rafmacalaba/data-use-mentions-extended huggingface dataset:
first, by using a "poverty map" to assign resources to small geographic areas, and then conducting an informal on-site assessment of the "poverty" of the community requesting a project.<sup>5</sup>

# 3. The data set

In 1997, Peru was divided into 13 administrative regions, 24 departments, 194 provinces, and 1812 districts (Webb and Femrndez Baca 1997, p. 112). Regions and departments are administrative arms of the central government, which appoints a governor for every region. Provincial and district-level mayors are chosen at municipal elections every three years. Data on FONCODES expenditures, socio-economic characteristics, and voting patterns is available at different levels of geographic aggregation.

FONCODES itself keeps monthly records on the number of projects and aggregate amounts spent in each district. Three points are worth noting about these data. First, because expenditures are recorded in the month in which a project is _approved,_ there is a lag of about two weeks before _disbursement_ of the first installment of funds, and of several months before the second (and final) disbursement. Second, only expenditures on projects are included, and not administrative costs or expenses for general overhead. Third, district-level information on the distribution of expenditures is only available for the cornmunitybased projects. There is no information on the allocation formulas or the actual distribution of the special projects.

The Peruvian National Statistical Institute (INEI) has estimated population size, the proportion rural, and a host of socio-economic indicators at the district level. Most of these indicators are based on a population and housing census conducted in 1993. The one important exception is the rate of chronic malnutrition, which is based on a census of height and weight amongst schoolchildren also conducted in 1993.

The Jurado Nacional de Elecciones, the body which supervises elections in Peru, keeps records on electoral outcomes for elections held since 1990. Some of these data have also been compiled and published (Tuesta 1994, Jurado Nacional de Elecciones). Results are generally available for all
Trade and competition.** Trade policy influences the allocation of resources across heterogeneous producers and consequently impacts aggregate productivity. Two approaches are used to quantitatively assess the impact of tariffs and/or other distortionary forms of protection. On the one hand, evidence comes from model-based estimates. For example, building on Arkolakis, Costinot, and Rodríguez-Clare (2012), Edmond, Midrigan, and Xu (2015) study the impact of moving from autarky to free trade by calibrating a model to Taiwanese manufacturing data. Opening to trade leads to greater competitive pressure and substantially reduces markup distortions. Consequently, it reduces misallocation and improves total factor productivity by more than 12%.

On the other hand, specific trade policy changes are examined for causal inference. Khandelwal, Schott, and Wei (2013) study the elimination of externally imposed quotas on Chinese textile and clothing exports. Interestingly, the distortionary effects of the quotas imposed by the United States, Canada and European Union were compounded by the effects of government-imposed quotas allocated in favor of (less productive) state-owned enterprises. <u>The authors find that 71% of the productivity gains derived from the empirical analysis are</u>

> 4 Incidentally, it is interesting noting that models tend to explain a larger share of the changes in agricultural rather than manufacturing productivity.

16
# **3. Data and descriptive statistics**

Household data show that, although continued access to non-agricultural incomes, access to public social support and the scope to draw on informal safety nets provided short-term support, the war led to a dramatic drop in long-term perspectives. In the agriculture sector, continued high demand for renting in or buying land together with low willingness to sell land points to strong sectoral fundamentals. Size-biased access to credit that is reinforced by traditional agricultural subsidy policies may, however, limit access to working capital finance even for investments that would be advantageous in the short term and, together with a complete lack of long-term finance, may limit farmers’ ability to take advantage of opportunities for long term investment and diversification into higher value crops in due course.

