The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Ichiro Kawachi - One of the best experts on this subject based on the ideXlab platform.
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Income Inequality mortality and self rated health meta analysis of multilevel studies
BMJ, 2009Co-Authors: Naoki Kondo, Ichiro Kawachi, S V Subramanian, Grace Sembajwe, Zentaro YamagataAbstract:Objective To provide quantitative evaluations on the association between Income Inequality and health. Design Random effects meta-analyses, calculating the overall relative risk for subsequent mortality among prospective cohort studies and the overall odds ratio for poor self rated health among cross sectional studies. Data sources PubMed, the ISI Web of Science, and the National Bureau for Economic Research database. Review methods Peer reviewed papers with multilevel data. Results The meta-analysis included 59 509 857 subjects in nine cohort studies and 1 280 211 subjects in 19 cross sectional studies. The overall cohort relative risk and cross sectional odds ratio (95% confidence intervals) per 0.05 unit increase in Gini coefficient, a measure of Income Inequality, was 1.08 (1.06 to 1.10) and 1.04 (1.02 to 1.06), respectively. Meta-regressions showed stronger associations between Income Inequality and the health outcomes among studies with higher Gini (≥0.3), conducted with data after 1990, with longer duration of follow-up (>7 years), and incorporating time lags between Income Inequality and outcomes. By contrast, analyses accounting for unmeasured regional characteristics showed a weaker association between Income Inequality and health. Conclusions The results suggest a modest adverse effect of Income Inequality on health, although the population impact might be larger if the association is truly causal. The results also support the threshold effect hypothesis, which posits the existence of a threshold of Income Inequality beyond which adverse impacts on health begin to emerge. The findings need to be interpreted with caution given the heterogeneity between studies, as well as the attenuation of the risk estimates in analyses that attempted to control for the unmeasured characteristics of areas with high levels of Income Inequality.
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whose health is affected by Income Inequality a multilevel interaction analysis of contemporaneous and lagged effects of state Income Inequality on individual self rated health in the united states
Health & Place, 2006Co-Authors: S V Subramanian, Ichiro KawachiAbstract:Abstract The empirical relationship between Income Inequality and health has been much debated and discussed. Recent reviews suggest that the current evidence is mixed, with the relationship between state Income Inequality and health in the United States (US) being perhaps the most robust. In this paper, we examine the multilevel interactions between state Income Inequality, individual poor self-rated health, and a range of individual demographic and socioeconomic markers in the US. We use the pooled data from the 1995 and 1997 Current Population Surveys, and the data on state Income Inequality (represented using Gini coefficient) from the 1990, 1980, and 1970 US Censuses. Utilizing a cross-sectional multilevel design of 201,221 adults nested within 50 US states we calibrated two-level binomial hierarchical mixed models (with states specified as a random effect). Our analyses suggest that for a 0.05 change in the state Income Inequality, the odds ratio (OR) of reporting poor health was 1.30 (95% CI: 1.17–1.45) in a conditional model that included individual age, sex, race, marital status, education, Income, and health insurance coverage as well as state median Income. With few exceptions, we did not find strong statistical support for differential effects of state Income Inequality across different population groups. For instance, the relationship between state Income Inequality and poor health was steeper for whites compared to blacks ( OR = 1.3 4 ; 95% CI: 1.20–1.48) and for individuals with Incomes greater than $75,000 compared to less affluent individuals ( OR = 1.6 5 ; 95% CI: 1.26–2.15). Our findings, however, primarily suggests an overall (as opposed to differential) contextual effect of state Income Inequality on individual self-rated poor health. To the extent that contemporaneous state Income Inequality differentially affects population sub-groups, our analyses suggest that the adverse impact of Inequality is somewhat stronger for the relatively advantaged socioeconomic groups. This pattern was found to be consistent regardless of whether we consider contemporaneous or lagged effects of state Income Inequality on health. At the same time, the contemporaneous main effect of state Income Inequality remained statistically significant even when conditioned for past levels of Income Inequality and median Income of states.
