rafmacalaba/data-use-mentions-extended huggingface dataset:
4

# II. **HEALTH INSURANCE IN CHINA—SOME SALIENT FACTS**

Under China’s pre-reform planned economy, almost all citizens were covered by some form of health insurance. Agricultural workers were covered by the old commune-based cooperative medical scheme (CMS), state-owned enterprise (SOE) workers were covered by the Labor Insurance Scheme (LIS), and civil servants and other government workers were covered by the Government Insurance Scheme (GIS). There were some gaps in coverage (not all urban schemes covered dependents, for example), but the gaps were relatively small (during the 1970s the CMS covered an estimated 90% of the rural population).

China’s transition from a planned to a market economy from 1980 onwards brought dramatic reductions in health insurance coverage. The decollectivization of agriculture resulted in an almost total collapse of the CMS. By 1993 less than 10% of the rural population had health insurance.<sup>4</sup> The mid-late 1990s saw several attempts to resuscitate the CMS, but despite these initiatives, CMS coverage nationally remained stubbornly low. By 2003 80% of China’s rural population—some 640 million people—lacked health insurance. In that year, half of the rural residents in 2003 who said they did have insurance said they were covered by either private (i.e. commercial) insurance or ‘other’ insurance, up from 31% in 1993.

Coverage in China’s cities has also declined, though less dramatically than in rural areas. As China transitioned to a market economy, the SOE—the backbone of the LIS—came under increasing pressure. LIS coverage fell, as did GIS coverage. By 1998 nearly half the urban population lacked insurance coverage. A variety of reforms have been introduced, including the

> 4  Figures on coverage are from China’s National Health Survey (NHS), undertaken by the Ministry of Health (MOH) in 1993, 1998 and 2003. The figures for 1993 and 1998 are published
14_._09|53_._80|102_._49|
|Wheat||0_._70||20_._98|12_._51|57_._37|91_._79|
|Wheat|||0_._05|24_._91|10_._91|60_._10|94_._95|
|Wheat||||24_._91|10_._91|60_._11|94_._96|

Notes. In this table we present the results of the SRHS approach using the groundwater supply or volume measure using the aquifer dataset constructed by World Bank. Each row represents one simulation. Column (1) specifies the crop for which the analysis was run. Columns (2)-(4) specify whether or not constraints were imposed; if yes, then what the thresholds were. Column (5) presents the fraction of all croplands where the constraints were met. Column (6) presents the share of croplands where we see production gains, as compared to the all the croplands where the constraints were met. Columns (7) and (8) present the median and mean of the simulated gains in production.

30
sources, because different data sources cover different sets of countries with different underlying distributions of governance. For example, a score of 6 out of 10 might mean something different in a data source that covers only advanced

> 8 In addition, the World Bank and the International Monetary Fund use the Country Policy and Institutional Assessment data as a key indicator in their Low-Income Country Debt Sustainability Framework (LIC-DSF), recognizing that there is a strong empirical relationship between institutional quality and the risk of debt servicing difficulties (see IMF (2017)).  In the same vein, the International Monetary Fund uses components of the WGI as key measures of institutional quality in its Debt Sustainability Framework for Market-Access Countries because their analysis shows that the WGI has statistical predictive power for debt servicing difficulties (see IMF (2021)). 9 For a small number of data sources that are commercially available by subscription only, we cannot report the individual questions from these sources.  Instead, we report averages of questions assigned to each of the six aggregate WGI measures.

8
|Employment rate (emp/hhsize)|0.20|0.55|0.72|
|---|---|---|---|
|Dependency ratio|-0.49|-0.44|-0.31|
|Female headed household|-0.09|-0.03|0.10|
|Household size|-0.07|-0.09|-0.05|
|IDP|-0.01|-0.28|0.08|
|Constant|5.98|5.84|5.56|
|Observations|540|300|660|
|_R_-squared|0.24|0.50|0.28|

_Data source_ : Rapid Welfare Monitoring Survey (SWIFT) 2017-18.

