rafmacalaba/data-use-mentions-extended huggingface dataset:
Edmonds and Shrestha (2012) investigate the impact of MEA on child labor and schooling using micro-data from around 60 countries, mostly low-income countries. They found no short-term effects of enforcement of MEA in all countries but one.

The evidence of long-term consequences of child-labor laws is also very limited. Most of what is known has used CSL as an instrumental variable to estimate returns on education (Angrist and Krueger 1991; Oreopoulos 2006a and 2006b). As far as we are concerned, this is the first study to look at long-term effects of a child-labor ban. Depending on how the problem is framed—either as an earlier or later exposure to the labor market—some of the findings discussed in this paper can contribute specifically to the literature on returns to experience (Imbens and van der Klaauw 1995; Connolly and Gottschalk 2006; Grooger 2009; Angrist 1990; Angrist and Krueger, 1994; Angrist et al. 2011).

In fact, this paper relates more broadly to the growing literature on long-term effects of interventions designed for the youth groups. A great deal of these studies look at educational policies such as Dustmann et al (2012) on high-school quality, Deming et al (2013) on high-school accountability, Chetty et al (2014) on teacher quality, Lavy (2015a) on school choice, and Lavy (2015b) on teacher pay-for-performance. Others assess the impact of either youth training or vocational education on labor-market outcomes (Card et al. 2011; Hicks et al. 2013; Hirshleifer et al. 2013; Ripani et al. 2015; Attanasio et al. 2015) or ‘remedying’ interventions targeted at disadvantaged children (Angrist et al. 2006). The evidence that comes out of these studies point to a long-term effect on education attainment or labor-market outcomes. Our study adds new evidence to this body of the literature by evaluating the long-term effects of an active labormarket policy aimed at young people that acts through a channel underexplored so far— restricting the choice-set of time allocation of the youth.
# **3.4. Scenario Analysis with the Global Computable General Equilibrium (CGE) Model**

The global CGE modeling framework of the GTAP uses aggregated data on regions and commodities for its objectives.<sup>33</sup> Version 7 is used here, covering 57 commodities, 113 countries/regions, and 5 factors of production––although for purposes of this study the 113 countries/regions are aggregated to 6.<sup>34</sup> Three scenarios are considered: (i) a full FTA for goods between Bangladesh and India, (ii) India‘s unilateral duty-free, quota-free (DFQF) offer to Bangladesh, and (iii) a full FTA for goods and improved connectivity (FTA plus). To capture the improvement in connectivity, a 25 percent drop in the bilateral trade-cost margin between Bangladesh and India is simulated.

An FTA-plus–improved-connectivity option clearly would have the greatest impact on world imports to both countries (Figure 5). In both FTA-only and FTA-plus scenarios, Bangladesh‘s imports would rise more than India‘s because India is Bangladesh‘s primary source and Bangladesh is an insignificant source for India. With the DFQF option, imports into Bangladesh would increase by only 0.29 percent, since Bangladesh would not liberalize its trade regime. With regard to exports (Figure 6), it is notable that Bangladesh‘s increase would be higher with the FTA-only scenario than the DFQF option. This is because the FTA would increase access to cheaper raw materials through tariff liberalization, which would not occur in the DFQF scenario. However, exports from Bangladesh would rise most in the FTA-

> 31 Rahman (2002) found that about 20 percent of the approximately 50,000 Bangladeshis that chose to go to India for treatment in 1999 went without the right visas: in most cases, patients chose touri **s** t visas to avoid the more arduous medical visa process.

> 32

> Another new Apollo Group hospital is
## **Figure 4: Relative prices (World vs. Ethiopia)**

<!-- Start of picture text --> 0.80<br>0.60<br>0.40<br>0.20<br>0.00<br>-0.20<br>-0.40<br>-0.60<br>-0.80<br>relative price (all CPI) relative non-food price relative food price relative cereal price<br>1997M07 1998M02 1998M09 1999M04 1999M11 2000M06 2001M01 2001M08 2002M03 2002M10 2003M05 2003M12 2004M07 2005M02 2005M09 2006M04 2006M11 2007M06 2008M01 2008M08 2009M03 2009M10 2010M05 2010M12 2011M07 2012M02 2012M09 2013M04 2013M11 2014M06 2015M01 2015M08 2016M03 2016M10 2017M05 2017M12 2018M07 2019M02 2019M09 2020M04<br><!-- End of picture text --> _Sources_ : Authors’ construction using data from NBE database and the World Bank’s Commodity Markets database. _Note_ : An increase represents a real appreciation in favor of Ethiopia.

