rafmacalaba/datause-encoder-data huggingface dataset:
# **3. Diversity of the world**

Figure 2 combines the two aspects of within-national and international distributions. Income of each country ventile is shown in the global distribution. Consider Germany. Since Germany is a rich country, and its income inequality is moderate, most of its population will be highly placed in the world income distribution. The poorest German ventile is at the 73<sup>rd</sup> percentile of the world income distribution. All other ventiles are obviously higher, and the richest ventile belongs to the top world percentile. The same interpretation is for other countries. We call such curves “the position curves”. Unlike Germany, where the span between the richest and the poorest ventile is 27 percentiles, in China, the distribution covers a much wider range, from the third to the 85<sup>th</sup> percentile. Brazil, with its unequal income distribution, covers practically the entire global spectrum, from the lowest percentiles to the richest. India, in contrast, is shown to be fairly poor with the poorest ventile belonging to the 4<sup>th</sup> poorest percentile in the world and the richest ventile to the 70<sup>th</sup> . This last position shows that the richest people in India (as a group—admittedly a large one since it contains more than 50 million people) have lower per capita income than the poorest people (as a group) in Germany.

The graph can also be read as a type of generalized Lorenz curve where instead of the income level on the vertical axis, we have income position in the world. The advantage of this “positional” approach is that it reduces the measurement error,<sup>17</sup> but since position is bounded from above these specific generalized Lorenz curves will in many cases be concave rather than convex. The interpretation however is the same as with the generalized Lorenz curves.<sup>18</sup> From Figure 2 we can easily conclude that Sri Lanka’s distribution is first-order dominant with respect to India’s, and that Germany’s distribution is first-order dominant compared to any other country save Brazil. No first-

> 17 Household surveys do not measure income or expenditures perfectly. They are less likely however to make large mistakes that  may result in the misplacing of individuals into “wrong” world percentiles.

> 18 The first-order positional dominance _must_ imply the first-order income dominance. The reverse may not hold because a distribution may be income dominant but the difference in income may be so small as to place the ventiles from both countries into the same global percentile.

10
**LV.4**

||||Sub<br>|sidization||
|---|---|---|---|---|---|
|Title of Project,<br>Country|Contraceptlves<br>Donated|CompanySubsidy|Donor Subsidy<br>for Services|Client PaysFees|Policy and**Etimatese**of<br>Costs/Revenuesor budget|
|XPLomW<br>ITNR/F<br>0DU|STI-3ASEDSEVIcES(co|ntd)||||
|Indonesia:<br>P.T.CGasy Djaja<br>Family Planning<br>Program|Yes, by OKXENin<br>year one**and**by<br>3111**snd**gnter-<br>prie<br>inyear<br>two.|Yes|Yes,for<br>two years|Noinformation|Project cost- $25,180|
|mexico:<br>FamllyPlanning<br>Industries at<br>IUSAZPq Indus-<br>trial<br>Complex|No, obtained<br>through sub-<br>contract vith<br>WO|Yes, for space<br>equipmnt. May<br>also coverlong<br>term operation|Yes,through<br>EXFAM: training<br>materials, dona-<br>ttons<br>sservices|Unclear, but no<br>sention is made<br>ofthis|Project coat- $83,000|
|NiZeria:<br>LBN Emplroyee<br>Clinic<br>Family<br>Planning<br>Child<br>Spacing<br>Program|**Yes,**and company<br>will<br>obtain<br>sme<br>contraceptive.**at**<br>wholesale<br>prices|Yes|Yes|Not yet<br>determtned|Project<br>cost - $114,070,<br>ith<br>435,000<br>from Enter-<br>prite<br>Program.<br>The**costs**<br>of contraceptives<br>arenot<br>included.|
|Thailand:<br>Factory-based<br>Family Planning<br>Services<br>Project|Yes|No|Yes|Yes|Project<br>coat<br>- $260,255<br>0|
|OWTlCNG MIAuT IUMT|U<br>IN FAMILY_FNAIN_|||||
|Niseria:<br>Gulf Oil|No|Yes|No|No|Noinforuatton<br>predomi-<br>nately<br>technical<br>**assistance**|
|Zimbabwe:<br>Comercial .nd<br>Industrial<br>Medical Aid<br>Society|No|Yes|No|Yes|<br>$31,911 for employce survey|
|Indonesia<br>Feasibility of<br>Comercial<br>Clinics<br>Providing<br>Sterili-<br>zation<br>inJakarta|N/A|N/A|N/A|N/A|Project coat- $24,000|
|TheYKBEntrepre-<br>'neurial<br>Develop-<br>mentProject|Yes, byBKKBN|N/A|Yes, from PVO|Yes|Projectcost<br>-<br>$10,552|
The COVID-19 crisis has also led to a lower likelihood of being employed full-time, with men more adversely affected than women. Among those working, the pandemic has reduced the weekly hours of women and men by 2.3 and 2.6 hours, respectively, relative to the average total hours worked per week pre-pandemic. Moreover, we find that employed women and men earn 16 percent and 15 percent less in monthly earnings, respectively.