_Table 4. Pseudo-PMT for the SEVAT model_

||(1)|(2)|(3)|
|---|---|---|---|
||**Kurdistan**|**North**|**Center-South**|
|Home: not owned by HH|-0.03|-0.14|-0.04|
|Water: no public network tap|--|0.12|--|
|Household size|-0.07|-0.10|-0.05|
|Employment rate (emp/hhsize)|0.48|0.83|0.93|
|Constant|5.70|5.65|5.40|
|Observations|540|300|660|
|_R_-squared|0.19|0.47|0.27|

_Data source_ : Rapid Welfare Monitoring Survey (SWIFT) 2017-18.

# 3.4 Cross-Eligibility Calculation and Referral Accuracy

This exercise attempts to create a tool to assess the eligibility of the CLCI’s beneficiaries for the MoLSA’
“I don’t have the time” 7. Religious reasons 8. Not eligible, which included “counter-indication,” “recent medical discharge, “have an underlying health condition and believe taking the vaccine will make it worse” 9. Other The surveys also differed across countries in terms of whether a single concern or multiple concerns were collected. To account for the difference in the number of response options, the results are presented separately.

# _2c. Contextual data_

Country-level contextual data were drawn from other sources. New COVID-19 cases per million, measured as a 7-day rolling average prior to the midpoint of the month household survey data was collected in each country, were obtained from Dong and colleagues (2022), and the Oxford Stringency Index was drawn from Hale et al. 2022. The latter is an index, ranging from 0–100, that indicates the degree to which various restrictions were put in place by governments to control the pandemic (for example, school closures and shelter-in-place requirements). Confidence in the press, the government, and the WHO was drawn from the World Values Survey Wave 7, fielded in 2017-2020, and aggregated up to the country level (Inglehart 2022). Excess deaths due to COVID-19 draw on WHO data (WHO 2022). Country geographic region and income group are based on the World Bank classifications.

# _2d. Analytical strategy_

Data from 53 countries was pooled into a single data set. First, we report point estimates and 95% confidence intervals for each country based on standard errors clustered at the state or province level within each country. We also report the simple average across all countries and stratified by: (i) World Bank region, (ii) World Bank country income group, (iii) urban vs. rural residence, (iv) gender of the 6
which happen to correlate with exposure to US and retaliatory tariffs. We attempt to address this concern by running a placebo test on the pre-trade war period. To do this, we keep only the 2017 data and lag the 2018 tariff exposures by one year to see whether job postings respond to these changes in 2017 when there were in fact no tariff changes. If the baseline results capture medium-term trends that are not related to tariff exposure then we would expect to see similar results in this placebo test. Insignificant results would support the claim that it is in fact the tariff changes that matter.<sup>20</sup> Table 9 in the Appendix presents the results of this placebo test. The resulting coefficients are not significant across all specifications, suggesting that this impact was not observed prior to the start of the trade war.

# **6.2 Alternative tariff exposure measures**

The particular form of the exposure measures used in this paper follows examples such as Blanchard et al. (2019) and Autor et al. (2013), but there are a range of ways in which tariff exposure can be calculated. We additionally consider five other formulations to check robustness, and the results are presented in Table 10 in the Appendix along with full definitions of the measures. Column (1) repeats the main measure used in the paper, while column (2) adjusts this measure applying the weighting to _ln_ (1 + tariff rate _pc,t_ ) rather than directly to the US or retaliatory tariff rates. Column (3) takes a similar approach but applies the log transformation to the measure after the trade and employment weighting is already applied. Column (4) weights only by import shares rather than incorporating sectoral labour.

Columns (5) and (6) weight by sectoral output rather than employment. For example, the sectoral output tariff exposure (later weighted by CZ employment shares) for the specification in column (5) is constructed as follows: where _c_ is the county of
rate in agriculture and manufacturing, relative to services. Other factors that impact calibrated labor productivity include an exogenous improvement in energy efficiency, agricultural yields, and international trade and transport margins.