# 4. Modeling inflation in Ethiopia

The modeling approach adopted in this study accounts for structural features of the Ethiopian economy, notably: (i) exposure to agricultural shocks that affect food prices and the general price level; (ii) import dependence and exposure to shocks to international prices, particularly grains, food, and oil prices; and (iii) financial repression with strong pressure from direct and indirect financing of the fiscal deficit. This approach draws from the study by Durevall et al. (2013) regarding modeling and estimation methodology, as well as Nell (2004) in incorporating structural factors of inflation. This section presents the main blocks of the inflation model.

## **_Structural factors of inflation_**

Drawing on the studies by Nell (2004) and Durevall et al. (2013), this analysis models inflation as driven by deviations of output from its trend level due to shocks as well as changes in the prices of imported goods that are transmitted into domestic prices. This can be
# **Figure VI-5: Medium-term Credit Cycle and GDP Growth**

## **A- Oil exporters**

<!-- Start of picture text --> Kuwait: Medium-term Credit Cycle and GDP Growth<br>(in percent)<br>1967 1977 1987 1997 2007 2017<br>year<br> Medium-term credit cycle GDP Growth<br>40<br>20<br>0<br>-20<br><!-- End of picture text --> <!-- Start of picture text --> Algeria: Medium-term Credit Cycle and GDP Growth<br>(in percent)<br>1967 1977 1987 1997 2007 2017<br>year<br> Medium-term credit cycle GDP Growth<br>30<br>20<br>10<br>0<br>-10<br>-20<br><!-- End of picture text --> <!-- Start of picture text --> UAE: Medium-term Credit Cycle and GDP Growth<br>(in percent)<br>1967 1977 1987 1997 2007 2017<br>year<br> Medium-term credit cycle GDP Growth<br>20<br>10<br>0<br>-10<br>-20<br><!-- End of picture text --> <!-- Start of picture text --> Iran: Medium-term Credit Cycle and GDP Growth<br>(in percent)<br>1967 1977 1987 1997 2007 2017<br>year<br> Medium-term credit cycle GDP Growth<br>Bahrain: Medium-term Credit Cycle and GDP Growth<br>(in percent)<br>1967 1977 1987 1997 2007 2017<br>year<br> Medium-term credit cycle GDP Growth<br>Oman: Medium-term Credit Cycle and GDP Growth<br>(in percent)<br>1967 1977 1987 1997 2007
yields in the context of the LSMS-ISA data are measured at the plot level. Ideally, the panel data used would thus also be identified at the plot-crop level in order to hold differences in soil quality and other plot characteristics constant. However, plot boundaries and crop choice frequently vary across years and the LSMS-ISA data are thus household-level (and in the case of Malawi and Ethiopia parcel-level) panels but not necessarily plot-level panels (Carletto, Gourlay and Winters, 2015). As a result, it would likely be necessary to move to farm-level aggregate yields in order to reduce the idiosyncratic uncertainty associated with varying plot management decisions and growing conditions.

More fundamental than these concerns on data requirements is a conceptual issue with relying on past yield data. By definition, we only observe past yield _realizations_ which will differ from attainable harvest in the presence of crop losses. In Ethiopia and Malawi, however, harvest losses are very common affecting, for instance, between 55 percent and 65 percent of maize plots across years in Malawi and between 41 and 56 percent of maize plots in Ethiopia. As such, any past

> 32 As a reminder, Yr and hac are always observed in the LSMS-ISA data. They are the realized production and GPS measured area, respectively.

> 33 Data sources such as FAOSTAT’s yield database, for example, contain yearly data but cover the country-level which may be too coarse to accurately accommodate sub-national, sub sub-national, or even micro-level variation. 34 Projects such as the 50x2030 initiative are planning on collecting agricultural statistics in recurring patterns including a core of agricultural data at yearly frequency (50x2030 Initiative, 2020).

> 35 Between the first and third round of the Integrated Household Panel Survey (IHPS) in Malawi, for example, almost 40 percent of households moved to a different location.

