if this message does not display correctly, click here | Table of Contents Tommaso Proietti, University of Rome II - Department of Economics and Finance
Martyna Marczak, University of Hohenheim
Gian Luigi Mazzi, Eurostat Leonardo Becchetti, University of Rome II - Faculty of Economics
Pierluigi Conzo, University of Turin - Department of Economics and Statistics, Centre for Studies in Economics and Finance (CSEF)
Fabio Pisani, University of Rome II Sofia Amaral-Garcia, ETH Zurich
Paola Bertoli, University of Economics, Prague, Charles University in Prague - CERGE-EI (Center for Economic Research and Graduate Education - Economics Institute)
Veronica Grembi, Copenhagen Business School | |
CEIS: CENTRE FOR ECONOMIC & INTERNATIONAL STUDIES
Vincenzo Atella - Director "EuroMInd-D: A Density Estimate of Monthly Gross Domestic Product for the Euro Area" 
CEIS Working Paper No. 340 TOMMASO PROIETTI, University of Rome II - Department of Economics and Finance
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MARTYNA MARCZAK, University of Hohenheim
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GIAN LUIGI MAZZI, Eurostat
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EuroMInd-D is a density estimate of monthly gross domestic product (GDP) constructed according to a bottom-up approach, pooling the density estimates of eleven GDP components, by output and expenditure type. The components density estimates are obtained from a medium-size dynamic factor model of a set of coincident time series handling mixed frequencies of observation and ragged-edged data structures. They reflect both parameter and filtering uncertainty and are obtained by implementing a bootstrap algorithm for simulating from the distribution of the maximum likelihood estimators of the model parameters, and conditional simulation filters for simulating from the predictive distribution of GDP. Both algorithms process sequentially the data as they become available in real time. The GDP density estimates for the output and expenditure approach are combined using alternative weighting schemes and evaluated with different tests based on the probability integral transform and by applying scoring rules. "Education, Health and Subjective Wellbeing in Europe"
CEIS Working Paper No. 341 LEONARDO BECCHETTI, University of Rome II - Faculty of Economics
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PIERLUIGI CONZO, University of Turin - Department of Economics and Statistics, Centre for Studies in Economics and Finance (CSEF)
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FABIO PISANI, University of Rome II
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The productive and allocative theories predict that education has positive impact on health: the more educated adopt healthier life styles and use more efficiently health inputs and this explains why they live longer. We find partial support for these theories with an econometric analysis on a large sample of Europeans aged above 50 documenting a significant and positive correlation among education years, life styles, health outputs and functionalities. We however find confirmation for an anomaly already observed in the US, namely the more educated are more likely to contract cancer. Our results are robust when controlling for endogeneity and reverse causality in IV estimates with instrumental variables related to quarter of birth and neighbours’ cultural norms "Does Experience Rating Improve Obstetric Practices? Evidence from Geographical Discontinuities in Italy"
CEIS Working Paper No. 342 SOFIA AMARAL-GARCIA, ETH Zurich
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PAOLA BERTOLI, University of Economics, Prague, Charles University in Prague - CERGE-EI (Center for Economic Research and Graduate Education - Economics Institute)
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VERONICA GREMBI, Copenhagen Business School
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Using data from 2002 to 2009 inpatient discharge records on deliveries in the Italian region of Piedmont, we assess the impact of an increase in malpractice pressure on obstetric practices, as identified by the introduction of experience-rated malpractice liability insurance. Our identification strategy exploits the exogenous location of public hospitals in court districts with and without schedules for noneconomic damages. We perform difference-in-differences and difference-in-discontinuities analyses. We find that the increase in medical malpractice pressure is associated with a decrease in the probability of performing a C-section from 2.3 to 3.7 percentage points (7% to 11.6% at the mean value of C-section) with no consequences for a broadly defined measure of complications or neonatal outcomes. We show that these results are robust to the different methodologies and can be explained by a reduction in the discretion of obstetric decision making rather than by patient cream skimming. | | ^top
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