rafmacalaba/data-use-mentions-extended huggingface dataset:
**Table 2. Political-Economy Typologies**

||**Credibility of interte**<br>|**mporal commitment**<br>|
|---|---|---|
|**Political inclusiveness**|Less credible / weaker enforcement|More credible / stronger enforcement|
|Less inclusive /<br>less collectively oriented|**Patrimonial Rule**<br>Individualized political authority, built on a<br>hierarchy of cronyism; emphasis on private<br>(elite) goods; exploitation of public resources<br>for private gain|**Hegemonic Government**<br>Institutionalized one-party regime; either<br>predatory or benevolent; emphasis on<br>private (elite) goods with some particularist<br>and public goods|
|More inclusive /<br>more collectively<br>oriented|**Clientelist Pluralism**<br>Political competition based on extensive use<br>of clientelism; provision of particularist<br>goods; low horizontal accountability|**Programmatic Pluralism**<br>Electoral competition based on programs<br>geared toward collective welfare<br>enhancement; provision of public goods;<br>democratic accountability|

_Source:_ Barma, Kaiser, Le and Vinuela (2011) 21. We draw on proxy indicators to broadly situate the MENA countries at the on-set of the Arab Spring by this typology in Figure 4. This raises questions about what kind of shifts one might want to look out for, and in turn what implications these will have for intertemporal credibility and inclusiveness. Ideally political transitions would see movements over time to programmatic pluralistic democracies (i.e., to the North East quadrant), and the policies associated with them. But as democratic transitions from other regions demonstrate (see Box 1), major regional political transition episodes can yield a significant diversity of associated policies and institutional evolutions. These may also have implications
# The Impact of COVID-19 on Formal Firms: Micro Tax Data Simulations across Countries

Pierre Bachas, Anne Brockmeyer, Camille Semelet<sup>_∗_</sup>

## _JEL classification:_ H25, H32, H61, O12

## _Keywords:_ COVID-19, firms, corporate income tax, wage subsidies, administrative tax data

> _∗_ Pierre Bachas: World Bank Research, pbachas@worldbank.org; Anne Brockmeyer: Institute for Fiscal Studies, University College London and World Bank, abrockmeyer@worldbank.org; Camille Semelet: World Bank Research csemelet@worldbank.org. This work was funded by the World Bank through the Knowledge for Change Trust Fund and the Fiscal Policy and Sustainable Growth Unit and by UKAID through the Centre for Tax Analysis in Developing Countries (TaxDev). The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. We are grateful to the Ministries of Finance and/or Tax Authorities in Albania, Costa Rica, Eswatini, Ethiopia, Guatemala, Montenegro, Rwanda, Senegal, Uganda for their collaboration. We thank Giulia Mascagni, Adrienne Lees, Giovanni Occhiali and Fabrizio Santoro from the International Center for Tax and Development, Tom Harris and Edris Seid from the Institute for Fiscal Studies TaxDev Center and Kyle McNabb from the Overseas Development Institute and the TaxDev Center for an excellent collaboration on the data analysis for Eswatini, Ethiopia, Rwanda and Uganda. We are grateful to Pablo Garriga for excellent research assistance and to Laurent Corthay, Barbara Cunha, Elwyn Davies, Ivan Gachet, Leonardo Iacovone, Milan Lakicevic, Magaly S ́aenz Somarriba, Marc Schiffbauer and Christoph Ungerer for to their generous collaboration and inputs.
Policy Research Working Paper 6137

# **Abstract**

This paper exploits the staggered rollout of Vietnam’s hospital autonomization policy to estimate its impacts on several key health sector outcomes including hospital efficiency, use of hospital care, and out-of-pocket spending. The authors use six years of panel data covering all Vietnam’s public hospitals, and three stacked crosssections of household data. Autonomization probably led to more hospital admissions and outpatient department visits, although the effects are not large. It did not, however, affect bed stocks or bed-occupancy rates. Nor did it increase hospital efficiency. Oddly, despite the volume effects and the unchanged cost structure, the analysis does not find any evidence of autonomization leading to higher total costs. It does, however, find some evidence that autonomization led to higher out-ofpocket spending on hospital care, and higher spending per treatment episode; the effects vary in size depending on the data source and hospital type, but some are quite large—around 20 percent. Autonomy did not apparently affect in-hospital death rates or complications, but in lower-level hospitals it did lead to more intensive style of care, with more lab tests and imaging per case.

This paper is a product of the Human Development and Public Services Team, Development Research 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 author may be contacted at awagstaff@worldbank.org.

