rafmacalaba/data-use-mentions-extended huggingface dataset:
in real world applications to conduct design-based validations. The results are expected to provide a guideline to others undertaking small area estimation. The results from design-based validation show that all small area estimation methods represent an improvement, in terms of MSE, over direct estimates. However, given the inherent high level of bias of methods relying solely on aggregate information (see Nguyen, 2012; Lange et al., 2018; Masaki et al., 2020) these should be used with caution and only under certain circumstances.

The paper first presents an overview of the small area estimation methods considered, directing readers who are interested in a more in-depth description to the appropriate sources. Then the model-based simulation design is detailed and results of the simulation experiments are presented. This section is followed by a description of the 2015 Mexican Intra Censal Survey and how it is adapted to represent a census and how samples are drawn from the created census. Results from the design-based simulation experiments are then presented. Finally, conclusions and lessons learned are provided.

# **2 Unit-level models**

The nested error model used for small area estimation by ELL (2003) and Molina and Rao (2010) was originally proposed by Battese, Harter and Fuller (1988) to produce county-level corn and soybean crop area estimates for the U.S. state of Iowa. For the estimation of poverty and welfare, the ELL and MR methods assume the transformed welfare _ych_ for each household _h_ within each location _c_ in the population is linearly related to a 1 _× K_ vector of characteristics (or correlates) _xch_ for that household, according to the nested error model: where _ηc_ and _ech_ are respectively location and household-specific idiosyncratic errors, assumed to be independent from each other, following: where the variances _ση_<sup>2and</sup><sup>_σ_</sup> _e_<sup>2areunknown.Here,</sup><sup>_C_isthenumberoflocationsinwhichthe</sup> population is divided and _Nc_ is the number of households in
applications in lowincome countries, including high-resolution crop type mapping and crop yield estimation, would be important not only for assessing the utility of existing georeferenced household survey data for earth observation research but also informing the design of future large-scale household and farm surveys that can provide the required training and validation data for downstream earth observation efforts.<sup>5</sup> Against this background, this paper addresses several operational and inter-related research questions in the context of high-resolution maize area mapping in Malawi and Ethiopia: 1) what is the minimum volume of household survey data that is required to reach an acceptable level accuracy of a crop classification algorithm? and 2) how does the approach to georeferencing plot locations in household surveys impact the accuracy of the same crop classification algorithm?

> type mapping and yield estimation at the village-level in Konigue commune. Relatedly, Hegarty-Craver et al. (2020) mapped four crop types (maize, beans, bananas, cassava) in Senegal using training data derived from high-resolution UAV imagery which they collected in the field.

> 4 These findings are corroborated by Abay et al. (2019) and Desiere and Jolliffe (2018), in Ethiopia and Uganda, respectively.

> 5 Future large-scale surveys that can be a source of training and validation data for earth observation efforts include surveys that are supported by the 50x2030 Initiative.

3
4.4. The government use of disaster-related finance

A similar government choice needs to be made for the use of the payouts received from an insurance or contingency fund. Payouts enter the government accounts immediately after a disaster. The standard equations in MFMod, including those for government expenditure, are calibrated and estimated using historical data. If the payout were simply added as a government revenue, this estimated use of revenue would determine the use of payouts as well. This is not likely to be a realistic model for the use of disaster payouts.

In principle, it would be possible to estimate the government reaction in terms of expenditure categories empirically from post-disaster data. However, there is insufficient historical data on hurricanes to allow an estimation of the reaction function. For the purposes of the simulations conducted here, the estimated government behavior is overridden for the treatment of payouts and a specific model reaction to an insurance payout is specified. As modeled, post-disaster payout is assumed to be spent only on rebuilding destroyed infrastructure – consistent with the financing assumption.

Since a payout from an insurance or contingency fund is likely to exceed the reconstruction capacity of a country after a large disaster, the rebuilding is assumed to take five years to complete. Alternative spending rules were examined to test the sensitivity of results to this assumption.

