rafmacalaba/data-use-mentions-extended huggingface dataset:
, 2011). Moreover, while the data to assess poverty rates at the individual level are not yet available, time use surveys have provided information to study the concept of time poverty.<sup>1</sup> This allows adjusting the measurement of such concept from the household to the individual level to assess gender differences in paid and unpaid work (Floro and Srivastava, 2017). Results of this type of analysis have shown that women are more likely than men to be time poor (Gammage, 2010; Bardasi and Wodon, 2010) especially in rural areas (Arora, 2015).

Time use surveys have also been used to further understand individual decisions to work as well as decisions on how to allocate time to different activities. A growing body of evidence shows that across countries: (i) women specialize in housework and care activities, while men focus on market work (Apps, 2004; Berniell and Sánchez-Páramo, 2011; Ferrant et al., 2014; Campaña et al., 2015); (ii) women work more hours in total than men when productive activities such as market work, housework and care are considered altogether (Haddad et al., 1995; Ilahi, 1999; Berniell and Sánchez-Páramo, 2011); and (iii) lifecycle milestones such as marriage and parenthood are the

> 1 The literature has defined the concept in different ways. According to Vickery (1977), time poverty refers to the notion that to stay above the poverty threshold, households need a minimum amount of time in addition to income. Goodin et al. (2008) define it as the deprivation of “discretionary” time.

2
study for several reasons. Female labor force participation (LFP) in the Islamic Republic of Iran is among the lowest

> 1 Most existing studies for developing countries rely on high-frequency phone surveys (Egger _et al._ , 2021; Khamis _et al._ , 2021; Mahmud and Riley, 2021; Krafft _et al._ , 2022; <mark>Bundervoet, Dávalos, and Garcia, 2022)</mark> , which can be prone to various data quality issues. These issues include low response rates or undercoverage and shorter questionnaires with fewer variables than the typical household survey, so typically do not allow for the rigorous and comprehensive analysis that can be implemented with nationally representative data (Miguel and Mobarak, 2022).

2
Policy Research Working Paper 9437

# **Abstract**

How is the COVID-19 pandemic affecting firm profits and tax payments in developing countries? This paper uses administrative corporate tax records from 10 low- and middle-income countries around the world to provide plausible estimates. Modeling the lockdown-triggered revenue shock with simple and transparent assumptions, the analysis predicts that less than half of all firms will remain profitable by the end of 2020, about 5–10 percent of the formal aggregate annual payroll will be lost, and firm exit rates will double. As a result, it is expected that tax revenue remitted by the corporate sector will fall by at least 1.5 percent of baseline gross domestic product. Differences in sectoral composition and firms’ cost structures generate heterogeneity in the results across countries: wage subsidies are less effective in low-income countries and government revenue losses are smaller.

This paper is a product of the Development Research Group, Development Economics. 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 pbachas@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
was mixed, implying that these episodes did not display the features of a global recession. For example, the main activity indicators did not suggest a broad-based weakness in the global economy in 1998. In 2001, although industrial production fell and the rate of global unemployment picked up slightly, both global trade flows and oil consumption increased. Equity prices declined substantially in 2001, and prices of commodities fell significantly in both episodes. During the global downturn of 2012, while some activity indicators did not show much weakness, global capital flows slowed, equity prices collapsed, and inflation declined.

The U.S. economy played a key role in global recessions and downturns. Although the four global recessions between 1975 and 2009 coincided with recessions in the United States, not every U.S. recession was associated with a global recession, since the United States experienced six additional recessions during 1950-2019, including recessions in 1958 and 2001 that coincided with global downturns. But it grew strongly during the 1998 global downturn and, to a lesser extent, during the 2012 global downturn.

# 3. Before the recession: A seemingly golden era

During 2001-07, the world economy appeared to be enjoying a golden era of growth. During this period, average output growth reached its highest pace since the early 1970s. Not only was growth buoyant, but inflation appeared to have been tamed in what was termed “the Great Moderation” (Figure 3). EMDEs were expanding rapidly as global supply chains and financial institutions expanded around the world.

