rafmacalaba/data-use-mentions-extended huggingface dataset:
household in moves into poverty if and , where is the international poverty line of 6.85 a day in purchasing power parities (PPP) 2017. ii2 ii1 ii jj = 2 yy < zz yy� > zz zz There are a few reasons why it might be useful to define the lower bound of the middle class as the median of the income distribution of people who have recently moved out of poverty. First, the median income represents the midpoint of the income distribution, so it is less affected by extreme values that could skew the results. This can help to ensure that the middle-class thresholds are fair and representative of the income needs of a typical household.

A second advantage of using the median income as the lower bound of the middle class (upper bound of the vulnerable group) is that it highlights the fact that the vulnerable population is not static, but rather constantly changing. Additionally, using a more reliable statistic like the median allows for a more precise estimate of the minimum income needed to be considered middle class. It is important to note that it does not imply that the probability-based approach (Lopez-Calva & Ortiz-Juarez, 2014) fails to fulfill these conditions; both methods acknowledge the dynamic nature of the vulnerable population.

Finally, employing the median income as the lower bound of the middle class can contribute to making the middle-class thresholds more responsive to economic changes and shifts in income distribution. As the economy grows and more people rise out of poverty, the middle-class thresholds can be adjusted accordingly to reflect these changes. This responsiveness allows for a more inclusive definition of both the vulnerable and middle-class populations, preventing the exclusion of individuals who are making

> 8 World Bank (2021).

8
to maintain credit balance on the Treasury accounts (Bhutan, The Gambia), to finance damages resulting from natural disasters and to obtain foreign currency (Namibia). In some states, borrowing purposes are specific in an annual budget law (Cape Verde) or specified and approved by the Parliament before a loan contract is signed (Maldives).

# **_Procedures for borrowing in domestic markets are relatively strong._**

Documented procedures for local currency borrowing in the domestic market was also found to be another area of relative strength in debt management capacity, with 11 small states meeting the minimum requirement again, in part, reflecting the institutional strength of central banks (that were responsible for issuing domestic debt in these small states). Progress has also been made in developing effective capacity to maintain a complete and up-to-date record of all holders of domestic government securities in a secure registry system.

On the other side of the balance sheet, the DeMPA determined that deficiencies in debt management performance in small states are many and widespread.

# **_Lack of capacity to monitor external borrowing and assess cost-effective terms and conditions_**

Small states score extremely poorly on dimensions of debt management that relate to determining the most beneficial and cost effective borrowing terms and conditions (DPI9.1) and the availability and quality of documented procedures for borrowing in foreign markets (DPI9.2). Only 3 small states met the minimum requirement for DPI9.1, while one has the appropriate quality of documented procedures for borrowing in foreign markets available. This is a glaring omission given that in the majority of small states external debt is the most important component of public debt and the state’s largest portfolio.

# **_Debt reporting_**

The quality of reporting debt data in small states is poor and there is an absence of timely and comprehensive information on public debt. Only 4 of the small states assessed met the statutory and contractual reporting requirement of central government debt to all domestic and external entities (DPI15.1) and none
sent to parents and focused on the youngest child below 6 years old in the household. The text messages were personalized (making a reference to the name of the child) and age appropriate (with different messages sent to parents of children 0-6 months old, 7-12 months old, 13-24 months old, and older than two years old). Messages were designed to actionable advice based on a childhood cur- provide government early development riculum, and built on prior experiences with early childhood development programs in the country. The text message intervention was designed by a Nicaraguan early childhood specialist, in consultation with the ministry of the family and with support from the World Bank.

Prior to program implementation, a baseline survey was conducted in 97 rural villages in the four all households with children 0 to 6 of or municipalities, including years age pregnant women. Earlier work in nearby municipalities (Macours and Vakis, 2014) had demonstrated the role of local leaders in influencing behavioral changes for investment in nutrition and health of young children. The baseline survey therefore also identified, among households with children 0-6 (or pregnant women), all households with local opinion leaders regarding early childhood practices. This included community health workers, preschool teachers, primary school teachers, and a village leader.<sup>4</sup> In the 97 villages, there were a total 2,990 households with at least one child younger than 6 years old, including 406 opinion leaders. Five villages had no opinion leaders among households with young children.

