rafmacalaba/data-use-mentions-extended huggingface dataset:
From 2010 to 2011, food stress probability and the affected population rose sharply, peaking during the global food price crisis. After stabilizing in mid-2011, food stress declined from 2012 to 2014, reaching a low in 2013, reflecting economic stabilization and better climatic conditions. Starting in 2015, the model estimates show a sharp rise, with peaks in 2016 and 2017 that align with FEWS NET trends, climatic shocks, and political instability.

From 2018 onward, the model indicates worsening food insecurity, with consistently high food stress from 2019 to 2022. These levels highlight Afghanistan's ongoing challenges, driven by conflict, economic disruptions, and adverse climatic events. After 2022, a slight improvement in food stress aligns with a stabilizing exchange rate and lower food and fuel prices. FEWS NET data during this period are interpolated due to the absence of assessments between June 2021 and February 2023.

The bottom panel of Figure 6 shows sharper fluctuations in food crisis risks compared to food stress. The model reveals significant volatility from 2016 to 2020, coinciding with droughts, conflict, and economic shocks. The left panel shows that food crisis estimates are more variable than food stress estimates, indicating that severe food security shocks are typically shorter. Estimated values spiked during the 2010-2011 global food price crisis, while historical values remained low, possibly due to under-reporting or the model's sensitivity to early warning signs.

Peaks in estimated values during the crises of 2016, 2017, and 2018 demonstrate the model's ability to detect early warnings of risk escalation. From 2019 onward, historical and estimated trends converge, though the model shows higher peaks, capturing extreme events not fully reported. Note that no assessments were caried out between June 2021 and February 2023 and the FEWS NET data is held constant over the period. This suggests the model's utility as a versatile tool for identifying potential crisis escalation before periodic assessment data reflect it.

# 6. Discussion

## 6.1 Joint Effects of Climatic Shocks and Economic Variables

This study analyzed the
# **1 Introduction**

The rise of income inequality and the increasing trend of automation have been preoccupied economists and policy makers alike. International trade and technological progress have received significant attention in the literature as key explanations for the growing wage inequality in advanced economies, by disproportionally favoring the demand for more-skilled workers (Acemoglu and Autor, 2011; Autor and Dorn, 2013; Michaels et al., 2014; Maloney and Molina, 2016; Acemoglu and Restrepo, 2017). Less attention has been given to the role of FDI in labor outcomes in developing countries. FDI may play a key role in technology transfer from advanced economies to developing nations (Baldwin, 2016; Javorcik, 2004, 2015; Gorg and Strobl, 2001). If similar skillbiased technologies are embedded in new greenfield FDI projects, this could lead to a similar trend, with an increase in the wage gap between skilled and unskilled workers among those regions and sectors that proportionally receive more FDI projects.

In this paper we use a novel approach, by merging greenfield project-level FDI data with household surveys, to revisit the effects of FDI on the wage skill premium. Our approach is based on a within-country analysis exploiting both regional and sectoral variation, using Mincer-like wage equations in line with Dix-Carneiro and Kovak (2015). To the best of our knowledge, this method and database have not been used to study the effect of FDI on the skill premium. The analysis aims to determine whether FDI affects income inequality within countries via differential wage effects on skilled and unskilled workers. We focus on seven emerging economies, i.e. Brazil, Colombia, Ethiopia, Mexico, the Philippines, South Africa, and Vietnam, driven by data availability and their relevance as FDI host countries.

The literature linking the skill premium to globalization has been motivated partly by classical trade theory, notably factor-proportion theory. In particular, the StolperSamuelson theorem suggests that the sectoral specialization that comes along with comparative advantage and international trade should increase the returns of the factor 1
response to budget processes and managerial needs than in connection with the analytical agenda. As a result, the relevant information is currently scattered across the World Bank.

A contribution of this paper is to painstakingly match entries from three self-standing digital platforms to assemble a consolidated database of knowledge-related World Bank work. One of the platforms is a filing system for documents of all sorts, another one contains information on each of the budget codes the World Bank uses, and the third one hosts all the publications it has put in the public domain.

For each of the pieces of knowledge work identified through this matching process, the consolidated database brings together the information available on a broad set of indicators. On the output side, it may report the internal quality rating at completion and the number of downloads over time. On the input side, it may include the name of the task team leader (TTL), the financial resources and time devoted to the task, and the identity of the units in charge of producing it and supervising it. Important gaps remain, as information is not available on all indicators for all entries, but the result is probably the most comprehensive database of World Bank analytical work produced to date.

