Assessing equitable health financing for universal health coverage: a case study of South Africa

This article argues that an assessment of progressivity over time can provide an indication of progress towards a ‘more’ progressive or a ‘less’ regressive health financing system and can be useful to policymakers. It introduces a framework to characterize ‘shifts’ in progressivity in health financing between two time periods using the popularly known Kakwani index of progressivity and other associated indices. It also decomposes the ‘shifts’ in progressivity into the relative contributions of the changes in income distribution and the changes in the distribution of health payments. Further, it proposes graphics that statistically analyses how the ‘shifts’ in progressivity vary along the distribution of income. A pro-poor (pro-rich) shift implies that the health financing mechanism is becoming more (less) progressive or less (more) regressive between two time periods. A proportional shift means that progressivity is constant between the two periods. This framework is applied to nationally representative household data from South Africa. It emerged that such characterization is a very useful tool for policy in assessing progress towards equitable health financing.     

Convergence in per capita health expenditures and health outcomes in the OECD countries

Our analysis of 19 Organization for Economic Co-operation and Development (OECD) countries over the period 1972 to 2006 provides evidence of convergence in per capita health care expenditures for 17 countries, while the US and (to a lesser degree) Norway follow a different path. A simple decomposition of per capita health expenditures reveals that the divergence of the US comes from the divergence of the ‘ratio of health care expenditures to Gross Domestic Product (GDP)’ component, while Norway's divergence is mainly caused by the ‘labour productivity’ component. Interestingly, our results suggest that convergence in per capita health expenditures among the 17 OECD countries does not lead to convergence in health outcomes. Finally, we extend our analysis to examine convergence in various determinants of health expenditures.     

Aggregation bias-correcting approach to the health–income relationship: Life expectancy and GDP per capita in 148 countries, 1970–2010

A large amount of data consisting of 148 countries for the years 1970 to 2010 is analysed in the context of the health–income relationship. The literature suggests that the biased income–health effect obtained with macro data can be a result of the aggregation of individual concave income functions on average health. This aggregation problem is analysed in detail, and a bias-correcting method is proposed to overcome it. The results with new model alternatives show that they correct the income effects on average health in the right direction; that is, they produce smaller parameter estimates than biased models. Augmenting the results with the quantile regression approach, which is sensitive to health differences between countries, indicates that the poorest countries’ income gradient is still much larger than that of rich countries. However, the median life expectancy effect of the log of GDP per capita across the countries decreased during the sample decennials. The results for income inequality measured with the Gini coefficient indicate that the effects of inequality on health are still significant in the poorest countries but non-significant among rich countries after the year 2000. We argue that the proposed bias-correcting method retains the interest in macro health modelling and offers new model alternatives in other contexts.     

How do income and education affect health inequality: evidence from four developing countries

Using household survey data from four countries ? Albania, Nepal, Tajikistan and Tanzania ? this article calculates income-related inequality in health care utilization. We measure health disparity separately for generally and chronically ill individuals by constructing two models: one for the probability of a visit to a physician and another for the number of visits. Following model-based measurements, we decompose inequality into two major parts: one accounted for by identity-related factors and another by socioeconomic and other factors such as education, geography and distance to a clinic. We propose a new method to quantify the effect of changes in income and education on health disparity. One of our important findings suggests that health disparity is pro-rich in all our sample countries. The pro-rich disparity is prevalent among generally ill as well as chronically ill patients, in both visit probability and visit frequency models. Health inequality seems primarily driven by income differences followed by nonidentity factors. Further, the principle of equal treatment for equal need is not fulfilled in any of our countries. Among policy implications, increasing average income and education in a way that also reduces disparity in income and education, respectively, will substantially shrink inequality in health care utilization.     

SOME COMPARISONS OF THE CANADIAN-U.S. INCOME DISTRIBUTIONS

This paper compares the income distribution of Canada and the United States as well as other characteristics of the population such as the labour force and income trends in the two countries in the post-war years. In both countries family income distributions show similar degrees of inequality and similar movements in real incomes through time. However, an examination of Canadian data suggests that differences do exist in underlying patterns. For example, there are greater earnings differentials between skilled and unskilled workers in Canada than in the United States while on the other hand in the United States greater differences exist between family incomes with heads in different age groups than is the case in Canada.     

