rafmacalaba/data-use-mentions-extended huggingface dataset:
basic needs, defined by the national poverty line.<sup>2</sup> A new IE-LFS was started in April 2021 (IE-LFS 202122). However, due to the rapidly deteriorating security situation, fieldwork was suspended in June 2021. Data collected between April and June 2021 cover a total of 4,871 households. Information from the ILLFS 2021 provides an additional baseline and benchmark model performance.

The regime change brought a halt to data collection in the country. To understand the evolution of welfare, the World Bank implemented three rounds of the Afghanistan Welfare Monitoring Survey (AWMS), a phone survey covering a wide range of indicators, including employment and labor earnings, food security and access to safety nets, school attendance, and health services. The phone surveys are administered on the subsample of the original IE-LFS 2019/20 and IE-LFS 2021 participants for which phone numbers were available.

As expected from a phone survey, the sample of phone owners includes some expected biases, given that (i) not all of the households from IELFS provided telephone numbers, and those who do are, on average, better off; and (ii) not all of the available numbers could be reached.<sup>3</sup> Sampling differences in the AWMS are adjusted by reweighting to match the original full IE-LFS 2019/20 distributions. These adjustments reduced the biases, although the final sample is still slightly more educated. Additionally, as found in previous AWMS rounds, household size is relatively larger, possibly reflecting internal migration dynamics and/or household consolidation. Overall, the differences in welfare and education levels are not large enough to introduce crippling biases to the results, and every category considered has substantial representation (Figure 1). The next section further discusses the comparability of the IE-LFS 2019/20 and AWMS R3 samples.

> 2 In line with best international practices, the poverty line for Afghanistan is estimated following the Cost of Basic Needs (CBN) methodology. There are no PPP conversion factors
contract with the government that the manager reports that is expected in bribes to obtain the contract, Individual or family ownership of the fi rm is a dummy variable that equals one if the largest shareholder of the fi rm is either an individual or a family, Internal ownership of the fi rm is a dummy variable that equals one if the largest shareholder of the fi rm is either the management or the employees, Government ownership is a dummy variable that equals one if the largest shareholder of the fi rm is the government or a government owned fi rm, Corporate ownership is a dummy variable that equals one if the largest shareholder of the fi rm is either a domestic or a foreign fi rm, Bank ownership is a dummy variable that equals one if the largest shareholder of the fi rm is a bank or an investment fund, Other ownership includes other types of fi rm ownership.

Data on the enforcement of labor regulation in 2002 comes from the Ministry of Labor. The federal system of labor inspections, which is part of the Ministry of Labor, has the objective of enforcing all the laws and regulations, including international conventions, related with labor and employment relations and contracts (Law 55.841/65). The inspectors of the federal system of labor inspections verify the enforcement of laws and regulations, including those related with heath and security at work. In particular, they try to avoid labor informality verifying that workers are formally registered with the labor authorities, i.e., that they have a work permit (or carteira de trabalho). The Ministry of Labor is a decentralized structure with a regional branch in each of the 27 Brazilian states (“Delegacia Regional do Trabalho” or DRT). Within each of these branches, there are several administrative units, or subdelegacias. The concept of subdelegacia is administrative and does not correspond to any geographical unit.<sup>47</sup> In particular, a “subdelegacia” includes more than one city (or municipio). In each subdelegacia
# 7. Psacharopoulos & Arriagada 1986

Psacharopoulos, George & Ana-Maria Arriagada. "The educational attainment of the labor force: an international comparison." The World Bank, October 1986. Report No.: EDT38. Appendix B, Table B-i: The Structure of Educational System.

8. EDI, EDV, EDS, and EDZ First, we obtained education distribution data for 1970, 1975, 1980, 1985, and 1990 from Barro & Lee data file "School4.raw," then make the categories of education distribution mutually exclusive. Second, we obtained the school cycling data from Psacharopoulos & Arriagada data Table B-I. Then we calculated the following: EDI: mean years of education for the population age over 15 EDV: variance of education for the population age over 15 EDS: standard deviation of education for the population age over 15 EDZ: coefficient of variability of education for the population age over 15 GINI: GINI index of education for the population age over 15. The formula to calculate the GINI is: Y=NE Eli | _x;j_ |. Where y is the GINI index, ,u is the mean of the variable, and

N is the total number of observations.

