rafmacalaba/data-use-mentions-extended huggingface dataset:
The global financial crisis, well under way by the third quarter of 2008, did not originate in the developing world. It sparked immediate concerns, however, that its effects would be felt widely, particularly in those economies in which a substantial share of the workforce was engaged in export-oriented activities. China met the onset of the crisis with a strong fiscal stimulus program, coupled with active labor market policies, aimed both at providing training to laid-off migrant workers and at supporting the medium- and small-scale enterprises that were more exposed to shocks from the crisis. This paper reviews evidence on the incidence of shocks related to the financial crisis in China, documents employment effects, and presents evidence of the recovery in 2009.

# **1. Analyzing the Effects of the Crisis**

The lack of publicly available and nationally representative firm, labor force, and household surveys complicates an analysis of the precise effects of the financial crisis on China. Incidental surveys—such as a firm survey carried out by the People’s Bank of China, a rural household survey conducted by China Center for Agricultural Policy (CCAP) at the Chinese Academy of Sciences, and the China Urban Labor Survey (CULS) conducted by the Chinese Academy of Social Sciences—may nonetheless be used in conjunction with information from national surveys and published research to tease out the employment effects of the crisis and recovery. This paper reviews critically the evidence from these sources, with an eye toward highlighting data and measurement issues, while documenting a consistent narrative of crisis and recovery in China.

According to evidence from multiple sources, migrant workers were exposed more than other workers to the financial crisis. Given that migrant workers typically lack the formal employment contracts enjoyed by urban workers, they were easier for firms to dismiss, providing flexibility to employers who needed to reduce costs in the face of crisis-related shocks. As migrants also typically lack the benefits that urban workers have, they were in a much more precarious position with little access to formal safety nets protecting them against unemployment
migration data collection efforts in low- and middle-income origin countries. Despite some recent progress, there is a specific scarcity of longitudinal and long-term data from migration surveys in developing contexts. Identification issues due to the lack of panel data have long hampered empirical progress, so data collection efforts should be primarily focused on tracking individuals over time, either using self-reported data or information from proxy respondents, also to address non-response issues.

From the discussion on the tight nexus between migration and adaptation emphasized in the previous section, there is a strong case for integration, in multi-topic household surveys, between questions on migration and those on risk management, mitigation and coping strategies adopted in response to shock, such as an explicit distinction between voluntary vs involuntary migration, survival vs risk management migration, immobility due to _in-situ_ adaptation vs immobility due to liquidity constraints and inability to move.<sup>10</sup> These nuances and amendments to the existing surveys and modules would greatly enhance the scope for empirical applications in this active area of research, while being relatively low-cost and easy to implement and collect.

As far as short-term, temporary and seasonal migratory flows are concerned, not only should data be longitudinal, but they should also be high-frequency, i.e., they should be collected annually. As emerged from the meta-analysis of Beine and Jeusette (2021), the frequency of the data employed plays a significant role in determining the findings of econometric analyses: data sampled at higher frequencies tend to support the case of an effect on mobility more, since migration measures spread over several years or longer periods are less able to capture short-term migratory flows driven by climatic hazards.

The use of direct measures of mobility, rather than indirect proxies, has often also been stressed as important but remains the exception rather than the rule. Following Beine and Jeusette (2021), an example of direct measure of mobility can be found in survey data where people are directly asked about their migration history, whereas an indirect measurement means that migration is inferred
Policy Research Working Paper 10224

# **Abstract**

Atmospheric methane is a potent greenhouse gas that has accounted for 23 percent of radiative forcing in the lower atmosphere since 1750. Since methane has a much shorter atmospheric duration than carbon dioxide and other greenhouse gases, it provides a critical opportunity for near-term atmospheric greenhouse gas reduction. Thus, 122 countries have joined the recently launched Global Methane Pledge to reduce methane emissions at least 30 percent from 2020 levels by 2030. Unfortunately, the Pledge confronts a serious information problem at the outset: the near-total absence of directly measured data for problem diagnosis, program design, and performance assessment. At present, priority areas for emissions reduction are identified with spatially formatted “bottom-up” emissions inventories, such as the Emissions Database for Global Atmospheric Research, which combines sectoral activity data with broadly calibrated emissions factors from engineering studies. This paper addresses the information problem by introducing a new World Bank database of monthly atmospheric methane concentrations, calculated for a high-resolution spatial grid from data provided by the European Space Agency’s Sentinel-5P satellite platform. It illustrates the potential utility of the database with a global study of methane emissions from irrigated rice production, which accounts for about 10 percent of agricultural methane emissions. A comparative analysis suggests that the Sentinel-5P data supplement the Emissions Database for Global Atmospheric Research data with more fine-grained spatial information, which may support local programs to track, verify, and reward adoption of methane-reducing rice production techniques. If this approach proves valuable for irrigated rice production, it seems likely to work for other methane sources as well.