Why Do the Rich Save More? A Theory and Australian Evidence*

We provide a theory to explain the existence of inequality in an economy where agents have identical preferences and have access to the same production technology. Agents consume a ‘health’ good which determines their subjective discount factor. Depending on initial distribution of capital the economy gets separated into different permanent‐income groups. This leads to a testable hypothesis: ‘The rich save a larger proportion of their permanent‐income’. We test this implication for savings behaviour in Australia. We find that even after controlling for lifecycle and health characteristics, higher permanent income is positively related with higher savings rates and better saving habits.     

Robust determinants of health care expenditure growth

Our aim is to disclose robust explanatory variables for health care expenditure (HCE) growth by introducing to this field of research a method that is especially well suited for situations of ‘model uncertainty’: the Extreme Bounds Analysis (EBA). We analyse data for 33 OECD countries over the period 1970–2010 and include – as far as it is statistically feasible – all macroeconomic and institutional determinants of HCE growth in the EBA that have been suggested in the literature. Furthermore, we analyse to what extent outliers in the data influence the results. Our results confirm earlier findings that GDP growth and a variable representing Baumol’s ‘cost disease’ theory emerge as robust and statistically significant determinants of HCE growth. Depending on whether or not outliers are excluded, we find up to six additional robust drivers: the growth in expenditure on health administration, the change in the share of inpatient expenditure in total health expenditure, the (lagged) government share in GDP, the change in the insurance coverage ratio, the growth in land traffic fatalities and the growth in the population share undergoing renal dialysis.     

Infant mortality,relative income and public policy

Do health outcomes depend on relative income as well as on an individual's absolute level of income? We use infant mortality as a health status indicator and find a significant and positive link between infant mortality and income inequality using cross-national data for 93 countries. Holding constant the income of each of the three poorest quintiles of a country's population, we find that an increase in the income of the upper 20% of the income distribution is associated with higher, not the lower infant mortality. Our results are robust and not just caused by the concave relationship between income and health. The estimates imply a decrease in infant mortality by 1.5% for a one percentage point decrease in the income share of the richest quintile. The overall results are sensitive to public policy: public health care expenditure, educational outcomes, and access to basic sanitation and safe water can explain the inequality–health relationship. Thus, our findings support the hypothesis of public disinvestment in human capital in countries with high income inequality. However, we are not able to determine whether public policy is a confounder or mediator of the relationship between income distribution and health. Relative deprivation caused by the income distance between an individual and the individual's reference group is another possible explanation for a direct effect from income inequality to health.     

Two separated effects of employer-provided health insurance on job mobility

We estimate the effect of employer-provided health insurance (EPHI) on job mobility via a dynamic model of joint employment and health insurance decision in the presence of uncertainty about wage rate and health status transitions. The model is based on a Markov decision process in which a hedonic wage approach provides an economic rationale for the different choices and health insurance serves as an input to the health production process. Including health transitions in the model helps us to understand how the availability of EPHI (positive job characteristic) and holding EPHI (the wage-health insurance trade-off) enter into the individuals’ decisions. The model is estimated using the 1999–2000 Medical Expenditure Panel Survey panel 4, and the results show that the ‘pure’ effects of holding EPHI are negligible, the ‘full’ effects of EPHI are significant and the degrees of the inefficiency vary between 14% and 25% across different states.     

The Impact of Power Equality,Income, and the Environment on Human Health: Some Inter‐Country Comparisons

Economic studies on environmental degradation generally have a narrow focus on per capita income as an explanatory variable, and often fail to distinguish among the various types of environmental quality or damage. This paper addresses both problems by examining the effect of relative equality in the distribution of power on environmental outcomes, and making a clear distinction between health‐related environmental outcomes and so‐called ‘environmental amenities,’ only the latter of which should correlate strongly with income. This paper introduces a national index of power equality that is derived from related socioeconomic variables, and studies its effects on individual country achievement in addressing environmental quality and population health. This model is applied to a data set of 180 countries, as well as to subgroups of the entire country set. Employing disability‐adjusted life expectancy and the population child mortality rate as two health proxies, this paper finds that power equality in most cases positively influences population health, and that power equality is in every case no worse and in some cases better than per capita income at explaining population health.     