The contribution of this paper is twofold. First, findings from Indonesia add to the rapidly growing literature on the gendered impacts of the pandemic-induced crisis on labor markets. This paper employs the seasonality difference-in-differences approach to investigate gender differences in the impact of the pandemic on employment. However, it improves on earlier work by extending the baseline period to 2016 to capture more years of seasonal pre-pandemic trends. The paper also goes one step further than earlier studies, as it not only measures the overall employment impacts, but also explores how the pandemic has impacted the structure and composition of the labor market.

Second, the paper contributes to the literature on the impacts of the COVID-19 pandemic on employment in developing countries, as it also considers pre-pandemic employment dynamics in measuring the causal effect of the pandemic on employment. Due to social distancing regulations, regular face-to-face (F2F) data collection efforts were halted in many countries. In the context of low- and middle-income countries which predominantly relied on F2F surveys prior to the pandemic, incredible efforts were undertaken to quickly roll out remote data collection to measure the early impacts of the COVID-19 pandemic, such as with the World Bank’s HighFrequency Phone Surveys (HFPS) in more than 100 countries.<sup>3</sup> However, this new wave of data

> 3 Given the importance, albeit difficult circumstances, of monitoring the welfare impacts of the COVID-19 pandemic on households, the World Bank administered High Frequency Phone Surveys (HFPS) in more than 100 countries, including Indonesia (for more details: <u>https://www.worldbank.org/en/country/indonesia/brief/indonesia-covid-19observatory). The surveys are conducted regularly and are aimed to gather information on key household socio-</u> economic indicators, including employment, as well as access to public services and safety nets.

5
Warner, J. T., & Pleeter, S. (2001). The personal discount rate: Evidence from military downsizing programs. American Economic Review, 91(1), 33-53.

- Whitty, M. T., & Buchanan, T. (2012). The online romance scam: A serious cybercrime. CyberPsychology, Behavior, and Social Networking, 15(3), 181-183.

- Wooldridge, J. M. (2010). Econometric analysis of cross section and panel data. MIT press.

- Wu, J., Gyourko, J., & Deng, Y. (2012). Evaluating conditions in major Chinese housing markets. Regional Science and Urban Economics, 42(3), 531-543.

- Xu, N., Shi, J., Rong, Z., & Yuan, Y. (2019). Financial literacy and formal credit accessibility: Evidence from informal businesses in China. Finance Research Letters, 101327.

- Zeldes, S. P. (1989). Consumption and liquidity constraints: an empirical investigation. Journal of political economy, 97(2), 305-346.

31
Fukase, E., and W. Martin (2000). ‘The Effects of the United States Granting MFN Status to Vietnam’. _Weltwirtschaftliches Archiv_ , 136(2): 539–59.

- —— (2001.) ‘A Quantitative Evaluation of Vietnam’s Accession to the ASEAN Free Trade Area’. _Journal of Economic Integration_ , 16(4): 545–567.

- Glewwe, P., M. Gragnolati, and H. Zaman (2002). ‘Who gained from Vietnam’s boom in the 1990s?’. _Economic Development and Cultural Change_ , 50(4): 773–792.

- Harrison, G. W., T. F. Rutherford, and D. G. Tarr (2003). ‘Trade Liberalization, Poverty and Efficient Equity’ _. Journal of Development Economics_ , 71: 97–128.

- Heng, M. T., and V. Gayathri (2004). ‘Impact of Regional Trade Liberalization on Emerging Economies: The Case of Vietnam’. _ASEAN Economic Bulletin_ , 21(2): 167–182.

- Hertel, T. W. (1997) (ed.). _Global Trade Analysis: Modeling and Applications_ . Cambridge: Cambridge University Press.

- Hertel, T.W., and L. A Winters (eds.) (2006). _Poverty and The WTO: Impacts of the Doha Development Agenda_ . World Bank, Washington, 334pp.