# **3.1 Sample, household characteristics, coping strategies, and conflict effects**

To obtain the sample that could form the basis for a phone-based farm survey, we exclude conflict affected areas and define four farm size strata (< 50 ha, 50-120 ha, 120-500 ha, and > 500 ha) for a stratified random sample.<sup>14</sup> To assess representativeness, panel A of table 1 compares median and mean farm size between SAR and Form 29, the frame currently used by SSSU, in each stratum, pointing towards a near perfect match in the 50-500 ha category, no difference in the median for farms in the > 500 ha category (but better coverage of large farms in Form 29) and a much better coverage of small farms in SAR as compared to official statistics. A graphical representation of the sample’s geographic coverage in figure 1 shows it covers most of the rayons in areas not affected by conflict but coverage is scant in the East and the North.<sup>15</sup> At the farm level, the survey asked about total output and market participation as well as input costs for key inputs (hired labor; fertilizer and chemicals; machinery and fuel
- Corral, P., Kastelic Himlein, K., Mcgee, K.R., Molina, I. (2021), A Map of the Poor or a Poor Map?, World Bank Policy Research Working Paper Series No. 9620. Washington DC: The World Bank.

- Dabalen, A., Ferrè, C. (2008), Updating Poverty Maps: A Case Study of Albania. Unpublished working paper. Washington DC: The World Bank,

- Dang, H.A., Lanjouw, P., Serajuddin, U. (2014), Updating Poverty Estimates at Frequent Intervals in the Absence of Consumption Data: Methods and Illustration with Reference to a Middle-Income Country, World Bank Policy Research Paper No. 7043. Washington DC: The World Bank.

- Dang, H.A., Lanjouw, P., Serajuddin, U. (2017), Updating Poverty Estimates at Frequent Intervals in the Absence of Consumption Data: Methods and Illustration with Reference to a Middle-Income Country, _Oxford Economic Papers_ , **69(4)** , pp. 939-962.

- Elbers, C., Lanjouw, J.O., Lanjouw, P. (2002), Micro-level estimation of welfare. World Bank Policy Research Working Paper No 2911. Washington DC: The World Bank.

- Elbers, C., Lanjouw, J.O., Lanjouw, P. (2003), Micro-Level Estimation of Poverty and Inequality. _Econometrica_ , **71(1)** , pp. 355–364.

- Institut National de la Statistique (INS) (2010), Enquête nationale sur le Budget, la Consommation et le Niveau de vie des ménages pour l’année 2010, Tunis.

- Institut National de la Statistique (INS) (2015), Enquête nationale sur le Budget, la Consommation et le Niveau de vie des ménages pour l’année 2015, Tunis.

- Institut National de la Statistique (INS) in collaboration with the
I POLICY RESEARCH WORKING PAPER 2224

# Summary findings

Kraay and Monokroussos consider two alternative methods of forecasting real per capita GDP at various horizons:

* Univariate time series models estimated country by country.

* Cross-country growth regressions. They evaluate the out-of-sample forecasting performance of both approaches for a large sample of industrial and developing countries.

They find only modest differences between the two approaches. In almost all cases, differences in median (across countries) forecast performance are small relative to the large discrepancies between forecasts and actual outcomes.

Interestingly, the performance of both models is similar to that of forecasts generated by the World Bank's Unified Survey.

The results do not provide a compelling case for one approach over another, but they do indicate that there are potential gains from combining time series and growth-regression-based forecasting approaches.

- - This paper a product of Macroeconomics and Growth, Development Research Group is part of a larger effort in the group to improve the understanding of economic growth. Copies of the paper are available free from the World Bank, 1818 H Street, NW, Washington, DC 20433. Please contact Rina Bonfield, room MC3-354, telephone 202-473-1248, fax 202522-3518, email address abonfield@worldbank.org. Policy Research Working Papers are also posted on the Web at http: //www.worldbank.org/research/workingpapers. The authors may be contacted at akraay@worldbank.org or gmonokroussos@worldbank.org. November 1999. (32 pages)

_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 view of the World Bank, its Executive Directors, or the countries they represent._ Produced by the Policy Research
years, its water infrastructure has failed to keep pace with population increase. As a result, it is unable to provide adequate service coverage to its population<sup>4</sup> . This is reflected in the mere 2 percentage points increase in the improved water coverage between 1990 and 2015. In fact, in urban areas, due to population growth and migration, improved water coverage actually fell from 92 percent in 1990 to 77 percent by 2015 (JMP, 2015). In rural areas on the other hand, improved water coverage is estimated to be at 45 percent in 2015 (JMP, 2015).

