if this message does not display correctly, click here | Table of Contents Carlo Ciccarelli, University of Rome Tor Vergata - Faculty of Economics
Matteo Gomellini, Bank of Italy
Paolo Sestito, Bank of Italy Stefano Gagliarducci, University of Rome, Tor Vergata - Faculty of Economics, Einaudi Institute for Economics and Finance (EIEF), IZA Institute of Labor Economics
Daniele Paserman, Boston University - Department of Economics, Hebrew University of Jerusalem, National Bureau of Economic Research (NBER), IZA Institute of Labor Economics
Eleonora Patacchini, Cornell University Federico Belotti, University of Rome Tor Vergata - Department of Economics and Finance, University of Rome, Tor Vergata - Centre for Economics and International Studies (CEIS)
Giuseppe Ilardi, Bank of Italy
Andrea Piano Mortari, CEIS Tor Vergata | |
CEIS: CENTRE FOR ECONOMIC & INTERNATIONAL STUDIES
Furio Camillo Rosati - Director "Demography and Productivity in the Italian Manufacturing Industry: Yesterday and Today" 
CEIS Working Paper No. 457 CARLO CICCARELLI, University of Rome Tor Vergata - Faculty of Economics
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MATTEO GOMELLINI, Bank of Italy
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PAOLO SESTITO, Bank of Italy
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Population ageing and lack of productivity growth characterize most western countries. We focus on Italy and investigate whether the availability of a young population represents a determinant of manufacturing productivity growth. We follow a historical comparative analysis and provide evidence of the strength of this relation in the past (1861-1911) and today (1961-2011). To account for the sizeable regional heterogeneity characterizing historically the country we use data disaggregated at the provincial level. Our analysis suggests that the availability of a young population represents indeed one of the determinant of manufacturing productivity growth. The strength of the relation was higher in the past than today, but ageing is still nevertheless a factor that cannot be neglected from a policy perspective. "Hurricanes, Climate Change Policies and Electoral Accountability"
CEIS Working Paper No. 458 STEFANO GAGLIARDUCCI, University of Rome, Tor Vergata - Faculty of Economics, Einaudi Institute for Economics and Finance (EIEF), IZA Institute of Labor Economics
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DANIELE PASERMAN, Boston University - Department of Economics, Hebrew University of Jerusalem, National Bureau of Economic Research (NBER), IZA Institute of Labor Economics
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ELEONORA PATACCHINI, Cornell University
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This paper studies how politicians and voters respond to new information on the threats of climate change. Using data on the universe of federal disaster declarations between 1989 and 2014, we document that congress members from districts hit by a hurricane are more likely to support bills promoting more environmental regulation and control in the year after the disaster. The response to hurricanes does not seem to be driven by logrolling behavior or lobbysts' pressure. The change in legislative agenda is persistent over time, and it is associated with an electoral penalty in the following elections. The response is mainly promoted by representatives in safe districts, those with more experience, and those with strong pro-environment records. Our evidence thus reveals that natural disasters may trigger a permanent change in politicians' beliefs, but only those with a sufficient electoral strength or with strong ideologies are willing to engage in promoting policies with short-run costs and long-run benefits. "Estimation of Stochastic Frontier Panel Data Models with Spatial Inefficiency"
CEIS Working Paper No. 459 FEDERICO BELOTTI, University of Rome Tor Vergata - Department of Economics and Finance, University of Rome, Tor Vergata - Centre for Economics and International Studies (CEIS)
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GIUSEPPE ILARDI, Bank of Italy
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ANDREA PIANO MORTARI, CEIS Tor Vergata
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This paper proposes a stochastic frontier panel data model in which unit-specific inefficiencies are spatially correlated. In particular, this model has simultaneously three important features:
i) the total inefficiency of a productive unit depends on its own inefficiency and on the inefficiency of its neighbors;
ii) the spatially correlated and time varying inefficiency is disentangled from time invariant unobserved heterogeneity in a panel data model à la Greene (2005);
iii) systematic differences in inefficiency can be explained using exogenous determinants.
We propose to estimate both the "true" fixed- and random-effects variants of the model using a feasible simulated composite maximum likelihood approach. The finite sample behavior of the proposed estimators are investigated through a set of Monte Carlo experiments. Our simulation results suggest that the estimation approach is consistent, showing good finite sample properties especially in small samples. | | ^top
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