rafmacalaba/data-use-mentions-extended huggingface dataset:
Policy Research Working Paper 7755

# **Abstract**

The paper compares the distribution of energy and food subsidies across households and the impact of subsidy reforms on household welfare in the Middle East and North Africa region. The analysis uses a unified model and harmonized household data. The results show that the distribution of subsidies and the welfare effects of subsidy reforms are quite diverse across countries and products. Energy subsidies tend to be pro-rich in terms of absolute amounts, but tend to be more important for the poor in terms of expenditure shares.

Instead, food subsidies are larger for the poor in absolute and relative terms. These findings do not apply everywhere, and the scale of these phenomena are different across countries and products. The welfare effect of a 30 percent reduction in subsidies can be important, especially considering the cumulated effect across products, but the cost of compensating the loss in welfare for the poor is generally low compared with the budget benefits of decreasing subsidies.

This paper is a product of the Poverty and Equity Global Practice Group. 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://econ.worldbank.org. The authors may be contacted at Araar. Abdelkrim@ecn.ulaval.ca and pverme@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
Policy Research Working Paper 6244

# **Abstract**

Using an extraordinarily rich panel dataset from Ghana, this paper explores the nature of self-employment and informality in developing countries through the analysis of self-reported happiness with work and life. Subjective job satisfaction measures allow assessment of the relative desirability of different jobs in ways that, conditional wage comparisons cannot. By exploiting recent advances in mixed (random parameter) ordered probit models, the distribution of subjective well-being across sectors of employment is quantified. There is little evidence for the overall inferiority of the small firm informal sector: there is not a robust average satisfaction premium for formal work vs. self-employment or informal salaried work, and owners of informal firms that employ others are on average significantly happier than workers in the formal private sector. Moreover, the estimated distribution of parameters predicting satisfaction reveal substantial heterogeneity in subjective well-being within sectors that conventional fixed parameter models, such as standard ordered probit models, cannot detect: Whatever the average satisfaction premium in a sector, all job categories contain both relatively happy and disgruntled workers. Specifically, roughly 67, 50, 40 and 59 percent prefer being a small-firm employer, sole proprietor, informal salaried, civic worker respectively, than formal work. Hence, there is a high degree of overlap in the distribution of satisfaction across sectors. The results are robust to the inclusion of fixed effects and alternate measures of satisfaction. Job characteristics, self-perceived autonomy and experimentally elicited measures of attitudes toward risk do not appear to explain these distributional patterns.

This paper is a product of the Macroeconomics and Growth Team, Development Research Group; and the Office of the Chief Economist, Middle East and Northern Africa Region. 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://econ.worldbank.org. The authors may be contacted at wmaloney@ worldbank.org and brijkers@worldbank.org
. input-output table.<sup>42</sup> Additionally, our model controls for three types of tari¤ measures: tari¤s imposed at home on imports of the sector, tari¤s imposed at home on imports of intermediate inputs used by the sector, and tari¤s imposed in destination markets on exports of the sector. The tari¤s draw on a newly constructed database by Felbermayr et al. (2019), which is based on the UN-TRAINS and IDB databases, as well as on WITS import and export data. To compute the three types of tari¤ measures, we draw on tari¤ and trade data at the reporting country-HS6-digit-partner country-year level from WITS.

First, to construct tari¤s imposed at home on imports of the sector we ...rst aggregate tari¤s (taking the simple average) and imports (taking the sum) to the EORA sector level. We then sum imports across countries of origin to obtain import weights which are used to compute tari¤s imposed at home on imports of a sector as a weighted-average tari¤ at the reporting country-EORA sector-year level.

Second, we construct tari¤s imposed at home on imports of intermediate inputs used by the sector as follows. We keep tari¤ data and import data only for HS 6-digit products classi...ed as intermediates according to the UN Broad Economic Categories (BEC) classi-

> 42Nunn uses data on the fraction of each input that is not sold in an organized exchange nor referencepriced according to Rauch (1999) to construct the share of intermediate inputs that require specialized and customized business relationships. Nunn’s contract intensity measure (based on Rauch’s liberal classi...cation) is available at the 3-digit ISIC revision 2 level which is concorded to the eight manufacturing sectors in the EORA database based on industries’verbal descriptions.