To address the shortfalls in water supply infrastructure and to improve water resource management throughout the country, in the wake of the Millennium Development Goals (MDG) the Tanzania government developed the Water Sector Development Program (WSDP) which is set to run

> 2 Data are from World Development Indicators (database). 2016. World Bank, Washington, DC. <u>http://databank.worldbank.org/data/home.aspx</u> 3 Other than that, the country’s climate and hence rainfall pattern also plays a significant role in influencing the supply of water resources. The country experiences a monsoon-type climate with annual rainfall ranging from a high of >1000mm in the coastal and highland areas to a low of around 600mm in the dryer central and northern areas. In the latter, the dry season can last up to 7 months, and rivers tend to run dry (Basalirwa et al., 1999). The El Niño/La Niña South Oscillation (ENSO) phenomenon can also result in substantial impacts on intra-seasonal rainfall variability and inter-annual rainfall variability is a key challenge resulting in droughts and floods (White and Tourre, 2007; Nicholson & Kim, 1997). Projections of Tanzania’s future rainfall patterns based on climate change vary widely, which results in a challenging environment for planning and investment (Basalirwa et al., 1999). There
<!-- Start of picture text --> Objective data support perceptions of documentation requirements and cost as barriers<br>to use of formal accounts<br>1.14 FIGURE<br><!-- End of picture text --> <!-- Start of picture text --> Non-account-holders Non-account-holders<br>citing lack of documentation as a barrier (%) citing cost as a barrier (%)<br>50 40<br>•<br>40 •<br>• 30<br>•<br>•<br>30 •<br>• • •<br>• 20<br>20 • • • • •<br>• • • •<br>10 • • • ••• • •• • • • 10<br>• •<br>• ••<br>•<br>1 2 3 4 5 NEGLIGIBLE LOW MEDIUM HIGH<br>Number of documents<br>required to open a checking account Annual fees for a checking account<br><!-- End of picture text --> _Note:_ Data on number of documents required are for 2005. Data on annual fees are for 2010 and reflect scoring by the national central bank. The sample for the left-hand panel includes 38 economies, and the sample for the right-hand panel 100 economies. _Source:_ Demirguc-Kunt and Klapper 2012; World Bank, Bank Regulation and Supervision Database; World Bank Payment Systems Database.

For example, distance from a bank is a much greater barrier in rural areas, as expected. Technological and other innovations that help overcome the barrier of physical distance could potentially increase the share of adults with a formal account by up to 23 percentage points in Sub-Saharan Africa and 14 percentage points in South Asia.<sup>14</sup> Among developing economies there is a significant relationship (after accounting for GDP per capita) between distance as a self-reported barrier
the monetary base, reserves excluding foreign<br>liabilities or short-term debt,and adjusted dollar deposits.|No|0.05|55.7|

# **_Law of One Price (LOP)_**

The law of one price has been used to construct several measures of currency over and undervaluation. We consider the overvaluation implied by The Economist’s Big Mac and Commsec’s iPad price indices, under the assumption that the law of one price holds. This hinges on the restrictive (and implausible) assumptions regarding the absence of: barriers to trade (e.g., tariffs), transport costs, adjustment costs (causing price differentials to respond with a lag), and market power (which leads firms to price to market). We calculate the implied exchange rate as the local price of the good in pesos relative to its price in US dollars abroad and measure the percentage misalignment.

The Economist’s Big Mac index computes the exchange rate that would equalize prices of a Big Mac burger in MacDonald’s across countries, while an adjusted index attempts to correct for country differences in labor costs and GDP per capita. The adjusted index suggests the overvaluation of the peso has fallen from 50% in July 2011 to -5% in July 2015 (see Figure 10).<sup>45</sup> Yet we caution against this indicator of exchange rate overvaluation for Argentina as a result of market-diverging burger prices. Big Mac prices for Argentina have been subject to large controversy since 2011,<sup>46</sup> when the Big

> 44 However, costs of doing business by using this exchange rate are high as securities priced in US dollars must be purchased and exchanged to obtain scarce foreign currency.

