rafmacalaba/data-use-mentions-extended huggingface dataset:
a healthy diet in Bulgaria was EUR 169 for a single person and EUR 635 for a family of two adults and two children. If the budget needed for physical activity and for the other functions of food (eating out, holidays, etc.) is also taken into consideration, the total monthly food budget amounted to EUR 196 for a single person and EUR 690 for a family of two adults and two children (Table 3).<sup>23</sup> When converted to 2020 Bulgarian Levas using official food CPIs, these monthly food expenditures correspond to BGN 387 for a single person and BGN 1,455 for a family of two adults and two children. In relation to the AROP poverty line, the cost of a food basket for a single person amounts to approximately 76% of the 2021 AROP poverty line (based on the 2020 income year). The corresponding food basket represents about 137 percent of the AROP corresponding poverty line for a family consisting of two adults and two children<sup>24</sup> .

**Table 3** . **Cost of Food Basket Estimates, Monthly Average**

||2015<br>Euros|2015<br>BGN|2020 BGN|
|---|---|---|---|
|Single Person|169|330|387|
|Single Parent and One Child|330|644|755|
|Single parent and Two Children|490|958|1,122|
|Family of two adults and one child|499|975|1,142|
|Family of two adults and two children|635|1,242|1,455|
|Single Person, Including physical activity and other functions|196|383|449|
|Family of two adults and two children - Including physical activity and other functions|690|1,349|1,581|

_Source: Own estimates based on EC reference food baskets, official Food
- Mahmud, M. and E. Riley (2021). Household response to an extreme shock: Evidence on the immediate impact of the COVID-19 lockdown on economic outcomes and well-being in rural Uganda. _World Development 140_ , 105318.

- Malawi National Statistical Office (NSO) (Government of Malawi) (2020). Malawi - Fifth Integrated Household Survey 2019-2020. Public Use Dataset. Ref: MWI_2019_IHS-V_v05_M. Dataset downloaded from `https://doi.org/10.48529/yqn3-zv74` .

- Malawi National Statistical Office (NSO) (Government of Malawi) (2022). Malawi - High-Frequency Phone Survey 2020-2022. Public Use Dataset. Ref: MWI_2020_HFPS_v13_M. Dataset downloaded from `https://doi.org/10.48529/q6pt-dk67` .

- Mathieu, E., H. Ritchie, L. Rodés-Guirao, C. Appel, C. Giattino, J. Hasell, B. Macdonald, S. Dattani, D. Beltekian, E. Ortiz-Ospina, and M. Roser (2020). Coronavirus pandemic (COVID-19). Our World in Data. https://ourworldindata.org/coronavirus.

- McKenzie, D. (2012). Beyond baseline and follow-up: The case for more T in experiments. _Journal of Development Economics 99_ (2), 210–21.

- Michler, J. D. and A. L. Josephson (2017). To specialize or diversify: Agricultural diversity and poverty dynamics in Ethiopia. _World Development 89_ , 214–226.

- Mottaleb, K. A., S. Mohanty, and A. K. Mishra (2015, February). Intra-Household Resource Allocation under Negative Income Shock: A Natural Experiment. _World Development 66_ , 557– 571.

- Mulwa, C. K. and M. Visser (2020). Farm diversification as an adaptation strategy to climatic shocks and implications for food security in northern Namibia. _World Development 129_ , 104906.

- National Bureau of Statistics (NBS) (2019
poverty rate that was close to Abidjan, but then rose abruptly between 1986 and 1987. Was the West Forest region so much better off than the East Forest region in 1985 and 1986? If so, what would account for the dramatic decline in per capita expenditures over the four years?

**Table 2 Headcount Index of Poverty by Region**

_(Poverty Line = 75000 CFAFper year in 1985 CFAF)_

|_Region_|_1985_|_1986_|_1987_|_1988_|_1993_|_1995_|
|---|---|---|---|---|---|---|
|Abidjan|0.007|0.014|0.018|0.004|0.051|0.202|
|Other Cities|0.080|0.064|0.059|0.125|0.312|0.286|
|East Forest|0.144|0.095|0.105|0.176|0.389|0.410|
|West Forest|0.016|0.019|0.105|0.193|0.382|0.501|
|Savannah|0.259|0.132|0.248|0.354|0.494|0.494|
|C6te d'Ivoire|0.111|0.069|0.115|0.178|0.323|0.368|