- Jenkins, R. (2004). ‘Vietnam in the Global Economy: Trade, Employment and Poverty’. _Journal of International Development_ , 16: 13–28.

- Jensen, H. T., and F. Tarp (2005). ‘Trade Liberalization and Spatial Inequality: A Methodological Innovation in a Vietnamese Perspective’. _Review of Development Economics,_ 9(1): 69–86.

- Kanbur, R. (2001). ‘Economic Policy, Distribution and Poverty: The Nature of Disagreements’. _World Development_ , 29(6): 1083–1094.

- Krueger, A. O. (1998). ‘Why Trade Liberalisation is Good for Growth’. _Economic Journal_ , 108(450): 1513–1522.

- Le, T. H., and P. Winters (2001). ‘Aid Policies and Poverty Alleviation: The Case of Vietnam’. _Asia-Pacific Development Journal_ , 8(2): 27–44.

31
Figure 3: Comparison of Inflation Estimates

# **(a) WCPD-vw versus Engel Curve Method**

<!-- Start of picture text --> Rural Mekong Delta<br>Rural South East<br>Rural Central Highlands<br>Rural Northern & Central Coast<br>Rural Midlands & Nth Mountains<br>Rural Red River<br>WCPD-vw<br>Urban Mekong Delta Engel<br>Urban South East<br>Urban Central Highlands<br>Urban Northern & Central Coast<br>Urban Midlands & Nth Mountains<br>Urban Red River<br>-10 0 10 20 30 40<br>Percentage Change in Price Level (2012 survey relative to 2010)<br><!-- End of picture text -->

# **(b) WCPD-fw versus Engel Curve Method**

<!-- Start of picture text --> Rural Mekong Delta<br>Rural South East<br>Rural Central Highlands<br>Rural Northern & Central Coast<br>Rural Midlands & Nth Mountains<br>Rural Red River<br>WCPD-fw<br>Engel<br>Urban Mekong Delta<br>Urban South East<br>Urban Central Highlands<br>Urban Northern & Central Coast<br>Urban Midlands & Nth Mountains<br>Urban Red River<br>-10 0 10 20 30 40<br>Percentage Change in Price Level (2012 survey relative to 2010)<br><!-- End of picture text --> 27
vice (GES). In our evaluation districts these dissemination efforts were supplemented by teams of enumerators who worked with community leaders and religious institutions to bolster the outreach efforts.

To apply to the program, applicants submitted a formal application to the district office and attended an interview with a panel of district officials. The interview panel assessed all applicants and determined whether they were eligible for the program. Due to political considerations, district officials were given the opportunity to “handpick” to about 16 of the slots. The were applicants fill percent remaining eligible applicants then placed in the random lottery. The randomization was stratified by choice of training and district and was conducted electronically but announced locally in conjunction with district officials. In our sample districts 3,928 youth applied to the program. The selection committees selected a total of 329 youth as priority applicants. The randomization assigned 2,031 applicants to the treatment group and 1,568 to the control group. The treatment was than the control because the selection group larger group process had to ensure that that there were no unused training slots. This selection process was completed by the end of 2012.

The 2012 elections resulted in a change in the political regime, and this delayed the implementation of the program. The program was finally launched in late 2013. Treatment group applicants were informed by phone and were invited to a series of “matching meetings,” where prospective training providers introduced themselves and their firms. Potential trainers described the location of their shops, their experience in training apprentices, a summary of their firm, and any trade specializations. Potential apprentices then completed a preference sheet, identifying the set of trainers they could feasibly train with based on distance. For clarity we suggested that potential apprentices focus on listing “trainers within walking distance.”<sup>9</sup> Apprentices were then randomly assigned to a provider in their feasible set. Training began in late 2013 and lasted between two and three years.

# **3.2 Data and Balance**

We collected baseline data from applicants while they waited to be interviewed by the district selection committees. The baseline apprentice survey covered a broad range of information, including educational attainment, family background, cognitive and noncognitive assessments, and labor market outcomes. Baseline data on trainers were

> 9Apprentices could also list trainers who were further away as long as they had reliable means of transportation.

9
employment and wages. At the same time, there is a less flexible segment, consisting of large public or privatized firms with strong unions, where actual firing and hiring costs are higher, and thus the adjustment capacity is lower. And on top of this there is a substantial informal sector where employers by definition face virtually no regulatory constraints and flexibility is unfettered.<sup>32</sup> All in all, employers in Lithuania face few effective constraints to employment adjustment, although it involves some procedural and monetary costs. However, they face a constraint to wage adjustment resulting from a relatively high minimum wage, despite the fact that enforcement is not very strict. As a consequence, job turnover is high but so is unemployment, concentrated among those with low-skills and little labor market experience.