THL: Theil index of education for the population age over 15. The formula to calculate the theil index is: = XI E _in_ **_xL_** i Where X is the theil index, p is the mean of the variable, and N is the total number of observations.

SDL: Standard Deviation of Logs of education for the population age over 15. Finally, we estimated the values in between through linear interpolation.

30
interviewers can rerform to assess the respondent's level of disability (es asking the respondent to say how many fingers the interviewer is raising while the interviewer stands at certain - distances away to test sight). No proxy responding can therefore be allowed. There is a need to develop simple methodologies and interviewer instructions for measuring disability which a WHS might apply. The strong points of a number of different previous disability surveys need to be identified and used. A WHS core questionnaire might contain a question on 1 year recall of chronic illness for adult members of the household.

In terms of specific behaviour rather than specific illness some countries may be interested in sets of questions on smoking or the use of alcohol (see ndO et al 1986 for an array of questions on these topics).

The WHS could be a useful vehicle for assessing the coverage of programmes which are either targeted at all individuals within the population or all individuals within a defined age group or sex (Ross in WHO et al 1986). The methodologies for each tvpe of programme will be different and an array of optional modules could be developed. The coverage of vaccination, oral rehydration therapy and malaria chemoprophylaxis are three obvious subjects of interest.

The determination of vaccination status is difficult excepting the use of scars to identify those who have received a BCG vaccination, and only vaccination cards or clinic records can provide reliable information.

Questions on treatment received for diarrhoeal episodes and source of treatment (eg. home, pharmacy, health facility) should directly follow questions on morbidity, severity and duration. The recall period should therefore be the same i.e. 14 days (this is accepted as the norm by the WHO Diarrhoeal Diseases Control Programme, see WHO 1981).

The recall period for questions on consumption of antimalarials should not exceed four weeks for weekly or biweekly drugs, and should be much shorter, probably two days, for daily preparations. Possession of 30
||PPR<br>Title|Working Paper Series<br>Author|Date|Cuntact|
|---|---|---|---|---|
|WPS73|Taxation and Output Growth in Africa|Jonathan SkInner|August 1988|A. Bhalla<br>60359|
|WPS74|Fiscal Stabilization<br>and Exchange Rate<br>Instability: A Theoretical<br>Approach<br>and Some Policy Conclusions<br>Using<br>Mexican Data|Andrew Feltenstein<br>Stephen Morris|August 1988|A. Bhalia<br>60359|
|WPS75|Welfare Dominance and the Design of<br>Excise Taxation In the Cote d'lvoire|Shlomo Yitzhaki<br>Wayne Thirsk|August 1988|A. Bhalla<br>60359|
|WPS76|On the Shadow Price of a Tax<br>Inspector|Shlomo Yitzhaki<br>Yitzhak Vakneen|||
|WPS77|<br>Incentive<br>Policies and Agricultural<br>Performance in Sub-Saharan<br>Africa|Bela Balassa|August 1988|N. Campbell<br>33769|
|WPS78|Economists, Institutions<br>and Trade<br>Restrictions: A Review Article|J. Michael Finger|September 1988|<br>N. Artis<br>33731|
|WPS79|Quantitative<br>Appraisal of<br>Adjustment Lending|Bela Balassa|August 1988|N. Campbell<br>33769|
|WPS80|Emerging Issues of Privatization<br>and the Public Sector|Samuel Paul|September 1988|<br>E. Madrona<br>61711|
|WPS81|Reaching People at the Periphery:<br>Can the World Bank's Population,<br>Health, and Nutrition Operations<br>Do 1Better?|Richard Heaver|September 1988|<br>S. Ainsworth<br>31091|
|WPS82|Microeconomic Theory of
# Table 4: Heterogeneity of treatment impact by ease of mechanization index

