rafmacalaba/datause-encoder-data huggingface dataset:
Dang _et al._ (2023) show that while all SPI pillars are positively correlated with one another, no pillar is perfectly correlated with any of the other pillars, indicating that each pillar provides additional information on a country’s statistical performance. Further decomposing the SPI into the contributions from each pillar suggests that in low income countries, adequate data sources (Pillar 4) and data infrastructure (Pillar 5) represent severe capacity limitation but high-income countries are doing relatively poorly in terms of data products. Overall, countries with a higher income level or a non-fragile-and-conflict status have a higher SPI score. We provide detailed discussion on the data collection process for the SPI indicators and other related challenges (e.g., potential issues with missing data) in Dang _et al._ (2023). The SPI is publicly available at <u>www.worldbank.org/spi. The associated code and underlying raw data are available at our project</u> site https://github.com/worldbank/SPI.

# **Statistical analysis: Country fixed-effects regressions**

As a start, we estimate the following pooled OLS model 0 1S (4) where represents the outcome variable for country cc,cc cc,cc cc,cc in year , which can be either GDP per YY = αα + αα SS + ηη capita (in logarithmic form based on 2015 constant US dollars) or the WGI. cc,cc is an idiosyncratic YY cc tt error term. S is the value of the country overall SPI score in year . Furthermore, we also cc,cc ηη examine another model specification where we replace the overall SPI score with the five SPI cc,cc SS tt pillar scores (on data use, data services, data products, data sources, and data infrastructure). This disaggregation allows us to probe more deeply into the relationship of the outcome variable and the different SPI components.

While Equation (4) offers a useful exploratory analysis, it does not control for country-specific or year-specific characteristics that can affect the outcome variables. These can include, for example, country income or education levels or the structure of its economy, or global macroeconomic time trends. Consequently, we further estimate a panel data model with country and year fixed effects (FE): 0 1SS (5) where is the country fixed effects, cc,cccc,cc is a year dummy variable. We also estimate the following cc,cccc,cc cc cc cc,cc YY = ββ + ββ SS + ππ + ττ + εε 0 1SS (5) where is the country fixed effects, cc,cccc,cc is a year dummy variable. We also estimate the following cc,cccc,cc cc cc cc,cc country and year FE panel data model where we explicitly control for several country cc cc ππ ττ characteristics: 21
in the poverty headcount from Market Income (pre-fiscal income) to Consumable Income (Market Income after taxes and transfers, excluding in-kind benefits from health and education). We include 58 countries in total.

**Globally, total poverty change due to the combination of taxes and transfers modeled ranges from the worst case of an 8.9 percentage point increase in Armenia to the best case of an 8.4 percentage point decrease in Spain.** The fiscal system in the West Bank and Gaza increases the poverty rate at the $5.5 2011 PPP poverty line by 6.0 percentage points. Note, however, that this result can vary substantially depending on the poverty line used. At the $3.20 and $1.90 2011 PPP per day international poverty lines, the combination of taxes and transfers in the West Bank and Gaza is poverty- _reducing_ by 1.2 and 0.8 percentage points respectively.

Figure 8.2 Total poverty impact at the $5.50 line is severe relative to other CEQ assessments Percentage point change in poverty rate, 2011PPP international poverty lines (changes from Market to Consumable Income)

