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on Insurance Economics |
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Issue of 2020‒02‒17
eleven papers chosen by Soumitra K. Mallick Indian Institute of Social Welfare and Business Management |
| By: | Rajashri Chakrabarti; Maxim L. Pinkovskiy |
| Abstract: | Getting health insurance in America is intimately connected to choosing whether and where to work. Therefore, it should not be surprising that the U.S. health insurance market may influence, and be influenced by, the market for higher education—which itself is closely tied to the labor market. In this post, and the staff report it is based on, we investigate the effects of the largest overhaul of health insurance in the United States in recent decades—the Patient Protection and Affordable Care Act of 2010 (ACA) -- on college enrollment choices. |
| Keywords: | Affordable Care Act; For-Profit Colleges |
| JEL: | Q12 |
| Date: | 2020–02–05 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fednls:87436&r=all |
| By: | Jing Guana; J.D. Tena |
| Abstract: | This study investigates the causal impact of acquiring social medical Insurance on hospital utilization and health status for children under 16 years old in China from 2010 to 2016. We consider the China Family Panel Studies (CFPS), a longitudinal database which allows us to control for the effect of unobserved individual heterogeneity by means of difference-in-difference regressions combined with matching regression techniques. Our findings suggest that participating in social medical insurance schemes significantly increases children’s yearly hospital use, especially for low income and rural children. Moreover, this increase is not significantly different for people who were not previously sick. It is also found that social medical insurance schemes have no effect or even a marginally negative effect on children’s health status in some cases. We discuss some potential explanations for this result. |
| Keywords: | China; Social Medical Insurance; Health Outcomes; Difference-in-difference; Propensity Score Matching |
| JEL: | I13 |
| Date: | 2018–11 |
| URL: | http://d.repec.org/n?u=RePEc:liv:livedp:20188&r=all |
| By: | Simplice A. Asongu (Yaoundé/Cameroon); Nicholas M. Odhiambo (Pretoria, South Africa) |
| Abstract: | In this study, we examine how insurance affects income inequality in sub-Saharan Africa, using data from 42 countries during the period 2004-2014. Three inequality variables are used, namely: the Gini coefficient, the Atkinson index and the Palma ratio. Two insurance premiums are employed, namely: life insurance and non-life insurance. The empirical evidence is based on the Generalized Method of Moments (GMM). Life insurance increases the Gini coefficient and increasing life insurance has a net positive effect on the Gini coefficient and the Atkinson index. Non-life insurance reduces the Gini coefficient and increasing non-life insurance has a net positive effect on the Palma ratio. The analysis is extended to establish policy thresholds at which increasing insurance premiums completely dampen the net positive effects. From the extended analysis, 7.500 of life insurance premiums (% of GDP) is the critical mass required for life insurance to negatively affect inequality, while 0.855 of non-life insurance premiums (% of GDP) is the threshold required for non-life insurance to negatively affect inequality. Policy thresholds are provided at which insurance penetration decreases income inequality in sub-Saharan Africa. |
| Keywords: | Insurance; Inclusive development; Africa; Sustainable Development |
| JEL: | I28 I30 I32 O40 O55 |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:exs:wpaper:20/005&r=all |
| By: | Simplice A. Asongu (Yaoundé/Cameroon); Nicholas M. Odhiambo (Pretoria, South Africa) |
| Abstract: | In this study, we examine how insurance affects income inequality in sub-Saharan Africa, using data from 42 countries during the period 2004-2014. Three inequality variables are used, namely: the Gini coefficient, the Atkinson index and the Palma ratio. Two insurance premiums are employed, namely: life insurance and non-life insurance. The empirical evidence is based on the Generalized Method of Moments (GMM). Life insurance increases the Gini coefficient and increasing life insurance has a net positive effect on the Gini coefficient and the Atkinson index. Non-life insurance reduces the Gini coefficient and increasing non-life insurance has a net positive effect on the Palma ratio. The analysis is extended to establish policy thresholds at which increasing insurance premiums completely dampen the net positive effects. From the extended analysis, 7.500 of life insurance premiums (% of GDP) is the critical mass required for life insurance to negatively affect inequality, while 0.855 of non-life insurance premiums (% of GDP) is the threshold required for non-life insurance to negatively affect inequality. Policy thresholds are provided at which insurance penetration decreases income inequality in sub-Saharan Africa. |
| Keywords: | Insurance; Inclusive development; Africa; Sustainable Development |
| JEL: | I28 I30 I32 O40 O55 |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:agd:wpaper:20/005&r=all |
| By: | Simon Jager; Benjamin Schoefer; Josef Zweimuller |
| Abstract: | This paper examines the labor market effects of unemployment insurance extensions. It uses administrative Social Security matched employer-employee data from Austria. Critical components of the analysis are effects on wages as well as retirement/job separation effects. |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:crr:crrwps:wp2020-3&r=all |
| By: | Mohammad Abu-Zaineh (Aix-Marseille Univ., CNRS, EHESS, Centrale Marseille, AMSE); Olivier Chanel (Aix-Marseille Univ., CNRS, EHESS, Centrale Marseille, AMSE); Khaled Makhloufi (Faculty of Medicine, Aix-Marseille Univ, INSERM, IRD, UMR 912 (SESSTIM)) |
