rafmacalaba/data-use-mentions-extended huggingface dataset:
taken from the 2008–2009 Consumer Expenditure Survey (POF) administered by the Brazilian Institute of Geography and Statistics (IBGE). The fieldwork for the survey was carried out between May 2008 and May 2009.

The value of all non-purchased items was about 11 percent of total purchased expenditure, while non-purchased food accounted for about 20 percent of all non-purchased items. These ratios tended to decline at the upper quintile levels. The fullest set of data provided by the survey had deflated all items.

The questionnaire asked a single question concerning LPG: the expenditure during the previous 90 days. The survey also asked for expenditures on a range of other sources of energy, without specifying what these were used for or distinguishing between purchased and freely acquired. The Ministry of Energy publishes annual average retail prices in the country’s 27 regions (ANP 2010), and this study used the national average price for 2008 and 2009 of 2.66 reais per kg. The coefficient of variation (not adjusted for regional populations) across regional average retail prices was 0.2, indicating that 95 percent of prices were within 60–140 percent of the national average, possibly reflecting size of Brazil and the need of retail prices to reflect internal transport costs. As long as these price variations were weakly correlated with the variations in survey variables, the bias in the selection and consumption equations would still be small, but the calculated quantities consumed could have large measurement errors.

Brazil exhibited a much higher selection rate of LPG than other countries studied, recording a national average uptake rate of 88 percent of households (Table A2.19). LPG was used by the great majority of households at all income levels in both rural and urban areas. The share of households using LPG increased with income level in rural areas but fell from 90–95 percent to less than 80 percent in the top urban quintile. Nationally, of the 6 million households that had not purchased LPG during the 90 days of the survey period, 1 million had paid
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Queiroz, B. L., B. Figoli, and M. Gonçalves (2010), _The Social Protection System for the Elderly in_ Brazil, Paper presented at the Workshop Country Study on Aging in Brasília, Brazil.

- Rodrik, D. (2000), Saving Transitions, _The World Bank Economic Review_ , Vol. 14 (3): 481-507.

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# **<mark>A Novel Approach to the Automatic Designation of Predefined Census Enumeration Areas and Population Sampling Frames: A Case Study in Somalia</mark>**

**Sarchil Qader Veronique Lefebvre Amy Ninneman** **<mark>Kristen Himelein</mark> Utz Pape Linus Bengtsson Andy Tatem Tomas Bird**

JEL: C55, C83, C80 Keywords: Census; Enumeration Areas; Sampling Frame; Somalia
availability, temperature, and soil nitrogen dynamics at the level of an individual field. Crop growth is broken into six phenological stages and leaf and stem growth rates are calculated for each stage. Management factors are also considered, including choice of variety, planting date, row spacing, irrigation and nitrogen fertilizer application amounts and timing. By varying temperature and precipitation inputs, users can simulate the impact of climate change on agricultural productivity.

Important strengths of crop simulation modeling include: (a) the simulation of growth by stage so that daily temperature data can be utilized and the impact of extreme events on yields can be assessed, and (b) the ability of users to specify crop varieties, fertilizer applications, as well as irrigation availability, all of which are critical elements in any climate adaptation strategy. However, despite its use in global studies, the DSSAT approach remains fundamentally a highly calibrated, field-based approach which has not yet been validated on a global basis.

This limitation has stimulated new work by Deryng, Sacks and Ramankutty (2009) who have developed a simpler, less highly calibrated variant of the crop simulation model, nick-named Agro-PEGASUS. It has been designed to operate at global scale and simulates growth as a function of light use efficiency, daily average absorbed photo synthetically active radiation, temperature, soil moisture, and fertilizer availability. It has also been validated at that scale.