**Table 3 Mean Household Expenditure Per Capita by Region**

|_(in_<br>_1985 CFAFpe_|_r year)_||||||
|---|---|---|---|---|---|---|
|_Region_|_1985_|_1986_|_1987_|_1988_|_1993_|_1995_|
|_Mean expenditure_|_per capita_||||||
|Abidjan|
. We conducted a behavioral experiment on a nationally representative sample of the middle class in Jordan– the Jordan Gives experiment– to identify the effect of enhanced transparency on the support for, and the preferred design of, social safety nets.<sup>3</sup> The experiment involved a nationallyrepresentative sample of 420 participants recruited from 21 middle-class primary sampling units (PSUs) (ie localities) across Jordan; within each PSU, participants were randomly assigned to treatment and control groups of 10 subjects. Each participant received a fuel voucher roughly comparable to the daily minimum wage.<sup>4</sup> Participants in the control

> 1 For example, the literature has established that trust in the goverment is an important determinant of compliance with taxation obligations of citizens and firms (Barone and Mocetti 2011; Friedman, Johnson, and Kaufmann 2000; Johnson et al. 2000; Silverman, Slemrod, and Uler 2014).

> 2 A government’s failure to provide such credibility could affect the provision of public goods in different forms: in more mature democracies through voting outcomes, and in other cases, through tax evasion, exercise of corruption, or public protest.

> 3 Social safety nets (SSNs), also known as social assistance or welfare schemes, are defined as noncontributory transfers targeted to the poor or vulnerable. They include income or in-kind support and can be made conditional on certain behaviors of recipients’households (e.g. conditional cash transfers, CCTs) or provided without any conditions (e.g. unconditional cash transfers, UCTs) (Grosh et al. 2008, World Bank 2009).

> 4 The experiment was followed by a Becker, DeGroot, and Marschak (1964) auction to establish valuation

2
> <!-- Start of picture text --> = Ln[new women-owned establishments per worker, 1994]<br>3<br>g<br>Fay<br>=2 eT<br>& .<br>aN °<br>oOo °<br>3 . °<br>= °<br>so ; i :<br>Cc ° Pg<br>z5 3 . i ry:<br>5°<br>= 1992 1996 2000 2004<br>= Year of First Election Under 73rd Amendment<br><!-- End of picture text --> <!-- Start of picture text --> Women-owned share of new establishments, 1994<br>Tt<br>fe))<br>ae - o ° e o o .<br>- s e<br>£<br>Eo5 . [. ¢<br>= 7 e<br>re=oO * b@ 4 ¢t °o ———_—_.<br>oo2 $of° 3 ° o<br>c bd : o<br>5 ° Py . °<br>ow ° ¢<br>£ . .<br>° 3 + ¢ °<br>te . ry 3 3 . °<br>cs - 3 io; 3 .<br>8<br>5r}= .sb ia zi . ‘3 .<br>1992 1996 2000 2004<br>Year of First Election Under 73rd Amendment<br><!-- End of picture text -->
|39.2|37.1|76.3|6.8|3.0|4.9|
|IV|95.1|94.8|94.9|66.3|71.4|68.8|7.9|3.3|5.6|
|V|97.6|97.2|97.4|72.9|78.6|75.8|9.2|3.8|6.5|
|Rural|92.3|87.6|90.1|34.8|31.0|32.9||||
|Urban|96.8|96.6|96.7|70.2|75.0|72.5||||

Source: Staff estimates from SSB and State Education Commission data.

This trend owes much to the increasing enrollments in private universities and introduction of user fees in public higher education. However, the differences in the rates of cost recovery and unit costs within higher education are not captured here. But, it is very unlikely that a more sophisticated calculation would reverse the finding that Chinese system of education is fairly egalitarian in its global structure of access and public expenditure.

Yet, the structural equity has not translated into equitable educational benefits across provinces. While primary education are relatively targeted to poor provinces, accessibility to post-primary education shows marked interprovincial variance. When provinces are ranked by per capita income from poor to rich, the avowed policy of the government to ensure an egalitarian distribution of educational expenditure increasingly vanishes (Fig 5). Per-pupil expenditures are disproportionately higher in rich provinces compared to those in poor provinces. The richest quintile of provinces Shanghai,

> 3 Cumulative public spending on education refers to the total amount of public resources appropriated to a generation of people passing through their schooling years. It captures the distribution of cumulative benefits (education) among people with different school careers,
_Work : Climatic Water Variability and Labor MarketOutcomes in Sub-Saharan Africa_ (Policy Research Working Paper Series No. 10823). The World Bank. Retrieved from https://ideas.repec.org/p/wbk/wbrwps/10823.html

