rafmacalaba/data-use-mentions-extended huggingface dataset:
on the underlying distribution of income (ideally microdata), and presents various challenges associated with data quality.

“Progressive capacity” is a type of hybrid approach, producing global metrics of progressivity of income taxes, but attempting to abstract away from the underlying pre-tax income distribution to focus on the tax structure. This approach may be particularly useful for cross-country comparison where the analyst is interested purely in comparing tax rate structures. The approach essentially looks to model the different tax schedules of countries using a common income distribution. A drawback of the approach is that the progressive capacity metrics, and consequent country rankings, are not necessarily invariant to the chosen “base” income distribution. However, recent papers have looked to address this base sensitivity problem, though they rely on strong assumptions.

This paper has examined in detail the merits of different progressivity metrics under each of these three approaches, finding strengths and weaknesses in each approach. An overarching finding is that, due to the various data and other analytical limitations, detailed measurement of the _degree_ of progressivity is limited largely to the PIT, and to a lesser extent, VAT and excise taxes. These taxes, and particularly the PIT, have consequently been the main focus of the paper. However, because of the need to provide an assessment for IDA countries of the progressivity of the entire tax system, the paper has also illustrated how aggregate tax revenue data – which is available for a larger number of countries in a timely manner – can be used to assess the likely degree of progressivity of tax systems in IDA countries.

Given the varying strengths and weaknesses of different approaches, a suite of metrics is proposed to assess tax progressivity in IDA countries over FY23-25. First, aggregate tax revenue-based metrics would be relied upon to provide a basic assessment of the progressivity of the overall tax system. These metrics assess the degree of reliance of countries on direct taxes – on the basis that these are likely to be the predominant sources of progressivity in tax systems. The degree of progressivity of the
.|45|

_Source_ : Dependent variable is from the GWP (Gallup 2011) . The sources of the independent variables are as follows: _World Bank_ , World Bank (2010b) _WDI_ ; _World Bank Povcal_ , World Bank (2010a); _FAO_ ; Food and Agriculture Organization (2011); _DHS_ ; Demographic Health Surveys (2010); _WHO_ , World Health Organization (2010).

_Note_ : *, **, and *** indicate significance at the 10 percent, 5 percent, and 1 percent levels, respectively. All variables are measured in 2005 or the nearest available year. _Log_ indicates that variable is expressed in logarithms to account for a nonlinear relationship. _Excluding outliers_ refers to the exclusion of six countries with the highest prevalence of low-BMI women in the sample, all above 20 percent: India, Bangladesh, Ethiopia, Cambodia, Nepal, and Madagascar. Without this exclusion, the correlation is statistically insignificant. Samples vary in size because of the paucity of some of the poverty and malnutrition indicators.

In table 3, we also show that the GWP food insecurity indicator is significantly explained by “relative food prices,” which is measured as the ratio of the purchasing power parity for food items to the exchange rate (both measured in 2005). This index can be interpreted as the extent to which a country’s food basket is expensive or cheap relative to the costs of importing food 12
xxii,1 (2) where ii denotes the indirect utility function, and ii1 ii1 (. ) the equivalent income function of household . νν(pp , ΓΓ (pp , pp , xx )) = νν(pp , xx Given that all households face the same price 1 , hii(. ) can be considered as a monetary measure of νν(. ) ΓΓ ii utility. 1 ) given that h(. ) is a monotonic transformation of . Inverting the indirect utility pp ΓΓ function, the equivalent income can be derived as: ii1 νν(pp , xx ΓΓ νν(. ) 0 1 (3) Γii0 = Γii 0 1 ii0 ii0 (4) ΓΓ = ΓΓ (pp , pp , xx ) = xx where ii1 ii and ii1 denote pre and post pandemic equivalent incomes, and ii0 ii1 is the equivalent loss. The (pp , pp , xx ) = xx −EELL price effect of the pandemic on household is estimated by the . ii0 ii1 ii1 ΓΓ ΓΓ EELL Suppose that consumer preferences are represented at the Stone-Geary utility function. The ii1 ii EELL corresponding indirect utility function is given by:

> 9 Consumption surveys only provide information on consumption and not income.

12
Single-Family Housing Markets _. Appraisal Journal_ 62, 600-603.

- Rosen, S. (1974). Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition. _Journal of Political Economy_ , 82 (1), 34–55.