Agro-PEGASUS model predictions for planting and harvest dates for global maize area agree with observed ranges in about three-quarters of all grid cells where maize is grown. Predicted global maize yields also compare reasonably well to actual yields. For a 2°C rise in global temperatures, the authors find that average maize and soybean yields rise in high income countries, while falling slightly for wheat. The lowest income countries experience the sharpest 8
in expenditures was due to indirect effects, mostly through higher food prices. At the same time, because the poor spend far less on energy and food in absolute terms, the top quintile captured 40 percent of the total benefits of lower oil prices, whereas the bottom quintile captured only 9 percent (Andriamihaja and Vecchi 2008). Most poor do not own motorized vehicles or backup electricity generators and hence they may spend less than the rich on oil products not only in absolute terms but also as a percentage of total household expenditures. However, in countries where the poor rely on kerosene for lighting, they may be the largest spenders on oil products in terms of the percentage of total household expenditures, as shown by an analysis of household expenditure surveys in Bangladesh, Cambodia, and Uganda (Bacon, Bhattacharya, and Kojima 2010). What these observations suggest is that, even purely from the standpoint of equity, there is a cost associated with reforming oil price subsidies, and that cost should be weighed against the opportunity cost of maintaining the subsidies.

Some may argue that a fuel price subsidy is justified when the fuel is a merit good, such as a clean cooking fuel that causes much less pollution and has health benefits. Given cash instead of price subsidies, households may use the cash for other purchases while reverting to traditional fuels that are cheaper or collected for free, with attendant air pollution and health problems. As section 5 shows, however, it is difficult to target price subsidies for oil products, and universal price subsidies have large leakages.

Price subsidies for oil products are provided today because they are easier to administer than social services or social protection and are visible and politically popular. Although they benefit the politically powerful disproportionately (both legally and illegally through diversion and smuggling), subsidies can be billed as a pro-poor policy if necessary. All too often, if the government in power is attempting to reform universal price subsidies on the grounds that the bulk of the total subsidy goes to the rich, the
2018). Cultural Biases in Migration: Estimating Non-monetary Migration Costs. _Papers in Regional Science 97(2)_ , 411–438.

- Ferreras, L. (2013). Corruption and Foreign Education. _The Journal of Politics and Society 24(1)_ , 160–189.

- Fiorino, N., E. Galli, and I. Petrarca (2012). Corruption and Growth: Evidence from the Italian Regions. _European Journal of Government and Economics 1(2)_ , 126–144.

- Geis, W., S. Uebelmesser, and M. Werding (2013). How do Migrants Choose their Destination Country? An Analysis of Institutional Determinants. _Review of International Economics 21(5)_ , 825–840.

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framework makes it possible to measure time and cost for such activities as trade document processing, approvals needed for import or export transactions, customs clearance, technical clearances, inland transport, terminal handling, and container security measures. In addition, the data illuminate underlying policy and institutional issues that affect time and cost along the supply chain, such as the percentage of containers inspected, the number of agencies with the power to inspect goods, and whether risk-based criteria are used for inspections.

> 2 The data set includes either 2003 data or the most recent data available as of August 2005. Of the 80 economies, 70 had 2003 data available, 6 had 2002 data, 2 had 2001 data, 1 had 2000 data, and 1 (Angola) had 1999 data. 3 The survey excluded ocean freight time and cost, since that would have involved an extremely large number of bilateral trade partners for each country. It included distance, however, used as a surrogate for shipping cost.

6
were generally conducted in environments where such a contract was embedded in enduring family and patron-client relationships or where effort was easily monitored.

Even within households, imperfections in land and labor markets, together with the inability to commit, may prevent individuals from achieving an optimal allocation of productive factors. For plot level panel data from Burkina Faso, Udry (1995) finds that reallocation of factors from male to female controlled plots within the same household could increase output by 6% - less than half of the estimated output loss from imperfect allocation of productive factors at the village level (13%), but still significant. One interpretation is that, by "renting" out land to their husband, women would risk losing these rights. In the absence of other assets that could be transferred from the husband to the wife to provide assurance, they fail to do so, despite the productivity increases that this might entail.

All this implies that, although land rental markets can not completely eliminate structural impediments and bring about a fully efficient allocation of land in an economy, they can go a long way in bringing the operational distribution of holdings closer to the optimum. However, in quite a few countries, the extent of land rental markets has been greatly diminished by large landowners reluctance to engage tenants due to concern for potential challenges to their property rights. Furthermore, rental markets' potential to increase overall welfare was not well understood by governments. Consequently, the static productivity loss entailed in sharecropping tended to induce interventions that have limited the extent of rental transactions, thus causing a larger inefficiency in resource allocation. We turn now to discuss these and other policy issues related to land markets.

