rafmacalaba/data-use-mentions-extended huggingface dataset:
The latter is computed as a sum of population 15-64 years old and above 65 years old multiplied by the employment-population ratio of 15+ years old. The comparison indicates that some countries have more than a 10 percent deviation in employment data during one or more years over the period of 2000-2016.<sup>16</sup> Countries with more that 10 percent deviations are excluded from the analysis. Country and sectorspecific annual GDP-employment elasticities for average elasticities approach are constructed by dividing annual employment growth by GDP growth. Similarly, changes in labor productivity are divided by GDP growth to discount the share of economic growth explained by improvements in labor productivity, following the decomposition approach. Finally, average of annual elasticities over the period 2000-2016 are used as estimates of country and sector GDP-employment elasticities.

To study the relationship between labor productivity and informal employment, sector-specific informal employment shares (in agriculture, manufacturing and services) were computed using harmonized labor force surveys using the World Bank’s International Income Distribution Data Set (I2D2).<sup>17</sup> Informal employment is defined for the purposes of this paper as those individuals that declare to be self-employed or are non-paid employees.<sup>18</sup> Several stylized facts emerge when comparing informal employment across countries, country income groups and sectors; such as prevalence of informality in low-income countries and in the agriculture sector. Figure 1 shows that lower-income countries tend to have higher informal employment than highincome ones; and this pattern is consistent across all aggregate sectors. Low-income countries have sizable employment informality and thus under-utilized labor due to the limited number of formal jobs available in the economy relative to the size of the working-age population. In most cases, informal jobs do not provide sufficient income, benefits, or certainty for workers who are either poor or vulnerable to poverty in the face of economic shocks. In addition, the share of informal employment is the highest in agriculture, reaching on average 70 to 80 percent in low-income and lower-middle-income countries. In low-income countries most
program, and those living in villages without the program (not shown). This suggests little evidence of program impact on child nutrition outcomes.

To investigate this more rigorously, we modeled the impact of the ICDS program on child nutritional status, comparing anthropometric outcomes for the children in the beneficiary villages with those of children from a comparison group of villages. We use the Propensity Score Method, which removes the selection bias due to differences between villages with and without projects (Rubin 1973), to the extent that selection of a village into the program is based purely on observable characteristics. Each child in the villages with the ICDS program (the treatment group in evaluation literature terminology) is paired with one in the villages without the program (the control group), with similar observed characteristics of the child (age, birth order and gender); of the mother (age, education, caste, religion); household wealth; and of the village (population, and development indicators<sup>25</sup> ). We then test for significant differences in nutritional

> 25 The village development indicators include electrification, drainage, road connection, primary health centre, women’s association, controlled-price shops, and development programs such as the IRDP, EGS and NREP for income-generation.

12
%|26.0%|32.2%||
|_National Moderate PL_|**Poverty Gap**|24.3%|19.1%|11.5%|14.4%||
||**Squared Poverty Gap**|19.9%|14.5%|6.9%|8.6%||

Source: authors’ estimations based on surveys PNAD-C, POF, and PNS, and admin data from the Ministry of Finance, Ministry of Health, and Government Open Data Portal.

Appendix Table A.2 shows results on the size, the concentration coefficient, the Kakwani coefficient, and the marginal contributions to inequality and poverty. Concerning market income from the PGT analysis, the contributions of contributory pensions are pro-poor (see the negative concentration coefficient in the third column). Their marginal contribution to inequality reduction is almost 3 Gini points. In comparison, its marginal contribution to poverty reduction in terms of the national line is nearly 7 points. In this case, some people have meager incomes close to zero and depend exclusively on contributory pensions. In the case of social security contributions, they are generally neutral, although the sum of all contributions has a slightly progressive effect. In this case, the original income distribution starts from a Gini of 0.61. The 46
How might one measure the effect of child labor on schooling? A common method is to compare the educational attainments of children who work with those who do not. From such comparisons, Psacharopoulos (1997) concludes that child labor leads to two years less schooling on average (using data for Bolivia and Venezuela). This suggests that child labor entails a large cost to childrens' future welfare. However, the possibility of selection bias through the choices made by parents clouds such comparisons. The parents of children who currently work may well send their kids to school less than do other parents even when work is not an option.