||All of India|
|---|---|
|(A)Quartile 1 of Ease of Mechanization Index||
|Post-MNREGA|-0.013<br>(0.087)|
|Districts|140|
|Months|144|
|N|20,160|
|Avg. monthly fres pre-MNREGA|2.82|
|(B)Quartile 2 of Ease of Mechanization Index||
|Post-MNREGA|-0.008<br>(0.075)|
|Districts|143|
|Months|144|
|N|20,592|
|Avg. monthly fres pre-MNREGA|2.7|
|(C)Quartile 3 of Ease of Mechanization Index||
|Post-MNREGA|0.144<br>(0.112)|
|Districts|135|
|Months|144|
|N|19,440|
|Avg. monthly fres pre-MNREGA|3.06|
|(D)Quartile 4 of Ease of Mechanization Index||
|Post-MNREGA|0.265<sup>_∗∗∗_</sup><br>(0.084)|
|Districts|140|
|Months|144|
|N|20,160|
|Avg. monthly fres pre-MNREGA|13.28|
|District FE|X|
|Month _×_ Year FE|X|
|Weather Controls|X|

Notes: Coefficients can be interpreted as the approximate percentage change in fires after MNREGA was statutorily implemented in a district. The sample is all districts in India. The specification is a fixed effects Poisson where the outcome is monthly cropland fires in district _i_ in month _m_ in year _y_ . The ease of mechanization index is the sum of a district’s Z score across measures of land concentration, combine presence and crop types. The mechanization index is calculated based on levels of each component variable in the district
.05</mark> <!-- Start of picture text --> 0 .2 .4 .6 .8 1<br>Pvalue<br>2.5<br>2<br>1.5<br>Density<br>1<br>.5<br>0<br><!-- End of picture text --> Note: This figure shows the distribution of the p-value of the variable “born earlier” in the reduce-form regressions of maternal employment on “born earlier” (1, 2, or 3 months earlier). Source: Estimation from VHLSS 2010, 2012, 2014 and 2016.

32
||(17.95)***|(23.74)***|(19.75)***|(26.13)***|
|---|---|---|---|---|
||[22.78]***|[54.14]***|[23.99]***|[57.27]***|
||{43.75}***|{79.43}***|{44.32}***|{85.89}***|
|No. of Children||-161.1||-178.0|
|||(7.164)***||(7.963)***|
|||[19.38]***||[19.83]***|
|||{22.93}***||{24.72}***|
|No. Observations|27810|27810|24443|24443|

Notes: (1) The data used are IHDS 2005 and NSS 1995 respectively. (2) Robust standard errors in parentheses; standard errors clustered at district-level in square brackets; standard errors clustered at state-level in braces; *** p<0.01, ** p<0.05, * p<0.1.
Aggregating this up across MNEs in a given sector _s_ and, as is standard in the literature, normalizing by sectoral employment, we see that total horizontal spillovers in period _t_ depend on the number of firms of each type: The literature to date implicitly assumes that _δ_ = 1, so that all spillovers are transitory and depend solely on FDI that is currently present. Put differently, this assumption implies a symmetry between increases and decreases in FDI so that, when measured in changes over time, only net inflows of FDI matter. Nevertheless, for spillover mechanisms that are persistent, this need not be true.

Following the literature, in period _t_ for sector _s_ , we construct our backward and forward spillovers using the horizontal spillover: where _γk,s_<sup>_O_istheshareofoutputfromsector</sup><sup>_s_soldtosector</sup><sup>_k_,</sup><sup>_γ_</sup> _k,s_<sup>_I_istheshareofinputs</sup> sector _s_ sources from sector _k_ . Let the (logged) unit labour requirement be: where _age_ , _size_ , and _fgn_ denote the age, size, and foreign ownership of _i_ in _t_ . Given that older and foreign-owned firms are typically found to be more productive, we presume that _ψ_ 1 _, ψ_ 2 _<_ 0, i.e. they lower the unit labour requirement, with a similar result for productivityenhancing FDI spillovers. First differenncing (5), for firm _i_ in sector _s_ in year _t_ , labour growth is: where the “dots” indicate changes. Equation (9) then provides the basis for our empirical specification. Note that for the spillover variables, even if there is no net change in FDI levels, that there can still be a change in the spillover. For example, suppose that there is entry and exit in a sector _s_ yet total foreign employment does not change. For spillover of type _j_ , this would result in: 7
markets, they typically make their purchase via mutual funds. In actively managed funds, it is the fund manager who ultimately determines the portfolio allocation, **by** choosing how the fund invests its assets (within the limits of the fund's defined scope). In index funds, the manager's role is passive, aimed at replicating a predetermined index.