Income-related inequalities of health and health care utilization

By utilizing the China Health and Nutrition Survey (CHNS) data, this paper examines the extent of deviations in terms of horizontal equity in the field of China’s health and medical community, i.e., that those in equal demand ought to be treated equally, and computes the contribution of income in health inequality and utilization inequality of health care. The main conclusions are: There is pro-rich inequality in health and utilization of health care; income contribution to inequality of health care utilization accounts for 0.13–0.2; insurance also enlarges the inequality of health care utilization; health inequality in rural area is larger than that of in urban area; and both rural and urban health inequality are increasing. From 1991 to 2006, income changes in urban districts and rural area account for 7.08% and 13.38% respectively of raising inequality of rural and urban health.     

How Many Jobs Must We Provide for a Balanced Postwar Economy

This study investigates how unemployment and income influence the length of time an individual remains in good health. This is a complex relationship since unemployment or low income deteriorates health but poor health can become a barrier to obtaining higher income or gaining re-employment. Data are from the British Household Panel Survey, using two measures of physical health: an index of mobility problems and a measure of self-assessed health. The results show that unemployment, low income and poor education adversely affect the time that people remain in good health. These results have important implications for public policy, particularly in an age of austerity when social protection mechanisms are under threat. In fact, the results suggest that to improve health and reduce health inequality, more investment needs to be directed at policies that enhance labour force participation, improve education and reduce income inequality.     

LONG‐RUN INEQUALITY AND SHORT‐RUN INSTABILITY OF MEN'S AND WOMEN'S EARNINGS IN CANADA

This paper examines the variability of workers’ earnings in Canada over the period 1982–2006. We decompose the total variance of workers’ earnings into a ‘permanent’ component between workers and a ‘transitory’ earnings instability component over time for given workers. We then investigate the statistical relationships between these components and indicators for the business cycle. The most marked change in earnings variances in Canada since 1982 is the general rise in total earnings variance, which is essentially driven by a quite dramatic rise in long‐run earnings inequality. The patterns across age categories of the two variance components are almost opposite. Long‐run earnings inequality generally rises with age, but earnings instability is seen to generally decline with age, so that earnings instability is markedly highest among entry age workers. Unemployment rate effects are positive on almost all variance measures, while higher unemployment is associated with widened long‐run earnings differentials and greater short‐run earnings instability.     

Income, income inequality, and health: Evidence from China

This paper tests using survey data from China whether individual health is associated with income and community-level income inequality. Although poor health and high inequality are key features of many developing countries, most of the earlier literature has drawn on data from developed countries in studying the association between the two. We find that self-reported health status increases with per capita income, but at a decreasing rate. Controlling for per capita income, we find an inverted-U association between self-reported health status and income inequality, which suggests that high inequality in a community poses threats to health. We also find that high inequality increases the probability of health-compromising behavior such as smoking and alcohol consumption. Most of our findings are robust to different measures of health status and income inequality. Journal of Comparative Economics 34 (4) (2006) 668–693.     

Transition welfare gaps: One closed,another to follow?

Respondents from post‐communist countries have been found to systematically report lower levels of happiness and self‐rated health. While the first welfare gap in happiness has closed recently, the second transition gap in self‐perceived health only started to close. Specifically, this paper shows that treating all transition countries as a homogeneous group may be misleading and therefore divides 28 transition countries into three groups. As a result, in the most recent 2016 round of the ‘Life in Transition’ survey, transition countries in Southern Europe are no longer found to be different from non‐transition nations in terms of their self‐rated health. Although the gap in self‐perceived health for transition nations in Eastern Europe is present in a basic model, it becomes less statistically and economically significant when subjective beliefs and macro‐level variables are added. Countries from the former Soviet Union and Mongolia remain the only group in which respondents report 16.5%–29.1% lower probability of ‘Good’ or ‘Very Good’ health compared to other transition and non‐transition countries. Controlling for communist party membership, ideological beliefs and macro‐level variables somewhat reduces the gap for the former Soviet Union and Mongolia but it remains significant in multiple robustness checks. Although the gap in self‐rated health now applies to only one group of transition countries, it remains an important empirical puzzle with far‐reaching implications for health policy, demand for healthcare and the process of transition.     

Inadequate Bivariate Measures of Health Inequality: The Impact of Income Distribution*

Bivariate measures of health inequality are influenced by changes in two variables: health and a socioeconomic variable, such as income. For these measures, what is reported as an increase in health inequality might just as well be a reduction in income inequality. In particular, several papers have found that socioeconomic health inequalities in Nordic countries are no less than in other European countries. The correct interpretation could just be that income inequality is no higher in Nordic countries than in the rest of Europe. The problem is especially profound when the causality is running from health to income.     