The baseline also incorporates the following list of exogenous assumptions:

- Bilateral tariff rates are modified over time according to a schedule of tariff rates prepared by the ITC (2015). This schedule is based on existing trade agreements. More details are available from the authors.

- The income parameter of the CDE is adjusted between periods based on an estimated economic relation between the income parameter and aggregate per capita consumption. The parametrization of the relationship is based on a least-squares estimate using the base year GTAP database. One key purpose is to reduce the share of food expenditures as incomes rise.

- Capital accumulation is based on the standard capital motion equation: _Kt_ =(1- δ ) _K_ t-1+ _It_ -1, thus the capital stock trends depend on investment/savings decisions. In the baseline, household savings are adjusted in order to target future trends in the investment to GDP ratio—with the basic idea that these trends should more or less line up with steady state

> 28  http://www.un.org/en/development/desa/publications/world-population-prospects-2015-revision.html

> 29 _Global Economic Prospects, January 2018: Broad-Based Upturn, but for How Long?_ Advance edition. Washington, DC: World Bank. License: Creative Commons Attribution CC BY 3.0 IGO (https://openknowledge.worldbank.org/bitstream/handle/10986/28932/9781464811630.pdf).

> 30  A Special Issue of _Global Environmental Change_ provides significant background material on the SSPs and their development. See in particular Dellink et al. 2017 for a discussion of the OECD-based macroeconomic drivers.

> 31  In other words, we overlay SSP2’s population projection with the UN’s, but assume the same growth rate of GDP in per capita terms.

- 64 -
|**Gender [female=1]**|0.20|0.27|0.23|0.18|
||[0.40]|[0.44]|[0.42]|[0.38]|
|**Manager**|0.25|0.12|0.32|0.26|
||[0.44]|[0.33]|[0.47]|[0.44]|

**Notes:** Standard deviations are in parentheses.  The unit of observation for the first panel is the civil servant and for the second panel the organization.  Only employees and managers responded to the information module and hence only these individuals are used for the statistics in the first panel.  These statistics are based on the survey sample and not on administrative data.  The span of control is taken from the survey question "How many personnel do you manage?"; the average is taken for an organization if there is more than one manager; and the organization-level statistics are reported (each organization has an equal weight in the `By Organization' statistics).  `Manager' refers to managers within the organization.  Grade is the official civil service grade of the professional civil servant, ranging from 1 to 17 in the sample. The 2013-14 National Civil Service Human Resource Statistics Abstract (Ministry of Civil Service) records the overall female employee percentage to be 35%; this statistic includes frontline staff.  Figures are rounded to two decimal places.
of picture text --> Source: Estimates based on Staudinger et al. 2016. Refers to 2013 data.

**The pattern of participation over the life cycle is similar across country income levels, despite very**

**different levels of participation** . Figure 3 presents three cases as an illustration: low-income Liberia, middle-income Morocco, and the high-income Republic of Korea. Across these very different countries, labor force participation falls after age 55, for both women and men. In Morocco, where female labor force participation is very low, the pattern for male participation is nonetheless similar to that of both richer and poorer countries, and even among women, there is an inverse u-shape

> 16 A complete assessment of labor market conditions for mature workers is outside of the scope of this paper. However, several World Bank country-level or regional studies provide more comprehensive overviews of labor market conditions for older workers including sector and occupations analysis, for example for Thailand (World Bank 2021b), Vietnam (World Bank 2021a), East Asia and the Pacific (World Bank 2016), Malaysia (World Bank 2020), and the Russian Federation (Levin 2015).

> 17 World Bank 2021b.

7
**<u>Figure 2.6:  Rural Income Composition in Mexico, Selected Years 1992-2002</u>**

<!-- Start of picture text --> 100<br>80<br>60<br>40<br>20<br>0<br>1992 1994 1996 1998 2000 2002<br>Year<br>farm_inc farm_lb self_consumption off_farm_labor Remmitances<br>private Public_transfer leasing oth_nomonetary nonfarm_enterprise<br>Percent<br><!-- End of picture text --> Source: Calculations based on the ENIGH surveys.