_The Impact Evaluation Series has been established in recognition of the importance of impact evaluation studies for World Bank operations and for development in general. The series serves as a vehicle for the dissemination of findings of those studies. Papers in this series are part of the Bank’s Policy Research Working Paper Series. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this
welfare of the top deciles of the distribution. This is principally due to the marginal propensity to consume that declines as household welfare increases (McCarthy 1995; Dynan et al. 2004; Jappelli and Pistaferri 2014; Gandelman 2017). Second, inequality calculated on consumption is likely to be biased downward if the set of goods in the consumption measure does not include items consumed by the rich (Beegle et al. 2016). Third, there may be households with zero annual income who, for example, finance their current spending out of previously accumulated savings, whereas people with zero annual consumption cannot exist. Finally, there are many income-rich people who save a part of their income; thus, their income can be greater than their consumption and, consequently, the high end of the distribution would be more elongated in the case of income (Milanovic 2010). This makes the distribution according to income more “elongated” both around the bottom and the top and thus more unequal: the consumption distribution will be “truncated” at some minimum amount necessary to survive and at the top since not all what households earn will be immediately spent.

Our empirical strategy, first of all, is to present the extent of the problem by conducting a multivariate analysis on a data set of developing and developed countries; this can show, all other things being equal, how much inequality is underestimated in SSA by means of using consumption. In the second part we propose our way to attain a better estimation of inequality in SSA. To our knowledge, this is the most reasonable way to correct the bias, since just substituting consumption with income would require a very expensive upgrade in the capacity of many national statistical offices in SSA and, second, because in many SSA countries’ consumption is still the best indicator for measuring the welfare of many households whose revenues are from the informal sector and very seasonal (Clementi et al. 2020).

# 3.2 Empirical Estimations

Figure 1 illustrates this latter point using data from Povcalnet.
upper- and lower-bound estimates of transitions into or out of poverty at an aggregate level.<sup>4</sup> An appealing feature of the method is that it also allows for delving deeper into the data to construct profiles of the groups who experience the various poverty transitions. We will focus specifically on the composition of the group of chronically poor, comparing the likelihood of chronic poverty along several dimensions, such as ethnicity and geography. The synthetic panel bounds approach has been validated against actual panel data for a range of countries and regions with good results (Dang et al. 2014, Cruces et al. 2015, Perez 2015). In this paper we focus on poverty dynamics in Malaysia as observed over intervals between adjacent survey rounds in the 2004-2016 period.

> 3 See Deaton (1985) for the initial setup of the approach, and Bourguignon et al. (2004) for an application to poverty. Kraay and van der Weide (2019) explore the feasibility of drawing inferences about intragenerational mobility from aggregate macro data.

> 4 We note that a different variant of the synthetic panel method produces point estimates, but applying it was not feasible in our case. We refer to Garces-Urzainqui et al. (2021) for further discussion of the two variants.

3
Global Investment Costs for Coastal Defense through the 21st Century Report to the World Bank 49

# **A.2.3      Pragmatic approaches for improving the global unit cost estimates of sea dikes**

This section discusses a pragmatic approach to improve global unit cost estimates of sea dikes, and the current data limitations to achieve this goal. Dronkers et al. (1990) and Hoozemans et al. (1993) multiplied unit cost estimates of the Netherlands by country unit cost factors to derive unit costs for all countries. More recent unit cost estimates of sea dikes are now available for the Netherlands. Jonkman et al. (2013) report that unit cost estimates of sea dikes range from 4.9 M to 13.5 M euros (2014) for rural areas in the Netherlands, and from 16.9 M to 24.4 M euros for urban areas.<sup>1</sup> One pragmatic approach to derive new rural and urban unit cost estimates at the global level would be to multiply the recent rural and urban unit cost ranges of the Netherlands with the original country unit cost factors. However, we hypothesize that applying the Dutch urban unit cost ranges would lead to an upward bias of unit cost estimates at the global level due to a set of specific circumstances in the Netherlands that have not been reflected in the country cost factors. These include the large national budget available for defense works, the large share of land below sea level, high protection standards, high protected value in rural areas, a strong solidarity which favors protection of rural areas more than in other countries, and the polycentric urban structure. Unfortunately, we cannot statistically test this hypothesis due to the low number of case studies reporting urban unit costs at the country level.

Alternatively, we apply the rural ranges of the Netherlands to the rest of the world by multiplying them with the DIVA country factors and compare the results with unit costs found in available case studies. Table A3 shows this comparison for the United States
the device, 245 students were able to name two, and 208 students were able to name three books (not shown).<sup>14</sup> Most students found the eReader easy and convenient to use. About 63 percent of respondents had to charge their eReaders once or twice a week with 84 percent claiming that charging had little or no impact on their use. More than 75 percent had no problems with eReader features (e.g. marking text, weight of the device, difficulty of use). Around 89 percent claimed difficulty in reading had little or no impact on their use. Safety concerns about device use in public or breakage concerns were limited, however, nearly half of the students used their eReader only at home. Around 84 percent of the sample reported being comfortable with the device; 90 percent claim that their overall experience with the device was positive. Despite this, one-fourth of the respondents claimed that their use of the device was limited because they have a preference for textbooks (27 percent).

