Sources of Geographic Variation in Health Care: Evidence from Patient Migration

Finkelstein, Amy; Gentzkow, Matthew; Williams, Heidi

doi:10.3386/w20789

Cited by 109 publications

(195 citation statements)

References 25 publications

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“…However, in typical matched employer employee data sets, the number of job movers (2015), Song, Price, Guvenen, and Bloom (2015), and Sorkin (2018), among others. The AKM estimator has been used in a variety of other fields, for example to link banks to firms, teachers to schools or students, and to document differences across areas in patients' health care utilization (e.g., Kramarz, Machin, and Ouazad (2015), Jackson (2013), Finkelstein, Gentzkow, and Williams (2016)). 2 Many structural models proposed in the literature build on Becker (1973).…”

Section: Introductionmentioning

confidence: 99%

A Distributional Framework for Matched Employer Employee Data

Lamadon

Manresa

2019

ECTA

187

173

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We propose a framework to identify and estimate earnings distributions and worker composition on matched panel data, allowing for two‐sided worker‐firm unobserved heterogeneity and complementarities in earnings. We introduce two models: a static model that allows for nonlinear interactions between workers and firms, and a dynamic model that allows, in addition, for Markovian earnings dynamics and endogenous mobility. We show that this framework nests a number of structural models of wages and worker mobility. We establish identification in short panels, and develop tractable two‐step estimators where firms are classified in a first step. Applying our method to Swedish administrative data, we find that log‐earnings are approximately additive in worker and firm heterogeneity. Our estimates imply the presence of strong sorting patterns between workers and firms, and a small contribution of firms—net of worker composition—to earnings dispersion. In addition, we document that wages have a direct effect on mobility, and that, beyond their dependence on the current firm, earnings after a job move also depend on the previous employer.

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Section: Introductionmentioning

confidence: 99%

A Distributional Framework for Matched Employer Employee Data

Lamadon

Manresa

2019

ECTA

187

173

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“…Finkelstein, Gentzkow, and Williams (2014) address the same question using longitudinal Medicare claims data that allow them to track the same patients as they move through different healthcare markets. They suggest that about half of the observed variation in procedure use is due to supply-side factors, while half is due to patient-level, or demand-side, factors.…”

Section: Introductionmentioning

confidence: 99%

Diagnosing Expertise: Human Capital, Decision Making and Performance Among Physicians

Currie

MacLeod

2013

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Expert performance is often evaluated assuming that good experts have good outcomes. We examine expertise in medicine and develop a model that allows for two dimensions of physician performance: decision making and procedural skill. Better procedural skill increases the use of intensive procedures for everyone, while better decision making results in a reallocation of procedures from fewer low-risk to high-risk cases. We show that poor diagnosticians can be identified using administrative data and that improving decision making improves birth outcomes by reducing C-section rates at the bottom of the risk distribution and increasing them at the top of the distribution.

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“…Among these factors are the need for medical care (eg, determined by the prevalence or severity of disease or prevalence of comorbid conditions) and the provision of care (6,7). Our findings expand on previous research by describing geographic variation in incremental costs of heart disease and offer initial insights into how differences in the use of services might drive some of this variation.…”

Section: Discussionmentioning

confidence: 99%

Geographic Variations in Incremental Costs of Heart Disease Among Medicare Beneficiaries, by Type of Service, 2012

et al. 2016

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Using 2012 data on fee-for-service Medicare claims, we documented regional and county variation in incremental standardized costs of heart disease (ie, comparing costs between beneficiaries with heart disease and beneficiaries without heart disease) by type of service (eg, inpatient, outpatient, post-acute care). Absolute incremental total costs varied by region. Although the largest absolute incremental total costs of heart disease were concentrated in southern and Appalachian counties, geographic patterns of costs varied by type of service. These data can be used to inform development of policies and payment models that address the observed geographic disparities.

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Sources of Geographic Variation in Health Care: Evidence from Patient Migration

Cited by 109 publications

References 25 publications

A Distributional Framework for Matched Employer Employee Data

A Distributional Framework for Matched Employer Employee Data

Diagnosing Expertise: Human Capital, Decision Making and Performance Among Physicians

Geographic Variations in Incremental Costs of Heart Disease Among Medicare Beneficiaries, by Type of Service, 2012

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