title: Heterogeneity in the Effect of Common Shocks on Healthcare Expenditure Growth.
abstract: Healthcare expenditure growth is affected by important unobserved common shocks such as technological innovation, changes in sociological factors, shifts in preferences, and the epidemiology of diseases. While common factors impact in principle all countries, their effect is likely to differ across countries. To allow for unobserved heterogeneity in the effects of common shocks, we estimate a panel data model of healthcare expenditure growth in 34 OECD countries over the years 1980 to 2012, where the usual fixed or random effects are replaced by a multifactor error structure. We address model uncertainty with Bayesian model averaging, to identify a small set of robust expenditure drivers from 43 potential candidates. We establish 16 significant drivers of healthcare expenditure growth, including growth in GDP per capita and in insurance premiums, changes in financing arrangements and some institutional characteristics, expenditures on pharmaceuticals, population ageing, costs of health administration, and inpatient care. Our approach allows us to provide robust evidence to policy makers on the drivers that were most strongly associated with the growth in healthcare expenditures over the past 32 years. Copyright © 2016 John Wiley & Sons, Ltd.
authors.affiliation: School of Public Health, Imperial College London, London, UK.
authors.forename: Katharina
authors.initials: K
authors.lastname: Hauck
authors.affiliation: School of Management and Governance, Murdoch University, Perth, Australia.
authors.forename: Xiaohui
authors.initials: X
authors.lastname: Zhang
mesh_terms: D000375:Aging; D001499:Bayes Theorem; D019049:Developed Countries / Q000191:economics / Q000706:statistics & numerical data; D003906:Developing Countries / Q000191:economics / Q000706:statistics & numerical data; D005102:Health Expenditures / Q000706:statistics & numerical data*; D006801:Humans; D062069:Inventions; D066150:Organisation for Economic Co-Operation and Development / Q000191:economics / Q000706:statistics & numerical data*; D011795:Surveys and Questionnaires
keywords: Bayesian model averaging; common factor models; healthcare expenditure growth; panel data analysis; technological change