Information on eReader usage was also derived from direct extraction of usage statistics from the eReaders themselves. The eReaders used in the experiment (Kindle, version 3.2) allowed for limited extraction of usage data – such as books read/opened, highlights, and notes. Two strategies were followed. First, data were collected by transcribing information from the ‘menu’ of actual eReaders recovered from students at endline. Second, functioning devices were connected to the internet to extract usage data. The extent to which these data can be used for rigorous analysis, however, is constrained by the high rates of device breakage and unavailability. Device status at endline is reported in Table 3.

Around 88 percent of devices showed some sign of physical damage (51 percent of which was damage to the screen). Analyzing usage data from 86 functioning devices stored on the cloud, we find that average number of books read - in the 6-8 months duration of treatment - was 4.
Maluccio 2000; Armand and others 2016). However, Benhassine and others (2015) found that, in Morocco, the gender of the unconditional cash transfer recipient has no differential impact; while Akresh, De Walque, and Kazianga (2016) found better outcomes among children (relative to regional macroeco- nomic conditions) when cash transfers were given to fathers rather than to mothers in Burkina Faso.

Public benefits directly supporting women may also indirectly support the unpaid social reproduction activities that women are often responsible for. However, indirect taxes (such as a value-added tax or an excise tax) on expenditures that women are typically responsible for may both directly reduce the bargaining power of women and indirectly discourage the social reproduction activities in which women are typically involved.

Finally, in many developing countries, women are denied the right to own and inherit a property or other productive assets. Men hold the majority of land and housing titles, and social norms may dictate that businesses are owned by male family members, and women may supply labor to them. Nonetheless, in recent decades, women have made strides in some areas of property ownership, most notably in entrepreneurship and business development. Taxes and transfers can promote or discourage female entrepreneurship and land ownership.

> 16. Neither the inputs to this transaction, the transaction itself, nor the results of the transaction are visible in a typical household survey.

8
coefficient of city FDI per capita and district average foreign ownership is high: 0.44. This should relieve our concern.

Another concern is that the district average foreign ownership is a simple average, which may lead to misleading results if not weighted by firm size. To address this concern, we construct the district average foreign ownership using firm size (i.e., the number of employees) as weight. The weighted foreign ownership is closely correlated with the simple average, with a correlation coefficient of 0.88. Table 4 reports the district level regression corresponding to column (1) of Table 3 but using employment size-weighted foreign share ownership of firms in a district as the dependent variable. The qualitative results are, not surprisingly, very similar.

# **5. Concluding Remarks**

In this paper, we have tried to show that the rule of law is not necessary for a country to attract FDI. In a self-enforcing contract model, we demonstrate that good economic fundamentals can attract FDI inflows in the absence of the rule of law. In fact, they are more important for a country without the rule of law than for countries with it. The model shows that in such a country, a locality can attract more investment by improving economic fundamentals, but not by simply lowering tax rates. The model also implies that a government leader who has a longer-term career horizon and cares about his or her reputation may be able to attract more investment. Our empirical evidence based on data from Chinese cities is largely consistent with the model‟s predictions.

Our paper echoes a number of recent papers that have questioned the fundamental importance of the rule of law in economic growth (Qian, 1999; Glaeser et al., 2004; Rodrik, 2004; Allen, Qian and Qian, 2005; Fan et al., 2009). As we read them, these papers all argue or imply 21
# **Table A2: Variables for the panel local projection models (quarterly data)**

|**Variable**|**Transformation**|**Source**||
|---|---|---|---|
|**Real GDP in local currency, seasonally**<br>**adjusted**|Log first difference|Haver Analytics||
|**Real private consumption expenditure,**<br>**seasonally adjusted**|Log first difference|Haver Analytics||
|**Real gross fixed capital formation, seasonally**<br>**adjusted**|Log first difference|Haver Analytics||
|**Real exports, seasonally adjusted**|Log first difference|Haver Analytics||
|**Headline consumer price index, seasonally**<br>**adjusted**|Log first difference|Haver Analytics||
|**Real effective exchange rate based on 120**<br>**trading partners deflated using consumer**<br>**inflation, not seasonally adjusted**|Log first difference|Darvas<br>(2021);<br>Analytics|Haver|
|**Portfolio (and other) investment liabilities to**<br>**GDP**|NA|International<br>M<br>Fund|onetary|
|**Stock market index**|Log first difference|Haver Analytics||
|**10-year local-currency government bond yield**<br>**(or nearest maturity)**|First difference|Haver Analytics||
|**3-month interest rate (or nearest equivalent)**|First difference|Haver Analytics||
|**EMBI+ spread**|First difference|J.P. Morgan||
|**Primary balance (general government or**<br>**
high impact scenario, the number of poor people rises by 130,000 people in the _poverty_ scenario, and the number of people below 4usd per day rises by 83,000 people. Here again, disasters have nearly no impact on poverty in the _prosperity_ scenario ( Figure 4).