# **Figure 8-2 Total poverty impact at the $5.50 line is severe relative to countries in other CEQ assessments**

Percentage point change in poverty rate, 2011 PPP international poverty line (changes from Market to Consumable Income) <!-- Start of picture text --> 10<br>8<br>West Bank and Gaza: 6.0 percentage point increase in poverty rate<br>6<br>4<br>2<br>0<br>-2<br>-4<br>-6<br>-8<br>-10<br>High incomeHigh income Upper middle incomeUpper middle income Lower mLower m idd le incomele income Low Low incom ee<br>Spain Mauritius United States Panama Chile Uruguay Romania Argentina Venezuela Iraq Ecuador Jordan Thailand Paraguay Russia Iran Malaysia Colombia Russia Indonesia South Africa Costa Rica Dominican Republic China Botswana Mexico Peru Namibia Guatemala Brazil Turkey West Bank and Gaza West Bank and Gaza Albania Armenia Ukraine Bolivia Sri Lanka Vietnam Nicaragua Moldova Comoros India Tunisia El Salvador Honduras Zambia eSwatini Lesotho Ghana Ivory Coast Kenya Tajikistan Ethiopia Uganda Guinea Burkina Faso Togo Tanzania<br><!-- End of picture text --> Source: World Bank estimations for the West Bank and Gaza based on PECS 2016-17. CEQ Data Center for the rest of the countries.

Note: Pensions treated as government transfers in China, Georgia, Guinea, Mali, Mongolia, Niger, and West Bank and Gaza.

54
one also included all possible interactions among these economic and demographic characteristics, the R<sup>2</sup> would reach about one-third (regression results are not shown for the sake of brevity).

# Appendix 3. Country share of HtM individuals, share of social transfers reaching HtM individuals, and social transfers targeting

Table A.3.1 shows the country share of HtM individuals, share of social transfers reaching HtM individuals, and social transfers targeting from Global Findex dataset (based on its latest survey for the year 2017).

# Appendix 4. Additional insigths regarding the relative importance of � vis-à-vis � driving large STMs

Table A.4.1 shows on-impact STM values using our benchmark calibration and combinations of � and � which are allowed to vary between 0 and 1 in 0.05 intervals. The shaded cells indicate combinations of � and � such that STT < 0. Recall that since STT � � � �, then STT < 0 implies that �> �.

This exercise provides additional insights as to the relative importance of � vis-a-vis � driving large STMs. In particular, the results show that it is not feasible to obtain truly large on-impact STMs (e.g., STM > 1) for low to moderate values of the share of HtM individuals, �, (e.g., �< 0:4). This implies that, in spite of important social transfers targeting e¤orts, even if � was the maximum possible (i.e., � = 1), in order to be able to achieve truly large on-impact STM, there exists the need to have large propagation forces via high average marginal propensity to consume, which can only be achieved by having a relatively large share of HtM individuals, �. In the extreme, for a su¢ ciently high share of HtM individuals, �, (e.g., �> 0:8) it is possible to have truly large STMs even when � is low enough such that STT < 0. This quantitative importance of the share of HtM individuals, �, provides another relevant dimension as to how to rationalize its practical importance in determining the size of STM in Latin America as well as in other emerging market economies with high prevalence of HtM individuals.
_Fareed M. A. Hassan, ECSPE_ 2 Tax Law enacted in March 1993 resulted in a substantial increase in tax rates and the number of tax brackets.

In late 1997 Bulgaria adopted major tax reform measures to be effective in 1998. These measures include: (i) reducing marginal tax rates on both personal and corporate incomes to 40 percent; (ii) aligning the top marginal personal tax rate with the corporate tax rate to diminish the incentive to shift income among the categories of personal income, partnership income, and corporate income; (iii) reducing tax burdens on the poor by raising the exemption level by 20 percent; and (vi) flattening personal income tax rate schedules as the number of tax brackets has been halved. However, the new personal income tax structure tax resulting from the 1997 amendment to the 1993 Personal Income Tax Law resembles, to a greater extent, the 1992 tax system'.

Given the 1992, 1993, and 1997 reform episodes, the similarity of the 1997 personal income tax schedule to the 1992 structure, and the availability of a detailed household budget survey for 1992, this paper attempts to examine the revenue adequacy and equity effects of Bulgaria's tax reform experience. In particular, the paper seeks to analyze the following two issues, which should be of broader interest in Bulgaria, and in other EMEs. First, it examines the effects of the 1992 personal income tax system on revenue and post-tax income distribution. Second, it explores if an alternative, simpler tax structure with lower tax rates could achieve at least equal revenue and distributional objectives as the 1992 system, and demonstrates tfhat a system with lower rates is superior in terms of revenues and distributional effects.

