rafmacalaba/data-use-mentions-extended huggingface dataset:
important since, despite global warming, unusually colder weather has become more common in many countries in the past decades. Overall, our results indicate that the distributional effects across temperature ranges (as well as across subnational regions) should be considered together with longer-term effects of temperature change as inputs for designing more effective policies aiming at fighting climate change, poverty, and inequality.

Finally, we offer new, disaggregated data on headcount poverty estimates and inequality indices for 1,594 subnational areas in 134 economies from 2003 to 2019, based on the GSAP database which is generated using household income and consumption surveys that underlie countries’ official poverty statistics. This helps distinguish our study from the few existing cross-national studies that predominantly focused on country-level datasets, which, although informative, were not able to adequately capture the intricate subnational dynamics of poverty, inequality and temperature change. As part of our analysis, we make this new dataset publicly available for the first time. Our results show that analysis based on subnational data yields more accurate estimates of the impacts of temperature on poverty and inequality; consequently, this new subnational dataset can contribute to further and better research on climate change and poverty and inequality on a global scale.

This paper consists of six sections. We discuss the data in the next section, and the analytical framework in Section 3. In Section 4, we report on the estimation results for poverty (Section 4.1), inequality (Section 4.2), their nonlinear effects (Section 4.3), and further robustness checks and heterogeneity analysis (Section 4.4). We offer further analysis on potential mechanisms, projected impacts under future climate change, and some back-of-theenvelope cost-benefit analysis in Section 5 and finally conclude in Section 6. We provide additional results in Appendix A, describe the data in more detail in Appendix B, offer more robustness checks and heterogeneity results in Appendix C and additional analysis on the potential mechanisms and projected impacts of temperature in Appendix D.

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are, in practice it is difficult to explore how people process economic information and make informed decisions about household finances.‖ As mentioned in the introduction, financial literacy encompasses a number of concepts, including financial awareness and knowledge, financial skills and financial capability, and it is hard to capture all of this information in a survey of reasonable length. However, a set of three questions first developed by Lusardi and Mitchell (2011a) for the American Health and Retirement Study (HRS) in 2004 are commonly used.

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smartphones, many of their customers will have them and the shutting down of the firm will be partially registered.

Data on restaurant reservations in the United States are taken from OpenTable.<sup>9</sup> Movie release and theater revenue data for Sweden are from International Movie Database.<sup>10</sup>

**COVID-19 Cases:** Though there may be several mechanisms through which cases translate into lower mobility, we interpret this as a signal to individuals about the likelihood of a serious negative health outcome. National cases can inform about the overall evolution of the disease, while local numbers finetune the proximate threat.  We standardize by the corresponding population in the figures.  In some regressions, we can expand the sample by using log (cases) and the population scaling is absorbed in the corresponding fixed effect. Global data are drawn from the Johns Hopkins Coronavirus Resource Center. Country-specific regional data come from national sources:  the United States:  Johns Hopkins Coronavirus Resource Center; Brazil, Italy, Japan, South Africa, Sweden, and the United Kingdom: from national sources (see Annex II).

> 9 <u>www.opentable.com</u>

> 10 <u>https://www.boxofficemojo.com/</u>

4
We also create more outwardly gendered categories by looking at whether men or women are the main income earners (earn more than 60 percent of household labour income).<sup>14</sup> As expected given the very low participation rate of Jordanian women in the labour force, almost 70 percent of households are ‘male earner majority’ households and only 10 percent are ‘female earner majority’ households (Figure 4). Again, there is some overlap with the fiscal and care categories, but not a perfect one. In particular, most of the households where men are the main income earners are in the ‘married couple with dependents’ care category (Table 4) or in the ‘worker(s)’ (with and without children in school) fiscal categories (Table 5).

<!-- Start of picture text --> No labour income<br>10<br>19<br>No earner majority<br>6<br>Male earner majority<br>(>60% income)<br>66 Female earner<br>majority (>60%<br>income)<br><!-- End of picture text --> Source: 2017-18 Household Expenditure and Income Survey (HEIS) and World Bank calculations.