| Abstract: | In their attempts to implement universal health coverage (UHC), different developing countries encounter different types of obstacles. In Tunisia, major challenges include a widespread informal sector and protestors’ general discontent with rising economic insecurity and inequality, the rollback of the state and public welfare. We apply a contingent valuation survey to a non-healthcare-covered Tunisian sample vis-à-vis joining and paying for a health insurance scheme. We pay attention to the nature of the willingness- to-pay (WTP) values obtained, distinguishing genuine null from protest values. The latter may reflect not only protesters’ beliefs regarding the survey, but also their lack of trust in government’s commitment to ensuring the provision of quality healthcare. We use alternative econometric modeling strategies to account and correct for selection issues arising from protest answers. Our results support the presence of self- selection and, by predicting protesters’ WTP, allow the “true” sample mean WTP to be computed. This appears to be about 14% higher than the elicited mean WTP. The WTP of the poorest non-covered respondents represents about one and a half times the current contributions of the poorest formal sector enrollees, suggesting that voluntary affiliation to the formal health insurance scheme could be a step towards achieving UHC. Overall, we highlight the importance of taking into account protest positions for the evaluation of progress towards UHC. |
| URL: | http://d.repec.org/n?u=RePEc:aim:wpaimx:1854&r=all |
| By: | Erin Weir Lakhmani; James Verdier |
| Abstract: | This technical assistance brief describes four options that states can use, individually or concurrently, to provide information to D-SNPs on their dually eligible members’ Medicaid plan enrollment and/or service use. |
| Keywords: | dually eligible beneficiaries, Medicaid, enrollment, service use, D-SNPs |
| URL: | http://d.repec.org/n?u=RePEc:mpr:mprres:c11b11c807eb41aaa7ba7c83f855ba0b&r=all |
| By: | Simplice A. Asongu (Yaoundé/Cameroon); Nicholas M. Odhiambo (Pretoria, South Africa) |
| Abstract: | This study investigates the role of insurance in economic growth on a panel of forty-eight countries in Africa for the period 2004-2014. The research question the study seeks to answer is the following: what thresholds of insurance penetration positively affect economic growth in Africa? The empirical evidence is based on Generalized Method of Moments. Life insurance increases economic growth while the effect of non-life insurance is not significant. Increasing both life insurance and non-life insurance has negative net effects on economic growth. From an extended analytical exercise, 4.149 of life insurance premium (% of GDP) is the minimum critical mass required for life insurance to positively affect economic prosperity while 1.805 of non-life insurance premium (% of GDP) is the minimum threshold required for non-life insurance to positively affect economic prosperity. Thresholds are also provided from the Hansen (1999) Panel Threshold Regression technique using a balanced sample of 28 countries. |
| Keywords: | Insurance; Economic Growth |
| JEL: | I28 I30 G20 O16 O55 |
| Date: | 2019–01 |
| URL: | http://d.repec.org/n?u=RePEc:abh:wpaper:19/037&r=all |
| By: | Nir Jaimovich; Itay Saporta-Eksten; Henry Siu; Yaniv Yedid-Levi |
| Abstract: | The U.S. economy has experienced a significant drop in the fraction of the population employed in middle wage, “routine task-intensive” occupations. Applying machine learning techniques, we identify characteristics of those who used to be employed in such occupations and show they are now less likely to work in routine occupations. Instead, they are either non-participants in the labor force or working at occupations that tend to occupy the bottom of the wage distribution. We then develop a quantitative, heterogeneous agent, general equilibrium model of labor force participation, occupational choice, and capital investment. This allows us to quantify the role of advancement in automation technology in accounting for these labor market changes. We then use this framework as a laboratory to evaluate various public policies aimed at addressing the disappearance of routine employment and its consequent impacts on inequality. |
| Keywords: | Polarization, automation, routine employment, labor force participation, universal basic income, unemployment insurance, retraining |
| JEL: | E00 E23 E25 E60 J01 J2 |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:zur:econwp:340&r=all |
| By: | Jaimovich, Nir (University of Zurich); Saporta-Eksten, Itay (Tel Aviv University); Siu, Henry E. (University of British Columbia); Yedid-Levi, Yaniv (Interdisciplinary Center (IDC) Herzliya) |
| Abstract: | The U.S. economy has experienced a significant drop in the fraction of the population employed in middle wage, "routine task-intensive" occupations. Applying machine learning techniques, we identify characteristics of those who used to be employed in such occupations and show they are now less likely to work in routine occupations. Instead, they are either non-participants in the labor force or working at occupations that tend to occupy the bottom of the wage distribution. We then develop a quantitative, heterogeneous agent, general equilibrium model of labor force participation, occupational choice, and capital investment. This allows us to quantify the role of advancement in automation technology in accounting for these labor market changes. We then use this framework as a laboratory to evaluate various public policies aimed at addressing the disappearance of routine employment and its consequent impacts on inequality. |
| Keywords: | polarization, automation, routine employment, labor force participation, universal basic income, unemployment insurance, retraining |
| JEL: | E22 E24 J23 J24 |
| Date: | 2020–01 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp12913&r=all |
| By: | Alexander M. Gelber (Wharton School, University of Pennsylvania; National Bureau of Economic Research); Damon Jones (University of Chicago - Harris School of Public Policy); Daniel W. Sacks (Indiana University - Kelley School of Business - Department of Business Economics & Public Policy); Jae Song (U.S. Social Security Administration) |
| Abstract: | We investigate the impact of the Social Security Annual Earnings Test (AET) on the employment decisions of older Americans. The AET reduces Social Security benefits by one dollar for every two dollars earned above the exempt amount. Using a differences-in-differences design, we find that the employment rate of those predicted to become subject to the AET decreases substantially relative to those not predicted to become subject to it. The point estimates suggest that the AET reduces the employment rate of Americans aged 63-64 by at least 1.2 percentage points. |
| JEL: | H55 J22 J26 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:bfi:wpaper:2020-05&r=all |