63 research outputs found

    GMM estimation of spatial panels

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    We consider Generalized Method of Moments (GMM) estimation of a regression model with spatially correlated errors. We propose some new moment conditions, and derive the asymptotic distribution of the GMM based on them. The analysis is supported by a small Monte Carlo exercise.Generalized Method of Moments, spatial econometrics

    Health Expenditure and Income in the United States

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    This paper investigates the long-run economic relationship between health care expenditure and income in the US at a State level. Using a panel of 49 US States followed over the period 1980-2004, we study the non-stationarity and cointegration between health spending and income, ultimately measuring income elasticity of health care. The tests we adopt allow us to explicitly control for cross-section dependence and unobserved heterogeneity. Specifically, in our regression equations we assume that the error is the sum of a multifactor structure and a spatial autoregressive process, which capture global shocks and local spill overs in health expenditure. Our results suggest that health care is a necessity rather than a luxury, with an elasticity much smaller than that estimated in other US studies. Further, we observe a significant spatial spill over, though with a smaller intensity than that detected in other studies on spatial concentration of US health spending. Our broad perspective of cross section dependence as well as the methods used to capture it give new insights on the debate over the relationship between health spending and income.Health expenditure; income elasticity; cross section dependence; panels

    Health Care Expenditure and Income in the OECD Reconsidered: Evidence from Panel Data

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    This paper reconsiders the long-run economic relationship between health care expenditure and income using a panel of 20 OECD countries observed over the period 1971-2004. In particular, the paper studies the non-stationarity and cointegration properties between health care spending and income. This is done in a panel data context controlling for both cross-section dependence and unobserved heterogeneity. Cross-section dependence is modelled through a common factor model and through spatial dependence. Heterogeneity is handled through fixed effects in a panel homogeneous model and through a panel heterogeneous model. Our findings suggest that health care is a necessity rather than a luxury, with an elasticity much smaller than that estimated in previous studies.heterogeneous panels, cross section dependence, income elasticity, health expenditure, factor models

    Medical Technology and the Production of Health Care

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    This paper investigates the factors that determine differences across OECD countries inhealth outcomes, using data on life expectancy at age 65, over the period 1960 to 2007. We estimate a production function where life expectancy depends on health and social spending, lifestyle variables, and medical innovation. Our first set of regressions includes a set of observed medical technologies by country. Our second set of regressions proxy technology using a spatial process. The paper also tests whether in the long-run countries tend to achieve similar levels of health outcomes. Our results show that health spending has a significant and mild effect on health out- comes, even after controlling for medical innovation. However, its short-run adjustments do not seem to have an impact on health care productivity. Spatial spill overs in life expectancy are significant and point to the existence of interdependence across countries in technology adoption. Furthermore, nations with initial low levels of life expectancy tend to catch up with those with longer-lived populations

    Social Interaction in Patients'�Hospital Choice: Evidences from Italy

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    In this paper we study the influence of social interaction on patients' hospital choice and its relationship with quality delivered by hospitals, using Italian data. We explore the impact on individual choices of a set of variables such as travel distance, individual- and hospital-specific characteristics, as well as a variable capturing the effect of the neighbourhood. The richness of our data allows us to disentangle contextual effects from the influence of information sharing on patients' hospital choices. We then use this framework to assess how such interaction is related to clinical hospital quality. Results show that network effect plays an important role in hospital choices, although it is less relevant for larger hospitals. Another empirical finding is the existence of a negative relationship between the degree of interaction among individuals and the quality delivered by hospitals. The absence of a source of information on the quality of hospitals accessible to all individuals, such as guidelines or star ratings, exacerbates the importance of information gathered locally in hospital choices, which may result in a lower degree of competition among hospitals and lower quality.health care, social interaction, quality

    Medical Technology And The Production Of Health Care

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    This paper investigates the factors that determine differences across OECD countries in health outcomes, using data on life expectancy at age 65, over the period 1960 to 2007. We estimate a production function where life expectancy depends on health and social spending, lifestyle variables, and medical innovation. Our first set of regressions includes a set of observed medical technologies by country. Our second set of regressions proxy technology using a spatial process. The paper also tests whether in the long-run countries tend to achieve similar levels of health outcomes. Our results show that health spending has a significant and mild effect on health out- comes, even after controlling for medical innovation. However, its short-run adjustments do not seem to have an impact on health care productivity. Spatial spill overs in life expectancy are significant and point to the existence of interdependence across countries in technology adoption. Furthermore, nations with initial low levels of life expectancy tend to catch up with those with longer-lived populations

    Studying informal care during the pandemic: mental health, gender and job status

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    Unexpected negative health shocks such as COVID-19 put pressure on households to provide more care to relatives and friends. This study uses data from the UK Household Longitudinal Study to investigate the impact of informal caregiving on mental health during the COVID-19 pandemic. Using a difference-in-differences analysis, we find that individuals who started providing care after the pandemic began reported more mental health issues than those who never provided care. Additionally, the gender gap in mental health widened during the pandemic, with women more likely to report mental health issues. We also find that those who began providing care during the pandemic reduced their work hours compared to those who never provided care. Our results suggest that the COVID-19 pandemic has had a negative impact on the mental health of informal caregivers, particularly for women

    Hospital Quality Interdependence in a Competitive Institutional Environment: Evidence from Italy

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    In this paper we explore the geographical scope of hospital competition on quality, using Italian data on over 207,000 patients admitted to 174 hospitals located in the Lombardy region in the years 2008–2014. We propose an economic framework that incorporates both local and global forms of quality competition among hospitals, the latter emerging from periodically released hospital performance rankings. Under this framework, we derive the hospital reaction functions and, accordingly, we characterize the structure of interdependence among hospital qualities. We employ recent methods from the graphical modelling literature to estimate the set of local rivals for each hospital, as well as the degree of global interdependence among hospitals. Consistently with our micro-founded framework, our results show a significant positive degree of short- and long-range dependence, suggesting the existence of forms of local and global competition amongst hospitals with relevant implications for health care policy

    GMM estimation of Spatial Panels with Fixed Effects

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    In this paper we consider the estimation of a panel data regression model with spatial autoregressive disturbances, fixed effects and unknown heteroskedasticity. Following the work by Kelejian and Prucha (1999), Lee and Liu (2006a) and others, we adopt the Generalized Method of Moments (GMM) and consider as moments a set linear quadratic conditions in the disturbances. As in Lee and Liu (2006a), we assume that the inner matrices in the quadratic forms have zero diagonal elements to robustify moments against unknown heteroskedasticity. We derive the asymptotic distribution of the GMM estimator based on such conditions. Hence, we carry out some Monte Carlo experiment to investigate the small sample properties of GMM estimators based on various sets of moment conditions
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