The analysis in the paper is conducted for knowledge-related documents completed between July 1<sup>st</sup> , 2015, and June 30, 2019. This choice is determined by the stability of the rules guiding the preparation of analytical work during that four-year period. Indeed, most knowledge-related tasks in the World Bank were by then under the management of central units. These included the research department – or DEC, for Development Economics – as in the past, but also 14 Global Practices introduced on July 1, 2014, as part of a major institutional reorganization. A significant departure from this centralized approach to knowledge generation was six relatively small regional Chief Economist offices, which continued preparing analytical products for the country groupings they served.

This period was also characterized by a relative stability of other relevant criteria,
across sectors: among those 4-digit sectors where the estimated coefficients are statistically significant, the productivity growth dividends of a 10 percent decrease in markup vary from 7.01 percentage points to 0.16 percentage points, respectively, for NACE sector 1041– Manufacture of oil and fats and sector 4649–Wholesale of other household goods (figure 15).<sup>35</sup> Productivity dividends from a potential markup reduction are also positive in sectors where the top decile firms in the markup distribution are overly represented; for instance, in sector 4711– Retail sale in non-specialized stores with food, beverages or tobacco predominating, a 10 percent decrease of average markup would be associated with an increase in TFPR growth of 0.22 percentage points per year. For sector 4690–Non-specialized wholesale trade and sector 4673–Wholesale of wood, construction materials and sanitary equipment, the productivity dividends would be 0.18 and 0.21 percentage points, respectively.

**Figure 15. Productivity (TFPR) growth dividends from a 10 percent reduction of average markup: Results by NACE 4-digit sector**

<!-- Start of picture text --> 8.0<br>7.0<br>6.0<br>5.0<br>4.0<br>3.0<br>2.0<br>1.0<br>0.0<br>Percentage points per year<br><!-- End of picture text --> _Source:_ World Bank staff calculations based on SBS data set.

> 35 There are, however, some sectors where markup reduction brings detrimental impacts to productivity expansion. See complete set of results in table A1.8in annex 1, for instance, in NACE sector 8010–Private security activities and sector 2432–Precious metals production, where a reduction of average markup in the 2008–17 period would imply a decrease of TFPR growth of 0.30 percentage points and 6.
# **2 Data and Descriptive Statistics**

This paper is based on a unique firm-level data set that resulted from merging three different sources of information in Brazil: 1) the _Rela ̧c ̃oes Anual de Informa ̧c ̃oes Sociais_ (RAIS), a linked employer-employee data set from the Brazilian Ministry of Labor;<sup>7</sup> 2) the SECEX/MDIC data set, which provides firms’ exporting status and 3) the Peiex data, identifying the firms that received assistance from Peiex.<sup>8</sup> The database was merged using a unique identifier at the firm level.<sup>9</sup> It covers the period between 2006 to 2010. We focused on manufacturing firms and adopted the sectoral definition of CNAE 2.0 (Portuguese acronym for National Economic Activity Classification) that is equivalent to the International Standard Industrial Classification of All Economic Activities (ISIC, Rev.4.).<sup>10</sup> Also, given that for the analysis we need information on firms for at least two subsequent years, we kept firms that are in RAIS for at least 2 years.<sup>11</sup> We measure firms’ organization following Caliendo et al. (2012) and Helpman et al. (2012) to classify the number of layers. We use the _Classifica ̧c ̃ao Brasileira de Ocupa ̧c ̃ao_ (CBO) definition of occupation, which is composed by 9 different categories according to similar level of authority and/or competencies.<sup>12</sup> Table 1 describes the original categories and the way we aggregated them for the analysis. This classification was used to define the number of “knowledge-based” layers in each firm. If a firm has employees belonging to only one of these categories (e.g. blue collars), this firm will have no layers of knowledge. If there are employees in two of these categories (
>Rwanda<br>Nigeria<br>Bhutan<br>Dominican Republic<br>Bangladesh<br>Egypt<br>Nepal<br>Uruguay<br>Vietnam<br>Madagascar<br>North Macedonia<br>Mauritania<br>Afghanistan<br>Hungary<br>Slovenia<br>Sri Lanka<br>Montenegro<br>Poland<br>Indonesia<br>Chile<br><!-- End of picture text --> <!-- Start of picture text --> 0%<br><!-- End of picture text --> <!-- Start of picture text --> 10%<br><!-- End of picture text --> <!-- Start of picture text --> 20%<br><!-- End of picture text --> <!-- Start of picture text --> 30%<br><!-- End of picture text --> <!-- Start of picture text --> 40%<br><!-- End of picture text --> <!-- Start of picture text --> 50%<br><!-- End of picture text --> <!-- Start of picture text --> 60%<br><!-- End of picture text --> <!-- Start of picture text --> 70%<br><!-- End of picture text --> <!-- Start of picture text --> 80%<br><!-- End of picture text --> <!-- Start of picture text --> 90%<br><!-- End of picture text --> Source: Authors’ elaboration based on ORBIS data and BOS database We find that omission error varies significantly
.1.1), estimates of the growth rate of consumption using the