> 45 In January 2016, the Big Mac index implied the peso is undervalued by an even larger 33% (106% according to the unadjusted index).

> 46 The Big Mac index for Argentina provides suggestive evidence of official inflation statistics
# **1. Introduction**

Early sexual initiation puts adolescent girls at risk for early childbearing and marriage. To test the impact of policy interventions, researchers often rely on self‐reported sexual behavior data obtained from face‐ to‐face surveys [e.g. Duflo _et al._ 2015]. However, survey methodologists have long been concerned with respondents’ tendency to misreport sensitive behaviors to avoid embarrassment or possible repercussions of disclosing the truth [Tourangeau and Yan 2007].

To assess those threats and adjust responses accordingly, respondents must form impressions of and make inferences about the preferences, values, and intentions of the interviewer. Most research on the role of interviewer characteristics on misreporting of sensitive behaviors focuses on Western adult respondents and observable interviewer characteristics, such as race and gender [West and Blom 2016]. In contrast, we use data from adolescent girls in Liberia and examine how self‐reports of sexual behaviors vary by both observable (gender, physical attractiveness) and seemingly unobservable (attitudes, beliefs) interviewer characteristics.

Our results highlight the importance of physical appearance and nonverbal communication in the social cognition processes that take place in a survey. In particular, interviewer’s physical attractiveness could evoke stereotypes among survey respondents, such as the belief that better‐looking individuals are sexually warmer or more trustworthy as long emphasized by the social psychology literature [e.g. Langlois _et al._ 2000]. Whether such stereotypes induce girls to report more or less truthfully is ambiguous. For example, if girls expect better‐looking interviewers to be sexually warmer, they may over‐report sexual activity to impress them. Or if girls see them as more trustworthy, they might feel more comfortable to disclose the truth to them.

Perhaps more surprising is the evidence that girls’ responses are also affected by seemingly unobservable interviewer attitudes, given the structured and scripted nature of the interview. This finding suggests that interviewers signal (possibly unconsciously) their views through nonverbal cues, such as subtle changes in
with a lack of evidence around their impact on firm performance, this paper contributes to a largely unexplored empirical literature. It does so thanks to a novel and unique dataset that includes detailed information on firms both within and outside economic zones across Bangladesh, Bhutan, India, and Nepal. It employs standard econometric techniques in the empirical literature on estimating the impact of zones on firm performance.

The first main finding of the paper is that being inside a zone has a positive and significant effect on FDI and employment. This lends support to the idea that when governments are unable to rectify constraints at an economy-wide level, addressing challenges within discrete areas can be a viable alternative to support firm performance.

The second main finding is that the effect of zones is mixed across zone types. Industrial areas and estates show significant and negative effects on exports and employment. Conversely, industrial parks have positive effects on FDI and employment, while EPZs demonstrate the most consistent positive effects across all measures of firm performance.

The third main finding is that controlling for zone status, public support services have significant impacts on firm performance. In particular, infrastructure support and trade and connectivity facilities have the most consistent positive effects across measures of firm performance. Governance and fiscal incentives have positive effects only on the measures of employment and exports, respectively. These findings further underscore the notion that policymakers need to worry about the design and implementation arrangements of zone programs.

Finally, we explore the effects of zone status on firm growth. Zone status is positively and significantly associated with younger firms and EPZs have a positive effect on employment generation.

In terms of future research, the heterogeneous performance of zones raises questions about why EPZs overall seem to improve firms’ competitiveness and efficiency, and why some zone types produce negative or no discernible effects on firm performance. Given the range of possible government interventions delivered through such programs, and the relative importance of infrastructure and trade facilitation, it seems that the success of zone programs depends largely on providing the “right” support services
the ages of 15 and 59 were return migrants.<sup>3</sup> This figure is in line with the World Bank report by Brodmann, Pouget, and Gatti (2010), who document that Egyptian migrants constitute 85% of temporary workers in Arab countries, representing as much as 10% of the Egyptian labor force in recent years. Based on the Development Economics Group data from the World Bank, Brodmann, Pouget, and Gatti (2010) show that, in 2005, Egypt was among the top 10 emigration countries in the world. Second, our data provides unique information on migrants’ legal status while abroad, which allows us to distinguish between return migrants according to their type of international migration—documented versus undocumented. Return migrants were asked whether they had a visa or legal document to enter the destination country, as well as the type of document they had.