**_Table 4. Care and gender earner category comparison (percentage of total households)_**

|||**GE**|**NDER EARNE**|**R CATEGORIE**|**S**|
|---|---|---|---|---|---|
|||Female<br>>= 60%|Male<br>>= 60%|No income|Neither<br>earns 60%|
|**ES**|No dependents|3|15|6|1|
|**RE**<br>
Male HHH|41.0%|39.8%|35.7%|32.6%|
|Female HHH|37.8%|40.3%|38.0%|49.0%|
|Couples with children|54.1%|47.9%|39.9%|34.8%|
|Couples without children|14.7%|15.9%|25.6%|31.8%|
|Single caregivers|40.0%|42.3%|37.9%|47.9%|
|Single person households|10.3%|19.9%|29.1%|51.2%|
|Unaccompanied children|34.5%|46.4%|57.5%|73.2%|
|Non-nuclear and other households with children|46.7%|45.9%|36.3%|35.3%|
|Non-nuclear and other households without children|21.0%|20.3%|26.4%|31.6%|
|No children in the hh|13.4%|19.4%|28.1%|42.1%|
|Children in the hh|50.6%|47.2%|39.5%|37.7%|
|Dependency ratio <1|18.1%|21.7%|27.0%|32.3%|
|Dependencyratio >=1|54.3%|50.9%|42.0%|42.7%|

_Note_ : Own calculations based on ProGress and JD-HV database. This table shows the percentage of households below the 40<sup>th</sup> percentile of the expenditure distribution, for each wave and each demographic group.

Table 3 also compares households with and without children over
buyer of electricity, the recently established Palestinian Electricity Transmission Company (PETL). The PETL sources electricity from the Palestine Power Generation Company (PPGC), Israel, and other neighboring countries. In Gaza, the Palestine Electric Company (PEC) operate the Gaza Power Plant at partial capacity.

**The current electricity tariff structure for domestic consumers (Table 2.4) was promulgated in 2017 in Article 5, Ministerial decision N 03/137/17.** It applies in all regions of the Palestinian Territories except for residents of Jericho and the Palestinian Jordan Valley. Access to the electricity is widespread with 98 percent of the PECS survey respondents in all the regions of the Palestinian Territories reporting having access in 2017. Most consumers (approximately 65 percent) consume in slab 2 (161-250 kWh) and slab 3 (251-400 kWh) of the tariff structure.

**Table 2-4 The price of electricity per kWh for domestic consumers ranges between 0.458 and 0.6731 in the West Bank and Gaza**

Price of electricity by consumption slab, West Bank and Gaza

|**Consumption slabs**|**Price**|
|---|---|
|**(kWhper month)**|**(NISper kWh)**|
|1- 160|0.458|

> 25 As of its 2017 Annual Statistical Report, the MoSD (2018) estimated the extreme poverty line at NIS 1,970 per month and the national poverty line at NIS 2,470 per month for a family of two adults and three children, with the specific amount determined by the PMT.

> 26 Ministry of Social Development (Jan 2018); Ministry of Social Affairs (Jan 2017); The Office of the European Union Representative (Oct 2019); The World Bank (Dec 2018).

> 27 The specific amount depends on households PMT score.

> 28 <u>https://www.worldbank.org/en/country
**Table 26 Headcount Index of Poverty Among Farmers, Corrected for Seasonal Variation** _(Poverty line = 75, 000 CFAF per year in 1985 CFAF)_

||_Seasonally_|_unadjusted_|_Seasonall_|_y adiusted_|
|---|---|---|---|---|
|_Region_|_1993_|_1995_|_1993_|_1995_|
|Other Cities|||||
|Export crop farmer|0.334|0.071|0.296|0.071|
|Food crop farmer|0.540|0.645|0.523|0.645|
|East Forest|||||
|Export crop farmer|0.407|0.406|0.400|0.363|
|Food crop farmer|0.414|0.567|0.429|0.557|
|West Forest|||||
|Export crop farmer|0.340|0.515|0.352|0.561|
|Food crop|0.503|0.594|0.516|0.604|
|Savannah|||||
|Export crop farmer|0.524|0.406|0.531|0.406|
|Food crop farmer|0.532|0.577|0.552|0.603|