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response in defence of the Income Inequality hypothesis
International Journal of Epidemiology, 2003Co-Authors: S V Subramanian, Ichiro KawachiAbstract:Lynch, Harper, and Davey Smith’s metaphor of the SS Income Inequality 1 is amusing, but we think that a more accurate representation of the current debate in this area would be a kangaroo court, in which the defendant (viz. the hypothesis that Income Inequality is detrimental to population health) is in imminent danger of being summarily executed without the benefit of a fair hearing. Indeed, some jurors already seem to have decided that a relationship between Income Inequality and health does not exist. One recent assertion, for instance, was that ‘statistical adjustment for ethnicity statistically accounts for all of the association between Income Inequality and health within the US’. 2 Other assertions, based on an ecological analysis, 3 were that ‘adjustment for education … also accounted for all of the association between Income Inequality and mortality‘ 2 and that the ‘evidence for the Income Inequality hypothesis is weak, beyond its important mechanical effects on individual Income’, 1 also based on ecological evidence. 4,5 Examples of other claims include: ‘the evidence favoring a negative correlation between Income Inequality and life expectancy has disappeared’ 6 and that ‘we can muster little evidence to show that the extent of Income Inequality, per se, affects population health’. 7 These are strong claims which, taken at face value, imply that Income Inequality is not a public health concern and the public health community has no cause to be alarmed about the sharp increase in Income Inequality that has occurred in the last two decades both within and between countries. However, we are not so confident that the Income Inequality story can be so hastily dismissed. In particular, several key accusations levelled by the prosecutors in this case can be tested with new evidence and better-designed studies. As witnesses for the defence, we would like to draw the attention of the jurors to evidence based on the more appropriate multilevel methods.
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teen births Income Inequality and social capital developing an understanding of the causal pathway
Health & Place, 2002Co-Authors: Rachel Gold, Bruce P Kennedy, Fred A Connell, Ichiro KawachiAbstract:Many studies have demonstrated a relationship between Income Inequality and poor health, but how does Income Inequality impact health? One possible explanation is that greater Income Inequality undermines social capital (social cohesion, civic engagement, and mutual trust in a community). We conducted path analyses of the relationship between Income Inequality, poverty, and teen birth rate, testing for the mediating effect of social capital in 39 US states. Birth rate was affected by both poverty and Income Inequality, though Income Inequality appeared to affect teen birth rate primarily through its impact on social capital.
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metropolitan area Income Inequality and self rated health a multi level study
Social Science & Medicine, 2002Co-Authors: Tony Blakely, Kimberly Lochner, Ichiro KawachiAbstract:We examined the association of Income Inequality measured at the metropolitan area (MA) and county levels with individual self-rated health. Individual-level data were drawn from 259,762 respondents to the March Current Population Survey in 1996 and 1998. Income Inequality and average Income were calculated from 1990 census data, the former using Gini coefficients. Multi-level logistic regression models were used. Controlling for sex, age, race, and individual-level household Income, respondents living in high, medium-high, and medium-low Income Inequality MAs had odds ratios of fair/poor self-rated health of 1.20 (95% confidence interval 1.04-1.38), 1.07 (0.95-1.21), and 1.02 (0.91-1.15), respectively, compared to people living in the MAs with the lowest Income Inequality. However, we found only a small association of MA-level Income Inequality with fair/poor health when controlling further for average MA household Income: odds ratios were 1.10 (0.95-1.28), 1.01 (0.89-1.14), and 1.00 (0.89-1.12), respectively. Likewise, we found only a small association of county-level Income Inequality with self-rated health--although only 40.7% of the sample had an identified county on CPS data. Regarding the association of state-level Income Inequality with fair/poor health, we found the association to be considerably stronger among non-metropolitan (i.e. rural) compared to metropolitan residents.
Mark Bils - One of the best experts on this subject based on the ideXlab platform.
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has consumption Inequality mirrored Income Inequality
The American Economic Review, 2015Co-Authors: Mark Aguiar, Mark BilsAbstract:We revisit to what extent the increase in Income Inequality since 1980 was mirrored by consumption Inequality. We do so by constructing an alternative measure of consumption expenditure using a demand system to correct for systematic measurement error in the Consumer Expenditure Survey. Our estimation exploits the relative expenditure of high- and low-Income households on luxuries versus necessities. This double differencing corrects for measurement error that can vary over time by good and Income. We find consumption Inequality tracked Income Inequality much more closely than estimated by direct responses on expenditures. (JEL D31, D63, E21)
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has consumption Inequality mirrored Income Inequality
Social Science Research Network, 2011Co-Authors: Mark Aguiar, Mark BilsAbstract:We revisit to what extent the increase in Income Inequality over the last 30 years has been mirrored by consumption Inequality. We do so by constructing two alternative measures of consumption expenditure, using data from the Consumer Expenditure Survey (CE). We first use reports of active savings and after tax Income to construct the measure of consumption implied by the budget constraint. We find that the consumption Inequality implied by savings behavior largely tracks Income Inequality between 1980 and 2007. Second, we use a demand system to correct for systematic measurement error in the CE's expenditure data. Specifically, we consider trends in the relative expenditure of high Income and low Income households for different goods with different Income (total expenditure) elasticities. Our estimation exploits the difference in the growth rate of luxury consumption Inequality versus necessity consumption Inequality. This "double-differencing,'' which we implement in a a regression framework, corrects for mis-measurement that can systematically vary over time by good and Income group. This second exercise indicates that consumption Inequality has closely tracked Income Inequality over the period 1980-2007. Both of our measures show a significantly greater increase in consumption Inequality than what is obtained from the CE's total household expenditure data directly.