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 sdasgupta@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings
included to control for monetary policy and exchange rate is included to better understand the transmission process of the trade shocks. It was not possible to add more variables due to data unavailability for many of the ASEAN countries.

GDP growth and trade data were collected from Oxford Economics and the IMF’s IFS dataset respectively. Since this paper investigates the spillover effects via the trade channel, it is important to define the trade variable correctly. Trade data for each country is the sum of the value of exports and imports of that country with other countries in the sample. Rather than using total trade data with all the countries of the world, using data specific to the countries in the sample helps to isolate the effects of trade within this region. Many analysts focus on the value of the trade balance (difference between exports and imports) of a country rather than using total trade (sum of exports and imports). However, the trade balance can be a poor indicator of the overall economic prosperity in the region. Trade, whether it is exports or imports, allows each nation to concentrate its labor, capital, and other resources on the economic pursuits at which it is most productive relative to other countries. This helps to generate greater output in the region which is shared by its participants, even though the effect on the trade balance might be negative in some countries. This is why total trade is used in this paper instead of the trade balance.

Real effective exchange rate data for China, Japan, Indonesia, Malaysia, the Philippines, Singapore and Thailand are taken from IMF’s IFS dataset. For other countries, exchange rate in terms of the US dollar is used as a proxy of the real effective exchange rate due to data unavailability. The source of short term interest data is OECD and Oxford Economics for China, Japan, Indonesia, Malaysia, the Philippines, Singapore and Thailand. For others the lending rate is used as a proxy for the short term interest rate and they are collected from the
# **1 Introduction**

Following the implementation of lockdown policies in March 2020 in response to the COVID-19 pandemic, governments and international organizations predicted a massive decline in remittances. As of April 2020, remittances to developing countries were expected to fall by 20 percent during the year due to the unprecedented slowdown in economic activity in remitting countries and a disproportionate increase in unemployment among migrants (World Bank, 2020; Capps et al., 2020; Garrote Sanchez et al., 2020; Caruso et al., 2021). Instead, formal remittances to several developing countries grew at unprecedented rates.<sup>1</sup> Given the high unemployment rates in remitting economies since the start of the pandemic, these patterns are difficult to reconcile with the literature about the determinants of remittance flows (Ratha et al., 2007; Frankel, 2011; Gupta, 2006). In contrast, household survey data show that most recipient households in Latin America reported a drop in remittances during 2020.<sup>2</sup> Unlike official estimates, these survey data more likely capture the change in both formal (also known as “registered,” “recorded,” and “electronic”) and informal remittances, since they rely on actual individual responses rather than only on data from electronic transfers.

In this paper, we suggest that a shift from informal to formal channels during the economic crisis caused by COVID-19 partly explains the increase in formal remittances coupled with the decline reported in household surveys. Since official remittance data sources often struggle to accurately measure informal remittances—that is, cash carried by hand or sent through other informal channels—a shift in the composition of remittances from informal to formal may be misleading as to the actual change in total remittances. It is challenging to estimate the number of informal remittances as they involve many transactions of minor value that are not recorded anywhere and thus easily go undetected.<sup>3</sup> However, scholars have argued that trends in formal
largest manufacturing industry in India, accounting for 22% of manufacturing employment. The fourth panel shows the management scores for the 232 textile firms in the BVR Indian sample, which look very similar to Indian manufacturing in general.

Within textiles, our experiment was carried out on 28 plants operated by 17 firms in the woven cotton fabric industry. These plants weave cotton yarn into cotton fabric for suits, shirts and home furnishing. They purchase yarn from upstream spinning firms and send their fabric to downstream dyeing and processing firms. As shown in the bottom panel of Figure 1, the 17 firms involved had an average BVR management score of 2.60, very similar to the rest of Indian manufacturing. Hence, our particular sample of 17 Indian firms also appears broadly similar in terms of management practices to manufacturing firms in developing countries.

# **_II.B. The selection of firms for the field experiment_**

The sample firms were randomly chosen from the population of all publicly and privately owned textile firms in Maharashtra, based on lists provided by the Ministry of Corporate Affairs.<sup>6</sup> We restricted attention to firms with between 100 to 1000 employees to focus on larger firms but avoided multinationals. Geographically we focused on firms in the towns of Tarapur and Umbergaon (the largest two textile towns in the area) since this reduced the travel time for the consultants. This yielded a sample of 66 potential subject firms.