> 17 Deaton (2005) argues that when rich households are less likely to cooperate with the survey than poor people, survey-based estimates of consumption will understate mean consumption. On the other hand, various differences with national accounts estimates can overstate the rate of growth of average consumption, both over time in poor countries, and in comparisons between poor and rich countries at a moment in time. This finding also concurs with the results from an earlier study by Ravallion (2003).

> 18 We provide a similar figure for some other countries, including Bangladesh, Indonesia, Nigeria, and Turkey (Appendix 2, Figure 2.1). All these countries, except for Indonesia, saw their GDP per capita grow faster than the survey mean in the period under consideration. Moreover, for Nigeria, the growth rate of the survey mean is even negative while that of GDP per capita is positive.

18
Colombia Mayor, which puts them at 718,376 and 1,259,004, respectively. The data of the 2013 round of the Encuesta Nacional de Calidad de Vida (National Survey of Quality of Life, ENCV) used in the analysis were collected during September and October of 2013. The Consorcio Colombia Mayor also provided us with figures for October of 2013, putting the number of beneficiaries at 1,012,724. The numbers implied by the ENCV are a little lower, but not by much. A weighted total of the number of beneficiaries declared by each household yields 828,738 beneficiaries. If most of the program’s expansion occurred in the second half of the year, this calculation seems fairly reasonable.

Table 1 presents this last total, together with other estimates of the target population that are also derived as weighted totals from the 2013 round of the ENCV. We present totals for different agegroups and subgroups by socioeconomic status. The first age-groups refer to the minimum age of eligibility for the program (52 or older for women, 57 or older for men), followed by the 60–65 agegroup. For socioeconomic status, we first consider whether an appropriately aged person would qualify for the benefit based on the household’s Sisben score. We have also created indicators for whether a household’s per capita income puts it below Colombia’s poverty line and below the extreme poverty line (indigence). For this, we followed the Ministry of Labor’s own methodology.<sup>3</sup> The main insight is that the total number of the poor in each age-group is only slightly lower than the number of people living beneath the Sisben eligibility threshold. This bodes well for the Sisben criterion in providing a good proxy for poverty. Moreover, given the enrollment numbers supplied by the ministry, the poor 65 years of age or older should be largely covered.

**Table 1: Estimates of the Target Population according to ENCV 2013**

|Total beneficiaries
La Porta et al. (1998a, b), Lins and Servaes (1998) and Claessens et al. (1998a, b)). As our starting point for the data collection, we use the Worldscope database, which generally provides the names and holdings of large owners. Worldscope has over 8,000 publicly-traded firms in the nine East Asian countries, but only 2,300 companies provide detailed ownership information. We supplement the data with information from the Asian Company Handbook 1999, the Japan Company Handbook 1999, the 1997 Annual Reports of the Hong Kong, Jakarta, Seoul, Kuala Lumpur, and Manila Stock Exchanges, as well as with ownership data from the Korean Fair Trade Commission, the Securities Exchange of Thailand Companies Handbook (1998), and the Singapore Investment Guide (1998). We exclude 852 companies across the nine countries, which have proxy ownership that cannot be traced to a specific owner. In all cases, we collect the ownership structure as of December 1996 or the end of the 1996 accounting year. We end up with 2,980 companies for which have complete ownership information and where we can trace the ultimate owners.

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Policy Research Working Paper 8979

# **Abstract**

Using administrative data for an exhaustive sample of formally registered firms, reveals that the engagement of Rwandan firms in global value chains (GVCs) is remarkably limited. The paper documents several patterns of firm-level exports and compares firm characteristics between exporters and non-exporters. It also illustrates which firm-level characteristics are good predictors for a variety of extensive margins of export and import activities. The analysis includes firms from three goods-producing sectors, agriculture, mining, and manufacturing, but focuses mostly on manufacturing firms. The results indicate large differences between small and large exporters in terms of export market participation, type of products exported, and destinations served. GVC engagement has increased over the 2008– 2016 sample period, especially for manufacturing firms, but this is a slow process with frequent set-backs.