11
/10 round. This was then adjusted to 2011 by multiplying by the increase in net per capita income for the state of Gujarat between 2009/10 and 2010/11, which reflected growth of 14% in nominal terms. Since we measure affordability in relation to nominal housing prices, it is important to estimate the income distribution in nominal terms as well. As can be seen in Annex 2, prices of housing appear to be rising more rapidly than incomes for the state as a whole.

To test the slight difference in coverage between the AMC and the Ahmedabad urban area, we generated an expenditure distribution for the AMC area using the poverty mapping methodology prepared for the Planning Commission by the India Development Foundation based on mapping the 2001 census data and the 2004/05 NSS expenditure survey data<sup>33</sup> . To do this, we included those census areas that were outside the AMC in 2001 to obtain census data for 2001 covering the same geographical area as the current AMC. This methodology also permits us to increase the sample size considerably and hence improve the reliability of the estimates. This was compared to the expenditure distribution for the same area in 2004/05 using the NSS data. The difference between the NSS median expenditure for 2004/05 and the AMC estimates for 2004/05 using the poverty mapping methodology is 2.8%, which gives us confidence that we have a reasonably reliable estimate of the NSS expenditure distribution as of 2004/05. Using the NSS data for both 2004/05 and 2009/10, we were able to estimate two different expenditure distributions at two points in time and capture recent developments in the income distribution.

> 33 See Hentschel, Jesko, Jean Olson Lanjouw, Peter Lanjouw, Javier Poggi. (1998). “Combining Census and Survey Data to <u>Study Spatial Dimensions of Poverty and Inequality.”</u> _<u>The World Bank Economic Review</u>_ for a description of this
in non-conflict affected regions for the six months following the event, which gives an indication that these floods prolonged the recovery period for conflict-affected populations.

In conclusion, despite existing methodological constraints, our study demonstrates that the impacts of disasters are significantly more pronounced in conflict settings compared to non-conflict areas. In the next phase of our analysis, we aim to supplement the current 'top-down' approach of assessing disaster impacts through satellite imagery with a 'bottom-up' approach using panel household survey data. By combining both approaches, we will gain insights into household-level impacts and 29
# **5 Bibliography**

<mark>Alene, A.D., Manyong, V.M., Omanya, G.O., Mignouna, H.D., Bokanga, M. and Odhiambo, G.D., 2008. Economic efficiency and supply response of women as farm managers: Comparative evidence from Western Kenya.</mark> _<mark>World Development</mark>_ <mark>,</mark> _<mark>36</mark>_ <mark>(7), pp.1247-1260.</mark> <mark>Blinder, A.S., 1973. Wage discrimination: reduced form and structure estimates.</mark> _<mark>Journal of Human resources</mark>_ <mark>, pp.436-455.</mark> <mark>Carletto, C., Jolliffe, D. and Banerjee, R., 2013. The Emperor has no data! Agricultural statistics in SubSaharan Africa.</mark> _<mark>World Bank Working Paper</mark>_ <mark>.</mark> Carranza, E., Donald, A., Jones, R. and Rouanet, L., 2017. Time and Money: A Study of Labor Constraints for Female Cotton Producers in Cote d'Ivoire. Brief No. 27951. The World Bank.

Chauvin. N. D.. Mulangu. F. and Porto. G.. 2012. Food Production and Consumption Trends in SubSaharan Africa: Prospects for the Transformation of the Agricultural Sector. UNDP Working Paper 2012011.

Chayanov, A.V. 1926 in: D. Thorner et al., eds., The theory of peasant economy (Irwin, Homewood, IL).

<mark>Firpo, S., Fortin, N.M. and Lemieux, T., 2009. Unconditional quantile regressions.</mark> _<mark>Econometrica<
# **1 Introduction**

The COVID-19 crisis has renewed the interest of economists in the determinants of firms’ ability to adjust to economic shocks. A relatively large literature has analyzed different types of firm-level characteristics such as innovation activities, management practices and market power that determine the extent of adjustment to such shocks (Gupta, 2020; Hyun et al., 2020; Ding et al., 2021). Despite yielding important findings on firms’ resilience to shocks, these studies may provide limited guidance to policy makers as many factors that are not directly affected by policies can explain the variations in these characteristics across firms.