Mutual funds have become one of the main instruments for investing in emerging markets. The first funds, in the 1980s, were closed-end funds; they are well suited to invest in illiquid markets, because their shares cannot be redeemed. With increasing liquidity in emerging markets, open-end funds have become the most widely used instrument. It is important to recognize that mutual fund investors include other types of institutions as well. For example, more than half of pension funds invest in emerging markets through existing mutual funds. This is considered better for liquidity reasons and is also less expensive than giving specific mandates to mangers. Therefore, **by** looking at mutual funds, one is counting much of pension fund investment in emerging markets as well. **A** survey published at World Bank **(1997)** estimates that pension funds hold around **_1.5_** to 2 percent of their portfolios **_($50_** billion-$70 billion) in assets from emerging markets.

Hedge funds are a newer type of institutional investor. They are still small relative to the other institutional investor types. It is estimated that hedge funds held total assets of around **$81** billion **by** year-end **1997,** only a small fraction of which is invested in emerging markets.'<sup>0</sup> Like other institutional investors, insurance companies are also believed to invest only a small proportion of their assets in emerging markets. However,

> to See Eichengreen and Mathieson **(1998)** for a detailed study
effective and transparent law enforcement is in place (Van Rijckeghem and Weder, 1997). Authors such as Lacko (1996) argue that countries that have adopted common law systems (i.e., Great Britain and former colonies) with the ultimate goal to protect propriety owners against harmful interventions by the sovereign are much more effective in this sense in preventing corruption practices than civil law systems. The latter were adopted by most continental European countries and their former colonies. They were originally developed by monarchs to be used for state building with great focus on respect of hierarchy and the authority of offices (Lacko, 1996). Failure of the internal control and monitoring system to detect and punish the self-motivated agent at an early stage provides an additional incentive for the latter to select the second or third best candidate. This situation will undermine the performance of the employees and the overall productivity of the economy causing a large segment of the active population to be pushed outside the labor market. In contrast, the presence of internal political checks and balances contributes to maintain the pressure for more transparency and accountability of government officials. In democratic societies, the opposition plays the central role in detecting any fraudulent maneuvers by officials representing the government in place. In contrast, where opposition is completely marginalized as in totalitarian regimes across the Arab world for instance, with no authority to question the practices of government officials, bribes are used to gain those officials’ sympathy before they make their decisions to grant public goods (Van Rijckeghem and Weder, 1997). We use as a proxy of the domestic political pluralism and participation, the percentage of **(the opposition vote share)** in the parliament as compiled by the World Bank Database of Political Institutions (Keefer, 2009). A higher index indicates a more dynamic political environment in which opposition parties hold an important share of the legislative branch and thus have more impact on denouncing fraudulent practices of government officials and questioning the causes of the growing number of unemployed youth.

The level of
the child is indeed not deprived of any dimension or is in fact deprived in the dimension where the information is missing.

# 5.2 Chronic Poverty and intergenerational poverty regression analysis

## 5.2.1 Chronic Poverty

The chronic poverty analysis in Figure 40 a and b presents large differences across regions, as well as an urban rural divide, with higher levels of chronic and transient child poverty in rural and northern regions. Whereas in urban South East over 80 percent of the children are never poor, this holds only for about 9 percent of the children in the rural North West. In rural areas in the North West of the country 43 percent of the children are chronically poor, defined as living in households that were always poor during the three waves of the GHS spanning from 2010-2016 with an additional about 47 percent of children transitory poor, meaning, considered poor at least once within the three waves. Compared to an earlier aggregate chronic poverty estimate by Dang and Dabalen (2019), this study’s twice higher chronic poverty estimate over a longer period seems alarming and requires further research.

