rafmacalaba/data-use-mentions-extended huggingface dataset:
occupation. There is, however, also a different and equally relevant dimension of measuring face-to-face interactions with consumers, which we aim to capture through a face-to-face index based on Blinder (2009).

Home-based work (HBW) and face-to-face (F2F) interactions represent related, but complementary aspects of how social distancing is likely to affect jobs. They differ along three main dimensions, namely a) temporal (short run vs. medium run), b) the primary channel of effects (supply vs. demand) and c) the relevant margins (intensive vs. extensive).

2
# Figure 3. Regional Potential Growth

# A. Potential growth in EMDE regions

# B. Potential growth in EMDE regions

<!-- Start of picture text --> Percent Percent<br>Potential growth Potential growth<br>12 Actual growth 12 Actual growth<br>10 1998-2017 potential growth 10 1998-2017 potential growth<br>8 8<br>6 6<br>4 4<br>2 2<br>0 0<br>EAP ECA LAC MNA SAR SSA<br>C. Share of economies and GDP with D. Share of economies and GDP with potential<br>potential growth below 1998-2017 average in growth below 1998-2017 average in EMDE<br>EMDE regions regions<br>Percent Percent<br>Share of countries<br>Share of countries Share of GDP<br>100 100 Share of GDP<br>80 80<br>60 60<br>40 40<br>20 20<br>0 0<br>EAP ECA LAC MNA SAR SSA<br>1998-2002 2003-07 2008-12 2013-17 2018-27 1998-2002 2003-07 2008-12 2013-17 2018-27 1998-2002 2003-07 2008-12 2013-17 2018-27 1998-2002 2003-07 2008-12 2013-17 2018-27 1998-2002 2003-07 2008-12 2013-17 2018-27 1998-2002 2003-07 2008-12 2013-17 2018-27<br>2003-07 2013-17 2018-27 2003-07 2013-17 2018-27 2003-07 2013-17 2018-27 2003-07 2013-17 2018-27 2003-07 2013-17 2018-27 2003-07 2013-17 2018-27<br><!-- End of picture text --> D. Share of economies and GDP with potential growth below 1998-2017 average in EMDE regions Sources: Penn World Tables, World Bank.

Notes: EAP = East Asia and Pacific, ECA = Europe and Central Asia, LAC = Latin America and the Caribbean, MNA = Middle East and North Africa, SAR = South Asia, and SSA = Sub-Saharan Africa.

A. B. GDP-weighted averages using potential growth estimate based on production function approach. C. D. Number of economies and their share of GDP in the region among 50 EMDEs with potential growth in each region.

21
<br>decreases over time.|obtain the implicit depreciation rate and the<br>subjective rate of time preference. We set a<br>minimum value of 1 percent.|
|Capital<br>stock<br>(K)|Goods<br>or<br>assets<br>used<br>for<br>production<br>in<br>the<br>modern<br>economy.|We develop historical estimates using Gross Capital<br>Formation in 2005 US dollars from WDI (1960‐<br>present), extrapolating using Investment from<br>Penn World Tables (1950‐2011) for past years in<br>which it is not available. For the initial conditions,<br>we use an average from 2008‐2012 and update<br>future years using the growth rate derived from<br>solutions of the model.|
|Total<br>factor<br>productivity of<br>the<br>formal<br>sector (A)|The total factor productivity of<br>firms operating in the formal<br>sector, using capital and labor.|We develop country‐specific estimates using the<br>production function of the modern economy and<br>our estimates of capital and labor in the modern<br>economy. For the initial conditions, we use an<br>average from 2008‐2012.|
|Growth<br>of<br>Total<br>factor<br>productivity of<br>the<br>formal<br>sector (A)|Growth of total factor productivity<br>of firms operating in the formal<br>sector, using capital and labor.|We calculate an annual log growth rate of the<br>historical estimates of A and take an average from<br>2000‐2012. We set a minimum value of 0.|
|Growth
computer, refrigerator, television, air conditioner (AC), or mobile phone, was also associated with a lower PMT score.