# **4 POLICY ISSUES**

This section draws the main policy conclusions from our earlier discussion, focusing on clarification and adjudication of property rights, ways to improve the functioning of land sales and rental markets, and redistributive land reform. These three steps form somewhat of a sequence, in the sense that it is difficult to improve the functioning
kilometer distance between country pairs) and other common gravity measures. The final dataset has just over one million observations in which about half are considered to be true zeros.

# _Tariffs_

One of the main problems with including labor clauses is that they may be correlated with the tariff changes that are part of the trade agreement. One solution is to incorporate the tariff data included in the HDTA (Mattoo et al. 2020). The HDTA includes three tariff measures at the six-digit Harmonized System (HS) level: the Most-Favored Nation (MFN) tariff level, the preferential tariff, and the tariff preference margin (the difference between the MFN tariff and the preferential tariff). The tariff preference margin (TPM) is a measure of the degree to which the preferential agreement reduces tariffs.

One of the concerns is that tariff levels, or TPMs, are correlated with labor clauses. Some industries might be more sensitive than others. For example, it seems likely that the more labor-intensive products (apparel, electronics, appliances, automobiles) might be more likely to be paired with more restrictive labor clauses. To get a heuristic sense of these relationships, Table 3 includes the unweighted and unconditional pairwise correlations between the Categorylevel labor clauses measures and the unweighted arithmetic average of all HS6 TPMs for sixteen industry groups (as well as the mean across all HS6 groups). The TPMs are all positive, so larger values indicate lower tariff levels (relative to the MFN tariff levels).

Positive correlations in Table 3 indicate that labor clauses would be more likely to appear when tariffs were lower and negative correlations would imply that labor clauses would appear when tariffs were higher. While it would be helpful to interpret these correlations as representing relationships that are either substitutes or complements, unfortunately it is not that straightforward. Lower tariffs might appear with labor clauses meant to reinforce and encourage trade. At the same time, lower tariffs might appear with labor clauses meant to offset the tradecreating effects of tariffs.

The second goal of Table 3 is to present
during this period (Blyde et al. 2016).

However, the lack of significant impacts on manufacturing employment at the aggregate level hides heterogeneous impacts across areas. Table 13 shows the labor market impacts on areas that had different shares of jobs susceptible to being replaced by robots. It is expected that among areas experiencing similar levels of exposure to US automation, those with a higher replaceability index would experience larger employment declines. In fact, as seen in column 2, the OLS results show that exposure to US automation had a disproportionate 22
2SLS estimates of the relationship between regency-level exposure to robots and employment. Exposure to robots is instrumented with the average exposure in the OECD region. The dependent variables are the 2008-2015 differences in log of employment by sector in each regency. The regency demand shifter is regency-level average global exports excluding Indonesia. Base year regency covariates include: i) population; ii) the shares of workers with tertiary and no education (separately); iii) real output per capita, and iv) the share of manufacturing employment. Standard errors are clustered at the regency-level. Weights are constructed using 2007 (base year) regency population. The coefficients with<sup>_⋆⋆⋆_</sup> are significant at the 1% level, with<sup>_⋆⋆_</sup> are significant at the 5% level, and with<sup>_⋆_</sup> are significant at the 10% level.

> 35This justifies our choice of relegating such specification in the appendix.

35
opposite effects on household expenditures. Foreign aid and the presence of troops have a positive effect, whereas conflict intensity has a negative effect. But these conflict-related variables are not independent from each other. Indeed, the estimates for Model 1 imply that there is a strong correlation between conflict intensity and the presence of troops. Previous research by Chou (2012), Douglas (2012), and Johnson, Ramachandran, and Walz (2012), also points out to a strong correlation between conflict intensity and the level of foreign aid. Because of these correlations, assessing the impact of conflict on household expenditures requires considering all conflict-related variables together, and not in isolation.

The provincial database constructed for this paper sheds additional light on the correlation patterns linking conflict-related variables (figure 7). Contemporary correlations at the province level between conflict intensity, foreign aid and the presence of troops, range from 0.2 to 0.4. But based on the time structure of the correlation coefficients, conflict intensity precedes aid, which is in turn followed by an increase in the number of troops, both international and Afghan. This dynamic suggests that mobilizing more financial resources is easier than handling the logistics of a larger military presence on the ground.

16
2018).<sup>1</sup> The federal Head Start program in the United States also induced switching out of private preprimary schools (Kline & Walters, 2016).