Tf one could do an experiment that created an exogenous increase in schooling, then one could simply see how much child labor fell as a consequence. An exogenous decrease in the price of schooling would qualify for such an experiment. An important element in the price of schooling is the wage rate for child labor. However, this is also the price of leisure (assuming that parents are free to allocate their children's time; we return to that assumption later). Thus disentangling the own price effect from the cross-price effect is problematic using wage data.<sup>6</sup> One might look for other indicators of school price. The presence of a school in the village of residence is one possibility (Rozenzweig, 1982). Another is the distance or travel time to the nearest school (Grootaert, 1998) or average out-of-pocket expenditures on schooling in the area of residence (Cartwright, 1998). On _a priori_ grounds it is unclear just how well such variables measure the price of schooling, and the usual concerns arise about attenuation bias due to the use of weak proxies. The endogeneity of both access and average school expenditures also raises concerns, since these measures may well pick up spurious geographic effects. The existing evidence for effects of school price on child labor is mixed, although it is recognized in the 6 To add to the difficulty, wages for child labor
of GEL 1,000 per 5.3 lives saved. The calculated return on investment (ROI) of the four policies would be GEL 357 for every GEL invested (UNDP et al. 2018).

Taxes on cigarettes were found to be most cost-effective, among the four interventions studied. Increasing taxes on tobacco to comply with FCTC Art. 6 could advert over GEL 2.2 billion in health care expenses and economic losses over a 15-year period, with a return of GEL 221 for every GEL invested. Expressed differently, taxation could save 13 lives at a cost of GEL 1000. See <u>Annex 2</u> for methodological details.

Another study by the NCDCPH et al. (2016) uses macroeconomic and customs data and a top-down approach to model the effect on tobacco consumption and revenue collection, of meeting two policy targets of (a) Implementing EU tax regulation (assuming excise duty per cigarette pack at 4.54 GEL minimum), and (b) Reducing smoking prevalence by 2 percent annually (assuming a 2 percent annual drop in volume consumed). Four policy scenarios are considered, based on different time-frames to meet the policy targets. Changes in consumption and revenue collection are estimated based on assumed elasticity parameters (price-elasticity of -.05 and income elasticity of .59) and macroeconomic projections. Results suggest that the scenario with the largest (quickest) annual shocks on excise duties could reduce cigarette consumption by an average of -5.25 percent annually between 2015 and 2020. This scenario would also result in additional tax revenues from excise duties and VAT on cigarettes of GEL 1.4 billion between 2015 and 2020. The study argues that large immediate tax shocks (like those under Scenario I) seem most adequate to reduce tobacco consumption in Georgia. Annex 3 includes further methodological details.

Price elasticities of demand for tobacco products Taxes and price policies on tobacco improve health and economic outcomes by inducing consumers to reduce smoking. They require that consumer behavior respond to price changes.
<!-- Start of picture text --> 1990 1995 2000 2005 2010 2015<br>Year<br>Number of refugees − all categories<br>1995 lower−bound flow 1995 lower−bound stock<br>2015 lower−bound flow 2015 lower−bound stock<br>500<br>400<br>300<br>200<br>Number of refugees (’000)100<br>0<br><!-- End of picture text --> Figure 3: Lower-bound envelope - the case of Somali refugees in Kenya (1990-2015)

# **4 Results**

**How long have refugees been in exile?** Figure 4 shows the distribution of the “global refugee flow” (aggregating all situations) by duration as of 2015. It provides a nuanced picture of the current refugee crisis.

<!-- Start of picture text --> 0 20 40 60<br>Duration of refugee status − reference year 2015<br>3<br>2<br>1<br>Number of refugees (million)<br>0<br><!-- End of picture text --> Figure 4: Distribution of refugees by exile duration (as of 2015) There is a large cohort of about 8.9 million “recent refugees”, who arrived over the last four years. This includes about 4.8 million Syrians, as well as people fleeing from South Sudan (.7 million), Afghanistan (.3 million), Ukraine (.3 million), the Central African Republic (.3 million), and Pakistan (.2 million).