All of these 66 firms were then contacted by telephone by our partnering international consulting firm. They offered free consulting, funded by Stanford University and the World Bank, as part of a management research project. We paid for the consulting services to ensure that we controlled the intervention and could provide a homogeneous management treatment to all firms. We were concerned that if the firms made any co-payments they might have tried to direct the consulting, for example asking for help on marketing or finance.

Of this group of firms, 34 expressed an interest in the project and were given a
continued increasing. Using the database presented in this paper, Demirgüç-Kunt et al. (2020) show that measures of liquidity support, borrower assistance, and monetary easing moderated the adverse impact of the pandemic on banks’ stock prices. However, the effect is heterogeneous across banks and countries. Banks that were already undercapitalized and/or operated in countries with little fiscal space were adversely affected by borrower assistance and prudential measures. Finally, there is not much evidence on the effect of emergency prudential regulations and banks’ internal policies on banks per se. Bergant and Kockerols (2020) show that for the case of Ireland the most common measure taken by banks, that is an increase in drawdown limits of credit lines, was effective in the short run, but no other measure (e.g., suspension of installment payments, the extension of loan maturity, credit rollover, and decrease in interest rates) significantly reduced the probability of default in the long run. Moreover, forbearance and new lending are interlinked, as new lending is subdued because capital and other resources within the bank are allocated to forborne loans. On the contrary, for a sample of European banks, Altavilla et al. (2020) argue that in the absence of funding and capital relief, banks’ ability to supply credit to the real economy would have been severely affected.

The remainder of the paper is structured as follows. Section 2 introduces the COVID-19 Financial Policy Response Database and the policy classification framework. Section 3 describes the methodological approach to analyze the determinants of the policy response and Section 4 documents the empirical results. Section 5 concludes.

# **2 COVID-19 Financial Policy Response Database**

In this paper, we present a new global database that collects financial sector policy measures that have been publicly announced by the governments, central banks, and financial sector authorities in 154 jurisdictions since the outbreak of the COVID-19 pandemic (see Appendix C for the list of countries). The database offers a regularly updated repository of emergency measures, adopted
transformation for the low-income rural economies of SSA. If financial and labor markets worked perfectly, there would be few productivity gains from intersectoral factor migration.

After robust agricultural growth has been established and sustained for some period and the nonagricultural sector has become significant, economies move into an integration phase in which growing agricultural surpluses accelerate growth in the nonagricultural sectors by further mobilizing labor, savings, and tax revenues. The shift in agricultural output from staples towards protein rich foods (meat, dairy), fruits and vegetables<sup>7</sup> and the expansion of agribusiness (storage, transport, processing, wholesale and retail of food), the latter recorded as nonagriculture in the national accounts, are part and parcel of this process (Tschirley et al 2015, Anriquez, 2016). The Asian experience further suggests that poverty reduction is fastest when the agricultural transformation - from staples to non-staples - complements the structural transformation - from agriculture to industry (Huang, 2016). Continued agricultural development depends on increasing integration into the rest of the economy through improved infrastructure and the development of competitive markets.

Obviously, the role of agriculture in an economy’s structural transformation described above heavily depends on the extent of economic integration within the domestic economy and with global markets. With full integration, food imports can in principle enable an economy to skip some of the above stages by redirecting labor directly from agriculture into industry, relying on manufactured export earnings to finance food imports (Dercon 2009, Dercon and Gollin 2014). But that trade-based approach has only worked for a very limited number of small developing countries – such as Hong Kong SAR, China, or Singapore – with reliable ocean port access and thus very low-cost connectivity to global markets. Most SSA countries have large populations distant from ocean ports and therefore must rely on domestic production for the overwhelming majority of their food supply for the foreseeable future. Indeed, during 1980-2009, the percentage of SSA agricultural output consumed within the country in which it was produced never fell below 80
1.5<br>-2.0<br>-2.5<br>1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009<br>GDP Poverty Inequality<br><!-- End of picture text --> Source: Source: own computations based on SEDLAC (CEDLAS and World Bank) and World Development Indicators.

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also expect our results to contribute to the conversation on the costs of the pandemic not only across space, but educational levels. Our findings indicate that the youngest children were the most affected. Given the importance of early childhood and primary education for human capital development, this evidence provides input for policy makers to design interventions that could help mitigate the medium- and long-term consequences of the pandemic ( <mark>Fuchs-Schündeln</mark> _<mark>et al</mark>_ <mark>., 2022)</mark> . Therefore, we hope that this research will be a timely guide for educational policy in Guatemala and other developing countries with similar education systems. While we are unable to study the consequences of the pandemic on learning, documenting that some students were more affected than others is a necessary step to consider when defining recovery policies.