A confluence of favorable circumstances fueled global trade and commodity demand. Advanced economies enjoyed a cyclical upturn after the global downturn of 2001, with output growth strengthening from 1.5 percent in 2001 to 2.6 percent in 2007. China was also growing rapidly as it integrated into global trade networks and supply chains, with its output almost doubling from the time of its World Trade Organization (WTO) accession in 2001 until 2007 (Koh and Yu 2019a).

Prolonged accommodative monetary policy in major advanced economies
of flaring requires detailed data on air quality, flaring volumes, and health records. To bridge this gap, we link geo-referenced child health data from Demographic Health Surveys with satellite-detected gas flaring locations in Nigeria (and estimates of gas flaring volumes). We examine the association between gas flaring and disease incidence, child anthropometric outcomes, and death among children under-5 in the oil producing Niger-Delta region of Nigeria. We find a positive association between gas flaring and the incidence of disease; specifically, cough, respiratory illness, and fever. We also find positive associations between flaring and the probability of a child being either wasted or underweight.

In a context like Nigeria, our study thus makes three important contributions: First, it provides the first comprehensive examination of gas flaring impacts on child health, for the country that contributes the most (by volume) to gas flaring in Africa and the seventh most globally. Also, most evidence on the health impacts of flaring is for recent unconventional gas production (fracking) whereas gas flaring in Nigeria is associated with conventional oil production. This distinction could be important as the process of fracking has been associated with other forms of air pollutants that may not solely be due to gas flaring. Moreover, most existing evidence is from richer countries, where confounding due to endogenous avoidance behaviour potentially complicates the analyses. In Nigeria there is limited scope for avoidance behaviour, especially due to land market rigidity in the densely populated NigerDelta area that stems from concerns over the distribution of oil wealth and the huge ethnic divide in this area. The Niger-Delta is home to over 40 different ethnic groups and the location of oil 3
# **1 Introduction**

The last decade has seen an unprecedented expansion in access to consumer financial products, with an estimated 1.2 billion adults gaining access to a bank or mobile money account over this period (World Bank, 2017). While this has expanded the financial tools available to households, there is also widespread concern that financial intermediaries can profit from exploiting inexperienced consumers (Campbell et al., 2011). This is especially true in developing economies where financial access has expanded rapidly against the backdrop of enormous variation in consumer experience and sophistication (Agarwal et al., 2018; Anagol et al., 2017; Badarinza et al., 2019).

This proliferation of new financial products and technologies has been accompanied by an extensive debate about the tradeoff between access and consumer protection. Some regulators have argued that predatory practices are sufficiently widespread to warrant outright limits to access, fees, and product features—potentially at the expense of gains from broader financial inclusion.<sup>1</sup> Proponents of lighter regulation, on the other hand, have advocated for information-based policies that instead aim to increase transparency to strengthen consumer knowledge and sophistication.

An important open question at the heart of this debate is to what extent risks to consumers can be mitigated by “learning-by-doing” that occurs naturally, as new financial technologies are introduced at scale and used on an everyday basis. Studying this question is empirically challenging for several reasons. First, the typically high degree of selection into _adoption_ and _active use_ of new financial technologies requires a setting with exogenous variation in access as well as incentives to engage with the technology to identify consumer learning. Second, many types of consumer protection risks, such as side payments to intermediaries, are difficult to observe in administrative data and may require surveys, audit studies, and other non-traditional data to be accurately measured.