To answer the second, counterfactual question, which is of particular interest for tax policy, I examine the effects of simplifying the existing personal income tax system in three interrelated areas: (i) reducing the number of tax brackets, (ii) lowering tax rates, and (iii) 1/The 1997 system exemplifies a progressive 5-tax bracket structure (including the lowest-tax free bracket) with five rates of zero, 20, 26, 30, andc40 percent. This pattern of tax rates is similar to the 1992 system given in Table 1 below.
Albania and Greece. Alternatively, one can first carry out a survey in destination countries and, using a similar approach, track down the original household in the sending countries. An example is the aforementioned study between New Zealand and Tonga (McKenzie et al., 2006).

Tracking surveys can also be used as validation of information that was gathered in the original household through proxy respondents, as well as to measure differences in perceptions between migrants and household members left behind. While allowing for direct interviews with the migrants, tracking presents a number of problems, which might outweigh the benefits. It can be too costly and is characterized by a high level of attrition, particularly when the share of undocumented migration is high.

# **_Sampling design_**

Within migration surveys, a traditional probability sample based on a multi-stage cluster design will not succeed in finding many migrants, whether this is done in origin or sending countries. A probability sample, by assigning a known non-zero probability of selection to each sampling unit, allows for making inferences to the whole population. The foundation of a proper sample is an updated sampling frame. However, this is the main stumbling block in the design of migration-focused surveys, in origin and destination countries. As mentioned earlier, migrants with certain characteristics or from certain origin countries might not be present in large enough numbers to be properly captured in the sample. Furthermore, certain types of migrants might be reluctant to participate for cultural and legal reasons. The Census Department in the USA, for 20
# **Figure 11. Composition of government expenditure in small states and other EMDEs**

_The share of capital expenditure in total government expenditures was slightly higher in small states than in other EMDEs during 2011-22. While varying greatly, small states’ interest payments were on average comparable to those of other EMDEs, and, as in other EMDEs, they increased markedly between 2019 and 2023. Small states spend more on health and education, as well as public investment, than other EMDEs._

## **A. Current and capital expenditure, 2011-22**

<!-- Start of picture text --> Percent of total spending Current expenditure<br>Capital expenditure<br>100<br>80<br>60<br>40<br>20<br>0<br>Small states EMDEs excl. small<br>states<br><!-- End of picture text -->

## **B. Net interest payments**

<!-- Start of picture text --> Percent of GDP Small states<br>2.5 EMDEs excl. small states<br>2.0<br>1.5<br>1.0<br>0.5<br>0.0<br>2011 2019 2023<br><!-- End of picture text --> <!-- Start of picture text --> C. Composition of expenditure, 2011-21 D. Expenditure on healthcare and education by<br>region, 2011-21<br>Percent of GDP Small states Percent of GDP Health Education<br>EMDEs excl. small states<br>8 8<br>6 6<br>4 4<br>2 2<br>0 0<br>Health Education Public LAC small EAP small Other small<br>investment states states states<br><!-- End of picture text --> _Sources_ : GFS (database); International Monetary Fund; WDI (database); WEO (database); WHO (database); World Bank.

_Note_ : EAP = East Asia and Pacific; EMDEs = emerging market and developing economies; LAC = Latin America and the Caribbean.

A. Panel shows the share of major components of total spending for 19 small states and 81 other EMDEs for the period 2011-22.

B. Average net interest payments as a percent of GDP for 32 small states and 110 other EMDEs.

C. Average expenditures on health, education, and public investment as a percent of GDP in 31 small states and 116 other EMDEs for the period 2011-21.

D. Average expenditures on health and education as a percent of GDP for the period 2011-21. EAP small states include 10 economies, LAC small states include 11 economies, and other small states include 10 economies.