The remainder of this paper is organized as follows. The next section describes trends in educational outcomes in Guatemala before and after the COVID-19 pandemic and introduces the warning index for infection rates developed by the government and used by the Ministry of Education to determine school restrictions on in-person instruction. Section 3 describes the administrative panel data and our selected educational outcomes. Section 4 discusses our identification strategy to estimate the effects of differential exposures to COVID-19. Section 5 presents our findings and tests their robustness. We conclude in Section 6.

# **2. COVID-19 and educational outcome trends in Guatemala**

## _2.1. Changes in educational outcomes before and after the pandemic_

Estimates using Guatemalan administrative records indicate that between-year school dropout increased between 2018 and 2021.<sup>7</sup> While 7.8% of school-age children dropped out in 2019, this

> 7 We define between-year school dropout when a student is observed in one school year but does not appear in the records for the following academic year. This differs from within-year dropout when a student does not finish the current school year. Throughout the remainder of the paper, we refer
# _Elite Capture_

One of the most frequently-raised concerns about locally-run organizations such as the Village Funds is that village elites might “capture” the million-baht windfall and help themselves to the proceeds (Lanjouw and Ravallion 1998; Bardhan and Mookherjee 2000). Well-connected villagers may stand for election to the VF committee, and once there, become self-serving. VF committee members might then pay lower interest rates, obtain larger loans, and/or be more casual about repayment. Alternatively, these benefits might flow disproportionately to the economically privileged, whether or not they serve on the VF management committees.

Despite the temptations, it is plausible that elite capture is unlikely because (i) better-off villagers already have good access to credit, and would not want to jeopardize their credit standing, (ii) if the elite were to appropriate the benefits of the VF, their social standing in the village would fall, (iii) the VF committee is, in principle, accountable to all the adults in the village, and (iv) there is a strong ethic of social solidarity.

The data marshaled in Tables 16 and 17, which are based on the 2010 Socio-Economic Survey, allow us to address the issue of elite capture directly. While just 10% of those in the poorest quintile (as measured by expenditure per capita) have served on a VF committee, 25% of those in the top quintile have done so.

On average, VF committee members paid 5.9% in interest on their VF loans, compared to 5.97% for those who never served. However, a more satisfactory measure is the difference between what a VF committee member in a given village pays (as reported by the individual), and the average interest paid in that village on VF loans. By this measure, VF committee members actually paid 0.015 percentage points _more_ than their peers, although the difference is not statistically significant (p-value of Wald-test is 0.70). VF committee members borrowed 21% more per loan than
accountability framework, states must provide performance data to the Commonwealth and to the general public. The COAG Reform Council will collate data for all states and will publish such statistics and analytical reviews of performance for government and general public use (The Australian Treasury, 2009).

_United States: Race to the Top (RTTT) Competitive Grant Program, 2009_ This $4.35 billion program was launched by President Obama on July 24, 2009 to mark a new federal partnership in education reform with states, districts and unions to accelerate change and boost improvements. The program invites states to apply for financing by undertaking to implement four core interconnected reforms as follows:

> 2 This section is based upon Shah (2009).

27
# **4 Methods**

## **4.1 Calibration**

The raw Purple Air sensor data can have significant biases. Therefore, the data needs to be calibrated. Different calibration equations have been developed for this purpose, including one from the U.S. EPA (Barkjohn _et al._ , 2023) and one from Barkjohn _et al._ (2021). More recently, Jaffe _et al._ (2023) find that while these calibrations perform well under certain conditions, such as urban aerosols and smoke aerosols, they largely underestimate PM under high dust pollution. They present an alternative calibration that involves identifying potential dust events and further adjusting the estimate by a factor of 5.6. We test both the Barkjohn _et al._ (2021) and Jaffe _et al._ (2023) calibrations.

The Barkjohn _et al._ (2021) calibration applies the following equation: The Jaffe 2023 calibration uses a two-step method that applies either the Barkjohn _et al._ (2021) calibration or a variation of it depending on the value of the 0 _._ 3 _μm/_ 5 _μm_ ratio. This is the ratio of the concentration of particles with a diameter of 0.3 micrometers to those with a diameter of 5 micrometers.

- If 0 _._ 3 _μm/_ 5 _μm >_ 190, use the original Barkjohn _et al._ (2021) calibration

- If 0 _._ 3 _μm/_ 5 _μm <_ 190, use the Barkjohn _et al._ (2021) calibration _×_ 5 _._ 6

As one of our low-cost monitors lacks data on levels of particles of size 0 _._ 3 _μ_ m and 5 _μ_ m, a substitution is made. An alternative criterion for identifying dust events is when the PM1/10 ratio < 0.25 (Jaffe _et al._ , 2023). Comparing the two Jaffe specifications, we find that approximately 86% of hourly