In this respect, the role of trade policy is a particularly important gap in the literature, given the increasing connectedness of firms through global value chains. Access to foreign intermediate inputs can increase the amount and quality of firm-level exports by exposing firms to new inputs as well as technologies (Goldberg et al., 2010; Fan et al., 2015; Halpern et al., 2015; Feng et al., 2016). As a result, a firm that is an exporter is also more likely to be an importer. Faced with a sudden change in demand for their goods, exporters need to optimally change their inputs and/ or input sources. To the extent that import measures change the relative costs of such adjustments, they could have a prominent impact on the resilience of to shocks.

This paper helps to fill this gap by examining the role of trade policy, both non-tariff measures (NTMs) and tariff measures, in affecting the resilience of exporters to a demand shock. To do so we match novel data on Indonesia’s trade policy measures at a highly disaggregated product level with data on the universe of Indonesian exporters.

While data on import tariffs are relatively more available, a key innovation of this paper is the extensive coverage of NTMs, which represent increasingly important but still under-researched trade policy instruments (Nicita, 2012). Specifically, we address the data limitation by
interruptions. In most countries, some sort of education was provided via TV, radio, or printed copies sent to the families. Furthermore, as in many other sectors, the use of online resources was expanded substantially. Figure 1 summarizes for each Latin American country the provision of offline and online remote learning resources during the pandemic. The axes represent indexes of offline and online learning drawn from Neidhöfer _et al_ . (2021). The offline learning index measures the incidence of strategies channeled through TV, cellphone, radio and printed copies, whereas the online learning index captures the preparedness of schools, teachers, and the education system to provide online learning resources. The graph suggests a positive correlation between the provision of offline and online resources across countries.

# **3. The impact on enrollment**

In this section we exploit harmonized microdata from national household surveys (NHS) to explore changes in the patterns of school enrollment in a large set of Latin American countries. In particular, we make use of recently available microdata from national surveys carried out in 2020, which allows us to study the impact of the pandemic on schooling.

We assess changes in enrollment in all education levels. We hereby compare the year 2020 with around ten years preceding the pandemic and quantify by how much enrollment rates in 2020 are deviating from the previous trend. This analysis sheds light on educational dropouts occurring due to the pandemic. Furthermore, we look at changes in the likelihood of enrollment in private schools that occurred in 2020.

## **3.1. Methodology and data**

The analysis of this section is based on microdata from the official national household surveys of 12 Latin American countries: Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, Mexico, Peru, 5
main _push_ factors highlighted in the literature (Mayda, 2010). Beyond the _push_ and _pull_ factors, country-pair specific characteristics may also affect bilateral migration settlement. In line with the gravity model for migration (Anderson, 2011), the geographic distance between countries has a strong negative effect on bilateral migration, while common culture traits (common language, religion, past colonial links) stimulate bilateral migration (Gross and Schmitt, 2003; Berthélemy et al., 2009). Few papers have tested the role of administrative burden at the border on bilateral migration. An exception is Bertoli and Fernández-Huertas Moraga (2015) who show that visa requirements reduce direct bilateral migration flows by between 40% and 47%. We contribute to this literature by looking at how _changes_ in the administrative burden for international migration affect the international settlement of immigrants.<sup>1</sup> Two papers have tested explicitly the effect of RTAs and visa provision on bilateral migration. Using IMD-OECD bilateral migration flows in the period 1998-2008 for 29 OECD destinations, Orefice (2015) finds a strong positive effect of RTAs and visa provisions on bilateral migration. Figueiredo et al. (2016) add a wider set of destination countries and longer time period to Orefice (2015) and confirm the positive effect of Visa provisions on bilateral migration stocks.<sup>2</sup> This paper adds to Orefice (2015) and Figueiredo et al. (2016) in many ways. First, as in Figueiredo et al. (2016) we rely on bilateral migration _stocks_ to cover a wider set of destination and origin countries, but base our identification on the within variation of migration stocks and signature of RTAs with visa provisions.<sup>3</sup> Second, we use information on the presence of visa-related provisions for a wider set of RTAs: while Orefice (2015) and Figueiredo et al. (2016) rely on a sample of 96 RTAs, the present paper benefits from recent World Bank data on the content
_oases_ have high data demand but little data supply, and _lakes_ have high data demand and high data supply. Nearly two-thirds of low-income countries and countries in Sub-Saharan Africa are oases, suggesting that these countries are getting relatively large evidence from their data supply and that they have relatively little issue with lack of demand, but that they could benefit from increasing the data available to researchers. By contrast, nearly half of countries in Europe are data swamps, suggesting a priority on increasing the use of existing data.