In this paper, we study consumer learning in the context of payroll accounts, a simple financial technology that is currently being rolled out to millions of
><sup>6</sup> <mark>It is also worth noting that separate research has shown that developing consistent interests (i.e., specializing) may, paradoxically, depend on diversification (i.e., sampling) of interests earlier in life.</mark><sup>7</sup> To cultivate grit, our intervention followed a two-pronged approach. First, drawing on the evidence on _deliberate practice_ (Ericsson, 2008; Ericsson et al., 1993), students were taught to distinguish effective, evidence-based ways of studying from ineffective ones as well as strategies to implement these more effective ways of studying. Second, we aimed to motivate effort. To do this, we focused on changing students’ beliefs about practice, by raising expectancies and values, two psychological antecedents of motivated, effortful behavior (Pintrich, 2003; Eccles and Wigfield, 2002; Wigfield and Eccles, 2000; Feather, 1982; Crandall, 1969; Battle, 1965; Atkinson, 1957). In Expectancy-Value Theory, expectancy is the extent to which individuals believe they will succeed and, whereby value refers to the subjective value the individual attaches to a positive outcome. The latter increases in expected benefits from effort and decreases in expected costs. Expectancy and value are reliably associated with effort expenditure and achievement, particularly in academic settings (Nagengast et al., 2013; Eccles et al., 1993; Meece et al., 1990; Eccles et al., 1984). We expect students to be more likely to engage in sustained effort if they hold a strong expectancy that doing so would improve achievement, and if they attach a high subjective value to academic achievement. It is important to instill this expectancy – particularly among disadvantaged students – given the prevalence of false, deter-

> 4 The pre-registered analysis plan in the AEA RCT Registry is: Arias et al. (2017). "Can Grit be Taught? Learning from a field experiment with middle school students in
# **1. Introduction**

The emergence of global value chains (GVCs) has opened up new ways for development and industrialization. Developing countries can now join existing supply chains instead of building complete chains domestically. This increased degree of specialization frees them from the need to develop a wide range of competitive tasks and emphasizes their respective finely defined comparative advantages. At the same time, GVCs can be a tool for industrialized countries to re-invigorate their slow growth in the absence of major innovations. Indeed, cross-country evidence and case studies show that GVC participation can on average be growth-enhancing and lead to economic and social upgrading (see, for example, UNCTAD 2013; WEF 2013). However, new evidence also shows that not all countries have gained from participating in GVCs and that the institutional and political environment of countries matters to their success in GVCs (Kummritz 2016; Taglioni and Winkler 2016).

This paper examines which national policies are crucial for successful economic upgrading in GVCs, combining two panel data sets of developing and industrialized countries at the sectoral level with a wide range of policy measures at the country level. Taglioni and Winkler (2016) differentiate between three types of economic upgrading based on a country’s current tasks of comparative advantage, skills, and capabilities (Humphrey 2004; Humphrey and Schmitz 2002): (i) product upgrading, which involves moving into more sophisticated products in the existing value chain; (ii) functional upgrading, which involves increasing the value-added share (in output of the final product) in existing GVC processes by integrating or moving into more sophisticated tasks; and (iii) inter-sectoral upgrading, which involves moving into new supply chains with higher value-added shares. Therefore, in this paper, we adopt value added as our measure of economic upgrading.

These three objectives can be achieved by upgrading the production factors of labor and capital, and also by increasing total factor productivity (TFP). First, skills upgrading refers to improving the skills and know-how of the workforce. Developing skills is
NOR, POL, SVN|
|France|0.537|0.526|0.555|AUT, BEL, CHE, FIN, ISL, LTU, NOR,<br>POL, SVN|
|Germany|0.501|0.491|0.512|BLR, CZE, ESP, LVA|
|Ireland|0.587|0.575|0.607|GBR, NLD, SWE|
|Luxembourg|0.487|0.475|0.503|BLR, DEU, GRC, ITA, UKR|
|Netherlands|0.581|0.568|0.597|GBR, IRL, SWE|
|Switzerland|0.553|0.542|0.570|BEL, CYP, DNK, EST, FIN, NOR, POL|
|United Kingdom|0.580|0.570|0.596|IRL, NLD, SWE|
|**Simple average**|**0.481**|**0.471**|**0.496**||
|**Population-weighted average**|**0.496**|**0.484**|**0.511**||

_Source_ : Authors’ calculations.