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## Policy Research Working Paper 10815

# **Abstract**

Using two decades of granular data on foreign direct investments, this study shows a consistent global rise in the concentration of cross-border investments within fewer multinational firms. This concentration is most prominent in developing economies, reaching record highs in recent years. Structural shifts into services do not stand out as the primary driver of variation in investment concentration across countries and over time. Instead, concentration has grown significantly more in destinations facing high economic uncertainty.

This paper is a product of the International Finance Corporation. It is part of a larger effort by the World Bank Group 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 aragoussis@ifc.org; d.rigo@lse.ac.uk; and gianluca.santoni@cepii.fr. A verified reproducibility package for this paper is available at http://reproducibility.worldbank.org, click **here** for direct access.

<!-- Start of picture text --> TRANSPARENT<br>ANALYSIS<br>G<br>R E<br>N<br>S<br>I P<br>Y E<br>K A<br>C A<br>R P<br>LI R<br>O E<br>O C<br>W R<br>H<br>S<br>P<br><!-- End of picture text --> _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
Policy Research Working Paper 9115

# **Abstract**

Using multiple sources of national- and firm-level data around the world, this paper investigates how the effects of the business environment depend on whether the measure is de jure or de facto, and how business environment effects differ by ownership and size. The paper compares estimates of business environment effects from three data sources, and modifies the priors on the relative importance of various elements of the business environment. Among four aspects of the business environment, at least two sets are robust and a third set does not contradict the other two: access to finance, electricity, internet, and human capital. The effects of de jure business environment indicators on firm performances depend on measures of contract enforcement. Foreign-owned firms benefit more from the maintenance of physical safety and ease in obtaining construction permits, and gain competitive advantage in productivity when domestic infrastructure or access to finance is worse. Relatively small firms benefit more from corruption control, basic and modern infrastructure, human capital, and land access. Relatively large firms benefit more from physical safety. Access to finance is important for the expansion of smaller firms and the productivity of large firms.

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 lxu1@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
coefficients on earnings are mostly indistinguishable from zero except for the month of May, further suggesting a swift recovery of household business performance.<sup>25</sup> Indeed, this clear reversion to the pre-COVID-19 level speaks to the resilience of the informal businesses in Vietnam.

# **5 Conclusion**

In this paper, we document novel stylized facts about entry and exit of household businesses in Vietnam between January 2018 and August 2020, a period covering the onset of the COVID-19 pandemic. The data include monthly information on a universe of household businesses’ (permanent) closure and (temporary) suspension filings. We find that tax-registered household businesses exhibit rates of entry and exit of about 5-6 percent a year. Our unique data set allows us to also document that an additional 25 percent of household businesses suspend their activity during part of a year. In 2020, the suspension rate spiked to 40 percent of registered household businesses.

We combine this high-frequency statistics of household-business closures and suspension with individual working hours and earnings data from the Vietnamese Labor Force Survey to measure the pandemic impacts on the survival of informal businesses—those accounting for over 30 percent of the labor force. Our two econometric methods, an event-study and a difference-in-differences strategy that employs a sectoral face-to-face intensity index as a proxy for businesses’ lockdown exposure, indicate significant damages to both business activities and earnings as soon as the first COVID-19 cases were reported in the country in February 2020. The greatest damage took place in April and May, following the mandatory national lockdown. Suspension and closure fillings surged by over three times the pre-COVID-19 level in April, and workload and income plummeted by more than a quarter. Across sectors, the greatest impacts were observed in accommodation, restaurant, entertainment, and transportation. Firms with a larger baseline in terms of revenue were more likely to shutdown.

Despite enduring such a dramatic impact on business activities and earnings in April and May, household businesses recovered quickly. We find an immediate rebound across both intensive and extensive margins,
incidence of crises. However, data for meaningful cross-country and over-time comparison, such as the Worldwide Governance Indicators (WDI; Kaufmann, Kraay and Mastruzzi 2010), is only available starting in the early 1990s. As a result, most sovereign debt and banking crises as well as many currency crises, which mainly occurred during the 1970s-1980s, will be omitted from the estimation sample. Indeed, the use of WDI data reduces the number of observations by almost a half. Furthermore, most measures of institutional quality are insignificant, while the results on other variables are broadly of the same magnitude, signs and significance as in the baseline specification. Several statistically significant results are counterintuitive and may reflect other omitted factors.

Second, to account for possible nonlinearity of the impact of debt increases on the probability of crises and its dependence on the level of debt, baseline regressions were augmented with squared changes in debt and interactions between a change in debt and the initial level of debt. In most specifications, these new variables are not statistically significant, while other coefficients remain consistent with the findings of the baseline model.