**Table 2.4:  Agricultural Income Shares by Source and Region, Rural Mexico 1992 and 2002**

||||**19**<br>|**92**<br>||||||**2002**<br>||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
||Cultiva<br>-tion|Farm<br>enter-<br>prise|Self –<br>consump<br>-tion|Agricul-<br>tural<br>labor|Farm<br>labor|**Total**<br>**Agricul**<br>**ture**|Cultiva<br>tion|Farm<br>Enter<br>prise|Self –<br>consump<br>tion|Agricul-<br>tural<br>Labor|Farm<br>Labor|**Total**<br>**Agricul**<br>**ture**|**Change**<br>**1991-2002**<br>
Areas of Pakistan. World Bank: Washington, D.C.

- Söderbacka, T., l. Nyholm, and L. Fagerström. Workplace interventions that support older employees’ health and work ability - a scoping review. BMC Health Serv Res 20 (472).

- Staubli, S. and J. Zweimüller. 2013. Does raising the early retirement age increase employment of older workers? Journal of Public Economics, 108(C): 17-32.

- Staudinger, U.M., R. Finkelstein, E. Calvo, and K. Sivaramakrishnan. 2016. A Global View on the Effects of Work on Health in Later Life. Gerontologist, 56(S2): 281–292

- Thanapop, S. and C. Thanapop. 2021. Work ability of Thai older Workers in Southern Thailand: a comparison of formal and informal sectors. BMC Public Health 21: 1218.  (2021).

- Thomas, Michael S.C.; Knowland, Victoria C.P.; Rogers, Cathy. 2020. The Science of Adult Literacy. Social Protection and Jobs Discussion Paper Series, no.  2001. World Bank: Washington, D.C.

- UNESCO. 2022. Global Review of Training Funds: Spotlight on levy-schemes in 75 countries. United Nations Educational, Scientific and Cultural Organization: Paris.

- UNFPA. 2012. Ageing in the Twenty-First Century: A Celebration and A Challenge. United Nations Population Fund Sexual & Reproductive Health Agency: New York:

- UN. 2007. World Economic and Social Survey 2007: Development in an Ageing World. Department of Social Affairs. United Nations: New York.

- UN. 2019. World Population Aging 2019: Highlights. United Nations: New York.

38
- LeCompte, M. D. and J. P. Goetz (1982). Problems of reliability and validity in ethnographic research. _Review of educational research 52_ (1), 31–60.

- Manski, C. F. (1990). Nonparametric Bounds on Treatment Effects. _American Economic Review 80_ (2), 319–323.

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lx
Policy Research Working Paper 9924

# **Abstract**

After increasing for years and reaching high levels, Brazil’s subjective well-being deteriorated following the economic contraction in 2015. Using data from the Gallup World Poll for the 2010s, this paper identifies the factors that underpin Brazil’s subjective well-being and its change, paying special attention to heterogeneity across population groups. Having sufficient income, financial security, economic optimism, satisfaction with living standards and health services, social capital, tertiary education, and digital access are the main factors associated with subjective well-being. These factors matter to different extents along the income distribution and across generations and space. The decline in subjective well-being since 2015 was heterogeneous and more pronounced among men, rural residents, and the old. Economic expectations increased in importance as they assumed a greater role in people’s preferences, especially those of men, and more people grew pessimistic about the economic outlook. The decline in subjective well-being and the switch in voter support from one end of the political spectrum to the other in the 2018 general elections were both associated with the grievances triggered by the economic and leadership crisis of the mid2010s. These grievances signal an erosion in the support for the social contract in place since the 1990s and the need to renew it.

This paper is a product of the Office of the Chief Economist, Latin America and the Caribbean Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at mburger@ese.eur.nl or eianchovichina@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry
to COVID should also have timelines for their removal as precrisis economic activity levels are restored (OECD 2021b; World Bank 2021c).