One problem in using the coefficients derived from the 1985 -1988 LSMS data to correct the 1993 and 1995 surveys is that the total expenditure aggregate for many food and some nonfood items is based on the average of the two week (annualized by multiplying by 26 weeks) and the normative estimate of monthly food expenditure multiplied by typical number of months of purchase. Unless there is seasonal recall bias, one would expect that there would be no seasonal variation in the normative estimate. Thus, the average of the two estimates would exhibit less seasonal variation and could result in a downward bias
others 2009. Derived from AICD water and sanitation utilities database downloadable from http://www.infrastructureafrica.org/aicd/tools/data The performance of Ghana Water Company (GWC) has improved somewhat in recent years following institutional reforms and the contracting of a private operator. As of 2005, the utility was recovering only 48 percent of costs and collecting only 75 percent of revenue. Since 2007, tariff increases have substantially improved cost recovery. At the same time, the private operator’s stronger commercial incentives have improved revenue collection from 75 percent to 95 percent in a short period of time. As a result, the hidden costs associated with the water sector fell from $113 million per year in 2001 to $96 million per year in 2009 (table 7), and they now absorb a much smaller share of GDP (figure 7). Relative to sector revenue, hidden costs have fallen from 190 to 129 percent over the same period. Nonetheless, Ghana remains only a middling performer on utility efficiency by regional standards (figure 8).

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Ragasa, Catherine, and John Mazunda. 2018. “The Impact of Agricultural Extension Services in the Context of a Heavily Subsidized Input System: The Case of Malawi.” World Development 105: 25–47.

Ricker-Gilbert, Jacob, and Thomas S Jayne. 2017. “Estimating the Enduring Effects of Fertiliser Subsidies on Commercial Fertiliser Demand and Maize Production: Panel Data Evidence from Malawi.” Journal of Agricultural Economics 68 (1): 70–97.

Tanko, M, S Ismaila, and S Abu Sadiq. 2019. “Planting for Food and Jobs (PFJ): A Panacea for Productivity and Welfare of Rice Farmers in Northern Ghana” 7 (1).

https://doi.org/10.1080/23322039.2019.1693121.

Wossen, Tesfamicheal, Tahirou Abdoulaye, Arega Alene, Shiferaw Feleke, Jacob Ricker-Gilbert, Victor Manyong, and Bola Amoke Awotide. 2017. “Productivity and Welfare Effects of Nigeria’s e-VoucherBased Input Subsidy Program.” World Development 97: 251–65.

Yi, FJ, WY Lu, and YH Zhou. 2016. “Cash Transfers and Multiplier Effect: Lessons from the Grain Subsidy Program in China” 8 (1): 99. https://doi.org/10.1108/CAER-07-2015-0078.

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40

**Country E R Pricing** **<u>policy and strategy</u>**

# **Fuel supply conditions**

<!-- Start of picture text --> 700<br>600<br>500<br>400<br>300<br>200<br>U.S. Gulf Coast spot price<br>100<br>Retail in Metropolitan Region<br>0<br>Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Jan-13<br>Protests : Taxis and mini-buses went on strike in Oct 2011,<br>protesting fuel price hikes and asking to be included in transport<br>policy, including subsidies.<br> / liter of diesel<br>Pesos<br><!-- End of picture text -->

**Hedging** : Hedging is explicitly regulated by law. **Information** : The National Energy Commission (Comisión Nacional de Energía, CNE) posts monthly average prices of all fuels by region, dating back to Jan 1994. A resolution issued in Jan 2012 require that prices of gasoline, diesel, kerosene, CNG, and automotive LPG at each filling station be published on CNE’s Web site, and they are ranked in order of increasing or decreasing price depending on the viewer’s preference. Resolution No. 60 issued in Jan 2012 requires that each filling station enter price information in a national online price database, which is published on CNE’s Web site, and also made available on iPhone, BlackBerry, and Android. The Web site displays minimum and maximum prices, the address of each filling station, prices, and the date and time of the last price change. Retailers are required to enter new prices no earlier than 15 minutes before price changes are implemented.

|China<br>√<br>**Pricing policy**: A new mechanism introduced in Jan 2009 bases fuel|**Supply**
of smaller firms is not as readily available, though there are a number of important sources. Amadeus, a commercial service from Bureau van Dijk, draws on sources – mainly credit registries – in 34 European countries to provide a standardized balance sheet and income statement, 7-digit production sector, employment and ownership information for 5 million firms, most of them micro by standard EU definitions.<sup>19</sup> In principle, this kind of material could be assembled for other countries too, but I am not aware of any cross-country effort to do this. There are also some surveys carried out by official statistical or regulatory agencies, such as the five-yearly Survey of Small Business Finances by the US Federal Reserve Board, of which the most recent, in 2003, collected financial information on some 600 firms with fewer than 500 employees (cf. Board of Governors, 2002).