23
the protective value of mangroves in the long run because mangrove protection may include additional benefits—such as lives saved, health outcomes, and human capital accumulation—that are not well captured by nightlight data. Second, while climate change and the resulting intensification of storms may increase the value of conservation for protection purposes, it is vital that that decisions around areas designated for conservation or restoration consider the threat of sea level rise. Consequently, identifying areas that should be prioritized for conservation and restoration and that have the potential to be mangrove habitats is an important avenue for future research.

20
# **Survey tools appendix**

Table A7: Summary of Enrollment Sample

|||Mode of Data Collection<br>||**Total**|
|---|---|---|---|---|
||Facebook|GlasswingCommunities|Tigo Clients||
|||Female Caregiver|||
||45|9|259|313|
|||Male Caregiver|||
||27|2|257|286|
|**Total**|72|11|516|599|

_Notes:_ This table presents the distribution of caregivers in the survey-mode experiment sample by recruitment mode and participant’s gender. Almost the full sample (86 percent) was recruited from the Tigo Clients dataset, 12 percent from Facebook, and only 2 percent from the NGO’s Communities program.

44
.g. national accounts, price indices, foreign trade, currency and credit, etc.).<br>Reliability of State-owned banks' accounts<br>Is the State economic policy (e.g. budgetary, fiscal, etc.)... communicated?<br>Is the State economic policy (e.g. budgetary, fiscal, etc.)... publicly debated?<br>Degree of transparency in public procurement<br>Freedom to leave the country (i.e. passports, exit visas, etc.)<br>Freedom of entry for foreigners (excluding citizens of countries under agreements on free movement, e.g. Schengen Area, etc.)<br>Freedom of movement for nationals around the world<br>Genuine media pluralism<br>Freedom of access, navigation and publishing on Internet<br>Military in politics<br>Democratic accountability<br>Press freedom index<br> Expanded freedom of expression<br>Freedom of association<br>Clean elections|
|**Non-re**<br>**AFR**<br>**BTI**<br>**CCR** <br>**EQI**<br>**FRH**<br>**GII**<br>**HRM**<br>**IFD**<br>**IRP**<br>**LBO** <br>**MSI**<br>**OBI**<br>**VAB**<br>**WCY** <br>**WJP**|**presentative Sources**<br>Trust parliament / national assembly<br>Satisfaction with democracy<br>Freeness and fairness of the last national election<br>Political participation (SI)<br>Stability of democratic institutions (SI)<br>Political
- Government should commit to the timely publication of comprehensive information of tax expenditures.

## **_Rule 3_**

- A statement of fiscal policy objectives and an assessment of fiscal sustainability should include both direct budget expenditure and tax expenditures. The complete budget document should include the normative tax structures with estimates of “imputed normative tax revenue.”

- Annual spending on tax expenditures should be prepared and presented within a comprehensive and consistent quantitative macroeconomic framework and the main assumptions underlying the budget should be provided.

- New tax expenditures being introduced in the annual budget should be clearly described.

- Tax expenditure information should be presented in a way that facilitates policy analysis and promotes accountability.

- Procedures for monitoring approved tax expenditures should be clearly specified.

- There should be regular fiscal reporting (annual or in a fixed time period) on tax expenditures (cost, effectiveness, and efficiency) to the legislature and the public.

## **_Rule 4_**

- Tax expenditure data should reflect recent flows and trends, underlying macroeconomic developments and well-defined policy commitments.

- Tax expenditure information should be subject to independent scrutiny and the data quality should be subject to verification.

- Tax expenditures should be audited for their performance, using economy and efficiency audit and programs audit to assess the performance of the government organization, program activity or function. This audit can provide information to improve the organization’s public accountability and facilitate decision making that initiates corrective action.  It can also be used to assess the performance of an entity, a program or an activity within that entity to determine whether the entity has complied with significant laws and regulations of tax expenditure programs.

