The wages of BMI: Bayesian analysis of a skewed treatment–response model with nonparametric endogeneity

Kline, Brendan; Tobias, Justin L.

doi:10.1002/jae.1028

Cited by 80 publications

(89 citation statements)

References 29 publications

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“…We are unable to test whether these are problems in the current context, and can only follow the previous literature (e.g. Smith et al, 2009;Kline and Tobias 2008;Cawley, 2004) in acknowledging them as possible limitations of the instrument.…”

Section: Discussionmentioning

confidence: 89%

“…We follow the previous literature (e.g. Cawley 2004; Kline and Tobias, 2008;Smith et al, 2009) and use the weight of a biological relative as an instrument for the weight of the respondent.…”

Section: Identification: Methods Of Instrumental Variablesmentioning

confidence: 99%

“…Our instrument for the respondent's weight is the weight of a biological relative, an instrument used in the previous literature to estimate the impact of weight on other outcomes such as wages (e.g. Cawley 2004; Kline and Tobias, 2008) and mortality (Smith et al, 2009). …”

Section: Introductionmentioning

confidence: 99%

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The Medical Care Costs of Obesity: An Instrumental Variables Approach

2010

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This paper is the first to use the method of instrumental variables (IV) to estimate the impact of obesity on medical costs in order to address the endogeneity of weight and to reduce the bias from reporting error in weight. Models are estimated using data from the Medical Expenditure Panel Survey for 2000-2005. The IV model, which exploits genetic variation in weight as a natural experiment, yields estimates of the impact of obesity on medical costs that are considerably higher than the correlations reported in the previous literature. For example, obesity is associated with $676 higher annual medical care costs, but the IV results indicate that obesity raises annual medical costs by $2,826 (in 2005 dollars). The estimated annual cost of treating obesity in the U.S. adult non-institutionalized population is $168.4 billion or 16.5% of national spending on medical care. These results imply that the previous literature has underestimated the medical costs of obesity, resulting in underestimates of the cost effectiveness of anti-obesity interventions and the economic rationale for government intervention to reduce obesityrelated externalities.

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Section: Discussionmentioning

confidence: 89%

Section: Identification: Methods Of Instrumental Variablesmentioning

confidence: 99%

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The Medical Care Costs of Obesity: An Instrumental Variables Approach

2010

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“…Recent work using nonparametric methods (Kline and Tobias, 2008) and quantile methods (Johar and Katayama, 2012) has shown that the effects of weight on wages varies over the distribution of wages. CDE also permits explanatory variables to have different marginal effects at different points of support of the dependent variable.…”

Section: Conditional Density Estimationmentioning

confidence: 99%

The Impact of Body Weight on Occupational Mobility and Career Development

Harris

2015

SSRN Journal

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This paper examines the relationship between individuals' weight and their employment decisions over the life cycle. I estimate a dynamic stochastic model of individuals' annual joint decisions of occupation, hours worked, and schooling. The model allows body weight to affect non-monetary costs, switching costs, and distribution of wages for each occupation; and also allows individuals' employment decisions to affect body weight. I use conditional density estimation to formulate the distributions of wages and body weight evolution. I find that heavier individuals face higher switching costs when transitioning into white collar occupations, earn lower returns to experience in white-collar occupations, and earn lower wages in socially intensive jobs. Simulating the model with estimated parameters, decreased occupational mobility accounts for 10 percent of the obesity wage gap. While contemporaneous wage penalties for body weight are small, the cost over the life cycle is substantial. An exogenous increase in initial body mass by 20 percent leads to a 10 percent decrease in wages over the life course.

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“…Shimokawa (2008) used data from China to estimate semiparametric models and fi nds that wages are lower for men and women in the tails of the BMI distribution. Kline and Tobias (2008), using data from the 1970 British Cohort study, found that marginal increases in BMI are most harmful for men who are overweight or obese and for women in the "healthy" weight range.…”

mentioning

confidence: 99%

Where Does the Wage Penalty Bite?

Gregory¹,

Ruhm²

2009

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The wages of BMI: Bayesian analysis of a skewed treatment–response model with nonparametric endogeneity

Cited by 80 publications

References 29 publications

The Medical Care Costs of Obesity: An Instrumental Variables Approach

The Medical Care Costs of Obesity: An Instrumental Variables Approach

The Impact of Body Weight on Occupational Mobility and Career Development

Where Does the Wage Penalty Bite?

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