# **_6. Concluding Remarks_**

This paper provides an extension of the Human Capital Index that makes it more relevant for the education and health challenges faced by countries in Europe and Central Asia. Specifically, the extension incorporates two elements that are particularly important for the region. First, there is an additional focus on quality adjusted years of tertiary education, in addition to basic education. Second, health status is captured by including risk factors such as obesity, smoking and heavy alcohol consumption, all of which are prevalent in the region. This exercise highlights the importance of investing in tertiary education for many countries in the region, as well as the importance of preventing risk
initiated by the United Nations led to the preparation of guidelines for refugee and IDP statistics including poverty statistics. The United Nations Statistical Commission (UNSC) established in 2016 an international Expert Group on Refugee and Internally Displaced Persons Statistics (EGRIS) made of national and international organizations and several expert statisticians. This process has produced two main documents: The International Recommendations on Refugee Statistics (EGRIS, 2018), and the International Recommendations on IDP Statistics (EGRIS, 2020).<sup>13</sup> The first document recommends measuring the proportion of population below the international poverty line among the social inclusion indicators (indicator 1.1.1), and the second document recommends measuring the proportion of population living below the national poverty line among the livelihoods and economic self-reliance indicators (indicator 1.2.1). While not specifically focused on poverty, these documents recognize the importance of measuring poverty among FDPs and provide general indications on the indexes to measure and the data necessary to measure such indexes. In 2022, monetary poverty was identified as one of the 12 priority SDG indicators that should be measured and disaggregated for both refugees and IDPs (UNHCR, 2020), with the recommendation being picked up by the IAEG-SDG (2019). As already mentioned, the UNHCR has started to introduce standards for the measurement of well-being of FDPs while the new World Bank-UNHCR Joint Data Center established in Copenhagen is expected to develop and fund further methodological advancements as well as playing a pivotal role in the production of poverty data for displaced populations especially through National Statistics Offices. Also other organizations such as WFP and IOM are developing their own standards for surveying FDPs and measuring various well-being indicators.

# Conclusion

The paper provided a first insight into the state of the literature on the measurement of poverty among FDPs. We argued that the economics profession and poverty specialists across the social sciences largely neglected these populations for a combination of factors including lack of interest and microdata. This changed with the beginning of the Syrian conflict in 2011 and the peak
percent in 2017. Hence, a potential U.S. disengagement from the world trading system will not have the same level of disruptive effects. Nevertheless, the United States, Europe, and China still account for about half of current world trade. So, the current disputes that involve these countries are expected to have significant spillovers on the rest of the world. As globalization boosted the integration of developing countries in the world economy, would the trade diversion resulting from the trade war benefit these countries? Or would GVC linkages in which developing countries provide more and more inputs to world trade hurt them instead? Are retaliatory measures justified, or should developing countries pursue trade liberalization measures? These are the questions the simulations seek to answer.

# **3 Methodology**

The analysis uses the GLOBE computable general equilibrium model calibrated to version 9 of the data of the Global Trade Analysis Project (GTAP) with 2011 as the base year. The model is comparative static and is a member of a family of CGE models that model trade relationships using principles described in the 1-2-3 model (de Melo and Robinson 1989; Devarajan et al. 1990) and standard multi-sectoral versions for developing countries (Dervis, de Melo, and Robinson 1982).

A range of possible developing country strategies is compared to the baseline scenario, capturing the marginal effects of different counterfactual scenarios. This ex-ante approach follows the rich tradition of using CGE analysis to examine policy issues in developing countries, such as the long-term effects of international trade agreements like the Doha Development Round (Hertel et al. 2009), effects of global protectionism (Kutlina-Dimitrova and Lakatos 2017), disintegration of NAFTA (Robinson and Thierfelder 2018), stress-testing Africa’s growth and poverty performance (Devarajan et al. 2011), trade reform in India (Go and Mitra 1999) or carbon tax and climate change in South Africa (Devarajan et al. 2011).