# **V. Conclusion**

Tax incentives are tax expenditures. Tax expenditures are conceptually and functionally distinct from those tax provisions that have the purpose of raising revenue. They are government spending programs comparable to entitlement programs. Therefore, they must be analyzed in spending terms and must be integrated into the budgetary process to ensure fiscal accountability. Tax expenditures must be audited
Policy Research Working Paper 5846

# **Abstract**

Data from three rounds of nationally representative health surveys in India are used to assess the impact of selective mortality on children’s anthropometrics. The nutritional status of the child population was simulated under the counterfactual scenario that all children who died in the first three years of life were alive at the time of measurement. The simulations demonstrate that the difference in anthropometrics due to selective mortality would be large only if there were very large differences in anthropometrics between the children who died and those who survived. Differences of this size are not substantiated by the research on the degree of association between mortality and malnutrition. The study shows that although mortality risk is higher among malnourished children, selective mortality has only a minor impact on the measured nutritional status of children or on that status distinguished by gender.

This paper is a product of the Human Development and Public Services Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at mlokshin@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
the black-market exchange rate, and the extent of international capital market controls. Regulation of credit, labor and business measures credit market regulations, labor market regulations, and business regulations. The EF index is constructed if the data is available on at least three out of the four areas of economic freedom; otherwise we marked the data as missing.

The index of entitlement rights _(ER)_ is computed from the fifth area of the Fraser Institute’s Economic Freedom of the World. It is a rough proxy to measure the inclination of government to expand the scope of their activities in providing goods, services and entitlements. It includes the general government consumption spending as a percentage of total consumption, transfers and subsidies as a percentage of GDP, government enterprises and investment, and top marginal tax rate. Because this measure is both broad and limited, it necessarily hides a lot of heterogeneity, especially regarding the quality of public expenditures and other forms of government intervention. In particular, among small governments, the index cannot distinguish between failed states and more effective states. Among larger governments, the index cannot differentiate efficient welfare states from ineffective and wasteful rent-seeking states. Yet, the index aims at capturing the overall characteristic that governments with large public spending, transfers and subsidies, numerous government enterprises, and high marginal tax rates are generally prone to provide various forms of entitlements (e.g., entitlement to healthcare, education, pension; entitlement to free or highly subsidized food, water, energy, and other goods and services; entitlement to public housing, rent controls, or publicly-guaranteed mortgage; entitlement to public employment, minimum wage; entitlement to be protected from foreign and domestic competition through bans, quotas, and other various limits to entry). The value of the index has been reversed so that the higher levels represent larger governments and by extension more extensive provisions of ERs.

The index of civil and political rights _(CPR)_ is computed as the simple average of Freedom House’s Civil Rights
non-performing?|28<br>(14)|39<br>(31)|23<br>(8)|
|If a customer has multiple loans and advances and one of them is classified as non-<br>performing,are all the other exposures classified as non-performingas well?|53<br>(50)|48<br>(35)|54<br>(55)|
|**C. Some Additional Information**|**Median**|**Median**|**Median**|
|What is the maximum time (in months) that a loan or advance can be non-performing<br>before it has to be written off?|12|18|12|
|Up to what level (if any) is specific provisions tax deductible?|0|0|1|
|Up to what level (if any) is general provisions tax deductible?|0|0|0|

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 (Table 1 provides the complete list of countries).

40
**

For both corn and soybean, we downloaded annual data on yield in bushels per acre at a county level from the USDA’s National Agricultural Statistics Service (NASS) database. We also collected total bushels produced for each crop in each county and year in the sample.

# **4.2 Empirical approach**

## **4.2.1 Estimation of smoke’s present day marginal impact**

In order to identify the marginal impact of smoke plumes on yields, we rely on the assumption that the incidence of smoke days across counties in a given year is plausibly random conditional on county and year fixed effects. In other words, we assume the amount of a given county’s exposure to smoke after removing the portion of a county’s exposure in a given year that would be considered average for that county and the portion that is experienced by all other counties in the same year, or the portion that is due to a universal increase in smoke, is quasi-random. Some counties may be consistently more exposed to smoke than others; we show that counties in the upper Midwest generally experience more smoke days in a given year than the rest of our sample (Figure 1), but we expect differences in year-to-year exposure within a county is quasirandom. These differences are driven by weather conditions in the location of fires, generally the

> 1The original data is available here: `http://www.columbia.edu/~ws2162/links.html`

> 2Data available here: `https://cds.climate.copernicus.eu/cdsapp#!/dataset/ reanalysis-era5-single-levels?tab=overview`

17
International Economics, 2004. - Vol. 12.

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