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- Uwayezu, E. & de Vries, W. T. (2020) Access to Affordable Houses for the Low-Income Urban Dwellers in Kigali: Analysis Based on Sale Prices. _Land_ <mark>9(3), 2-32.</mark>

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Policy Research Working Paper 10528

# **Abstract**

Using data on the paths of all hurricanes in the Atlantic Basin from 1992 to 2017, this paper studies whether migration has served as a form of adaptation to hurricane risk. The findings show that on average hurricanes have little to no impact on county out-migration, with population-weighted exposure to hurricanes increasing slightly over the sample period. Counties with high economic activity see net in-migration in the years after a hurricane. Further, return migration likely plays a role in offsetting any out-migration in the year of the storm. The intensity of pre-hurricane migration between county pairs is a strong predictor of excess migration after a hurricane, suggesting that existing economic and social ties dominate in post-hurricane migration decisions. Given existing policies and incentives, the economic and social benefits that people derive from living in high-risk areas currently outweigh the incentive to adapt to future storms by relocating across counties.

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 abehrer@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 they represent._ Produced by the Research Support Team
**Figure 4:** Zambia’s opaque external debts, 2010 – 2021

<!-- Start of picture text --> 15<br>Hidden debt (in 2021):<br>12 • USD 3.18bn<br>• 14% of GDP<br>9<br>6<br>3<br>0<br>2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021<br>Initially reported external public debt<br>External public debt added through revisions<br>(USD billion)<br>Public external debt stock<br><!-- End of picture text --> _Notes:_ The figure shows the initially and most recently reported public and publicly guaranteed debt stocks for Zambia between 2010 and 2021 in billion USD. The gray bars show the initially reported debt stocks. The red bars show additional debt stocks added through revisions in subsequent reporting. The data is from our new database (see Section 3 and Appendix A).

revision implies that a sovereign debtor now reports a liability to the World Bank that it had not previously reported.

- All debt instruments enter the World Bank’s debt statistics with their nominal or face value. They are not adjusted for fluctuations in their market value. This implies that ex post data revisions do not reflect valuation changes; rather, they indicate changes in the underlying debt reporting.<sup>14</sup>

- Since the first publication of the World Debt Tables in 1973, the World Bank’s reporting guidelines have essentially remained unchanged. Section B.1 in the appendix provides a systematic comparison of the Debtor Reporting System (DRS) reporting manual over time and confirms that only minimal refinements have occurred over the past four decades.<sup>15</sup> This finding ensures that ex post data revisions do not reflect the evolution of reporting guidelines; rather, they can be traced back to changes in compliance with a stable
_Table 2.6 Synthetic Indicators_ _<u>of Schooling Distribution and Income Profile, 1988, 1997–02</u>_

|_Year _|_1988_|_1992 _|_1996_|_2000_|_2002 _|
|---|---|---|---|---|---|
|_mt_|0.476|0.491|0.511|0.519|0.522|
|_it_|0.066|0.069|0.076|0.077|0.077|
|_st_|0.066|0.102|0.122|0.097|0.080|

_Source:_ Calculations based on the ENEU survey (third quarter).

# 3. METHODOLOGY

The dynamic decomposition analysis is a suitable tool for translating this stylized view into quantitative results, giving one a better understanding of the socioeconomic transformations responsible for changes in the earnings distribution. Besides permitting identification of the relevant individual variables, it also helps in understanding the nature of the contribution of each variable to the evolution of earnings inequality over time.

Ramos (1990), following Shorrocks (1980), shows that it is possible to break down the change in inequality between two points in time. This is done according to whether the change can be attributed to changes in the socioeconomic groups relative to incomes, to group sizes, or to internal inequalities, through use of the Theil T index. In generic terms, as shown before in a slightly different way, for a given partition of the population, the inequality indexes of this class can be written as: where α _g_ is the ratio between the average income of group _g_ and the average income of the whole population, β _g_ is the proportion of the population in group _g_ , and _Ig_ is the internal dispersion of incomes in group _g_ .

Of course, the αs are related to the indicator _st_ in the previous picture, and the βs
Accounting for the respondent’s primary source of information results in a significant increase in the age effect for three out of six questions. The age effect almost doubles for the question of whether climate change is real and whether it is manmade and increases the share of respondents who believe that it will affect their children by about 36 percent. These large and statistically significant changes do not alter the relationships uncovered by our baseline estimations, however; they do not eliminate the positive age gradient in climate change awareness and risk perceptions.