Determinants of private health insurance coverage among Mexican American men 2010–2013

Abstract

Background: Private health insurance (PHI) represents the largest source of insurance for Americans. Hispanic Americans have one of the lowest rates of PHI coverage. The largest group in the US Hispanic population are Mexican Americans; they account for about two in every three Hispanics. One in every three Mexican Americans aged 64 years and under did not have health insurance coverage. Mexican Americans have the most unfavorable health insurance coverage of any population group in the nation.

Objectives: The objective is to determine the factors associated with the gap in PHI coverage between Mexican American and non-Hispanic American men.

Methods: This study used the National Health Interview Surveys (2010–2013) as the sample. A non-linear Oaxaca-Blinder decomposition was run, estimating the explained and unexplained gap in PHI coverage between the groups. Several robustness tests of the model were also included.

Results: This study estimates that 44.4% of employed Mexican American men are covered by PHI compared to 79.5% of non-Hispanic American men. Nearly 60% of employed Mexican American men were found to be foreign born, 35% have an educational attainment less than a high school degree, and 40% are likely to have language barriers. Decomposition results show that income, low educational attainment, being foreign-born, and language barriers diminished the probability of private health insurance coverage for Mexican Americans, and that 10% of the gap is unexplained.

Conclusions: Most of the difference in the PHI rate between Mexican American men and non-Hispanic men is explained by observable differences in group characteristics: education, language, and immigration status. About 10% of the difference can be attributed to discrimination under the traditional interpretation of an Oaxaca-Blinder decomposition. The PHI rate gap is large and persistent for Mexican American men.     

EQUITY-SENSITIVE INDICATORS OF LIVING STANDARDS WITH AN APPLICATION TO NORTHERN IRELAND

The level of a region's achievement with respect to a particular outcome is usually measured by the mean value of that outcome. This, however, ignores the fact that the distribution of that outcome, between population or geographical subgroups in that region, may be unequal: in order to reflect this inequality, ‘equity‐sensitive’ indicators make a downward adjustment to the mean value of the outcome. This paper extends the notion of ‘equity‐sensitive’ indicators which take cognisance of inter‐group inequality, to ‘equity‐sensitive’ indicators which paid heed to intra‐group inequality. It constructs – using data from a Northern Ireland survey into poverty and social exclusion conducted in 2002/2003 –‘equity‐sensitive indicators’ of living standards in Northern Ireland. These take account of both the average level of the standard of living and also inequality in these levels between groups, and between persons in these groups.     

Growth,inequality, and poverty reduction in developing countries: Recent global evidence

The study presents comparative global evidence on the transformation of economic growth to poverty reduction in developing countries, with emphasis on the role of income inequality. The focus is on the period since the early-mid-1990s when growth in these countries as a group has been relatively strong, surpassing that of the advanced economies. Both regional and country-specific data are analyzed for the $1.25 and $2.50-level poverty headcount ratios using World Bank Povcalnet data. The study finds that on average income growth has been the major driving force behind both the declines and increases in poverty. The study, however, documents substantial regional and country differences that are masked by this ‘average’ dominant-growth story. While in the majority of countries, growth was the major factor behind falling or increasing poverty, inequality, nevertheless, played the crucial role in poverty behavior in a large number of countries. And, even in those countries where growth has been the main driver of poverty-reduction, further progress could have occurred under relatively favorable income distribution. For more efficient policymaking, therefore, idiosyncratic attributes of countries should be emphasized. In general, high initial levels of inequality limit the effectiveness of growth in reducing poverty while growing inequality increases poverty directly for a given level of growth. It would seem judicious, therefore, to accord special attention to reducing inequality in certain countries where income distribution is especially unfavorable. Unfortunately, the present study also points to the limited effects of growth and inequality-reducing policies in low-income countries.     

Corruption and public spending on education and health

Existing country and regional studies show that the effect of corruption on public spending on health and education is mixed. This letter reveals that the effect of corruption on health and education spending is significant and non-linear in a panel of 134 countries observed over two decades: For an overwhelming majority of countries, corruption has a positive effect on the share of public resources spent on public health and a negative effect in the case of education. The results presented are robust to several econometric challenges ignored in the literature.