# Health and high temperatures

We now include a set of additional impacts of climate change on health (malaria, diarrhea, and stunting), based on the literature reviewed in chapter 4 in _Shock Waves_ .

For _stunting_ , we include the additional share of children estimated to be stunted because of climate change in 2030. Today in Vietnam 25 to 40% of children under 5 in the three poorest quintiles get stunted. To factor in development, we use data from the Demographic and Health Surveys (DHS) by wealth quintile to explore the relationship between household income and stunting. We find that the prevalence of stunting drops for families whose income is above $8,000 per year. We calculate the fraction of the stunted individuals in the families with income below $8,000, so that stunting prevalence is consistent with data for the current situation. Then, we increase this fraction using projections from (Hales et al. 2014) to account for climate change. We assume that stunted individuals have lifelong earnings reduced by 5 percent (low‐impact scenario) and 15 percent (high‐impact scenario), regardless of employment sector and skill level.

> 3 We use the fraction of people who lose income. We cannot use data on the number of “affected persons” because the usual definition of _affected_ is much broader and includes people who do not lose income because of the disasters.

> 4 Because the analysis proposed in chapter 3 does not include all countries, we assume that poor and non‐poor people are equally exposed to natural disasters.

> 5 Note that the impact of droughts on children through stunting is accounted for in the health impact category.

13
Policy Research Working Paper 9594

# **Abstract**

Is privacy a luxury for the rich world? Remarkably, there is a dearth of literature evaluating whether data privacy is too costly for companies to implement, or too expensive for governments to enforce. This paper is the first to offer a review of surveys of costs of compliance, and to summarize national budgets for enforcement. The study shows that while privacy may indeed prove costly for companies to implement, it is not too costly for governments to enforce. This study will help inform governments as they fashion and implement privacy laws to address the “privacy enforcement gap”—the disparity between the privacy on the books, and the privacy on the ground.

This paper is a product of the World Bank’s _World Development Report 2021_ Team in collaboration with the Macroeconomics, Trade and Investment Global Practice. 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 ac1931@georgetown.edu.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
10.0<br>Gross fixed capital formation (GFCF) (WDI, 2018)<br>GFCF 7‐year average, 2001‐2007 (WDI, 2018) GCF (IMF WEO, April 2011), dashed line indicates estimate/projection<br>Gross capital formation (GCF) (IMF WEO, Oct 2018) GCF 6‐year average, 2011‐2016 (IMF WEO, April 2011)<br>GCF 10‐year average, 2001‐2010 (IMF WEO, Oct 2018)<br>1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016<br><!-- End of picture text -->

> 5 MFMod numbers suggest a slightly lower average of 20.5% over the same period (and 20.1% over 2001‐2010).

> 6 World Bank (2017b) reports I<sup>�</sup> ⁄Y of 9% and private fixed capital formation‐to‐output, I<sup>�</sup> ⁄ Y of 12% in 2010 giving a public investment share of total investment of 43%. Data in IMF (2010) indicate an average share of 38% over 2005‐2008, based on gross capital formation‐to‐output averaging 21.8%. Calculations using the IMF FAD Investment and Capital Stock Database 2017 suggest an average share of 47% over 2001‐2010, but the average value for total investment‐to‐output at 6% is relatively low compared to the other reported values.

5
erences in the evolution of inequality of educational opportunities over these decades? We make some progress on these questions in this section.

Figure 2 presents the estimates of sibling correlation for the six regions dis-aggregated by the decade of birth (1970s-1990s birth cohorts).<sup>35</sup> The rst impression that jumps out of

> 34For a comprehensive discussion on the school expansion in developing countries, see chapter 2 titled The great school expansion- and those it has left behind in World Bank (2018). For recent analysis of the eects of school construction on intergenerational mobility, see Mazumder et al. (2019) and Ahsan et al. (2023).

> 35The countries in a region in Figure 2 may vary from Figure 1, as we included only those countries for which estimates for all three decades are available. For example, Figure 2 does not include Brazil where the last DHS survey was done in 1986, and as a result, we do not have enough observations for the 1980s and 1990s birth cohorts. A cohort-wise graph including all countries can be found in the online appendix.

19