the GAEZ grid level.

In addition to productivity data, the GAEZ dataset offers insights into agro-climatic conditions such as soil conditions, temperature, precipitation during the agricultural growing season, water availability, and land type in the area. We focused our study on croplands to determine whether shifting toward groundwater irrigation could lead to significant gains in agricultural productivity. To answer this question, we examined yield and potential yield at the crop–grid cell–year level to identify productivity gaps by irrigation type.

We restrict our analysis to cereals, namely, barley, millet, maize, rice, sorghum, and wheat. We focus on cereals for our analysis, because they are the primary source of energy for most households and the demand for cereals is expected to grow in the coming decades (OECD, 2016).

Table 1 provides descriptive statistics for the GAEZ dataset, showing that despite the average harvested area of rain-fed croplands being higher than
# **5. Conclusion**

E-commerce has developed rapidly in rural China. As the penetration rate in rural areas is just 40 percent (Woetzel et al. 2017), there is still ample room to increase further. However, more studies are needed to understand whether and how e-commerce can help improve the livelihoods and production efficiency in rural areas. Using a nationally representative sample of Taobao Villages, we have detailed the characteristics of Taobao Villages and the households living there, as well as the pattern of e-commerce participation and its effect on income distribution across different stratified groups.

The empirical results show that: 1) e-commerce participation is not random, participation is higher among households with younger household heads, with secondary education (particularly those with technical and vocational education), urban work experience, and knowledge of e- commerce; 2) e-commerce participation is associated with higher household income, with some indications that participation has a strong positive effect on household incomes; and 3) e-commerce benefits among participants seem to be inclusive in Taobao Villages: among the households engaging in e-commerce, while the wealthy gain more in absolute terms, the less wealthy experience higher income growth in relative terms. While younger individuals with technical training, knowledge of e-commerce, and migrant experience are likely to have higher income increase in absolute terms through e-commerce participation, those older, with less education, knowledge, or migrant experience have the potential to benefit more in relative terms.

Due to data limitations, our analysis only estimates the direct effect of e-commerce participation on household income growth in Taobao Villages, where e-commerce is most developed in rural China. To further understand the effect of e-commerce on rural China, a panel data set including villages that significantly engage in e-commerce and those that do not is required. More research is needed to 1) quantify the impact of e-commerce on income growth in rural areas, including in the non-Taobao Villages (areas where e-commerce is less developed), to understand the difference between Taobao Villages and non-Taobao Villages and to identify the
access to financial services can therefore have direct negative repercussions not only for female entrepreneurs and individuals but for the overall economy.

This paper analyzes gender differences in access to credit by enterprises and use of formal and informal financial services by individuals in Sub-Saharan Africa. Specifically, we use enterprise surveys to assess whether female entrepreneurs in Sub-Saharan Africa are less likely to rely on formal bank finance, compared to male entrepreneurs and compared to female entrepreneurs outside Sub-Saharan Africa. We also use recent FinScope and FinAccess surveys across nine countries in Southern and East Africa to assess gender differences in the use of formal and informal financial services by individuals.

This paper relates to a growing literature on the gender gap in access to credit (see Klapper and Parker, 2010, for a survey). Cross-country studies have shown that women are less likely to get financing from a formal financial institution or are charged higher interest rate than men (Muravyev, et al., 2007) and generally raise less formal and informal venture capital than men (Brush, et al., 2004). Bruhn (2009), on the other hand, does not find any evidence for Latin America of a gender gap in access to credit by enterprises. Richardson, Howarth and Finnegan (2004) find for Sub-Saharan Africa that women entrepreneurs are more likely than male entrepreneurs to rely on internal or informal financing. This gender gap is also reflected in higher financing obstacles reported by women. The literature has also explored the reasons behind such a gender gap. Buvinic and Berger (1990) find that female entrepreneurs struggle more with loan applications, while Lusardi and Tufano (2009) find lower overall financial literacy among women. However, behavioral differences might also be important, leading to taste rather than statistical discrimination (Beck, Behr and Madestam, 2011). Evidence from Africa shows that in many instances, only male heads of households are able to successfully receive formal credit (Johnson, 2004).

2
**Policy Research Working Paper Series**

|**Title**<br>|**Author**|**Date**|**Contact**<br>**for paper**|
|---|---|---|---|
|WPS2328 Social Transfers and Social<br>Assistance: An Empirical Analysis<br>Using Latvian Household Survey Data|Branko Milanovic|April 2000|P. Sader<br>33902|
|WPS2329 Improving Russia's Policy on Foreign<br>Direct Investment|Joel Bergsman<br>Harry G. Broadman<br>Vladimir Drebentsov|May 2000|S. Craig<br>33160|
|WPS2330 Reducing Structural Dominance<br>and Entry Barriers in Russian<br>Industry|Harry G. Broadman|May 2000|S. Craig<br>33160|
|WPS2331 Competition, Corporate Governance,<br>and Regulation in Central Asia:<br>Uzbekistan's Structural Reform<br>Challenges|Harry<sup>G. Broadman</sup>|May 2000|S. Craig<br>33160|
|WPS2332 Financial Intermediary Distress in<br>the Republic of Korea: Small Is<br>Beautiful?|Paola Bongini<br>Giovanni Ferri<br>Tae Soo Kang|May 2000|K. Labrie<br>31001|
|WPS2333 Output Fluctuations in Latin America:<br>What Explains the Recent Slowdown?|Santiago<sup>Herrera</sup><br>Guillermo Perry<br>Neile Quintero|May 2000|C. Palarca<br>35328|
|WPS2334 Sex Workers and the Cost of Safe<br>Sex: The Compensating Differential<br>for Condom Use in Calcutta|Vijayendra Rao<br>Indrani Gupta<br>Smarajit Jana|May 2000|P. Sader<br>33902|
|WPS2335 Inflation and the Poor|William Easterly<br
outcomes ("beyond-the-border" metrics such as the _Logistics Performance Index_ or the Doing Business _Trading Across Borders_ data), which are primarily endogenous, and not tied to the geography of the network (Arvis et al., 2007 and 2010).

We implement our model empirically to produce an internationally comparable ACI for the year 2007 as an input into future research work, and a useful policy benchmarking tool. We show that, as expected, 4