Third, the foreign exchange regime or a shift in foreign currency regime influence the probability of financial distress but in different ways for different types of crises. An EMDE with a fixed exchange rate is more likely to suffer a sovereign debt crisis, while a shift to a flexible exchange rate increases the likelihood of a banking crisis. A currency 13
Guinea); Canadian Domestic (Canada); Continental European Domestic (Austria, Belgium, Bulgaria, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Spain, Sweden, and Switzerland); Indian and Subcontinent (Bangladesh, India, Pakistan, and Sri Lanka); International (Eurobonds and other cross-border issues); Japanese Domestic (Japan); Korean Domestic (South Korea); Latin American Domestic (Argentina, Bolivia, Brazil, Colombia, Costa Rica, Ecuador, Guatemala, Mexico, Panama, Peru, Uruguay, and Venezuela); United States (United States); United Kingdom Domestic (United Kingdom); and Rest of the World (countries not included in other SDC regional sub-databases, such as China). The academic version of SDC to which we have access does not include the Canadian and Korean Domestic sub-databases. Therefore, we exclude all Canadian and South Korean firms from our analysis.

> 12 The results are available upon request.

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being the most frequently selected, followed by drinking water, irrigation, and electricity. Electricity was the most frequently prioritized project.

There is no statistically significant effect of the selection and prioritization procedure on the type of projects that are proposed or selected. However, villages that are assigned to select and prioritize projects by referenda are more likely to prioritize electricity projects (difference is significant at the 1 percent level).

## IV.4. **Villagers’ Satisfaction**

Information on villagers‘ satisfaction comes from a survey administered a year after the start of project implementation. Enumerators revisited the ten randomly-selected households surveyed prior to the village council elections and administered separate questionnaires to both male household heads and a senior woman in the household. The data provide information on 4,666 male respondents and 4,234 female respondents (see Table 2).

To measure villagers‘ satisfaction, we use four perception-based binary indicators from male and female household surveys: (i) respondent disagrees with a recent decision or action of the village leadership; (ii); respondent attributes positive economic changes to actions of the village leadership; (iii) respondent is satisfied with the work of village leaders; (iv) respondent perceives that the household is better off than it was last year.

# V. **Results**

The following sections present the effects of variation in selection procedures on allocation outcomes (IV.1) and villager satisfaction (IV.2).

## V.1. **Effect of Proposal, Selection, and Prioritization Outcomes**

The effect of selection and prioritization procedure on allocation outcomes is estimated using the following conditional fixed effects logit model:

> 14 Schools and health facilities, despite being preferred by relatively large numbers of respondents across the ten sample districts, were very rarely proposed due to the requirement that such project types be coordinated through the respective line ministries.

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**Table 3: Summary statistics**

|**Variable**|**N**|**Mean**|**Std. Dev.**|
|---|---|---|---|
|_Enumerator_||||
|Male|6895|0.353|0.478|
|High education|6693|0.922|0.269|
|Birth year|6895|1988|3|
|Urban|6895|0.610|0.488|
|_Respondent_||||
|Age|6895|44|14|
|Gender|6894|0.490|0.500|
|Single|6893|0.193|0.395|
|Years education|6894|5.814|4.689|
|Household size|6894|8.167|3.461|
|Asset index|6774|3.258|2.416|
|Number of cattle|6889|2.313|5.561|
|Consumes alcohol or tobacco|6889|0.413|0.492|
|Spending on alcohol or tobacco|6799|1543|5437|
|Spending on alcohol or tobacco, conditional|2756|3806|8021|
|Support for opposition party (DP)|6294|1.868|1.282|
|Support for opposition party (FDC)|6404|1.966|1.308|
|Support for national party (NRM)|6753|3.811|0.640|
|Supportforoppositionparty (UPC)|6389|1.905|1.290|

_Source_ : Data for the study comes from a survey of farmers in northern Uganda. The survey was conducted by Innovations for Poverty Action.

_Notes_ : Table reports summary statistics for the full sample.

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# **3. Data**

We use financial and ownership structure variables at the firm level in nine countries at the end of 1996. Our primary data source is the WorldScope database, which contains information on 49 countries. We expanded our sample of firms using the Financial Times Extel database, which contains information on 49 countries. In order to test the significance of corporate ownership, we augmented these data with ownership information from the _Asian Company Handbook 1999_ (1998), the _Japan Company Handbook 1999_ (1998), Securities Exchange of Thailand Company Handbook, and the Singapore Investment Guide.