Figure 41 a: Chronic Poverty Status (USD 1.90$ International Poverty Line) <!-- Start of picture text --> Chronic Poverty Status (USD 1.90$ International Poverty Line)<br>70%<br>60%<br>50%<br>40%<br>30%<br>20%<br>10%<br>0%<br>aggregate urban rural<br>never poor transitory poor chronic(always) poor<br><!-- End of picture text --> Figure 41 b) Chronic Poverty Status by Geographic Region - (USD 1.90$ International Poverty Line) <!-- Start of picture text --> Chronic Poverty Status by Geographic Region - (USD 1.90$ International Poverty Line)<br>90%<br>80%<br
# **Welfare and Climate Risk in Coastal Bangladesh: The Impacts of Climatic Extremes on Multidimensional Poverty and the Wider Benefits of Climate Adaptation**

Jasper Verschuur<sup>1</sup> , Olivia Becher<sup>1</sup> , Tom Schwantje<sup>1</sup> , Mathijs van Ledden<sup>2</sup> , Swarna Kazi<sup>2</sup> , Ignacio Urrutia<sup>2</sup>

> 1University of Oxford, <mark>Oxford OX1 2JD, United Kingdom</mark>

> 2 World Bank, 1818 H Street, 20433, Washington DC, USA

**JEL Codes:** D02, O10, O18, Q25

## **Keywords: Welfare implications, Climate change, Adaptation co-benefits, Poverty, Household surveys**

**Acknowledgments:** We would like to thank Steven Rubinyi, Garrett Benz, Hamish Steptoe, Mohammad Abdul Kaium, Md. Habibur Rahman, Stephane Hallegatte, Professor Jim Hall, Professor Rob Hope, and Sonia Hoque for providing input and /or valuable comments that have helped improve this Working Paper. This research received financial support from the European Union (EU) in the framework of the EU-SAR Capacity Building for Disaster Risk Management Program, managed by the Global Facility for Disaster Reduction and Recovery (GFDRR).
assess the effects of different shocks to the economy. However, this approach tends to significantly overestimate employment growth relative to GDP growth across sectors and countries.<sup>4</sup> The second method uses an econometric-based approach to estimate the relationship between employment growth and GDP growth. This follows various studies in the literature. For instance, Kapsos (2005) applies a panel estimation in levels with country and sectoral dummies, Sahin et al. (2015) estimate a cointegration relationship, while Crivelli et al. (2013) use a panel in levels with lags of the dependent variable and country specific dummies.<sup>5</sup> The estimated elasticities in these studies differ substantially, influenced by the specific country and sector of analysis and the chosen regression specification. While the results of these studies vary substantially, it is important to note that the key challenge of these approaches is the endogeneity bias in the estimators generated by the simultaneous causality of employment and economic growth.

The third estimation method is derived from distributional properties of employment and GDP. Following Klenow and Rodriguez (1997), it can be shown that the expected growth in employment conditional on observed growth in GDP equals the covariance of employment growth and economic growth divided by the variance of GDP growth.<sup>6</sup> Finally, the fourth estimation approach follows a direct and straightforward calculation of the GDP-employment elasticities as the average ratio of annual percentage growth in employment to the annual percentage growth in GDP. This method does not impose any structural assumptions on the underlying variables and can be implemented for time series of different length.<sup>7</sup> To evaluate these estimation methods’ predictive power, a cross-country data panel for developing economies in the period 2000-2016 was used based on the value added and employment data from the World Development Indicators and International Labor Organization. Within-sample as well as out-ofsample GDP-employment elasticity estimates were produced under each methodology and used to estimate employment growth based on observed GDP growth. The results
te moter an ci an is<br>based on individual level intake information|

# **2.1.2 Available Indicators for Food**

Table 3 lists the various indicators of food security each capturing different dimensions of the ideal food security measure and the indicators that can be constructed from the surveys (mainly DHS) in the countries studied.

**Table 3: Components of Food Security Measured**

|**Ideal Indicators**|**AVAILABLE**|
|---|---|
|Children's DietaryDiversityScore(CDDS)|Yes|
|Mom’s DietaryDiversityScore(MDDS)|No|
|Minimum Acceptable Diet(for children 6‐24 months)|Yes|
|Food Insecurity Access Scale (HFIAS)|No (Only in Helen<br>Keller)|
|Food Consumption Score(FCS)|No|
|Relativeprices of different foodgroups|No|
|**PROXIES IF IDEAL INDICATORS ARE NOT AVAILABLE**||
|Household DietaryDiversityScore(for child/mom)|Helen Keller|
|Starchy Staple Ratio or the Fraction of household Calories<br>Derived from Starchy Staples|No (since surveys<br>in this study do<br>not contain<br>detailed<br>household<br>consumption<br>module)|

12