Socioeconomic Determinants of Mortality in Taiwan: Combining Individual Data and Aggregate Data

There is a very large literature that examines the relationship between health and income. Two main hypotheses have been investigated: the relative income hypothesis and the absolute income hypothesis. Most of previous studies that used mortality data have been criticized for estimating an aggregate model that does not account for non-linear links between health and income at the individual level. In this paper we follow a novel approach to avoid this bias, combining aggregate mortality data with individual level data on socio-economic characteristics. We test the relative and absolute income hypotheses using county level mortality data from Life Statistic of Department of Health and individual level data from Taiwan census FIES for 1976-2003. We find that there is no strong evidence supporting either hypothesis in the case of the general population. In contrast, we find strong evidence that education does have significant effects on individuals’ health and the estimates are not sensitive to income equivalent scales.mortality, relative income hypothesis, aggregation bias

The health income hypotheses test in Taiwan

The motivation for this thesis is the investigation of the socioeconomic determinants of health in Taiwan. When considering the variations in socioeconomic status, income is an indicator much discussed in the literature because it is a complex issue and yet easily measured. Many different economists investigate income issue from the perspective of their own particular expertise. For health economists, the influence of income on health outcome is primary. Therefore, many health income hypotheses have been advanced and the debate is ongoing. Among these hypotheses, the absolute income hypothesis, the relative income hypothesis, and the income inequality hypothesis are discussed primarily. The argument of these hypotheses is straightforward. The debates of these different hypotheses are based on two main dimensions, economic development and data. The advocates of the absolute income hypothesis claim that absolute income affects health significantly. The advocates of the relative income hypothesis or the income inequality hypothesis, however, argue that the absolute income hypothesis holds principally before a society moves to an affluent stage. After economic transition, the relative income or income inequality hypothesis becomes more influential. Wilkinson and Pickett (2006) summarize the conclusions of 169 papers relevant to the relative income hypothesis and income inequality hypothesis and find a phenomenon that the studies using large area data are more likely supportive than those using small area data. They argue that income inequality in large area is a good measure of the scale of social stratification or the degree of social hierarchy rather than in a small area. Another argument to explain this phenomenon is aggregate bias proposed by Gravelle et al. (2002). The thesis tries to find the answers for the following questions. What income hypotheses hold for Taiwanese society? Do these hypotheses coexist or are they mutually exclusive? Is aggregate bias a negligible issue in Taiwan when aggregate data are used to infer individuals’ health income relationship? Chapter 3 combines aggregate data and individual data and creates a panel dataset to examine the absolute income hypothesis and the income inequality hypothesis. The motivation is to avoid aggregate bias. Chapter 4 employs nonparametric estimations to describe the relationship between health outcome and income and compares the results of parametric estimations and of nonparametric estimations. Chapter 5 utilizes the quasi-experimental methods to identify the absolute income effect on health outcome. The nonlinear relationship between a) self-assessed health, b) depression, c) life satisfaction and income is found in chapter 4. This finding implies that in the Taiwanese studies the aggregate bias needs to be considered when aggregate data are used to infer individual health income relationship and it is consistent with the motivation of the proposed approach of combining aggregate data and individual data in Chapter 3. The difference between parametric estimations and nonparametric estimations is not only shown in the figures but the model specification test also shows that the parametric linear, quadratic, and cubic forms in terms of income are a misspecification in the estimations of depression and life satisfaction. The absolute income hypothesis and the income inequality hypothesis are supportive in this thesis when long-run income and long-run Gini coefficient are the regressors under the assumption of health social gradient. This finding shows that health income hypotheses are not contradictory. Chapter 5 also provides evidence to support that long-term income has a significant effect on mental health. Thus, the absolute income hypothesis is also supported after taking causality into consideration

The impact of spousal bereavement on hospitalisations: evidence from the Scottish Longitudinal Study.

This paper estimates the impact of spousal bereavement on hospital inpatient use for the surviving bereaved by following the experience of 94,272 married Scottish individuals from 1991 until 2009 using a difference-in-difference model. We also consider the sample selection issues related to differences in survival between the bereaved and non-bereaved using a simple Cox Proportional-Hazard model. Before conducting these estimations, propensity score approaches are used to re-weight the non-bereaved to generate a more random-like comparison sample for the bereaved. We find that those bereaved who survive are both more likely to be admitted and to stay longer in hospital than a comparable non-bereaved cohort. Bereavement is estimated to induce on average an extra 0.24 (95% CI [0.15, 0.33]) hospital inpatient days per year. Similar to previous studies, we estimate the bereaved have a 19.2% (95% CI [12.5%, 26.3%]) higher mortality rate than the comparable non-bereaved cohort

Socio-economic costs of bereavement in Scotland: main study report.

The Socio-Economic Costs of Bereavement in Scotland (SECOB) research study was funded by the Scottish Government Health Directorates in late 2010 as part of ongoing work to inform national policy on bereavement and bereavement care practice. The project aimed to: a) articulate the likely nature and scope of the impact of bereavement on social and economic aspects of life for Scottish citizens as evidenced in relevant literature; b) seek to estimate the socio-economic costs of bereavement in an emergent sub-set of key aspects, and c) develop methodological approaches that will enhance capacity for large-scale research into the socio-economic impact of bereavement

The economic cost of bereavement in Scotland.

Aspects of the socioeconomic costs of bereavement in Scotland were estimated using 3 sets of data. Spousal bereavement was associated with increased mortality and longer hospital stays, with additional annual cost of around {pound}20 million. Cost of bereavement coded consultations in primary care was estimated at around {pound}2.0 million annually. In addition, bereaved people were significantly less likely to be employed in the year of and 2 years after bereavement than non-bereaved matched controls, but there were no significant differences in income between bereaved people and matched controls before and after bereavement

The impact of spousal bereavement on self-assessed health status: evidence from the Taiwanese elderly population

経済学 / EconomicsBereavement is a grieved and inevitable event in our life. For an aging society, the incidence of spousal bereavement and parental bereavement is higher than the other kinds of bereavement events. This study employs the difference-in-differences (DiD) strategy and the Taiwanese panel Survey of Health and Living Status of the Elderly (SHLSE) to evaluate the impact of losing a spouse on well-being measured by self-assessed health status, depression, and life satisfaction.The results show that spousal bereavement causes substantial depression and loss in life satisfaction. The spousal bereavement impact increases depression by 1.46 CES-D points and reduces life satisfaction by 0.71 points. The decay effect of time is not observed in this study. We also examine the demographic differences of the spousal bereavement impact and find that the gap in life satisfaction between the bereaved who received more than 9 years education and the bereaved who received 9 years or less is 1.43 points, which implies that spousal bereavement causes less impact on more educated people in terms of life satisfaction. The increase in depression for the bereaved in a larger household is smaller than that for those in a small household by 2.75 CES-D points but it is weakly significant.The self-reported health outcomes are the intermediate outcomes between spousal bereavement and societal costs such as healthcare utilisation and death. The association between self-reported health status and mortality and health utilization has been well documented by literature. Thus, our results also provide the policy insight that giving proper interventions on the onset of bereavement may cause less societal costs afterwards.http://www.grips.ac.jp/list/jp/facultyinfo/leon_gonzalez_roberto