To evaluate the performance of the national PMT in identifying the poor for inclusion in welfare programs, we explore the PMT’s performance in identifying the bottom 20%, bottom 40% and the bottom 60% of the population. To do this, we set the PMT cutoff score equal to the observed per capita household consumption that identifies this group in the bottom of the consumption distribution, although in practice this PMT cutoff score could be set to any value based on program size and program objectives.

For comparison purposes, we evaluate model performance relative to randomly drawing beneficiaries from the sample of households surveyed in the NHBPS 2014/2015.<sup>18</sup> Table 4 below presents targeting results based on a random sample of household beneficiaries. In this case each household has a probability of being included in the social program equal to the household poverty

> 18 It may be the case that in practice a program not using a PMT could do better than randomly admitting applicants from the population, but a program could also do worse by admitting wealthy applicants not intended for the program.

14
workers - the less skilled, the older and less able - are more adversely affected by GFC firm shocks. This finding suggests that the GFC through its induced adverse firm shocks plays a role in exacerbating long-run inequality.

# **IV. Mechanisms for Long-Run Effects**

## _A. Worker Reallocation across Firms and Sectors_

An important set of questions concerning the employment and wage losses from GFC firm shocks identified in Section III is whether they result from adjustments at the initial employing firm or whether worker movement to other firms or sectors counteracts such adjustments. Our rich worker panel database allows us to study the employment and wage reallocation margins for workers in response to their firm’s shock. We consider a set of mutually exclusive channels of adjustment for the workers, including change at the initial firm (for incumbent workers, i.e., those that remain employed by that firm), reallocation to other firms in the 2-digit sector of the initial firm, reallocation to firms in another tradable sector, and reallocation to firms in a non-tradable sector. This decomposition follows that proposed by Utar (2014) and captures both the direct impact of the shock on workers’ employment and wages at the initial firm but also subsequent worker movements that may offset such direct impact.

The results from this decomposition are presented in Table 3 for employment (panel A) and wages (panel B).<sup>33</sup> The negative and significant coefficient in column (2) in panel A - and its larger magnitude relative to that in column (1) - shows that the adjustment to GFC firm shocks is driven by incumbent workers that remain at the initial firm. Columns (3) and (4) in panel A show a weak countervailing effect of increased employment in other firms in the same sector or in another tradables sector.<sup>34</sup> Column (5) in panel A shows a significant countervailing effect of increased employment in other firms in non-tradable sectors but insufficient to offset
For countries with two datasets under study (Rwanda (Census and LFS), South Africa (Census and GHS), Tanzania (Census and LSMS)), results were similar on education and work indicators. However, results varied in terms of prevalence rates and disparities for some living conditions, perhaps due to different disability questions under use or other differences across datasets.

# _Implications_

Results overall suggest that disability matters when it comes to human development policy. Policy work is needed to curb the stark inequalities across functional status shown in this paper. In the context of calls to “leave no one behind” in the SDGs, this paper shows some of the gaps that need to be addressed and closed.

The microdata used in this study are rich and yet have limitations for the purpose of this study. They focus on a small set of development indicators, often economic in nature. For instance, there is no information on individual subjective well-being, nor on social connections. Besides, one limitation of the data sets under consideration is that they only cover the household population in each country. They exclude the homeless and the institutionalized population such as people in nursing homes or psychiatric hospitals. This is problematic as functional difficulties may make individuals less likely to live in a household. While institutionalization among adults is suspected to be low in the countries under study, no data could be found to confirm this. Homelessness may be a more significant problem in the countries under study and could affect the results.

This study uses general household surveys and censuses and not data sets that focus on disability. This stems from the objective to exploit data sets that are collected on a regular basis and may be potentially used to document and track human development for persons with disabilities. Complementary research is needed to use disability focused datasets, such as the Model Disability Survey developed by the World Bank and the World Health Organization. This work is needed notably to highlight the structural factors (e.g. social norms, attitudes, physical environment) that
activity. We also asked farmers to assess their spouse’s agricultural knowledge, after the knowledge portion of the intervention had been completed.