# **Policy Recommendations**

Although the labor market in Lithuania is relatively flexible, there is a number of measures that if undertaken would improve labor market performance. These include:

- Lowering dismissal cots by making advance notice of dismissal related to job tenure and shortening it for workers with short tenure;

- Liberalizing the use of fixed-term contracts by removing a limit on the number of successive renewals while keeping the existing limit on total duration;

- Adopting the practice of annualization of working hours, i.e., calculating the weekly working time on a yearly basis;

- Lowering the cost of overtime work by allowing social partners to negotiate the number of hours as well as the amount and forms of compensation (monetary vs. time oft), while setting the ceiling on the total number of hours (at least 200 hours) and the minimum overtime premium at 25 percent of the base salary;

- Gradually lowering the minimum wage as proportion of the average wage (e.g., by suspending the cost of living adjustment) to about one-third of the

> 32 According to data compiled by SODRA (Social Security Institution), the share of informal sector **in** employment is from 8 to 13 percent (depending on the definition adopted).

69
The Mexican Pension Annuity Market withdrawal offered by an AFORE or an annuity offered by a specialized annuity provider. It is important to mention that, if the accumulated balance at retirement is less than what is needed to obtain an annuity greater than or equal to the minimum guaranteed pension (PMG), the worker is required to select a programmed withdrawal. When resources are exhausted, the government is responsible for paying the PMG to the worker.<sup>3</sup>

**Table 2: Accumulated Savings in the AFORE System**

|**Year**<br>**1/**|**Number of**<br>**AFOREs**|**RCV**<br>**account**<br>**(MXN 000,000)**|**Voluntary**<br>**account**<br>**(MXN 000,000)**|**Housing**<br>**account**<br>**(MXN 000,000)**|**Total**<br>**(% of GDP)**|
|---|---|---|---|---|---|
|1998|13|54,470.5|46.7|51,419.0|2.75|
|1999|14|104,194.8|331.3|81,039.7|4.03|
|2000|13|158,806.2|846.0|110,294.0|4.91|
|2001|13|242,242.2|1,513.8|148,148.2|6.74|
|2002|11|315,322.4|1,900.5|178,808.2|7.91|
|2003|12|392,881.8|2,221.3|210,071.6|8.78|
|2004|13|469,145.8|2,031.0|246,336.9|9.40|
|2005|18|577,008.7|1,981.4|284,599.1|10.31|

**Notes** : 1/ As of December of each year. **Source** : CONSAR, IFS.

Members of the transitional cohort with at least one contribution at the time of the reform can opt for old age retirement benefits under the provisions of the LSS-73. If they become disabled or die, they or their beneficiaries were originally required to buy an annuity from a private insurance sector specialized annuity provider, exactly like members of the new cohort.<sup>4</sup> Hence in general, benefits are either provided by private sector pension annuity companies or by the IMSS or by the federal government depending on the type of benefits and annuitant being considered (more on this is provided in section III).

The rationale behind mandating the purchase of IV and RT benefits in the private sector while allowing the transitional cohort the option to choose between the old and new old age benefits was related to the fact that, at the time of the reform, old age benefits under the LSS-73 were on average more generous than under the LSS-97, RT benefits were more or less equivalent under the two laws, and IV benefits were on average more generous under the LSS-97 than under the LSS-73. In addition, this would have allowed for the development of a private sector annuity market in Mexico by the time the new entrants to the labor force after 1997 started retiring. These are currently only 37 percent of the IMSS members as reported in the next table.

> 3 It is worth mentioning that when a pensioner with a PMG dies, IMSS has to buy a survivor annuity for his/her beneficiaries from a private sector annuity provider.

> 4 This, as it will be explained later changed in 2002.  Notice also that for simplicity we are not discussing the provision of the minimum pension guarantee discussed further in section III.

- 3 -
# **Appendix 1. Regression Results Underlying Fiscal Risk Analysis**

Given the short time series available for Burundi, we keep the estimation to the simplest possible forms. The following regression variables are used:

- GDP is the real GDP in local currency at 2005 prices

- AG_GDP is the agricultural value added in local currency at 2005 prices

- REVENUE is the central government revenue excluding grants in local currency at 2005 prices

- P_COFFEE is the world price of Arabica coffee in constant US cents per kilogram

- RAIN is the deviation of annual precipitation from the long run average, normalized to vary from 0 to 100

- WAR is the 1993–2000 civil conflict dummy.

