Measuring heterogeneity in hospital productivity: a quantile regression approach
Galina Besstremyannaya () and
Sergei Golovan ()
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Galina Besstremyannaya: National Research University Higher School of Economics
Sergei Golovan: New Economic School
Journal of Productivity Analysis, 2023, vol. 59, issue 1, No 2, 15-43
Abstract This paper focuses on acute-care local public hospitals in Japan and evaluates differences in hospital technology, as reflected in the productivity of labor specialties, physical capital and medicines, and in the impact of teaching activities and other hospital characteristics on hospital output. We use panel data quantile regressions with fixed effects to model a range of technologies for the multi-product output function of hospitals. The analysis reveals technological heterogeneity across high-output and low-output hospitals. We discover inexpedient labor/capital and labor/medicines mix, and vast opportunities for cost savings. The results contribute to scant empirical literature on variation in the hospital production.
Keywords: Quantile regression; Panel data; Productivity; Input mix; Hospitals; C440; C610; I130 (search for similar items in EconPapers)
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