In this paper, illegal status/undocumented migration refers to unauthorized entry, stay, or employment in a country.<sup>4</sup> Generally speaking, misreporting information regarding migrants’ legal status is problematic. This is especially the case for studies

> 3 Using the ELMPS 2018, we also find high rates of return migration. For example, in 2018, we find that 7.4% of households had a return migrant. We also find that 7.1% of individuals between the ages 15-59 and 9.2% of men between the ages 15-59 were return migrants in 2018.

> 4 We note the use of the terms undocumented and illegal interchangeably in the rest of the paper.

5
information that excludes the effects of specific, compound and mixed tariffs, and other charges such as antidumping duties. However, they are based on very widely dispersed real-world tariff data collected at a fine level of disaggregation, and probably do have some relevance for inferences about national and global efficiency gains from trade reform. We would draw the following conclusion. Whether and how we add flexibility is second order, and should not be a roadblock to achieving a reduction in the average. This means that the selection of which formula to choose, at least among the tops-down options spanned by the flexible Swiss formula, is nowhere near as important as the more basic issue of simply selecting and imposing a targeted reduction in the average<sup>8</sup> . It may be better to simply focus on achieving large reductions in average tariffs, even if the price is acceptance of an approach, such as a pure proportional cut, that allows some tariffs to remain relatively high. This result may, of course, not be acceptable, in particular if such approaches are found not to achieve needed reductions some of the key tariff peaks restricting global market access, and particularly market access by developing countries.

> 7 The importance of this problem can readily be overstated. At least at the level of aggregation used in a CGE model, Hertel and Martin (2001) found that these second-best welfare impacts were very small in a prospective new round of WTO negotiations.

> 8 Of course, if escalation-increasing approaches such as the Uruguay Round approach are considered, it may well be important to consider more than the resulting reduction in the average.

15
- De Luca, Giuseppe, Jan R. Magnus, and Franco Peracchi. (2018). "Balanced variable addition in linear models." _Journal of Economic Surveys_ , 32(4): 1183-1200.

- Deaton, Angus and Valerie Kozel. (2005). _The Great Indian Poverty Debate_ . New Delhi: Macmillan.

- <mark>Deaton, Angus, and John Muellbauer. (1980).</mark> _<mark>Economics and Consumer Behavior</mark>_ <mark>. C</mark> ambridge, UK: <mark>Cambridge University Press.</mark>

- Deaton, Angus and Salman Zaidi. (2002). _Guidelines for Constructing Consumption Aggregates for Welfare Analysis_ (Vol. 135). Washington, DC: World Bank Publications.

- Devarajan, Shantayanan. (2013). "Africa's statistical tragedy." _Review of Income and Wealth_ , 59: S9-S15.

- Douidich, Mohamed, Abdeljaouad Ezzrari, Roy van der Weide, and Paolo Verme. (2016). “Estimating Quarterly Poverty Rates Using Labor Force Surveys: A Primer.” _World Bank Economic Review_ , 30(3): 475-500.

- Elbers, Chris, Jean O. Lanjouw, and Peter Lanjouw. (2003). “Micro-Level Estimation of Poverty and Inequality.” _Econometrica_ , 71(1): 355-364.

- Fernandez, J., Olivieri, S., & Wambile, A. (2024). “Reconstructing 2010–2022 Poverty and Inequality Trends in Bangladesh: A Statistical Matching Approach”. Policy Research Working Paper 10749. Washington, DC: World Bank.

- <mark>Foster, J., Greer, J., & Thorbecke, E. (1984). A class of decomposable poverty measures.</mark> _<mark>Econometrica</mark>_ <mark>, 52(3): 761-766.</mark>

- <mark>---. (2010