Turning to the developing world, there have been a couple of major initiatives in the area of business surveys. The World Business Environment Survey (WBES) is a 81-country cross-sectional firm level survey conducted in developed and developing countries in 1999-2000 following an initiative of the World Bank.<sup>20</sup> Typically about 100 firms were

> 18 The researchers used the same mean travel time for all households, but this also would in general vary by household.

> 19 Currently EU defines a firm as micro if it has fewer than 10 employees and either a turnover of less than €2 million or a balance sheet total of less than €2 million.  The thresholds for small and medium firms are (50, €10m. and €10m.) and (250, €50m. and €43m.) respectively.

> 20 The WBES builds on a number of earlier exercises (including some carried out by the IFC), though its sheer scale now tends to push these others into the background. One significant study of this type was the

15
’s grade are obtained both from the student questionnaire and from the student tracking form. As with all variables that are on both the tracking form and the questionnaire, inconsistencies between the two sources are reviewed and resolved during datacleaning. In order to capture between-country variation, the relative grade index (GRADE) indicates whether students are at the modal grade in a country (value of 0), or whether they are below or above the modal grade level (+ x grades, - x grades)._ _The relationship between the grade and student performance was estimated through a multilevel model accounting for the following background variables: i) the PISA index of economic, social and cultural status; ii) the PISA index of economic, social, and cultural status squared; iii) the school mean of the PISA index of economic, social, and cultural status; iv) an indicator as to whether students were foreign-born first-generation students; v) the percentage of first-generation students in the school; and vi) students’ gender._ _Table A1.2 presents the results of the multilevel model. Column 1 in Table A1.2 estimates the score-point difference that is associated with one grade level (or school year). This difference can be estimated for the 32 OECD countries in which a sizeable number of 15-year-olds in the PISA samples were enrolled in at least two different grades. Since 15-year-olds cannot be assumed to be distributed at random across the grade levels, adjustments had to be made for the above-mentioned contextual factors that may relate to the assignment of students to the different grade levels.” (OECD, 2014 pg. 261)_ Country specific values can be found in Annex A1, tables A1.2 of both OECD reports (OECD, 2010 and 2014).

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36|2,401|2,437|
|- Tariff lines that disappear<sup>2/</sup>||||16|437|453|
|Relations tariff lines - country|461|9,826|10,287|612|28,307|28,919|
|1/Appear in 2009 but not in 1993.|||||||
|2/Appear in 1993 but not in 2009<br>Source: SUNAT-MEF.|||||||

To explore the issue of the growing diversification among non-traditional exports, Table 4 presents key data that compare the list of the most important export products (by value) in 1993 and in 2009 at a disaggregated level.<sup>17</sup> Overall, the evidence suggests that between these two years, there has been an increase in non-traditional exports both of the intensive margin (i.e., increase of exports due to products already exported to an established destination market) and of the extensive margin (i.e., increase of 17 Note that the data in Table 4 suggests that traditional exports have not expanded much on the intensive nor extensive margin. In 2009, these products accounted for 77% of total exports with only 7 subheadings explaining 97% of the total. As was the case in 1993, those subheadings were related to copper products, fishmeal, nonferrous metal transformation and coffee for consumption.

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# **2.2. Currency Composition of Public Debt: Domestic Currency Debt on the Rise**

Alongside the recent increase in public debt, the currency composition of debt portfolios has been changing.<sup>6</sup> Foreign currency denominated debt still accounts for the larger part of total debt; however, domestic currency denominated debt has been increasing at a faster pace. For the whole region, the median general government gross debt denominated in foreign currency stood at 29 percent of GDP at the end of 2018 whereas that of public debt in domestic currency was 22 percent of GDP. Between 2013 and 2018, however, median domestic currency debt increased by 10 percentage points, and median foreign currency debt by 7 percentage points (figures 7 and 8).