42
**The way forward points therefore at improving domestic determinants of volatility under countries’ control, so to counterbalance the upwards pressure caused by a more volatile world environment and high trade openness.** There seems to be space for improvement in the areas of institutional quality, as well as monetary and fiscal policies (Figure 2). The quality of institutions across the region could, on average, be further improved. It would be essential for parliaments to exert strong control over the executive, to prevent implementation of uncertain and discretionary policies and to avoid continuous shifts in fiscal policy. Furthermore, stable monetary and fiscal policies are essential instruments to reduce output growth volatility, and are also the areas where improvements could lead to the most significant drops in volatility (Figure 2). In that context, medium term monetary and fiscal frameworks could be adopted to better steer these instruments and provide policy makers with a benchmark and a target for monetary and fiscal policies. Finally, given the strong impact banking crises have on crisis volatility (Table A.1), it is vital to improve prudential supervision and create fast response plans for handling banking problems. Improved financial depth would also allow a better allocation of resources where needed, with a beneficial impact on volatility.

**Figure 2: Estimated average reduction in volatility if factors were brought at OECD levels (middle income East Asia)**

<!-- Start of picture text --> 20.7%<br>14.6%<br>11.1%<br>7.7%<br>5.8%<br>0.7%<br>Institutional Volatility of Volatility of Trade Volatility of Volatility of<br>Quality Inflation Gov. Openness TOT Foreign<br>Spending Growth<br><!-- End of picture text --> Non-OECD EAP (average of China, Indonesia, Thailand, Malaysia and the Philippines) vs. average OECD levels in 2000-05. The bars represent the estimates’ standard deviation. Source: Author’s own calculations using data from WDI, IMF and Polity IV.

The paper is structured as follows. Section 2 reviews the impact of output growth volatility on poverty, welfare, and economic growth. Sections 3 and 4 present world trends of output growth volatility and review its determinants. Section 5 discusses factors that contributed to the reduction in output growth volatility in East Asia, and factors that could further reduce it. Section 6 concludes.

5
households in advance of an expected flood shock were more helpful the earlier that they were received (Pople et al., 2021).

# **5.4 Financing of social protection programs and associated limitations**

A final and enduring challenge related to the COVID-19 social protection response has been financing of safety net programs. Even before the pandemic, more than half of the funding for social protection programs in Africa came from development partners (Bossuroy and Coudouel, 2018). During the pandemic, social protection responses in Africa have relied heavily on loans and grants from international financial institutions and NGOs. This has inhibited expansion of social protection programs because funding from development partners, which were also affected by the pandemic, has significantly declined. In a selected group of African countries for which data was available in 2020, only 23% of spending on COVID-19 expansions of social protection was from domestic financing (Alfemni, 2020). This tendency to rely on donor funding also explains the relatively slow rate of the social protection response in Africa.

On the other hand, some countries such as Kenya and South Africa ran considerable fiscal deficits in order to fund the COVID-19 social protection responses (Alfemni, 2020). While the macroeconomic implications of spending on social protection are still relatively understudied, the potential drag on longterm growth of reduced productive investment is worth comparing to the short-term benefits for households (Breisinger et al., 2021).

Nor is the use of external financing without trade-offs. Total aid flows to Africa increased in 2020, but remained small compared to total projected needs and in general were characterized by a sectoral reallocation in favor of social protection at the cost of investments in energy, transportation and storage. The bulk of the increase in official development aid came from international financial institutions, particularly the World Bank, and this aid surge is unlikely to be sustained. After high domestic spending during COVID-19 and now the economic implications of the Ukraine war, the largest bilateral donors are likely to have reduced development aid budgets (McCord et al., 2021).