The baseline and endline surveys both contain detailed plot and crop rosters, allowing us to compute number of plots, surface cultivated, production and yields separately by crop. For each plot, we also collect detailed information about the use of labor inputs (number of workers from inside and outside the household by gender, which tasks they did, as well as the intensity of this work – allowing us to observe effort) and nonlabor inputs (phytosanitary products, fertilizer and hybrid seeds). We also collected information on the farmers’ agricultural knowledge, their perception of their spouse’s knowledge, and several variables capturing women’s decision making in agricultural production and control over crop revenue and household savings.

We also collected information on other income sources, household composition and other aspects related to the couple, such as relationship quality, and whether they still have the action plan two years later. The baseline survey was administered in June-July 2016, while the endline was administered in June-July 2018.

# **3 Empirical Strategy and Sample**

## **3.1 Empirical Strategy**

Our primary results specification in this paper is ANCOVA. Our results using survey data are estimated as follows: Yijs = α + βSeedlingSubsidyijs+ δ CouplesTrainingijs + μYijs Where

- Yijs is the outcome of interest for farmer i in village j in strata s, at follow-up.

- 0

- • Yijs is the outcome of interest for farmer i in village j in strata s, at baseline.

- SeedlingSubsidyijs equals one if farmer i in village j in strata s is assigned to receive a seedling subsidy and zero otherwise.

- CouplesTrainingijs equals one if farmer i in village j in strata s is assigned to couple’s training and zero otherwise.

- Xijs is a vector of covariates, containing all socio-demographic variables, such as age, education, marital status, household size, and farm characteristics
4|39.2|-0.8%|38.1|32.0|-2.5%|39.3|35.6|-1.4%|
|Moldova,2001–10|65.3|66.1|0.1%|64.7|76.0|1.8%|64.1|71.0|1.1%|
|Nepal,1996–2003|32.7|33.8|0.5%|32.7|34.0|0.6%|32.7|34.2|0.6%|
|Peru,2004–10|69.4|72.5|0.7%|82.5|78.3|-0.9%|79.1|80.1|0.2%|
|Romania,2001–09|83.2|82.1|-0.2%|79.5|||83.6|74.1|-1.5%|
|Thailand, 2000–09|74.7|74.4|-0.1%|60.6|72.0|1.9%|78.2|71.3|-1.0%|

<mark>Source: Author’s calculations with data from SEDLAC (CEDLAS and the World Bank), RIGA, and National Household Surveys.</mark> 28
ment in schooling. This is important evidence for government policy, as substitutability implies that public investment to improve the quality of rural schools is desirable on both equity and efficiency grounds. The evidence on the slopes of the investment equation suggests that better educated peers are complementary to financial investment in urban areas, but separable in the rural areas. While adult role models are substitutes of financial investment by parents in the urban sample, they are separable in the rural areas. Theory provides plausible explanations for these contrasting effects. Peer and role model effects weaken the impact of family background on educational attainment of children, and this is true in rural and urban samples. The peer and role model effects are not responsible for the convexity observed in the intergenerational mobility equation, indicating that the higher efficiency of educated parents in financial investment decisions might be important, as emphasized recently by Becker et al. (2018). The empirical results are robust to controlling for the heterogeneity in cognitive ability of children. The theoretical and empirical approaches developed in this paper are of wider interest, as they can be applied to other developing countries with household panel data.

# **References**

- Akresh, R., Halim, D., and Kleemans, M. (2018). Long-term and Intergenerational Effects of Education: Evidence from School Construction in Indonesia. NBER Working Papers 25265, National Bureau of Economic Research, Inc.

- Asher, S., Novosad, P., and Rafkin, C. (2018). Intergenerational Mobility in India: Estimates from New Methods and Administrative Data. Working paper, World Bank.

- Autor, D. H. (2014). Skills, education, and the rise of earnings inequality among the “other 99 percent”. _Science_ , 344(6186):843–851.