**Figure 7. Domestic Currency Public Debt, by Income Group** _(% GDP)_

<!-- Start of picture text --> 35<br>30<br>25<br>20<br>15<br>10<br>5<br>0<br>2007 2013 2018 2007 2013 2018 2007 2013 2018 2007 2013 2018<br>Low-Income Countries Lower-Middle Income Upper-Middle Income Sub-Saharan Africa<br>Countries Countries<br><!-- End of picture text --> _Note: The columns represent group simple averages whereas red dots (diamonds) represent the group medians. Source: World Bank; IMF – World Economic Outlook Database, October 2018_ The increase in domestic currency debt was particularly pronounced in upper-middle-income countries ( **Figure 7** ). Median levels increased from 11 percent of GDP in 2013 to 29 percent in 2018. The median domestic debt of LICs and LMCs also increased although at a slower pace than UMCs, 8 and 14 percentage points of GDP, respectively. The heavier reliance on domestic currency financing in UMCs is not surprising, as these countries have deeper and more developed domestic debt markets and are therefore able to raise more domestic
of the crisis.

WorldBase is compiled by Dun & Bradstreet (D&B) and covers public and private enterprises in over 100 countries and territories. Dun & Bradstreet has been the leading source of commercial credit and marketing information since 1845, and presently operates in more than a dozen countries and territories either directly or through a¢ liates, agents, and associated business partners. D&B compiles data from a wide range of sources including public registries, partner ...rms, telephone directory records, and websites, and veri...es all information centrally via a variety of manual and automated checks. Early uses of the D&B data include Caves’(1975) size and diversi...cation pattern comparisons between Canadian and U.S. domestic plants and subsidiaries of U.S. multinationals in Canada, and Lipsey’s (1978) comparisons of the D&B data with existing sources with regard to the reliability of U.S. data.

> 7 For example, the latest UNIDO INDSTAT 2009 Database, an authority industry-level data source, reports industrial data only up to 2007. The OECD STAN Database, another widely used industry-level dataset, currently provides 2008 data for only 13 OECD countries.

> 8 To identify businesses numerically for data-processing purposes, D&B introduced in 1963 the Data Universal Numbering System (the D-U-N-S Number). The system supports the linking of plants and ...rms across countries and tracking of plant histories including name changes.

8
://www.allhealth.org/sourcebook2004/toc.asp.

American Medical Association (2004), “Physician Characteristics and Distribution in the US: 2004-2005”, AMA Press, Chicago.

Birkmeyer et al. (2002), “Hospital Volume and Surgical Mortality in the US”, New England Journal of Medicine 346(15): 1128-37.

Brush, Barbara L., Julie Sochalski, and Anne M. Berger (2004) “Imported Care: Recruiting Foreign Nurses to U.S. Health care Facilities”, Health Affairs 23(3): 78-87.

Business Standard (2005), “Apollo Wooing Foreign Insurers: Says it’s the prescription for health tourism growth”, article in the Business Standard, Feb. 16, 2005.

Census Bureau (2004), “Health Insurance Coverage in the US: 2003”, available at <u>http://www.census.gov/prod/2004pubs/p60-226.pdf.</u> 26
This is evidenced by the data in Table 1, showing the number of antidumping investigations — grouped by sets of products —<sup>18</sup> and the number of on-the-spot verifications conducted to determine injury (domestic firms) and dumping (foreign producers). It should be noted that in almost all actions regarding determination of injury, domestic producers were visited. However, with regards to determination of dumping, the number of on-the-spot verifications conducted on the exporting firms’ premises to verify domestic and export prices is still limited. Therefore, for dumping determination purposes, the DECOM still acts based on the data supplied by businesses and on the price information available in specialized journals.

Table 1 Number and Percentage of Investigations with on-the-spot Verifications for Injury and Dumping Determinations

|Year|No of investigations|Injury|(%)|Dumping|(%)|
|---|---|---|---|---|---|
|1996|7|2|28,6|1|14,3|
|1997|10|7|70,0|0|0,0|
|1998|10|9|90,0|3|30,0|
|1999|5|3|60,0|0|0,0|
|2000|7|6|85,7|1|14,3|
|2001|8|7|87,5|1|12,5|
|2002|11|10|90,9|2|18,2|

Source: DECOM/SECEX/MDIC Report, 2003. Author's calculations.

> 18 An “investigation” here means an action involving one product and all the countries concerned, because when conducting on-the-spot investigations for the purpose of determining injury, the country of origin of the imported good is irrelevant.

16