The combined sample contains income statement, balance sheet, and corporate ownership information for 5,928 firms. We excluded firms in the financial sector because the accounting standards for income and profits for these firms are significantly different from those in the other sectors. In addition, bankruptcy decisions for banks are driven by other factors, such as concerns about the systemic consequences of closures. We also excluded firms for which data required for our empirical tests was missing. After applying these selection criteria, 4,569 firms were available for our empirical analysis.

To identify firms that legally filed for bankruptcy protection, we collected information from the respective stock exchanges. Since the legal definition of bankruptcy is not consistent across the region, we used as a minimum standard that firms filed for legal creditor protection.<sup>3</sup> Table 1 provides descriptive statistics of our sample.

> 3The majority of firms in our sample filed for bankruptcy in the second half of 1998. In Indonesia, the Philippines, and Thailand, the Bankruptcy Code was amended in August, January, and April, respectively. These bankruptcy reforms increased the number of bankruptcy filings by allowing for Chapter 11-type

7
Before the crisis, and unsurprising given the sampling strategy, the main occupation for the interviewed people was commerce, while very few were farmers or shepherds. While most of the civil servants were able to keep their jobs, those working in commerce were badly affected by the crisis. As shown in the left panel of Figure 3, IDPs had the highest employment rate before the crisis, while only around half of the returnees used to work. All groups lost jobs during the displacement. Nevertheless, most returnees <!-- Start of picture text --> Figure 3: Employment rate by group<br>Baseline Follow-up<br>Displaced Refugee Returnee Displaced Refugee Returnee<br>Before crisis R1 R2 R3 R4<br>During displacement R5 R6 R7 R8<br>Once returned R9 R10 R11 R12<br>Analytic weights used<br>Source: LDPS 2014-15<br>1 1<br>.8 .8<br>.6 .6<br>.4 .4<br>Employment rate Employment rate<br>.2 .2<br>0 0<br><!-- End of picture text --> managed to work again once back, and in the last waves (right panel or Figure 3) they reached high employment rates, similar to those for IDPs. On the other hand, employment rates among refugees remained low and actually deteriorated over time. This may be one of the main reasons behind the high willingness to return among this group.

As already pointed out in Etang-Ndip et al. (2015), average asset ownership of the people in the <!-- Start of picture text --> Figure 4: Asset index<br>Displaced Refugee Returnee<br>Before simple Before weighted<br>Now simple Now weighted<br>Source: LDPS 2014-15<br>.6<br>.4<br>Index<br>.2<br>0<br><
# **3.2 Tariffs and Imports Data**

In the empirical part, we consider the effect of PECS, which relaxed EU-RoO among participating countries, on changes in Spokes’ import flows from non-participating countries (RoW) relative to Spokes themselves. For this purpose, we use trade data from the World Integrated Trade Solution (WITS) for 1995 and 2002, which correspond to pre- and post-PECS years. Using these years also allows us to exploit the available tariff information.<sup>9</sup> Our main group of importing countries is composed of the BAFTA and CEFTA members. After eliminating those countries with missing tariff observations for the pre-PECS period, i.e. Bulgaria, the Slovak Republic and Slovenia, we are left with 7 Spoke countries: Czech Republic, Estonia, Hungary, Lithuania, Latvia, Poland and Romania. The set of exporting countries is divided into non-participating countries (RoW), EU15 countries, and Spoke countries. In the period under study, members of EFTA (Iceland, Norway, and Switzerland) and Turkey (for the subset of industrial goods) also joined the PECS. To assess the impact of diagonal cumulation on a more homogeneous group of countries, our benchmark regression does not include EFTA and Turkey in the set of Spokes exporting countries. Nevertheless, these will be included in robustness checks.<sup>10</sup> Table 2 presents descriptive statistics of Spoke countries’ imports from RoW and among themselves. Looking at the total amounts, Spoke countries’ imports from non-participating countries (RoW) increased by 77%. The increase in imports among Spoke countries is much larger, at about 161%.

In the empirical specification, our dependent variable captures product-level changes in each Spoke country’s imports from RoW relative to imports from the Spokes themselves, ∆ _impj,srow −_ ∆ _impj,ss_ . In our data set, imports from RoW retain the by-product’s bilateral dimension, i.e. imports to Estonia at the