- Kurukulasuriya, P., Kala, N., & Mendelsohn, R. (2011). Adaptation And Climate Change Impacts: A Structural Ricardian Model Of Irrigation And Farm Income In Africa. _Climate Change Economics (CCE)_ , _2_ (02), 149-174. Retrieved from https://ideas .repec.org/a/wsi/ccexxx/v02y2011i02ns2010007811000255.html doi: 10.1142/S2010007811000255

- MacDonald, A. M., Bonsor, H. C., O Dochartaigh, B. , & Taylor, R. G.<sup> ́</sup> (2012). Quantitative maps of groundwater resources in Africa. _Environmental Research Letters_ , _7_ (2), 153161. Retrieved from https://iopscience.iop.org/article/10.1088/1748 -9326/7/2/024009 doi: 10.1088/1748-9326/7/2/024009

- Margat, J., & van der Gun, J. (2013). _Groundwater around the world: A geographic synopsis_ . doi: 10.1201/b13977

- Maru, H., Haileslassie, A., & Zeleke, T. (2023, 05). Impacts of small-scale irrigation on farmers’ livelihood: Evidence from the drought prone areas of upper awash subbasin, ethiopia. _Heliyon_ , _9_ , e16354. doi: 10.1016/j.heliyon.2023.e16354

- Mendelsohn, R., Nordhaus, W., & Shaw, D. (1994). The impact of global warming on agriculture: A ricardian analysis. _American Economic Review_ , _84_ (4), 75371. Retrieved from https://EconPapers.repec.org/RePEc:aea:aecrev:
Table 1: Application characteristics, by district

||Gatsibo|Kayonza|Kirehe|Ngoma|Nyagatare|Rwamagana|All|
|---|---|---|---|---|---|---|---|
|Applications|390|310|462|381|327|315|2,185|
|Qualifed|333|258|458|365|272|277|1,963|
|Has TTC score|317|233|405|338|260|163|1,716|
|Mean TTC score|0.53|0.54|0.50|0.53|0.54|0.55|0.53|
|SD TTC score|0.14|0.15|0.19|0.15|0.14|0.12|0.15|
|Qualifed female|0.53|0.47|0.45|0.50|0.44|0.45|0.48|
|Qualifed age|27.32|27.78|27.23|27.23|26.98|27.50|27.33|

applied to adjacent pairs of districts. In Appendix C, we use this geographical feature of applications to test for cross-district labor-supply effects and fail to reject the null that these are zero.

# **3.2 Teacher attributes**

During February and March 2016, we visited schools soon after they were enrolled in the study to collect baseline data using surveys and ‘lab-in-the-field’ instruments. School surveys were administered to head teachers or their deputies, and included a variety of data on management practices—not documented here—as well as administrative records of teacher attributes, including age, gender, and qualifications. The data cover all teachers in the school, regardless of their eligibility for the intervention. Teacher surveys were administered to
construction process. A check against the well-known Penn World Tables data (see <u>www.nber.org) for a range of countries suggests that physical capital/output ratios were</u> generally rising quite rapidly in the 1970-1990 period for which the capital accumulation data are available. The fact that the growth rates of K/Q and Edn/Q are generally lower than their growth relative to the labor input does, however, give reason for caution about common assumptions, such as Hicks-Neutral technical change in all sectors used by Harrigan (1997) and Kee (2001).

Despite the evidence from many different types of empirical studies on the potential role of Rybczynski effects, the coincidence of high rates of accumulation of physical and human capital over the period, and the rapid shift of developing countries into exports of manufactures and services, is clearly not definitive evidence of causation. However, it is strongly suggestive, and needs to be examined in conjunction with changes in trade policy and in technology.

# **Protection Policies**

Protection policy is frequently advocated as a means to promote industrial development. It can certainly do this for import competing activities, such as production of consumer goods. However, this production pattern locks producers into small, and typically slow growing, markets for their output. Further, it introduces a major discontinuity. Under a protectionist policy regime, an exporter must not only have sufficient comparative advantage to be able to compete in world markets, but must have sufficient advantage to be able to compete _despite_ the cost increases resulting from protection levied on its intermediate inputs, and the adverse effects of real exchange rate devaluation on its costs for factors and nontraded goods.