The unit root test results for the variables are reported in Table A1. The models and regression results are reported in Table A2–A3.

# **_Coffee shocks_**

The impact of coffee price shocks on government revenue is econometrically estimated using a simple reduced-form time-series regression. World coffee prices and civil war are treated as exogenous variables. Adding their lagged values did not significantly improve the estimation. The results imply: The impact of shocks to coffee prices on growth of revenue is given by: The stochastic coffee price shock to be applied to the baseline projection of growth in revenue is calibrated based on the historical data in 1980–2012, and assumed to be normally distributed with mean zero and standard deviation defined by the historical data: 30
of residence to estimate the impact of conict intensity, as measured by months of war, on adult height. Using the 2016 NDHS women sample, I nd that conict and, in particular, exposure starting very early in one's growing period, has highly signicant and negative impact on women's nal adult height. Findings are robust across (i) model specications and (ii) measures of conict. In validating the dierence-in-dierences estimation strategy used, I nd no evidence of presence of non-parallel dynamics nor of selective migration and fertility. These results are aligned with the biomedical literature that early childhood conditions are highly signicant in determining nal height  early life stunting increases the risk of being short as an adult (Golden, 1994; Martorell et al., 1994). Conditions in the fetal period and early years after birth are profound in inuencing human biology and long-term health. Responses to lack of adequate nutrition of developing fetus may be coded permanently, which is likely to increase later life health hazards (Barker, 1992). Similarly, early years of life are highly susceptible to environmental inuence on height (Schmidt et al., 1995). Nepalese children growing up during the conict experienced substantial levels of physiological and mental stress, and for many, mostly in rural areas under the control of the Maoists, it was a major nutritional shock and reduced access to healthcare. These are likely mechanisms at work and describe the results presented in the paper.

The sucient time gap between the start of the conict and the time of the NDHS 2016 allows me to explore the impacts of the conict on children of the women who were exposed to conict in their childhood. I nd that the mothers' exposure to conict is detrimental for their children's health. Although imprecise, impacts on children's height-for-age z-scores are negative. Results for children's weight-for-height, weight-for-age and BMI z-scores, on the other hand, are precisely estimated and again negative. Results are robust to alternative measure of conict intensity (mother's district of birth). To explore possible intergenerational transmission mechanisms, I investigate the impacts on mother's economic and fertility outcomes. I nd that women exposed to conict during childhood have more children and live in a household with signicantly less wealth. The combined eect of the two likely results in drastic decreases in the parental ability to invest in children.

25
their non-enrolled daughters going to school (30%) than to disapprove of schooling for non-enrolled sons (7.5%).

Field interviews conducted in five villages randomly selected, by region, from the PRHS-II sample also highlight the importance of mobility constraints for girls school enrollment, as the following quotes illustrate:<sup>5</sup> "...I took my daughters out of school because it was too far to walk and I feel that things are not safe there...” (woman, Southern Punjab) “When sons go to schools that are far away we don’t get worried, but for our daughter we get worried.” (woman, Southern Punjab).

“The problem is, when children are so small to attend primary school, we cannot expect them to walk all the way to a school in another settlement or another village. But when they grow a bit more mature, 8-9 yrs, we cannot send girls alone to walk this distance. There are tall sugarcane fields and all the way is deserted except young boys, who use the same route for going to school. This is very dangerous! The boys tease — young girls anyone could push a little child, girl or boy in the fields, one would not even know!" (woman, Southern Punjab)

# 3.2 Caste and Stigma

Caste has received scant attention in Pakistan, from any disciplinary perspective. Indeed, the PRHS-II is the first large-scale survey, as far as we are aware, to collect systematic data on caste affiliation in rural Pakistan. While caste groupings in Pakistan cannot be precisely mapped into the much more extensively studied social hierarchy of neighboring India, there are significant similarities between the two due to their long shared history. In particular, caste identity is embedded within occupational differences, which are associated with status and notions of purity and pollution. Various exclusionary norms follow from these hierarchies and are exercised in relations of mutual assistance, in social networks, and in the establishment and maintenance of political power within the village economy and without. Unlike the Indian context, there has been no official acknowledgement of caste-based

> 5Khan (1998) provides similar evidence from North Punjab.

6