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on Health Economics |
| By: | Courtemanche, Charles (Georgia State University); Soneji, Samir (Geisel School of Medicine at Dartmouth College); Tchernis, Rusty (Georgia State University) |
| Abstract: | We propose a Bayesian factor analysis model to rank the health of localities. Mortality and morbidity variables empirically contribute to the resulting rank, and population and spatial correlation are incorporated into a measure of uncertainty. We use county-level data from Texas and Wisconsin to compare our approach to conventional rankings that assign deterministic factor weights and ignore uncertainty. Greater discrepancies in rankings emerge for Texas than Wisconsin since the differences between the empirically-derived and deterministic weights are more substantial. Uncertainty is evident in both states but becomes especially large in Texas after incorporating noise from imputing its considerable missing data. |
| Keywords: | county, rank, health, factor analysis, Bayesian |
| JEL: | I14 C11 |
| Date: | 2013–09 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp7631&r=hea |
| By: | Dimitrios Varvarigos |
| Abstract: | I model an economy where the adverse health effects of pollution impede labour productivity and capital accumulation is the source of economic growth. Pollution is generated by firms that choose whether to employ a dirty technology and pay an environmental tax, or employ a clean technology and incur the cost of its adoption. The task of inspecting the environmental impact of each firm’s production technology is delegated to bureaucrats who are corruptible since they receive bribes in order to mislead authorities on the firms’ actual technology choice. The model can generate multiple steady state equilibria. In this context, the multiplicity of equilibria is associated with indeterminacy, due to the self-fulfilling nature of corruption incentives and the relevant implications for pollution, productivity and economic growth. |
| Keywords: | Corruption; Economic Growth; Health; Pollution; Productivity |
| JEL: | D73 O44 Q58 |
| Date: | 2013–09 |
| URL: | http://d.repec.org/n?u=RePEc:lec:leecon:13/22&r=hea |
| By: | Gilbert Gimm; Denise Hoffman; Henry T. Ireys |
| Keywords: | Disability, Employment, Mental Health, Early Intervention; Random Assignment |
| JEL: | I J |
| Date: | 2013–08–30 |
| URL: | http://d.repec.org/n?u=RePEc:mpr:mprres:7895&r=hea |
| By: | Ellen Bouchery |
| Keywords: | Dentistry, Dental Care, Medicaid, Pediatrics |
| JEL: | I |
| Date: | 2013–09–30 |
| URL: | http://d.repec.org/n?u=RePEc:mpr:mprres:7898&r=hea |
| By: | OECD |
| Abstract: | The economic and social impact of chronic brain disorders (CBD) such as Alzheimer’s disease (AD) and other neurodegenerative diseases will become the number one public-health problem worldwide, directly affecting 100 million people by 2050. On-going demographic trends, namely ageing populations worldwide, are leading to the unprecedented expansion of consumer demand for healthcare services. Healthcare systems worldwide soon will confront a serious crisis as a result of significant growth of the healthcare market, in a climate of shrinking resources. |
| Date: | 2013–06–14 |
| URL: | http://d.repec.org/n?u=RePEc:oec:stiaac:6-en&r=hea |
| By: | Ravesteijn, Bastian; van Kippersluis, Hans; van Doorslaer, Eddy |
| Abstract: | While it seems evident that occupations affect health, effect estimates are scarce. We use a job characteristics matrix in order to characterize occupations by their physical and psychosocial burden in German panel data spanning 26 years. Employing a dynamic model to control for factors that simultaneously affect health and selection into occupation, we find that manual work and low job control both have a substantial negative effect on health that increases with age. The effects of late career exposure to high physical demands and low control at work are comparable to health deterioration due to aging by 16 and 23 months respectively. |
| Keywords: | Health, labor, dynamic panel data |
| JEL: | C23 I0 J0 |
| Date: | 2013–09–18 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:50321&r=hea |
| By: | Martin Fischer; Martin Karlsson; Therese Nilsson |
| Abstract: | Theoretically, there are several reasons to expect education to have a positive effect on health, and empirical research suggests that education can be an important health determinant. However, it has not yet been established whether education and health are indeed causally-related, and the effects found in previous studies may be partially attributable to methodological weaknesses. Moreover, existing evidence on the education-health relationship using information of schooling reforms for identication generally uses information from fairly recent reforms implying that health outcomes are observed only over a limited time period. This paper examines the effect of education on mortality using information on a national roll-out of a reform leading to one extra year of compulsory schooling in Sweden. In 1936, the national government made a seventh school year compulsory; however, the implementation was decided at the school district level, and the reform was implemented over a period of 12 years. Taking advantage of the variation in the timing of the implementation across school districts by using county-level proportions of reformed districts, census data and administrative mortality data, we find that the extra compulsory school year reduced mortality. In fact, the mortality reduction is discernible already before the age of 30 and then grows in magnitude until the age of 55–60. |
| Keywords: | Returns to schooling; education reform; mortality |
| JEL: | I12 I14 I18 I21 |
| Date: | 2013–09 |
| URL: | http://d.repec.org/n?u=RePEc:rwi:repape:0441&r=hea |
| By: | David Madden (University College Dublin) |
| Abstract: | This paper measures the degree of inequality of opportunity in birthweight and birthlength for a sample of Irish infants. The sample is partitioned into eight types by mothers’ education and mothers’ smoking status. Stochastic dominance tests reveal the presence of inequality of opportunity but its fraction of total inequality is comparatively small at 1-2%, with the remainder of inequality assigned to random, unobserved factors. These results are robust to finer partitioning of the population and to re-definition of types’ opportunity sets which gives greater weight to inequality at the lower end of the distribution. Analysis of the incidence of low birthweight and short birthlength using measures from the poverty and segregation literature also reveal that incidence is not uniform across type and is consistent with the presence of inequality of opportunity. |
| Keywords: | Inequality of opportunity, decomposition, poverty, child health |
| JEL: | I14 I24 J13 |
| Date: | 2013–09–27 |
| URL: | http://d.repec.org/n?u=RePEc:ucn:wpaper:201313&r=hea |