# **6. Concluding Remarks**

This paper employs recent sources of data to estimate and reassess the impact of the pandemic on countrylevel poverty in Africa. We combine national accounts data along with High-Frequency Phone Surveys for several countries to estimate the impact of the pandemic on poverty. These data can help refine and update early poverty projections which were built on several assumptions about expected changes in income as well as trends about the evolution of the pandemic and public health measures. We also review and synthesize empirical evidence on the role of social protection systems to mitigate the adverse impact of the 29
# **Table 1.  Offspring sex ratio by parental HBV infection: evidence from some micro-studies**

|**Location**|**HBV Status**|**Sons**|**Daughters**|**Sex Ratio**|
|---|---|---|---|---|
|Greenland|Positive|64|60|1.07|
||Negative|174|194|0.90|
|Kar Kar|Positive|63|54|1.17|
|Island|Negative|163|206|0.79|
|Greece 1|Positive|90|51|1.77|
||Negative|287|255|1.13|
|Philippines|Positive|66|41|1.61|
||Negative|304|301|1.01|
|Greece 2|Positive|52|30|1.73|
||Negative|1006|955|1.05|
|France|Positive|20|12|1.66|
||Negative|149|122|1.22|
|Notes: This ta<br>parents in fou<br>_all cases exce_<br>study are as f<br>Kar Kar Islan<br>Blumberg (19<br>al(1979);Fra|ble shows sex ratio<br>r regions._Data wer_<br>_pt for Greenland, th_<br>ollows: Greenland -<br>d – Drew et al (198<br>75); Philippines – C<br>nce–Cazal,Lemai|s among the ch<br>_e collected by t_<br>_eir husbands f_<br>Drew, Blumbe<br>2); Greece 1 –<br>hanazarian et<br>re andRobinet|ildren of carrier a<br>_esting married wo_<br>_or HBV_....The cit<br>rg and Robert-La<br>Hesser, Economid<br>al (1988); Greece<br>-Levy (1976).|nd non-carrier<br>_men and, in_<br>ations for each<br>mblin (1986);<br>ou and<br>2 – Livadas et|

**_Source:_** Blumberg and Oster (2007: Table 1)

**_Note:_** The “Greece 2” study tested only women (not men) for HBV (Livadas et al 1979).  The italicized sentence in the footnotes to the table above is incorrect.

7
15 estimated that if all 3,000-4,000 public buses in the major Hungarian cities were converted, 6.4 kilotons of emissions per year would be abated (JIQ 1996).

The Gini analysis and decompositions used in this paper have been applied to projected real emissions only. However, given the likelihood of some form of TEPs and JI in the future, it may be thought the analysis becomes uninteresting. On the contrary, by defining quasi-emissions as real emissions minus TEPs purchased and minus JI carbon offset credits, the inequality in per capita quasiemissions may be analyzed readily.<sup>22</sup> This would enable the inequality impacts of various trading schemes to be assessed and compared against inequality in real emissions. Since it is likely that developed countries would buy TEPs and fund JI projects in developing countries, it is expected that inequality in quasi-emissions would exceed that in real emissions.

# **4. Conclusion**

Since the UN Conference on Environment and Development in 1992, the international community has devoted significant resources to assessing the threat of global climate change and forging a legally binding treaty to reduce emissions of greenhouse gases. The effort has been painstaking and the progress halting at times, but the complex process involving 166 formal parties has inched forward. In December 1997, the process was boosted by the adoption of the Kyoto Protocol at COP3, which mandates that 3 8 developed countries reduce six greenhouse gases by an average of 5.2 percent relative to 1990 levels by 2008-2012.

Despite that achievement, ratification and implementation of the Kyoto Protocol remains in doubt. And the recent COP4 made only limited gains toward cementing its implementation. The distribution of greenhouse gas emissions is a critical component of the equity issues that may influence the ultimate success or failure of the UN climate convention process. If per capita emissions equalize naturally through income convergence and improved energy use at higher levels of GDP, redistributive 22See Heil and Wodon (1997) for details on quasi-emissions.