- Azam, M. and Bhatt, V. (2015). Like Father, Like Son? Intergenerational Educational Mobility in India. _Demography_ , 52(6):1929–1959.
were substantial: for example, a mother received 255 pesos per month, or 40% of the typical male laborer’s monthly earnings in these rural communities, if her ninth grade daughter was enrolled in school. Using this setting, we first estimate income and price effects. To identify price effects, we exploit the fact that the introduction of the CCTs was randomized at the locality level: 63% of the localities received transfers immediately, while the other 37% started two years later. To identify income effects, we use variation in transfers to younger siblings below the age of 12 years, as enrollment below the age of 12 is almost 100%, implying the conditions of these transfers were non-binding.<sup>5</sup> In other words, transfers to younger siblings can be viewed as unconditional transfers to the household. Using detailed panel data from 1997-1999, we estimate income and price effects for secondary school aged children (children aged 12-15 years). We find substantial income effects, with average income effects around one-third as large as average price effects. These estimates imply a relatively high degree of curvature in the utility of consumption, with an implied coefficient of relative risk aversion of 1.05.<sup>6</sup> Using these estimates, we proceed to evaluate the size of the targeting benefit relative to the exclusion cost for households in Progresa villages with secondary school age children. Under the observed Progresa transfers, we find that this ratio is substantial: the targeting benefit is 88% as large as the exclusion cost. We then calculate the share of the Progresa budget that should be allocated to a CCT over a UCT based solely on targeting grounds (i.e., we calculate the share that equates the targeting benefit to the exclusion cost). We find that 41% of the Progresa budget should go to a CCT, implying that the targeting benefit is a quantitatively important benefit of CCTs in this setting (in comparison, under the observed transfers, 65%
# More Relatively-Poor People in a Less Absolutely-Poor World

## Shaohua Chen and Martin Ravallion<sup>1</sup>

_Development Research Group, World Bank 1818 H Street NW, Washington DC, 20433, USA_

### **Keywords:** Global poverty, absolute poverty, relative poverty, inequality **JEL classifications:** I32, E31, O10

> 1 Many colleagues at the World Bank have helped the authors in obtaining the necessary data for this paper and answered our many questions. An important acknowledgement goes to the staff of over 100 governmental statistics offices who collected the primary household and price survey data. The authors thank Prem Sangraula and Qinghua Zhao for their invaluable help in setting up the data sets we have used here. They have also benefited from the comments of numerous colleagues throughout the Bank. The support of the World Bank’s Knowledge for Change Program is gratefully acknowledged. These are the views of the authors and should not be attributed to the World Bank or any affiliated organization. Addresses: schen@worldbank.org and mravallion@worldbank.org.
Creditors, including international financial institutions, play an important role in mitigating the risks associated with debt accumulation. They need to ensure that their own lending practices are prudent. More broadly, while country authorities have the primary responsibility to transparently report their debt data, international financial institutions work to support such transparency and sustainable lending practices in several ways. The IMF and the World Bank collect and disseminate debt statistics that are used by a wide range of stakeholders; produce reports of public debt data at the country level via joint debt sustainability analyses; support countries’ efforts to produce medium-term debt management strategies; publish information on countries’ borrowing capacity; and directly liaise with other multilateral, bilateral, and private creditors (World Bank and IMF 2009a, 2009b).

# 6.2. Macroeconomic policies

Notwithstanding substantial improvements since the 1990s, macroeconomic policy frameworks can be strengthened further in many EMDEs (World Bank 2019b). Monetary policy frameworks and exchange rate regimes can be strengthened to increase central bank credibility. Fiscal frameworks can ensure that borrowing remains within sustainable limits and borrowed funds are used well.

The benefits of stability-oriented and resilient monetary policy frameworks cannot be overstated. During episodes of financial stress, when EMDE currencies tend to depreciate sharply, strong monetary policy frameworks will be helpful not least because the exchange rate pass-through to inflation tends to be smaller in countries with more credible, transparent, and independent central banks; inflation-targeting monetary policy regimes; and better-anchored inflation expectations (Kose et al. 2019). Flexible exchange rates can provide an effective mechanism for macroeconomic adjustment and help avoid currency overvaluations, as well as preventing the buildup of large currency mismatches on balance sheets—a common precursor of crises.

