if this message does not display correctly, click here | Table of Contents Gabriele Curci, affiliation not provided to SSRN
Domenico Depalo, Bank of Italy, Bank of Italy
Alessandro Palma, Gran Sasso Science Institute, University of Rome Tor Vergata - Centre for International Studies on Economic Growth (CEIS), DISAE - Department of Business and Economics Gianluca Cubadda, University of Rome Tor Vergata - Department of Economics and Finance
Alain Hecq, Maastricht University - Department of Quantitative Economics
Elisa Voisin, affiliation not provided to SSRN Gianluca Cubadda, University of Rome Tor Vergata - Department of Economics and Finance
Marco Mazzali, University of Rome Tor Vergata | |
CEIS: CENTRE FOR ECONOMIC & INTERNATIONAL STUDIES
Furio Camillo Rosati - Director "The Dirtier You Breathe, The Less Safe You Are. The Effect of Air Pollution on Work Accidents" 
CEIS Working Paper No. 554 GABRIELE CURCI, affiliation not provided to SSRN
DOMENICO DEPALO, Bank of Italy, Bank of Italy
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ALESSANDRO PALMA, Gran Sasso Science Institute, University of Rome Tor Vergata - Centre for International Studies on Economic Growth (CEIS), DISAE - Department of Business and Economics
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We estimate the effect of air pollution on work-related accidents and disabilities using administrative data from Italy in a setting characterized by strict air pollution and work safety regulations. Leveraging on winter heating rules to address the endogeneity of air quality, we find that a one unit increase in PM10 causes 0.014 additional accidents and 0.0014 disabilities. These results are robust to different model specifications and when we extend the geographical scale of the analysis using an alternative instrumental variable based on the height of planetary atmospheric boundary layer. We explore the theoretical implications of these findings and empirically confirm that firms have an incentive to deploy defensive investments also when the risk of accidents derives from external factors such as air quality. Our back-of-the-envelope calculation shows that each additional unit in PM10 concentration would increase the total cost of an accident by about 1.7%. "Detecting Common Bubbles in Multivariate Mixed Causal-Noncausal Models"
CEIS Working Paper No. 555 GIANLUCA CUBADDA, University of Rome Tor Vergata - Department of Economics and Finance
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ALAIN HECQ, Maastricht University - Department of Quantitative Economics
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ELISA VOISIN, affiliation not provided to SSRN This paper proposes concepts and methods to investigate whether the bubble patterns observed in individual time series are common among them. Having established the conditions under which common bubbles are present within the class of mixed causal-noncausal vector autoregressive models, we suggest statistical tools to detect the common locally explosive dynamics in a Student−t distribution maximum likelihood framework. The performances of both likelihood ratio tests and information criteria are investigated in a Monte Carlo study. Finally, we evaluate the practical value of our approach by an empirical application on three commodity prices. "The Vector Error Correction Index Model: Representation, Estimation and Identification"
CEIS Working Paper No. 556 GIANLUCA CUBADDA, University of Rome Tor Vergata - Department of Economics and Finance
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MARCO MAZZALI, University of Rome Tor Vergata
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This paper extends the multivariate index autoregressive model by Reinsel (1983) to the case of cointegrated time series of order (1, 1). In this new modelling, namely the Vector Error-Correction Index Model (VECIM), the first differences of series are driven by some linear combinations of the variables, namely the indexes. When the indexes are significantly fewer than the variables, the VECIM achieves a substantial dimension reduction w.r.t. the Vector Error Correction Model. We show that the VECIM allows one to decompose the reduced form errors into sets of common and uncommon shocks, and that the former can be further decomposed into permanent and transitory shocks. Moreover, we offer a switching algorithm for optimal estimation of the VECIM. Finally, we document the practical value of the proposed approach by both simulations and an empirical application, where we search for the shocks that drive the aggregate fluctuations at different frequency bands in the US. | | ^top
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