For households without leaders, a household-level randomization determined which households would receive text messages: 75% were randomly selected to receive text messages, with the remaining 25% serving as control.

In addition to treatment assignment, orthogonal treatment variations were introduced among households selected to participate in the program. First, we randomly selected whether text messages were sent to (i) the father figure (25 percent of the sample), (ii) mother figure (25 percent of the sample) or (iii
76|89|71|

Source: Calculations based on the 2011–12 Bank Regulation and Supervision Survey, which reflects values as of 2010. Values in parentheses refer to the 2007 Bank Regulation and Supervision Survey, which captures data as of 2005. ADV: advanced economies, EMDEs: emerging and developing economies (see Table 1 provides the complete list of countries).

* Such as information which omission or misstatement could change or influence the assessment or decision of a user relying on that information for making decisions.

** Including reasons for not including certain entities, where appropriate.

18 If we focus on the matched sample, the increase is smaller from 90 to 96 percent.

19 If we limit our analysis to only those countries that have responded to both surveys, the gap is smaller (92 percent in 2005 and 95 percent in 2010).

41
9

# _The Main Bottlenecks to Operating Officially: The Entrepreneur's Perspective_

When questioned in the various surveys conducted, entrepreneurs prominently and repeatedly mentioned as the main bottlenecks to operating officially the following: (1) the myriad of regulations in the foreign exchange and trade regimes; (2) high inflation; and (3) the high tax rates and volatile and often retroactive tax regulations. Interestingly, such highly restrictive bottlenecks, in the eyes of entrepreneurs, contrasted sharply with the entrepreneur and manager's relatively nonintrusive assessment of more conventional determinants, such as labor regulations, the skill and motivation of the labor force, enterprise registration, and infrastructure constraints. Not surprisingly, when questioned about the type of measures that would provide a strong incentive to return to the official economy, of paramount importance was the removal of administrative controls in the trade and foreign exchange regimes, as well as a stable and moderate tax structure and macroeconomic stability (that is, low inflation)."<sup>4</sup> From these microsurveys, the empirical link between the lack of liberalization and stabilization and the flight to the unofficial economy appears to be rather strong. In fact, in response to the question of timing and extent to which entrepreneurs would be prepared to switch toward operating officially, about 50 percent stated that they would come back from unofficialdom within two years of implementation of far-reaching economic liberalization and tax reform measures (30 percent would do so during the first year), and over 33 percent would come back thereafter. Only about 15 percent indicated that there would be no coming back to the official economy, some because they did not believe in the government's ability to carry out sustained liberalization reforms, and some because they were doing just fine where they were and intended to carry on regardless."<sup>5</sup> Clearly, however, the bulk of the unofficial economy appears to be shallow and thus amenable to reversal by liberalizing economic policies.

_The Extent of the Unofficial Economy in
**_Figure 2 Payments of Taxes and Benefits of Public Spending by Household Market Income Decile (Million JOD)_**

<!-- Start of picture text --> 400<br>300<br>200<br>100<br>0<br>-100<br>-200<br>-300<br>-400<br>-500<br>Decile 1 2 3 4 5 6 7 8 9 Decile 10<br>Household per capita market income decile<br>Direct Taxes Indirect Taxes – direct Indirect Taxes – indirect<br>Direct Transfers Total Indirect Subsidies – direct Total Indirect Subsidies – indirect<br>In-kind Spending (education) In-kind Spending (health) Total Impact<br>Figure 3 Payments of Taxes and Benefits of Public Spending by Household by Household Market Income Decile<br>(Percentage of Market Income)<br>100<br>80<br>60<br>40<br>20<br>0<br>-20<br>Decile 1 2 3 4 5 6 7 8 9 Decile 10<br>Household per capita market income decile<br>Direct Taxes Indirect Taxes – direct Indirect Taxes – indirect<br>Direct Transfers Indirect Subsidies – direct Indirect Subsidies – indirect<br>In-kind Spending (education) In-kind Spending (health) Total Impact<br>Millions<br>Fiscal Revenue / Expenditure (JD)<br>Income)<br>Fiscal Revenue / Expenditure (Percentage of Market<br><!-- End of picture text --> Notes: Households are grouped into per capita market income deciles. Direct taxes include personal income tax, property tax and border exit tax. Indirect taxes include GST and SST. Indirect taxes-indirect is the cascading indirect effect of GST exemptions on selected goods and services. It has been modelled using the 2010 IO table uprated to 2016. Direct transfers include NAF, bread subsidy compensation and other government
, Hossain, M. M., Huq, M., & Wheeler, D. (2014).</mark> _<mark>Climate change, soil salinity, and the economics of high‐yield rice production in coastal Bangladesh</mark>_ <mark>. The World Bank.</mark> De Louw, P. G. B., Oude Essink, G. H. P., Stuyfzand, P. J., and van der Zee, S. E. A. T. M.: Upward groundwater flow in boils as the dominant mechanism of salinization in deep polders, the Netherlands, J. Hydrol., 394, 494–506, 2010.