Fiscal rules can help prevent fiscal slippages, ensure that revenue windfalls during times of strong growth are prudently managed, and contain and manage risks from contingent liabilities.<sup>17</sup> Strong fiscal frameworks have also been associated with lower inflation and inflation volatility, supporting the central bank in delivering its mandate (Ha, Kose
resulted from a reform that limited insurance coverage. They show that the reform caused a 50% decrease in deposits above the insurance limit. DeLong and Saunders (2011) find that depositors were less prone to withdraw their deposits from weaker banks after the introduction of fixed-rate federal deposit insurance in the United States. Chernykh and Cole (2011) use the deposit-insurance scheme introduced into the Russian banking system as a natural experiment to examine the effects of deposit insurance. They find that the introduction of deposit insurance led to increased deposits and reduced reliance on state-owned banks as custodians of retail deposits. They find that the effect was stronger for regional and smaller banks. Angkinand (2009) examines whether deposit insurance can reduce the output costs of banking crises. Using data from 47 crises in 35 countries during 8
̄</sup>_Ii_|-0.065***|-0.057***|-0.070***|-0.066***|-0.050***|-0.046***|
||(0.009)|(0.013)|(0.013)|(0.009)|(0.012)|(0.012)|
|Num.Obs.|557|557|557|557|557|557|
|R2|0.433|0.569|0.535|0.475|0.677|0.652|
|Std.Errors|IID|IID|IID||||
|_S_(lat, lon)||||0.000|0.000|0.000|

Robust standard errors in parenthesis. * p _<_ 0.1, ** p _<_ 0.05, *** p _<_ 0.01. Panel OLS controls for latitude and longitude. Panel GAM shows semiparametric regressions with thin-plate spline in latitude and longitude, _S_ (lat, lon) shows the approximate p-value of the thin-plate spline.

We use the allocations of the Efficiency + Coordination counterfactual to isolate the effect of complementarities since the fully optimal model has an additional effect through the changes in aggregate budgets. To ease the interpretation, before interacting _Gi_ and _I_<sup> ̄</sup> _i_ , we demean them so that coefficients _β_ 2 and _β_ 3 denote the average effect of _Gi_ and _I_<sup> ̄</sup> _i_ , respectively.

We find that increases in the quality of electricity or roads are associated with reductions in the employment share in agriculture and increases in manufacturing and services. In fact, focusing on the GAM estimates, for a 1 percentage point increase in the quality of electricity (roads), the employment
relationship is most robust among the most recent cohort. Similarly, McKenzie (2003) finds evidence of deferred and/or lower fertility in response to the Mexican Peso Crisis of 1995. His analysis shows that about one in 20 households postponed or decided against having a child as a result of the crisis, among both educated and non-educated households, and both rural and urban households.

Some studies find that deferring fertility during economic crises is confined to a certain subset of women (mostly women who are more likely to be credit constrained), implying that economic crises change the composition of women giving birth, which may or may not be reflected in overall fertility rates. Using a large micro-dataset from India, Bhalotra (2010) shows that during periods of economic downturn, women at high risk of spontaneous abortions or stillbirths become more likely to defer fertility. Specifically, she finds that in both rural and urban areas, illiterate women are more likely to avert childbearing during economic recessions. Further, in rural areas, this is also true for women with illiterate husbands and for women from scheduled tribes, which represent a disadvantaged ethnic group in India. In a similar vein, but from a developed country context, Dehejia and Lleras-Muney (2004) find that in the United States, there is a reduction in the fraction of black mothers who are high school dropouts during recession (periods of high state-level unemployment). Since these women are more likely to have unhealthy babies, their deferred fertility during economic downturns translates into overall improvements in child health (Dehejia and Lleras-Muney, 2004).

14
internet services). Finally, we collect data on internet access, since internet access is found to significantly affect firms’ sales growth and productivity level around the world and is a general-purpose technology (Clarke et al. 2015).

Panel C in Table 1 indicates quantum leaps in infrastructure provision in China during the economic reforms, with the quantity of roads, railways, and expressways skyrocketing. For instance, the average length of highways at the provincial level rose from 3.6 (in 10,000 km) in 1993 to 14.8 in 2015. Within 10 years, the percentage of the population covered by internet service increased from 4.6 to over 50 percent. Infrastructure access exhibits some, but only _limited,_ regional variations. Compared with coastal provinces, firms in inland regions face 17