11
035)|(0.000)|(0.000)|(0.723)|(0.000)|(0.202)|
|MODEL**DR**CT|-0.022|1.078***|-0.086|0.083|1.413***|-0.079|
||(0.931)|(0.010)|(0.841)|(0.775)|(0.000)|(0.804)|
|MODEL**DR**LT|-0.325|-1.144*|-0.242|0.119|-1.196***|0.012|
||(0.468)|(0.065)|(0.691)|(0.842)|(0.004)|(0.984)|
|Obs|4096|4096|4096|4096|4096|4096|
|P-R2|0.983|0.964|0.959|0.961|0.931|0.968|
|Control GRAV|Yes|Yes|Yes|Yes|Yes|Yes|
|Control C|Yes|Yes|Yes|Yes|Yes|Yes|
|FE exp+ imp|Yes|Yes|Yes|Yes|Yes|Yes|

Note: * p<0.10; ** p<0.05; *** p<0.01. The dependent variable is bilateral digital services exports (DSX) using the underlying gross trade data from the TiVA database. Sector groupings in each column can be found in Annex Table A2. Robust standard errors are clustered at the country-pair level. Fixed effects for exporter and importer 28
# Transport Project Indicators

SEI indicators were selected to consider beneficiaries, job creation, extension of service to areas with higher poverty levels, and savings associated with reduced gas consumption.<sup>16</sup> Each of these input indicators is controlled for project size, yielding the following criteria inputs: beneficiaries per dollar invested (Ben_inv), jobs per dollar invested (Jobs_inv), and gas savings per dollar invested (Savings_inv). Beneficiaries is calculated by estimating traffic volumes, considering the occupancy rates for different types of vehicles. This information is taken directly from project proposal data included in the BIP. Data on the creation of jobs directly associated with construction and operation are also calculated based on BIP data, which were in turn derived from an estimation model based on the macroeconomic input-output matrix. Gas savings is an estimate of the annual savings in gas, measured in liters. The initial set of indicators also considered the extension of service to indigenous populations, but this criterion was later dropped due to limited variation.

Lastly, the SEI includes the poverty rate and tests the use of two alternative specifications to measure poverty. One takes a simple poverty rate (Pov_c) reflecting the percentage of people in the service area classified as “income poor”. It is important to note that it is not necessary that the users of the road are the same as the population that lives nearby the road that is under appraisal. It is possible that the locals could have a low vehicle per capita ratio, and the usage of the road is composed by transportation trucks, tourists, drive through or long-haul trips, etc. The other applies a multi-dimensional composite poverty index (MPI-CL) developed by MDS (Pov_multi) that accounts for five poverty dimensions: education, health, employment and social security, housing, and networks and social cohesion.

The FEI takes into account only one measure – the net present value index (IVAN) – derived from project CBAs. The IVAN is equivalent to a ratio of the net present value
stemming from differences in survey instruments. Furthermore, scholars have questioned the representativeness of the survey compared to NSS surveys, due to differences in sample design and geographical coverage (for instance Somanchi and Dreze 2021 and Somanchi, 2021). Both of these differences will have important impacts on poverty estimates for India (e.g., Deaton, 2003).

The objective of this paper is two-fold. First, we conduct a comprehensive examination of potential biases in the CPHS survey and propose adjustments to the survey weights that transform the CPHS into a nationally representative dataset. The outcome of this work will hopefully serve as a public good for anyone looking to use the CPHS for their empirical research. Second, we use the reweighted CPHS to construct NSS-compatible measures of poverty and inequality for the years 2015 to 2019. The challenge in this second objective is similar to that of Tarozzi (2007) which seeks to establish comparability in welfare aggregates across rounds of NSS’ consumption ex3
# **1 Introduction**

Up-to-date estimates of population density in small areas is a valuable input for policymakers (Stevens et al., 2015; Wardrop et al., 2018). They could, for example, facilitate efficient delivery of public goods and services and infrastructure projects (Guiteras et al., 2018); track net migration patterns, especially in response to civilian conflict, political upheavals, and climate tragedies; and help better understand the impact of geographically-targeted economic policy interventions such as Special Economic Zones. Traditional population data sources do not meet these requirements, as censuses provide local population measurements infrequently, typically decennially. Although household surveys can yield more frequent population estimates, they are not representative at small administrative levels. The challenge of tracking population is particularly exacerbated in low- and lower-middle- income countries where population growth rates are high and net migration patterns are rapid (Figure 1).