<mark>FAO (Food and Agriculture Organization of the United Nations). 2016. AQUASTAT Main Database, FAO, Rome.</mark> <u><mark>http://www.fao.org/nr/water/aquastat/data/query/index.html.</mark></u> <mark>Genua‐Olmedo, A., Alcaraz, C., Caiola, N., & Ibáñez, C. (2016). Sea level rise impacts on rice production: The Ebro Delta as an example.</mark> _<mark>Science of The Total Environment</mark>_ <mark>,</mark> _<mark>571</mark>_ <mark>, 1200‐1210.</mark> Holman, I. P., Whelan, M. J., Howden, N. J. K., Bellamy, P. H., Willby, N. J., Rivas‐Casado, M., and McConvey, P.: Phosphorus in groundwater – an overlooked contributor to eutrophication, Hydrol. Process., 22, 5121–5127, 2008 10
around 7 percent. This shows the importance of the gap measure, providing us further insight in addition to the headcount measures.

# _4.4 Income-group Analysis_

Next we conduct our analysis by different income groups as defined by the World Bank: low income, lower-middle income, and upper-middle income. The results are presented in Figure 4. Similar to our regional analysis, we find that the trend of the stunting gap can reveal a different story than the trend of the stunting headcount. Specifically, the stunting headcount of lowermiddle-income countries as a whole was slightly lower than that of low-income countries until sometime between 2000 and 2005. However, the trend of the stunting gap of lower-middle-income countries during this period of time was higher than that of low-income countries. In the reference year of 2000, the difference amounted to 2 percentage points.

Figure 4: Trends of stunting headcount and gap by income groups <!-- Start of picture text --> Stunting headcount<br>60%<br>50%<br>40%<br>30%<br>20%<br>10%<br>0%<br>1995 2000 2005 2010<br>Low income Lower middle income Upper middle income<br><!-- End of picture text --> 20
alone goes a long way in explaining why the poor are less sick than the rich in most self-reported data. In fact, the poor are sicker, a conclusion that is clear in this high frequency data.

Similarly, and possibly more importantly from the policy perspective, this pattern is evident in the number of visits to medical practitioners (Figure 3).<sup>12</sup> Surveys commonly show that doctor‘s visits are positively correlated with income. In Figure 3, this pattern does, in fact, emerge but with some interesting nuances. In the monthly data – the most common recall period in use – there is a clear increase in doctor visits in the lower half of the sample, which plateaus in the middle of the sample. There may be a further increase at the top of the income spectrum, but this is an area with fewer observations. Except for the leveling off – which, unless a demand function had a careful, non-linear, specification of income effects, rather than the standard log–log specification, the regression would miss – our monthly results are similar to standard results.

However, when we turn to the weekly data, an entirely different story emerges. There may be a tiny increase of doctor visits with income at the lowest level of income, though this is neither noticeably nor significantly different from a flat line. Much more prominent is the dramatic **decline** of doctor visits throughout the reliable range of the data. Again, the number of doctor‘s visits may increase at the very top of the income spectrum, but the data is too sparse to tell. The decline in doctor‘s visits as a function of income, when measured in weekly surveys as opposed to the increase when measured monthly, raises suspicions about the conventional wisdom dictating that richer people visit medical practitioners more frequently.