Developing countries have increasingly come to recognize the adverse impacts of protection on their export performance. and begun to adjust their policies towards more open trade regimes. The most profound and far-reaching manifestation of developing countries’ interest in greater participation in trade is evident from the wave of unilateral 20
0<br>False positive rate False positive rate<br>1.0 1.0<br>0.8 0.8<br>0.6 0.6<br>True positive rate 0.4 True positive rate 0.4<br>0.2 0.2<br>0.0 0.0<br><!-- End of picture text --> _<mark>Note:</mark>_ <mark>C</mark> DR represents Call Detail Record, and BIC Bayesian Information Criterion. <mark>Cells computed based on out of sample predictions resulting from 5 fold cross validation. Source: authors’ analysis from telecom data.</mark> 5
|**17**|<br>GOAL 13: Climate Action (5 year<br>moving average of availability)|<br>Dimension<br>3.3:<br>Environmental<br>(SDG 1315)|SDG 13|UN Global SDG Indicators<br>Database|
|**18**|GOAL 15: Life on Land (5 year moving<br>average of availability)|,<br>Dimension<br>3.3:<br>Environmental<br>(SDG 1315)|SDG 15|UN Global SDG Indicators<br>Database|
|**19**|GOAL 16: Peace and Justice Strong<br>Institutions (5 year moving average of<br>availability)|,<br>Dimension<br>3.4:<br>Instituational<br>(SDG 16-17)|SDG 16|UN Global SDG Indicators<br>Database|
|**20**|GOAL 17: Partnerships to achieve the<br>Goal (5 year moving average of<br>availability)|<br>Dimension<br>3.4:<br>Instituational<br>(SDG 16-17)|SDG 17|UN Global SDG Indicators<br>Database|
|**21**|Legislation and governance|<br>Dimension<br>5.1:<br>Legislation<br>and<br>governance|SDG<br>17.18.2|UN Global SDG Indicators<br>Database|

42
economies since the mid 1990s**

After an initial sharp drop in the early 1990s, real wages in virtually all transition economies have been growing at a pretty high rate since the mid 1990s, following gains in labor productivity.<sup>9</sup> However, the pattern of wage adjustment has differed considerably across ECA sub-regions. Generally, the wage drop has been much deeper in the CIS than in CEE. While in the CIS real wages are currently at around 50 percent of their pre-transition level, they close to it in CEE (Figure 10). After all in a few CEE countries wages are already higher than before the transition. Coupled with the earlier analysis of employment dynamics, these data suggest that while in CEE the brunt of adjustment to the transition shock was borne by employment, in the CIS it was borne by wages.

> 9  In most transition economies real wages are still lower than before the transition, but this result needs to be treated with caution.  The actual real wages decline was most probably much less then the measured one  This is due to the fact that the pre-transition level of real wages was overestimated in most of the transition economies.  This overestimation resulted from prices being set at below-the equilibrium level, as attested by pervasive consumer good shortages.  If prices were set so as to equate the demand for and the supply of goods, as it is the case in a market economy, then real wages before the transition would be correspondingly lower.  In other words, real wages before the transition were often not quite “real” in terms of consumer purchasing power.  If this factor were taken into account, the reported wage drop would be much less, although the degree of the correction varies by country.  In addition, wage data are likely to be affected by wage arrears and non-payment of wages, a problem particularly pronounced in CIS (particularly at the early stage of the transition).  Finally, a widespread practice of underreporting of wages to avoid tax payments also means that
_Note_ : South is defined as low- and middle-income countries and North is defined as high-income countries according the Bank’s current income classification. Excludes Palestinian refugees under UNRWA’s mandate. 2015 data excludes refugee situations with less than 1,000 people.

The story of global displacement can be explained largely by just a few significant historical conflicts. Data on UNHCR’s population of concern<sup>42</sup> show that 10 historical conflicts accounted for the majority of forcibly displaced under the agency’s mandate: around 40 to 50 percent from 1991 to 1995, between 50 and 60 percent from 1996 to 2004, and over 65 percent since 2005 (see Figure 5).<sup>43</sup> In South Asia and the Middle East, these include the prolonged conflicts in Afghanistan and Iraq and the more recent Syrian crisis. In Africa, the persistent conflict and instability in Burundi, DRC, Somalia and Sudan. In Latin America, four decades of internal armed conflict in Colombia. And in Europe and Central Asia, the wars in Azerbaijan and the former Yugoslavia. By the end of 2015, the top 10 origin countries accounted for more than two-thirds of IDPs, three-quarters of all refugees (including Palestine refugees) and more than 40 percent of all asylum-seekers. The top 15 origin countries accounted for more than 80 percent of IDPs, more than 80 percent of all refugees (including Palestine refugees) and over half of all asylum-seekers (see Figure 6).

> 42 Includes refugees, asylum-seekers and IDPs protected or assisted by the agency. Excludes Palestinian refugees under UNRWA’s mandate.