For the analysis, the world is divided into 18 regions. We define 16 sectors (see Table 2
<!-- Start of picture text --> We begin with an illustration of the mapping algorithm that we have used for this exercise. Figure 1<br>range includes areas in Argentina, Chile, Bolivia and Peru. Figure 1(a) presents an expert range map for<br>Lagidium viscacia developed by Burgin et al. (2020). Figure 1(b) shows the locations of the GBIF occurrence<br>reports used for our mapping exercise. The two figures show that reported sightings of this species include<br>the Burgin map but extends its northern and southern boundary areas to incorporate these sightings.<br>The mapping algorithm is a byproduct of recent research on machine-based pattern recognition, cluster<br>analysis and image processing. Formally, it addresses a problem in computational geometry: efficient<br>bounding of a spatial set, given a subset of points that are actually observed. Sets with irregular shapes<br>are poorly represented by traditional algorithms that draw simple convex hulls.<br>continuous non-convex boundaries for efficient representation. This powerful property has motivated<br>rapid adoption of alphahull for species range analysis in the recent professional literature (Kass et al. 2022;<br>Of the 610,694 species in our database, alphahull successfully estimates occurrence maps for 92.9%<br>occurrence reports into spatial clusters and draw a convex hull around each cluster. Overall, our algorithms<br>estimate occurrence maps for more than 560,000 terrestrial species and more than 41,000 marine species.<br>To our knowledge, this is the largest set of species maps that have been estimated from open-source data.<br>Our estimation algorithms are designed to support expansion of GBIF species maps with the continuing<br>As an illustration, Figure 1(c) displays the algorithm’s application to GBIF occurrence reports for Lagidium<br>viscacia. The alphahull boundary follows the curvilinear north-south orientation ofthe point set
Survey Measurement Errors and the Assessment of the Relationship between Yields and Inputs in Smallholder Farming Systems: Evidence from Mali<sup>_∗_</sup> Isma ̈el Yacoubou Djima<sup>_†‡§_</sup> Talip Kilic<sup>_§_</sup> `ismael.yacouboudjima@psemail.eu tkilic@worldbank.org`

**JEL Codes:** C53, C83, Q12.

**Keywords:** Agricultural development; Smallholder farming; Agricultural inputs; Crop yields; Measurement error; Crop cutting; Machine learning; Household surveys; Mali; Sub-Saharan Africa.

> _∗_ The authors would like to thank (i) Karen Macours, Sylvie Lambert, Luc Behaghel, David Rhys Bernard, Sydney Gourlay, and the participants of the World Bank Living Standards Measurement Study (LSMS) Internal Seminar and the Casual Friday Development Seminar at the Paris School of Economics for their comments on the earlier drafts, (ii) ICRISAT-Mali for the successful implementation of the ERIVaS methodological survey experiment, and (iii) Berenger Djoumessi Tiague for his research assistance. We are grateful for the funding from the Mali Mission of the United States Agency for International Development (USAID) for the implementation of the LSMS–Integrated Surveys on Agriculture (LSMS-ISA)-supported surveys in Mali, including ERIVaS. This paper was produced with the financial support from the World Bank LSMS Program (worldbank.org/lsms) and the 50x2030 Initiative to Close the Agricultural Data Gap (50x2030.org), a multi-partner program that seeks to bridge the global agricultural data gap by transforming data systems in 50 countries in Africa, Asia, the Middle East and Latin America by 2030.

> _†_ Corresponding author.

> _‡_ PhD Candidate, Paris School of Economics.

> _§_ Living Standards Measurement Study (LSMS), Development Data Group, World Bank.