Finally, we examine how recall and PCE affect health care expenditures. One issue that limits our ability to present a full characterization of the impact of
3.5|2,175|251,124|868,359|
|7|8.7|2.6|3.3|2,596|300,020|990,845|
|8|8.7|2.8|3.1|3,196|369,119|1,137,665|
|9|8.7|3.0|2.9|4,236|489,272|1,430,198|
|richest|8.7|3.5|2.5|8,149|941,671|2,318,160|
|Total|86.6|25.4|3|26,852|310,157|1,056,611|

Source: Forecasted numbers based on HEIS 2018/19. Note: GDP and CPI numbers are from Statistical Center of Iran.

2 This is a very crude prediction of poverty due to the assumption of a one-to-one relationship between GDP and consumption, but our main goal is to have consumption in the current prices and baseline poverty level to check the impact from the reform. It is the change over the forecast baseline which represents the magnitude of the impact of the reform; the precise levels matter less for our purposes.

3
27 The source of the dollar value of agriculture domestic subsidies is Ng and Olarreaga (2004), obtained from WTO members’ notifications during 1999. The method of computing the AVE of domestic support is to treat them as NTMs and apply the same method as for Core NTMs. Production subsidies vary widely in their uses and aims. They include direct payments to producers (such as deficiency payments), input subsidies (on irrigation water, for example), policies that distort market prices (market price supports), and interest subsidies on commodity loan programs. Also included in these measures are the “boxed” policies demarcated in the Uruguay round. These include direct payments and price support benefits that directly influence production (“amber box”), payments tied to limits on production (“blue box” policies), research, domestic food aid, environmental programs, and certain crop insurance and income safety net programs (“green box” policies).

28 The main source of the ad valorem tariff data is the WTO Integrated Data Base (IDB). Specific (dollar/unit) tariffs can be converted to their ad valorem equivalents by dividing the specific tariff by the unit value of the imported product. The International Trade Commission (ITC) provides the data to accomplish this at the tariff line level.

13
Evidence from other countries comes from Gilbert, Sakala, and Benson (2002), who find that in Malawi, male heads of household have significantly higher fertilizer use, cash crop area and total field area than female farmers, indicating higher levels of land, labor, and cash available to male farmers. Moock (1976) examines Kenya and finds that women use smaller bundles of physical inputs, especially store-purchased inputs, than do their male counterparts. Women use noticeably less chemical fertilizer, on average, and are less likely to plant a hybrid seed variety or to use insecticides.

Udry et al. (1995) examine households in Burkina Faso and show that plots controlled by women are farmed less intensively than plots controlled by men, and virtually all fertilizer is concentrated on plots controlled by men. Uttaro (2002) uses data from Malawi and finds that women’s marital status affects their use of fertilizer. As a group, married women are more likely to use fertilizer than are female-headed households by a margin of 62 percent to 45 percent. Indeed, married women are fairly close to the level of married men, 67 percent of whom are able to afford fertilizer.

For purchased inputs overall, Peterman, Behrman, and Quisumbing (2010) review 20 studies from the last decade on gender differences in the use of technological inputs (inorganic fertilizer, insecticide, improved seed varieties, and mechanical power). They find that in 16 out of 20 studies, men use more of these inputs than women, whereas in the other four studies, women use more of these inputs.

Returning to the cross-country data, an interesting pattern is that the gap between male- and female-headed households seems to _increase_ with higher overall use of fertilizer in a country, as shown in figure 8. This finding suggests that this is not simply a problem of 15
were aligned with what children were expected to know in the early years of primary school.

The cost of each early education pathway was drawn from the Indonesia ECED Project evaluation data (World Bank 2014) and the 2012 _Nomor Unik Pendidik Dan Tenaga Kepandidikan_

> 5 As a robustness check, we re-estimated the model in Table 5c using a sub-sample of children (N=2,874) for whom we have child development measures at age 4 using the Early Development Instrument (EDI). For this sub-group analysis, we included EDI scores at age 4 to control for children’s early childhood developmental outcomes. We find similar results: compared to their peers who enrolled in other early education pathways, children who enrolled in playgroup at age 3-4 followed by kindergarten at age 5-6 performing significantly better in language and math tests in primary schools. The results of this sub-sample analysis are available upon request.