Previous research has highlighted gaps between countries in economic research output and noted that richer countries are the subject of more economic research. For instance, Robinson, Hartley, and Schneider (2006), Das et al. (2013), and Porteous (2020) examine which countries are studied most by economists using the EconLit database. Cameron, Mishra, and Brown (2016) and Sabet and Brown (2018) extend this to note that impact evaluations are highly uneven across countries as well. Phillips and Greene (2022) show conflict research is biased towards Western countries, while Courtioux et al. (2022) show that academic research is highly related to public investments in scientific research.

We contribute to the literature by applying NLP to improve our understanding of what countries are under-researched. Using NLP allows us to go beyond the existing literature in three ways: (1) scale up the sample size and look at all fields of interest rather than only economics, (2) identify papers that use data, which is key to understanding whether data demand or data supply could be explaining a country’s lack of research, and (3) indicate measures countries can take to increase data research.

3
United Nations Statistics Division and UN Women, along with key regional and international agencies including the OECD and the World Bank. The UNEDGE guidelines were also informed by country pilots including the Methodological Experiment on Measuring Asset Ownership from a Gender Perspective (MEXA) in Uganda (Kilic and Moylan, 2016).

> 4 The anonymized unit-record data from all surveys are publicly available on the World Bank Microdata website: <u>https://microdata.worldbank.org/index.php/home</u>

6
ETHIOPIA’S INFRASTRUCTURE: A CONTINENTAL PERSPECTIVE Prices of ICT services in Ethiopia are also very low—except for international calls—and much lower than in the rest of Africa. For example, a standardized monthly basket of mobile telephone services costs $3.37 in Ethiopia compared with the African benchmark of $11.12. Such low tariffs for domestic mobile (and fixed) services seem to be supported by cross subsidies from international call charges, which are substantially higher than the African benchmark. This is because ICT tariffs in Ethiopia have not yet been rebalanced to bring them closer into line with cost structures, a move that most African countries have undertaken to prepare the market for competition. Surprisingly, the low cost of services does not seem to have promoted wider access to these services in Ethiopia.

Ethiopia’s central challenge is to introduce competition to the ICT sector. The Ethiopian market could potentially experience the same explosive growth of GSM coverage as has taken place across Africa. To make the transition, the country needs to modernize the sector’s institutional and regulatory framework, which is among the least developed in Africa. Ethiopia scores only 28 percent on an AICD index of institutional reform that captures the extent to which countries have modernized in terms of sector reform, regulatory framework and governance of state-owned ICT incumbents, compared with around 50 percent for the median African country (figure 10). The key step would be to license a second mobile operator in the market, and eventually additional ones. In addition to accelerating the expansion of GSM coverage, such a move has the potential to raise significant fiscal resources for the government—based on the experience if the 2000s in Africa, the license could potentially raise at least $0.5 billion.

**Table 6. Benchmarking ICT infrastructure**

||Unit|**Ethiopia**|Low-income countries|
|---|---|---|---|
|GSM coverage|% population|**9
1995. Note that expatriate workers (2,023 people in 1995) were subtracted from central government employees.