Government support packages have also encouraged continued credit extension to corporates. During the 2020 global recession, about 40 percent of the fiscal support from governments in EMDEs constituted liquidity support measures such as loans, equity injections, and guarantees (IMF 2020b).<sup>4</sup> Some governments have also encouraged banks to make use of available capital and liquidity buffers to support lending (Feyen et al. 2020a; IMF 2020a, 2020c). While these were necessary to avoid widespread bankruptcies, they may support nonviable “zombie” firms if maintained far into the recovery. In addition, these contingent liabilities could eventually migrate onto government balance sheets, either in a financial crisis or, indirectly, in a period of sustained low growth (Mbaye, Moreno-Badia, and Chae 2018).

# IV.2.2. Monetary and financial policies

Central bank credibility. In 2020, several EMDE central banks expanded their remit by starting asset purchase programs to stabilize financial markets (Arslan, Drehmann, and Hofmann 2020; IMF 2020d). These have helped ease borrowing conditions in financial market segments that would otherwise only be indirectly affected by monetary policy rate cuts. While appropriate in the midst of a deep recession, the prolonged use of these tools could dampen investor confidence and risk de-anchoring inflation expectations if central bank credibility is undermined by extended funding of large fiscal deficits (Ha and Kindberg-Hanlon 2021).

In some countries, central banks have also supported small and medium-size enterprises directly via back-stops for bank lending, such as by purchasing corporate securities (Borio 2020). This has

> 4 Despite the size of these packages there are concerns about their effectiveness: in a survey of firms in 51 countries (between May and August 2020) only around one-fifth of firms reported that they had received any type of policy support (World Bank 2021e).

7
Unadjusted and adjusted changes in risk associated with underlying pre-natal and postnatal risk factors for infant and early childhood stunting (6-23 months of age) <!-- Start of picture text --> Unadjusted Adjusted<br>pre-natal conditions (maternal nutrition, birth outcomes) ae oe<br>Adequate home care & feeding practices _—- —_—<br>Adequate HH food security. & diversity. . ——0.69 +0.74<br>Adequate post-natal maternal & child health care —+— —+—<br>Adequate HH water, sanitation infrastructure & environment oe J<br>Female —_0.66 —0.65<br>Single birth} —?s*—— +1<br>Urban a<br>Total HH size (N) +<br>Total children under five in HH (N) 3.<br>Total HH income per month (1 = 1000 PHP) (log) ——<br>In poorest quintile of total HH income per capita °<br>Mother has high school or tertiary education —_———<br>Mother is married —_——<br>Mom wasa teenager at time of birth o<br>Mother has a job or business a<br>0.4 0.6 0.8 1.0 1.2 04 06 08 1.0 1.2<br>Relative Risk (95% Cl)<br><!-- End of picture text --> <!-- Start of picture text --> Adequate pre-natal conditions (maternal nutrition, birth outcomes)<br><!-- End of picture text --> Source: Author's calculations based on 2015 National Nutrition Survey (NNS). Notes: Only the relative risk estimates for statistically significant predictors are labeled.
the Gini coefficient are used to capture the distributional impacts. We model the following fiscal instruments: Personal income tax (PIT), benefits from NAF, the bread subsidy compensation scheme and other cash transfers, sales taxes (GST and SST), water and electricity subsidies, and health and education in-kind benefits. The allocation of the fiscal instruments to households is done primarily based on the reported information in the household survey, making some adjustments to reconcile administrative figures when necessary. This means that the analysis already incorporates inclusion and exclusion errors in the allocation of different interventions.

> 17 A house owned by the household can be rented out or resided in. To compare across households making different decisions, the foregone rent for those who live in houses they own is estimated and added to household income.

> 18 Where income from pensions is added to factor income and contributions to old-age contributory pensions are subtracted from factor income.

> 19 Pension status is not recorded in HEIS. Instead, we use the self-reported income and expenditure information in HEIS to determine the amount of pension income received, and the contributions made to the pension system. We show the results from this sensitivity assessment in Appendix 2.