> 6 Our analysis based on the sub-sample of children for whom we have data on development outcomes at age 4 gives us qualitatively very similar results. (See footnote 6) However, we choose to be conservative in our interpretation and present the cost-effectiveness results as _indicative_ cost-effectiveness.

19
- Yang, T., Li, C., Zhou, C., Jiang, S., Chu, J., Medina, A., Rozelle, S., 2016. Parental migration and smoking behavior of left-behind children: evidence from a survey in rural Anhui, China. Int J Equity Health 15. https://doi.org/10.1186/s12939-016-0416-7

- Ye, J., Wu, H., Rao, J., Ding, B., Zhang, K., 2016. Left-behind women: gender exclusion and inequality in rural-urban migration in China. The Journal of Peasant Studies 43, 910–941. https://doi.org/10.1080/03066150.2016.1157584

- Yi, F., Liu, C., Xu, Z., 2019. Identifying the effects of migration on parental health: Evidence from leftbehind elders in China. China Economic Review 54, 218–236. https://doi.org/10.1016/j.chieco.2018.11.005

- Yi, H., Li, G., Li, L., Loyalka, P., Zhang, L., Xu, J., Kardanova, E., Shi, H., Chu, J., 2018. Assessing the Quality of Upper-Secondary Vocational Education and Training: Evidence from China. Comparative Education Review 000–000. https://doi.org/10.1086/696920

- Yi, J., Zhong, B., Yao, S., 2014. Health-related quality of life and influencing factors among rural leftbehind wives in Liuyang, China. BMC Womens Health 14, 67. https://doi.org/10.1186/14726874-14-67

- Zhang, H.-H., Jiang, Y.-Y., Rao, W.-W., Zhang, Q.-E., Qin, M.-Z
This is due to the absence of comparable measures of learning in developing countries. This excludes a significant portion of the global distribution, in particular countries with the most potential to gain from human capital accumulation.

In this paper, we bridge this gap. We introduce a database of globally comparable learning outcomes for 164 countries covering 98 percent of the global population from 2000 to 2017.<sup>5</sup> This is the largest and most current global learning database, one of the first to disaggregate learning results by gender, and introduces methodological improvements, such as inclusion of standard errors to quantify uncertainty. The database will be updated at regular intervals and made available

> 2 Examples include Mincer (1984), Mankiw, Romer, and Weil (1992), and Lutz and Samir (2011).

> 3 We refer to ‘schooling’ as measured by enrollment or average years of school and ‘learning’ measured by the stock of cognitive skills on basic proficiencies including mathematics, reading and science.

> 4 See related papers by Krueger and Lindahl (2001); Pritchett (2006); Hanushek and Woessmann (2012a).

> 5 There are two administrative regions: Hong Kong and Macao, which we refer to as countries for simplicity.

2
# Table D.2: **Household Survey** – Tests for Balance and Attrition

Panel A reports tests for balanced survey coverage. Each column represents results from a separate regression based on the entire sample frame (N=5,554). “Surveyed” is a dummy variable equal to one if a beneficiary household was located and completed the entire survey. Treated is a dummy variable equal to one for all households that had pledged _<_ 2 hectares of land as cllateral and were eligible for 100% debt relief. Panel B presents tests for balanced attrition across treatment and control. “Surveyed” includes duplicates, where the same beneficiary had multiple loans in the sample frame; 2,897 surveys were administered in total. “Other” includes a small number of surveys that were not attempted and respondents outside the sample area. Standard errors in parentheses. + p _<_ 0.10 ** p _<_ 0.05 *** p _<_ 0.01.

_Panel A : Survey Coverage_

||Surveyed=1||
|---|---|---|
||(1)|(2)|
|Treated|0.010|0.024|
||[0.01]|[0.03]|
|Log eligible balance||0.00|
|||[0.01]|
|Coop bank loan||0.051|
|||[0.04]|
|Crop loan||0.028|
|||[0.05]|
|Total land||0.027|
|||[0.06]|
|Year disbursed||0.023**|
|||[0.01]|
|Observations|5,554|4,808|
|R-squared|0.001|0.011|

_Panel B: Test for Balanced Attrition_

||Treatment|Control|