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CEIS: CENTRE FOR ECONOMIC & INTERNATIONAL STUDIES
Furio Camillo Rosati - Director "Who Did It? A European Detective Story Was it Real, Financial, Monetary and/or Institutional: Tracking Growth in the Euro Area with an Atheoretical Tool" 
CEIS Working Paper No. 481 MARIAROSARIA COMUNALE, Bank of Lithuania - Economics Department
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FRANCESCO PAOLO MONGELLI, European Central Bank (ECB), Goethe University Frankfurt
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During the past thirty years, euro area countries have undergone significant changes and experienced diverse shocks. We aim to investigate which variables have consistently supported growth in this tumultuous period. The paper unfolds in three parts. First, we assemble a set of 35 real, financial, monetary and institutional variables for all euro area countries covering the period between 1990Q1 and 2016Q4. Second, using the Weighted-Average Least Squares (WALS) method, as well as other techniques, we gather clues about which variables to select. Third, we quantify the impact of various determinants of growth in the short and long runs. Our main finding is the positive and robust role of institutional reforms on long-term growth for all countries in the sample. An improvement in competitiveness matters for growth in the overall euro area in the long run as well as a decline in sovereign and systemic stress. The debt over GDP negatively influences growth for the periphery, but only in the short run. Property and equity prices have a significant impact only in the short run, whereas the loans to NFCs positively affect the core euro area. An increase in global GDP also supports growth. "Nowcasting Monthly GDP with Big Data: A Model Averaging Approach"
CEIS Working Paper No. 482 TOMMASO PROIETTI, University of Rome II - Department of Economics and Finance
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ALESSANDRO GIOVANNELLI, University of Rome Tor Vergata
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Gross domestic product (GDP) is the most comprehensive and authoritative measure of economic activity. The macroeconomic literature has focused on nowcasting and forecasting this measure at the monthly frequency, using related high frequency indicators. We address the issue of estimating monthly gross domestic product using a large dimensional set of monthly indicators, by pooling the disaggregate estimates arising from simple and feasible bivariate models that consider one indicator at a time in conjunction to GDP. Our base model handles mixed frequency data and ragged-edge data structure with any pattern of missingness. Our methodology enables to distill the common component of the available economic indicators, so that the monthly GDP estimates arise from the projection of the quarterly figures on the space spanned by the common component. The weights used for the combination reflect the ability to nowcast quarterly GDP and are obtained as a function of the regularized estimator of the high-dimensional covariance matrix of the nowcasting errors. A recursive nowcasting and forecasting experiment illustrates that the optimal weights adapt to the information set available in real time and vary according to the phase of the business cycle. "Complexity and Growth"
CEIS Working Paper No. 483 ALBERTO BUCCI, University of Milan - Department of Business Policy and Economics
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LORENZO CARBONARI, Università di Roma "Tor Vergata"
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P GIL, affiliation not provided to SSRN
GIOVANNI TROVATO, University of Rome Tor Vergata - Faculty of Economics
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Over the past decades, research effort in high income countries has substantially increased. Meanwhile, the growth rates of per capita output have been rather stable. The first goal of this paper is to investigate the reasons for such trends. The second goal of the paper is to show that the occurrence of different phases in the economic growth dynamics traces back to the interplay between complexity and specialization in production. To do this we use data from a sample of OECD countries and estimate a Hidden Markov Model, through which we identify four distinct growth regimes. | | ^top
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Distributed by Economics Research Network (ERN), a division of Social Science Electronic Publishing (SSEP) and Social Science Research Network (SSRN) Directors ECONOMICS RESEARCH CENTERS PAPERS MICHAEL C. JENSEN
Harvard Business School, SSRN, National Bureau of Economic Research (NBER), European Corporate Governance Institute (ECGI), Harvard University - Accounting & Control Unit
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