Satellite imagery, in combination with survey data, has the potential to fill this gap by generating more frequent estimates of population that are representative in small areas. Satellites offer several advantages as data collection instruments. They systematically and universally capture large geographic areas, produce imagery at reasonably regular intervals, and are unaffected by topography, political climate, or conflict. The technology and market for both collecting and processing satellite-based imagery are developing rapidly, and with ever more satellites being launched, high-spatial resolution imagery is increasingly available at reasonable cost.

Although existing publicly available population products incorporate satellite data, this does not imply that they are up to date. Existing products typically rely on dasymetric mapping approaches to distribute population from the census to lower administrative units, either using equal weights, or weights based on satellite indicators and advanced statistical techniques. These “top-down” methods may not provide accurate or up-to-date population estimates for two reasons. First, the accuracy of distributing population relies heavily on the input population data, that is, on the census (Wardrop et al., 2018). However, the census itself may quickly become outdated
et al., 2018; Decarolis, 2014).

44. We further use delays and cost overruns in contract execution as proxy indicators of economy. Delays are captured by time overruns, that is by how many days the contract was extended beyond the original deadline. Such delays are typically associated with economic costs—for example, because citizens cannot use new infrastructure. They also often signal quality problems requiring corrections. Cost overruns are defined as the ratio of the final amount paid to a firm and the original contract price. Given that both measures capture performance during the contract implementation stage, which was not digitized by the e- procurement system during the period of study, they are indicative of potential displacement effects.

45. Administrative efficiency can be measured by monetizing and summing the government’s total costs of administering tenders and monitoring the implementation of contracts. These costs primarily include staff time, but also advertising costs, costs for printing and mailing tender documents and costs incurred by misprocurement due to administrative errors. The survey of procurement officials served to gather proxy measures of these costs which are not easily observable. The only efficiency-variable available at the tender-level is the time spent on the procurement process. We consider both the overall time required 15
|7.01%|26.80%|19.59%|17.78%|0.35%|6.72%|0.00%|0.04%|0.10%|
|MNA|68.94%|55.95%|6.48%|6.51%|29.18%|22.24%|20.75%|5.68%|0.38%|0.64%|0.07%|0.16%|
|SAS|50.38%|28.50%|10.14%|11.74%|48.32%|45.02%|39.60%|2.26%|0.66%|0.01%|0.18%|0.19%|
|SSA<br>|62.25%<br>|44.15%<br>|11.13%<br>|6.96%<br>|35.88%<br>|26.52%|24.44%|0.96%|1.68%|0.17%|0.07%|6.49%|
|*Capitalgood|s imports|exclude tr|ansportat|ion equipme|nt.||||||||

1HIEuro is comprised of the following high income European nations: Belgium, Cyprus, Denmark, Finland, France, Germany, Greece, Source: Authors' calculations based on WITS, UN COMTRADE database.

25 Yepes (2008) presents an estimate of about US$1.1 billion dollar in 2005 constant US dollars. These estimates are based on the methodology presented in Fay and Yepes (2003), which uses predicted GDP growth to estimate the demand for infrastructure services. This may be considered a lower bound. On the one hand, Yepes (2008
are accompanied by call-in radio shows and public forums designed to create engagement between taxpayers and governments. Recent research presents evidence that well-designed taxpayer education programs can significantly increase tax knowledge, while also having positive effects on compliance – effects that appear largely attributable to facilitating compliance but may also reflect improved willingness to pay.<sup>140</sup> An alternative approach is targeted communication about tax-expenditure links. As noted above, an experiment in Rwanda found that letters to taxpayers stressing the connections between taxes and services were generally at least as effective as enforcement threats in increasing compliance.<sup>141</sup> Still, communication-based interventions may have a limited ceiling, or diminishing returns. Telling taxpayers about the link between tax payments and public services is unlikely to be a

> 138 Prichard, W. (2015). _Taxation, responsiveness and accountability in developing countries: The dynamics of tax bargaining_ . Cambridge: Cambridge University Press.