# **Marshall Islands**

Labor force and population are taken from IMF Report 95/122 of May 26, 1995 and refers to 1994.

# **Micronesia**

Data on paid employment in non-agricultural activities are taken from the United Nation's Statistical Yearbook for Asia and the Pacific 1995 and refer to 1990. Unemployment data are taken from the United Nation's Statistical Yearbook for Asia and the Pacific 1995 and refer to 1990.

GDP, wages and salaries, and per capita GDP estimate (in US $ ) relate to 1994 and are taken from IMF Report No. SM/96/206 of August 6, 1996.

# **Mongolia**

Data on paid employment in non-agricultural activities are taken from the United Nation's Statistical Yearbook for Asia and the Pacific 1995 and refer to 1993. Unemployment data are taken from the United Nation's Statistical Yearbook for Asia and the Pacific 1995 and refer to 1993.

Military employment data include conscripts (estimated at 12,350).

# **Myanmar**

Data on paid employment in non agricultural activities is taken from the ILO's Yearbook of Labor Statistics 1995 and is for 1994. Unemployment data are taken from the ILO's Yearbook of Labor Statistics 1995, refer to 1994 and source IlIl, Code 1: _Employment office statistics_ and do not include persons who are already in employment. Central Government employment is taken from IMF Report No. SW951270 of October 16, 1995 and relates to 199/95. Data includes representative bodies and excludes casual labor. Local Government employment, exclude
al. (2016) to control for the interaction of structural changes with the economic cycle. This makes it possible to illuminate the effect of implementation gaps, which may undermine the effectiveness of reforms. While the literature is mainly concerned with labor market regulation, this analysis focuses on changes in regulatory quality.

Many studies have found that the long-run effects of structural reforms on output are strongly positive. For example, Egert (2018) studied the effects of structural reforms across the three channels on a large set of OECD and non-OECD countries. He found that lower barriers to entry and reduced state control of businesses improve productivity and the use of both capital and labor. Productivity is also affected by the degree of financial development. This is aligned with the findings of Biljanovska and Sandri (2018) and Elkhuizen et al. (2018). Based on a sample of 86 advanced and emerging countries, for instance, Biljanovska and Sandri (2018) demonstrated that structural reforms, including those of the banking sector, have positive effects on productivity growth. Similarly, this study finds that financial development has a positive impact on output growth, and the effect mainly works through capital deepening. In a literature review, Martins (2019) has highlighted the fact that investment in education is among the most critical ways to accelerate structural change—and thus aggregate productivity. In line with these findings, this analysis sheds light on the significant role of human capital and how it affects growth by favoring labor accumulation, productivity, and capital deepening. Also, recently, Rodriguez-Pose and Ketterer (2019) have instead focused on the impact that institutions and improvements in government quality have had for growth and in lagging regions of ECA. Also, IMF (2019), using a newly constructed database on structural reforms, finds that a reform push in areas including governance, domestic and external finance, trade, and labor and product markets could deliver sizable output gains in the medium term.

Timing has become a central issue in the literature on structural reforms.
the<br>0 0.5 1 1.5 2 2.5 organization 3<br><!-- End of picture text --> Source: Authors based on World Management Survey.

# **3 Data and measurement**

The analysis relies on representative data of firms that was newly collected in 2018 by the _World Bank Enterprise Survey_ , covering 650 formally registered non-farm firms with five or more employees.<sup>4</sup> Of these firms, 222 were firms also interviewed as part of the 2007 Enterprise Survey, while the other firms were newly sampled. The 650 firms were randomly sampled from the

> 4 Additional surveys were conducted among 120 formally registered micro-enterprises (with fewer than five employees) and among 554 informal business entrepreneurs. For these enterprises instead of questions on management practices, questions on business practices were asked, based on the methodology by McKenzie & Woodruff (2017). Instead of only management practices, these questions focus on organizational practices more broadly, such as marketing, stock-keeping, record-keeping and financial planning. The evidence for these firms is discussed in Aga et al. (2019).

10