Li Shi - One of the best experts on this subject based on the ideXlab platform.
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Income Inequality within and across counties in rural china 1988 and 1995
Social Science Research Network, 2003Co-Authors: Bjorn Gustafsson, Li ShiAbstract:Using household data from samples covering 18 provinces in 1988 and 1995, Income Inequality within and between counties in rural China is assessed. The approach enables us to aggregate average Income and Income Inequality to the levels of provinces and the three regions comprising eastern, central and western China. Most of the Income Inequality in rural China in 1995 was found to be spatial and the uneven development of mean Income across counties stood for most, but not all, of the rapid increase in Income Inequality. Mean Income of the three regions diverged most forcefully.
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Income Inequality within and across counties in rural china 1988 and 1995
Journal of Development Economics, 2002Co-Authors: Bjorn Gustafsson, Li ShiAbstract:Abstract Using household data from samples covering 18 provinces in 1988 and 1995, Income Inequality within and between counties in rural China is assessed. The approach enables us to aggregate average Income and Income Inequality to the levels of provinces and the three regions comprising eastern, central and western China. Most of Income Inequality in rural China in 1995 was found to be spatial and the uneven development of mean Income across counties stood for most, but not all, of the rapid increase in Income Inequality. Mean Income of the three regions diverged most forcefully.
Mark Aguiar - One of the best experts on this subject based on the ideXlab platform.
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has consumption Inequality mirrored Income Inequality
The American Economic Review, 2015Co-Authors: Mark Aguiar, Mark BilsAbstract:We revisit to what extent the increase in Income Inequality since 1980 was mirrored by consumption Inequality. We do so by constructing an alternative measure of consumption expenditure using a demand system to correct for systematic measurement error in the Consumer Expenditure Survey. Our estimation exploits the relative expenditure of high- and low-Income households on luxuries versus necessities. This double differencing corrects for measurement error that can vary over time by good and Income. We find consumption Inequality tracked Income Inequality much more closely than estimated by direct responses on expenditures. (JEL D31, D63, E21)
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has consumption Inequality mirrored Income Inequality
Social Science Research Network, 2011Co-Authors: Mark Aguiar, Mark BilsAbstract:We revisit to what extent the increase in Income Inequality over the last 30 years has been mirrored by consumption Inequality. We do so by constructing two alternative measures of consumption expenditure, using data from the Consumer Expenditure Survey (CE). We first use reports of active savings and after tax Income to construct the measure of consumption implied by the budget constraint. We find that the consumption Inequality implied by savings behavior largely tracks Income Inequality between 1980 and 2007. Second, we use a demand system to correct for systematic measurement error in the CE's expenditure data. Specifically, we consider trends in the relative expenditure of high Income and low Income households for different goods with different Income (total expenditure) elasticities. Our estimation exploits the difference in the growth rate of luxury consumption Inequality versus necessity consumption Inequality. This "double-differencing,'' which we implement in a a regression framework, corrects for mis-measurement that can systematically vary over time by good and Income group. This second exercise indicates that consumption Inequality has closely tracked Income Inequality over the period 1980-2007. Both of our measures show a significantly greater increase in consumption Inequality than what is obtained from the CE's total household expenditure data directly.
Philippe Aghion - One of the best experts on this subject based on the ideXlab platform.
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innovation and top Income Inequality
The Review of Economic Studies, 2019Co-Authors: Philippe Aghion, Ufuk Akcigit, Antonin Bergeaud, Richard Blundell, David HemousAbstract:In this article, we use cross-state panel and cross-U.S. commuting-zone data to look at the relationship between innovation, top Income Inequality and social mobility. We find positive correlations between measures of innovation and top Income Inequality. We also show that the correlations between innovation and broad measures of Inequality are not significant. Next, using instrumental variable analysis, we argue that these correlations at least partly reflect a causality from innovation to top Income shares. Finally, we show that innovation, particularly by new entrants, is positively associated with social mobility, but less so in local areas with more intense lobbying activities.
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innovation and top Income Inequality
Social Science Research Network, 2015Co-Authors: Philippe Aghion, Ufuk Akcigit, Antonin Bergeaud, Richard Blundell, David HemousAbstract:In this paper we use cross-state panel data to show that top Income Inequality is (at least partly) driven by innovation. We first establish a positive and significant correlation between various measures of innovativeness and top Income Inequality in cross-state panel regressions. Two distinct instrumentation strategies suggest that this correlation (partly) reflects a causality from innovativeness to top Income Inequality, and the effect is significant: for example, when measured by the number of patent per capita, innovativeness accounts on average across US states for around 17% of the total increase in the top 1% Income share between 1975 and 2010. Finally, we show that innovation does not increase broader measures of Inequality which do not focus on top Incomes, and that innovation is positively correlated with social mobility, but less so in states with more intense lobbying activities.