This paper is a product of the Office of the Chief Economist, Africa Region, commissioned as part of the _‘Industrialization for Jobs in Africa’_ regional study. 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 jo.vanbiesebroeck@kuleuven.be or garth.frazer@rotman.utoronto.ca.

_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
Results from the product-country relationship survival analysis show that the failure rate of exports and imports increased during both domestic and external lockdowns, but differences between sea and air freight trade were minimal. Notably, imports subject to NTMs had lower survival rates during both domestic and external lockdowns, especially those subject to port of entry restrictions and import approvals. Event-study results show that overall, imports were more negatively affected by lockdown policies than exports, which recovered during the sample period, unlike imports. The decline in imports was mainly attributed to lockdown policies by Indonesia’s trade partners. These affected imports entering Indonesia by air more than those entering by sea, mainly attributed to restrictions on international travel which limited the availability of air cargo during the pandemic. Imports subject to port of entry restrictions and pre-shipment inspections were also more negatively affected, which seem to have worsened the supply side factors for imports.

On the other hand, Indonesia’s lockdown policies on imports mainly negatively affected intermediate imports subject to NTMs, especially measures requiring physical inspection and testing (such as certification with Indonesian product standards or _Standar Nasional Indonesia_ (SNI)) and import approval processes. As for exports, domestic lockdowns had a mixed and large impact on air exports, but not sea exports, while external lockdowns affected sea and air exports relatively evenly.

These results suggest that supply factors had a larger role in the impact of external lockdowns on imports than demand factors related to the COVID-19 shock. However, NTMs on Indonesia’s imports exacerbated the impact of demand factors for imports. Meanwhile, demand factors (specifically workplace closures which imply lower or no income, and stay at home orders) in the partner countries were the drivers for the slump in exports. Enhanced – trade facilitation to keep goods moving as smoothly as possible including reforming burdensome non-tariff measures, improving customs and other procedures - would ensure fewer disruptions from shocks in a globally integrated world. These would also ensure that port inspections and procedures that necessitate port of entry restrictions are conducted more 2
;

- elaborating plans of water management for the territory of the state (i.e., lands beyond the jurisdictional reach of the RWMAs), taking into consideration the river basin divisions;

- drafting flood protection and drought mitigation plans on the territory of the state;

- keeping a water cadastre for the nation, taking into consideration the division into the river basin districts;

- approving projects concerning water use in the river basins;

- supervising the operation of hydro-meteorological and hydrogeological surveys;

- representing the State Treasury with respect to property related to water management and in particular, overseeing the performance of tasks related to maintenance of waters or water works; and

- adjusting, with respect to matters related to water management, draft lists of priority projects of the National Fund for Environmental Protection and Water Management.

> 10 These councils are to consist of about 30 persons, with half of them being water users.  The others would be representatives of various self-governmental/administrative bodies (e.g., provincial and/or local offices) and of other organizations.  The regulations for the establishment of these regional advisory councils were finalized in December 2002, so they have just been created recently.

17
Driest<br>Quarter|1km2|Bioclim (Hi-<br>jmans et al.<br>2005)|
|oxmap<br>~~d~~aylst|Day time land surface tem-<br>perature (Celcius)|5km2|MOD11A2 and<br>Weiss et al.<br>(2014)|
|oxmap<br>~~n~~gtlst|Night time land surface<br>temperature (Celcius)|5km2|MOD11A2 and<br>Weiss et al.<br>(2014)|

18
economic activity in the base wave of a pair, new enterprises in the subsequent wave. We further consider – among enterprises that survived across a pair of waves – the dynamics of (in)formalization, that is, changing formality status between the base and subsequent wave. We also consider, again among surviving enterprises across a pair of waves, employment growth, specifically whether the total number of workers in the enterprise is larger in the subsequent period than it was in the base period.

# **3. Methods**

# **3.1. Situating our universe of firms and employment**

We begin our analyses by situating our focus – private non-agricultural establishments with 1-24 workers – within the landscape of employment in Egypt. We describe the percentage of employment and the number of workers in this segment of the economy, in comparison to other sectors. We also describe employment formality by segment; note that this is distinct from firm formality, both in terms of the denominator, and in that, while a firm must be formal to have formal employees, not all employees within a formal firm are necessarily formal.

> 18 The distinction between relatives and non-relatives is not available in 1998 or 2006, so when analyzing dynamics we simply use an indicator for employment outside the household, which is available in all waves.

7