Respondents who plan to move away from their current place of residence, either within their country or abroad, do not exhibit significantly different levels of skepticism regarding the reality of climate change or its anthropogenic character, but they are more likely to think that climate change will affect both them and children. These correlations do not affect the age gradient observed in our baseline specification.

Risk aversion, beliefs that success is meritocratic, trust in government, and a preference for the market economy are all associated with climate awareness. Beliefs in meritocratic success and preference for the market economy are associated with greater perceived risks of climate impacts. Respondents with high future discount rates appear less convinced that climate change is real, and that variable has no significant effect on other climate beliefs. Including these confounding factors does not affect the age gradient.

If all confounding variables described above are added to the regression, the age-climate gradient becomes similar in magnitude to the regression that controls for the use of social media, which appears to account for the bulk of the overall increase in the marginal effect of age on climate beliefs.

For all countries in our sample except nine countries in the Middle East, North Africa, and Western Europe, we have sub-national administrative data on a number of environmental risks as well as critical infrastructure that can contribute to climate resilience. We capture the following dimensions of environmental risks: (i) _flood frequency_ – the number of flood incidents between 1985 and 2022 from the Dartmouth Flood Observatory; (ii) _drought
5<br>-10 -10<br>0 0 0<br>0 10 20 30 40 50 0 10 20 30 40 50 0 10 20 30 40 50<br>Share of the foreign private investors(%) Share of the foreign private investors(%) Share of the foreign private investors(%)<br>-10 -10<br>-7.5<br>-7.5 -5<br>-2.5<br>-10<br>-7.5<br>-10<br>-5<br>0 2.5<br>5<br>-2.5<br>-5<br>7.5<br>10<br>2.5<br>5<br>10<br>7.5<br>7.5<br>-2.5<br>10<br>5<br>0<br>2.5 0<br>-7.5<br>-2.5<br>2.50<br>-5<br>-7.5<br>5<br>-7.5<br>7.5<br>-5<br>10<br>-2.5<br>10<br>7.55<br>0<br>2.5<br>-7.5<br>-2.5<br>0<br>-5-2.5<br>Expected public debt to GDP ratio(%) Expected public debt to GDP ratio(%) Expected public debt to GDP ratio(%) 02.55<br><!-- End of picture text --> Notes: Basis points.
<mark>survey of public servants. What then are the key concepts for measurement in a survey of public servants that derive from patrimonial rule? In terms of management practices, politicization and ‘personalization’ (nepotism) are central: personnel decisions – such as recruitment or promotions – are decided on political and personal (family and friends) criteria. In terms of employee attitudes and behaviors, corruption (the abuse of public office for private gain) and clientelism (the exchange of state resources for electoral support) stand out – so much so that patrimonialism (or patronage) is often equated with both (Rothstein and Varraich 2017).</mark> <mark>Weber’s (1978) bureaucratic ideal-type was designed as an antidote to neopatrimonialism: bureaucrats were to become autonomous from political (or other particularistic) influences through merit examinations, job stability, seniority-based promotions, and sufficient pay to reduce corruption to supplement incomes. This was complemented by hierarchy and detailed rules, in line with a Rechtsstaat ideal (cf. Olsen 2006). This set of administrative characteristics was intended to foster key (Weberian) employee attitudes: an</mark> _<mark>esprit de corps</mark>_ <mark>, impartiality, political neutrality, integrity, rule following, and expertise. Our core questionnaire thus includes their measurement.</mark> <mark>While Weberian bureaucracy was an antidote to patrimonialism, it created problems of its own; in particular, a lack of incentives to perform and innovate (Osborne and Gaebler 1992). New Public Management (NPM) sought to address these (Hood 1991). While the term has competing conceptualizations (Dunleavy et al. 2006), at its core it is a “doctrine that the public sector can be improved [through] business concepts, techniques and values” (Pollitt and Bouckaert 2012). For personnel management, this implied a shift to performance: the setting of targets, the measurement of their achievement, and the
of Education||0.061<br>(0.042)|||||
|Patient Health Status (Bad or Very Bad)||2.680***<br>(0.667)|||||
|Distance from Home (in Km)||0.683***<br>(0.152)|||||
|Observations|3201|2938|648|189|5260|367|
|R<sup>2</sup>|0.07|0.09|0.77|0.08|0.21|0.79|
|Dependent Variable Mean|8.16|8.13|9.66|0.15|0.70|53.05|
|Mean (SD) JHIC Score at Baseline|36.63 (12.14)|36.68 (12.22)|33.55 (11.28)|32.66 (9.56)|42.90 (10.31)|41.18 (10.20)|
|Total Controls Selected by PDF (out of 23)|6|8|12|2|3|6|