> 43 Major displacement crises are identified based on their cumulative displacement figure over the period 1991-2015.
*|0.286***|
|(constant 2010 IDR)|(0.698)|(0.760)|(0.009)|(0.027)|(0.029)|
|Growth in GRP per capita|-0.163**|0.054|0.002**|-0.004|-0.001|
||(0.070)|(0.048)|(0.001)|(0.003)|(0.004)|
|Number of observations|272|272|272|272|272|
|R-squared|0.454|0.526|0.797|0.675|0.713|
|Year dummies|Yes|Yes|Yes|Yes|Yes|

Source: Author’s calculations using Sakernas data Notes: Robust standard errors in parentheses. ***p<0.01, **p<0.05, *p<0.1.

17
- Felman, Josh, Sandefur, Justin, Subramanian, Arvind and Duggan, Julian (2019). Is indias consumption really falling? Blog. Center for Global Development.

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- Gupta, Arpit, Malani, Anup and Woda, Bartek (2021a). Explaining the income and consumption effects of covid in india. NBER Working Papers w28935. National Bureau of Economic Research.

- Gupta, Arpit, Malani, Anup and Woda, Bartosz (2021b). Inequality in india declined during covid. NBER Working Papers w29597. National Bureau of Economic Research.

- Haziza, David and Beaumont, Jean-Franois (2017). Construction of weights in surveys: A review. _Statistical Science_ , **32.
Economies included in the Global Findex survey and database

|**Economy**|**Region**<sup>**a**</sup>|**Income group**|**Data collection**<br>**period**|**Interviews**|**Design**<br>**effect**<sup>**b**</sup>|**Margin**<br>**of error**<sup>**c**</sup>|**Mode of**<br>**interviewing**|**Languages**|**Over-**<br>**sample**<sup>**d**</sup>|**Exclusions and other sampling details**|
|---|---|---|---|---|---|---|---|---|---|---|
|Portugal|n.a.|High|Apr 5–May 12|1,000|1.81|4.2|Landline<br>and cellular<br>telephone|Portuguese|Lisbon||
|Qatar<sup>e</sup>|n.a.|High|Feb 10–Apr 19|1,032|1.49|3.7|Cellular<br>telephone|Arabic||The sample includes only Qataris and<br>Arab expatriates. The excluded population<br>represents approximately 50% of the total<br>adult population.|
|Romania|ECA|Upper middle|Apr 16–May 12|1,008|1.57|3.9|Face to face|Romanian,<br>Moldovian|Bucharest||
|Russian<br>
br>GE(0) and GE(1)<br><!-- End of picture text --> How about the dynamics of poverty over this period? Unlike many other countries, Brazil does not have an official poverty line. A set of regionally-specific poverty lines calculated by Rocha (1993) for use with PNAD 1990 data has historically been used by many researchers. Rocha

> 12 The E(2) series is not shown on Figure 1, but it is similar and available from the authors upon request.
middle.” Table 2 shows the correlation between income distribution variables: while poverty and the middle class are negatively correlated, they do so imperfectly, suggesting that each measure carries some information. Other variables that we use in the analysis are GDP per capita in 2005 PPP terms, public expenditures in education and health, and mean applied tariffs, all from the World Development Indicators; credit market liberalization, from the _Economic Freedom of the World_ project; the polity score for democracy, from _Polity IV_ ; and the corruption index from the _International Country Risk Guide_ .

# **3. Econometric Methodology**

We estimate a set of regression equations of the form, 5
**Figure 9:  Gender Differences in the Human Capital Index**

<!-- Start of picture text --> Human Capital Index (Gender Disaggregated)<br>Singapore<br>Korea , Rep.<br>Germ any<br>United St ates<br>Russia n Federation<br>Chi na<br>C o Thail lo mbiaan T urd key<br>Ph ili ppI nind eosn esia<br>M or oc co<br>In dia<br>B en in<br>S outh Africa<br>Côte d'Ivoire<br>C had<br>6 8 10 12<br>Log Real GDP Per Capita at PPP<br>Note: Dataset version 21 Sept 2018<br>Legend: Square -- Male, Line -- Female<br>1<br>.8<br>.6<br>.4<br>Productivity Relative to Benchmark<br>.2<br><!-- End of picture text --> Notes: This figure reports the Human Capital Index. The vertical axis measures productivity relative to the benchmark of complete education and full health. A value of x on the vertical axis means that the productivity as a future worker of a child born today is only x�100 percent what it would be in the benchmark of complete education and full health. Real GDP per capita adjusted for differences in purchasing power parity is taken from the Penn World Tables (Feenstra et. al. (2015)) , with missing countries filled using data from World Bank estimates of GDP at PPP. Graph shows the most recent data for 131 countries where gender‐disaggregated data for all of the HCI components is available. Selected countries are labelled for illustrative purposes.

18