A nonlinear dynamic factor model of health and medical treatment
Franco Peracchi () and
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Claudio Rossetti: University of Naples Federico II and CSEF
No 1901, EIEF Working Papers Series from Einaudi Institute for Economics and Finance (EIEF)
Quantitative assessments of the relationship between health and medical treatment are of great importance to policy makers.However, simply looking at the raw correlation between health and medical care is unlikely to give the right answer because of endogeneity problems. We overcome these problems by formulating and estimating a tractable dynamic factor model of health and medical treatment where individual observed health outcomes are driven by the individual’s latent health stock. The dynamics of latent health reflects both exogenous health depreciation and endogenous health investments. Our model allows us to investigate the effect of medical treatment on current health, as well as on future medical treatment and health outcomes. We estimate the model by maximum simulated likelihood and minimum distance methods using a rich longitudinal data set from Italy obtained by merging a number of administrative archives. These data contain detailed information on medical drug use, hospitalization, and mortality for a representative sample of elderly hypertensive patients. Our findings show that medical care consumption is highly correlated over time, and this relationship depends on both permanent and time-varying observed and unobserved heterogeneity. They also show that medical drug use significantly maintains future health levels and prevents transitions to worse health. These results suggest that policies aimed at increasing the awareness and the compliance of of hypertensive patients help reduce cardiovascular risks and consequent hospitalization and mortality.
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Date: 2019, Revised 2019-02
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Working Paper: A Nonlinear Dynamic Factor Model of Health and Medical Treatment (2019)
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Persistent link: https://EconPapers.repec.org/RePEc:eie:wpaper:1901
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