> 139 OECD. (2015). _Building Tax Culture, Compliance and Citizenship: A Global Source Book on Taxpayer Education_ . Paris: Organisation for Economic Cooperation and Development; Prichard, W., Beach, R., Mohiuddin, F., & van den Boogaard, V. (forthcoming). The micro-links between taxation and accountability initiatives. _ICTD Working Paper_ . Brighton: International Centre for Tax and Development.

> 140 Mascagni, G; Santoro, F. & Mukama, D. (2019). Teach to comply? Evidence from a taxpayer education programme in Rwanda. _ICTD Working Paper 91_ . Brighton: International Centre for Tax and Development; Similarly, a World Bank project that combined tax infrastructure improvements with a comprehensive education program resulted in significant increases in tax revenue. World Bank, (2017). Modernization, Taxpayer Education Provide Good Foundation for Tax Collection in Tanzania. Washington, DC: World Bank Group. http://www.worldbank.org/en/results/2017/01/05/modernization-taxpayer-education-provide-goodfoundation-for-tax-collection-in-tanzania

> 141 Mascagni, G.,
</sup> Misinformation spillovers generate correlated NCME, which considerably complicates econometric correction for measurement error, because incomplete correction of measurement error in the presence of correlated NCME can aggravate rather than reduce bias in key parameter estimates (Abay et al., 2019).

We embedded an information experiment within an agricultural household survey in Malawi, providing an uncommon opportunity to study the nature of NCME and learning in response to corrective information to subjects' erroneous self-reports regarding cultivated land areas. Part of the appeal of this design is that most economics studies on inattention, learning, or

> 2 For example, if providing farmers with GPS measures of their plots' size affects self-reported input use, introducing GPS-based plot area measurement in follow-up longitudinal data collection (as part of national panel surveys or impact evaluation studies) may compromise the inter-temporal comparability of self-reported, non-land variables.

3
Figure 15

# **Microeconomic Underpinnings**

The emphasis of this paper is on the macroeconomic aspects of transition. A running theme is that policies and institutions tend to be mostly right or mostly wrong. The same applies to the microeconomic aspects. Table 6 shows the correlation between a number of microeconomic transition indicators prepared by EBRD (averages of indicators concerning: enterprise restructuring, financial institutions development, infrastructure, legal and market reforms), two measures of macroeconomic policies (budget surpluses and inflation over the whole period 1991-98 or the last three years 1996-98), and two measures of economic performance (GDP growth over the whole period 1991-98 and 1998 GDP as a percent of 1989 GDP).

The table suggests a number of observations. Microeconomic transformation indicators are positively correlated among themselves, especially those concerning enterprise restructuring, financial institution development and market reforms. These three indicators are also correlated with the macroeconomic performance indicators and the growth performance, especially the budget surplus, with a further strong link between inflation over the whole period and market reforns. The table also confirms that inflation stabilization is a pre-condition for growth.

# Table 6

Which factors, microeconomic or macroeconomic, are more crucial for a successful transition? The collinearity of the EBRD indicators implies that it is nearly impossible to answer the question. Using the two growth indicators as a measure of success, Table 7 reports cross-country regressions. Both the small number of observations (the same 15 countries studied throughout the paper) and the high degree of collinearity imposes using very few regressors.

25
Thus, we constructed simple curves based on information about past floods on the Carretera Central, the only highway for which data were available (Figure 2). We validated those curves with expert consultations.

> 3 The GCMs used are GFDL ‐ ESM2M, HadGEM2 ‐ ES, IPSLCM5A ‐ LR, MIROC ‐ ESM ‐ CHEM, and NorESM1 ‐ M. For this study, we used climate projections based on one representative concentration pathway (RCP), RCP8.5. 4 2013 Dartmouth flood observatory flood extend v2 data set.

> 5 http://www.ingemmet.gob.pe/.

7