The inadequacy of stimulation in their counterfactual environment and lower access to substitute services may partially explain why children from more disadvantaged backgrounds tend to benefit more from preprimary education (Cascio and Schanzenbach, 2014; Currie, 2001).

# **Preprimary education in low- and middle-income countries**

According to UNESCO’s Institute of Statistics, preprimary enrollment has increased considerably around the world over the last two decades, from an average of 30 percent of children in 2000 to 50 percent in 2018.<sup>2</sup> Access to preprimary education in low- and middleincome countries is still low, with 19 percent of preprimary-aged children in low-income countries enrolled (UIS, 2018), a coverage rate less than half of what was observed in high-income countries fifty years ago. Beyond these averages, household survey data using UNICEF’s Multiple Indicator Cluster Surveys (MICS) suggest substantial variation in preprimary enrollment across and within countries that is associated with socioeconomic status, with the largest differences in enrollment in the poorest countries (Figure 1). This unequal access to preprimary education can exacerbate learning inequalities, as children in families from lower socioeconomic groups tend to also have limited learning opportunities and stimulation at home and in their communities _(_ McCoy et al., 2018) (Figure 2).

Domestic financing for preprimary education has increased over the past decade, amounting to 6.6 percent of domestic education budgets globally. Low-income countries allocate substantially less, with less than 2 percent of their education budgets going toward preprimary education (UIS, 2018). In these countries, standards and quality assurance systems are often nonexistent or under-resourced and learning spaces often do not meet minimum safety and

> 1 In contrast to the practice of “red-shirting” in higher-income countries, in many low-income countries, parents try to enroll their children in
Scientific reports, 2, 723.

Timmer et al. (2012), The World Input-Output Database (WIOD): Contents, Sources and Methods, WIOD Background document available at <u>www.wiod.org.</u> Timmer, Marcel P., Abdul Azeez Erumban, Bart Los, Robert Stehrer, and Gaaitzen J. de Vries (2014) "Slicing Up Global Value Chins" Journal of Economic Perspectives, 28 (2): 99-118.

Tri Thanh Vo and Rod Tyers. 1996. “Splitting Labor by Occupation in GTAP: Source and Assumptions,” Australian National University.

UNCTAD (2013), World Investment report 2013: Global Value Chains: Investment and Trade for Development, United Nations Conference on Trade and Development, United Nations Publication ISBN 978-92-1-112868-0.

Wang, Z., S.-J. Wei, X. Yu, and K. Zhu. 2017. “Measures of Participation in Global Value Chains and Global Business Cycles.” Working Paper 23222, National Bureau of Economic Research, Cambridge, MA World Bank Group; IDE-JETRO; OECD; UIBE; World Trade Organization. 2017. Global Value Chain Development Report 2017: Measuring and Analyzing the Impact of GVCs on Economic Development. Washington, DC: World Bank. © World Bank. <u>https://openknowledge.worldbank.org/handle/10986/29593</u> License: CC BY 3.0 IGO WTO (2018), Trade in value-added and global value chains profiles - explanatory note.

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Policy Research Working Paper 8692

# **Abstract**

Food consumed outside the home in restaurants or other food establishments is a growing segment of consumption in many developing countries. However, the survey methods that are utilized to collect data on expenditures on food away from home are often simplistic and could potentially result in inaccurate reporting. This study addresses the potential inaccuracy of commonly used methods and tests potentially superior methods to inform best practices when collecting data on consumption of food away from home. A household survey experiment was implemented in Hanoi, Vietnam, to test these different methods. Using a food away from home consumption diary as a benchmark, the study finds that many of the alternative methods considered—including asking about consumption in one line (the existing practice in Vietnam) or asking each individual about their food away from home—lead to underreporting (33 and 22 percent underestimates, respectively). Surprisingly, using one respondent and helping them with recall with a simple worksheet as well as bounding (two-visits) results in food away from home estimates that are indistinguishable from those reported in the benchmark diary. This finding implies that there is a more cost-effective way to collect accurate data on food away from home than an intensive daily diary. Furthermore, it highlights the inaccuracy associated with collecting data on consumption of food away from home from a single question in a survey. Although limited analysis can be conducted on the implications for poverty, the study finds that the profiles of the poorest households differ across different methods of collecting information on food consumed away from home.

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