_Notes_ . Robust standard errors reported in parentheses and clustered at the market level. *** (**) (*) denotes significance at 1% (5%) (10%) level. Controls are selected by PDSLASSO out of a list of 23 variables. Market size, facility opening year, facility levels and strata FE at baseline are partialled out for all regressions (imposed as controls in the regression) so not included in the list of 23 variables. The indicator for unlicensed at baseline is partialled out for the private facilities regressions. In Column 2, patient wealth index, years of education, health status, and distance from home are partialled out. HF = health facility; JHIC = Joint
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benefit amount (PRs 24 a year).<sup>21</sup> These values remained the same over the study’s observation period. Thus, the total annual per-beneficiary cost was PRs 2,624. This perbeneficiary cost almost perfectly matches the value from official government accounting records of actual annual outlays and beneficiaries for the program.

Note that the PRs 2,624 value reflects recurrent costs and does not capture fixed costs or costs incurred in designing and establishing the program. Moreover, for recurrent costs, the value does not capture the cost of time and other resources spent by provincial and district education department officials or schoolteachers in carrying out their program responsibilities. Nor does it capture any costs borne by households in ensuring that they were present when and where needed to receive the benefit transfer or in pursuing any grievances with the authorities relating to problems with receiving the benefit. While such omissions from cost calculations are not unusual in impact evaluation studies for developing countries (Dhaliwal et al. 2013), the PRs 2,624 value should be considered an underestimate of the actual annual per-beneficiary cost of the program.

In 2015, there were 28,559 girls in secondary grades in government schools in the RD program district. Comparing enrollment numbers from the school census rounds and program beneficiary numbers from government administrative data, we find that about 90 percent of enrolled girls receive program benefits.<sup>22</sup> Using these numbers, we estimate that the government spent PRs 67,496,341 on the program in the RD program district in 2015.

For the calculation of cost-effectiveness, we arbitrarily choose the program effect for the subperiod 2003–15 (that is, the full observation period), an average gain of 41 girls per school in the RD program district. This effect, which lies roughly in the middle of the range

> 21 This maximum administrative cost of PRs 224 per beneficiary per year is about 9 percent of the maximum benefit transfer per beneficiary per year. This percentage is on
analyze the characteristics of adults using formal and informal financial services and identify the barriers to formal account ownership. For the first time we can analyze the segments of the population served by formal and informal financial services in Africa. Then, using Enterprise Surveys data, we look at how SMEs in Africa compare with enterprises in developing regions in terms of account ownership and availability of a line of credit. All key indicators are presented in Appendix 1. We conclude with a few key messages.

# **2. Africa’s Financial Sector**

Financial systems in Africa generally lag behind those in other developing economies, despite the fact that many significant improvements were implemented within the past decades. An international comparison of private credit to GDP - a main indicator of financial depth - shows a gap with other developing economies (World Bank, 2012). For example, the ratio of private credit to GDP averaged 24% of GDP in Sub-Saharan Africa in 2010 and 39% in North Africa, compared with 77% for all other developing economies, and 172% for high income economies.

The nonbank segments of Africa’s financial systems show an even lower degree of development than banking. Less than half of African countries have stock markets and only a few of these are liquid (Beck, et. al. 2011). With the exception of South Africa, African stock exchanges are small as measured by the ratio of market capitalization to GDP—only 38% on average, as compared to 44% in all other developing economies and 62% including high-income economies (World Bank, 2012). In addition, African stock markets are among the most illiquid in the world as measured by the ratio of traded to listed stocks (Beck et al., 2011).

The depth of African financial systems has improved within the past two decades, but the gap with other developing economies still remains. In the following two sections we investigate what is behind the macroeconomic indicators and examine financial inclusion from the perspective of the users