if this message does not display correctly, click here | Table of Contents Luisa Corrado, University of Rome Tor Vergata Department of Economics and Finance
Thanasis Stengos, University of Guelph - Department of Economics
Melvyn Weeks, University of Cambridge - Faculty of Economics and Politics
Mustafa Ege Yazgan, Istanbul Bilgi University Paolo Andreini, University of Rome, Tor Vergata
Donato Ceci, University of Rome, Tor Vergata Luis F. Araujo, Michigan State University - Department of Economics
Leo Ferraris, Universidad Carlos III de Madrid | |
CEIS: CENTRE FOR ECONOMIC & INTERNATIONAL STUDIES
Furio Camillo Rosati - Director "Robust Tests for Convergence Clubs" 
CEIS Working Paper No. 451 LUISA CORRADO, University of Rome Tor Vergata Department of Economics and Finance
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THANASIS STENGOS, University of Guelph - Department of Economics
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MELVYN WEEKS, University of Cambridge - Faculty of Economics and Politics
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MUSTAFA EGE YAZGAN, Istanbul Bilgi University
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In many applications common in testing for convergence the number of cross-sectional units is large and the number of time periods are few. In these situations asymptotic tests based on an omnibus null hypothesis are characterised by a number of problems. In this paper we propose a multiple pairwise comparisons method based on an a recursive bootstrap to test for convergence with no prior information on the composition of convergence clubs. Monte Carlo simulations suggest that our bootstrap-based test performs well to correctly identify convergence clubs when compared with other similar tests that rely on asymptotic arguments. Across a potentially large number of regions, using both cross-country and regional data for the European Union we find that the size distortion which afflicts standard tests and results in a bias towards finding less convergence, is ameliorated when we utilise our bootstrap test. "A Horse Race in High Dimensional Space"
CEIS Working Paper No. 452 PAOLO ANDREINI, University of Rome, Tor Vergata
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DONATO CECI, University of Rome, Tor Vergata
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In this paper, we study the predictive power of dense and sparse estimators in a high dimensional space. We propose a new forecasting method, called Elastically Weighted Principal Components Analysis (EWPCA) that selects the variables, with respect to the target variable, taking into account the collinearity among the data using the Elastic Net soft thresholding. Then, we weight the selected predictors using the Elastic Net regression coefficient, and we finally apply the principal component analysis to the new “elastically” weighted data matrix. We compare this method to common benchmark and other methods to forecast macroeconomic variables in a data-rich environment, dived into dense representation, such as Dynamic Factor Models and Ridge regressions and sparse representations, such as LASSO regression. All these models are adapted to take into account the linear dependency of the macroeconomic time series.
Moreover, to estimate the hyperparameters of these models, including the EWPCA, we propose a new procedure called “brute force”. This method allows us to treat all the hyperparameters of the model uniformly and to take the longitudinal feature of the time-series data into account.
Our findings can be summarized as follows. First, the “brute force” method to estimate the hyperparameters is more stable and gives better forecasting performances, in terms of MSFE, than the traditional criteria used in the literature to tune the hyperparameters. This result holds for all samples sizes and forecasting horizons. Secondly, our two-step forecasting procedure enhances the forecasts’ interpretability. Lastly, the EWPCA leads to better forecasting performances, in terms of mean square forecast error (MSFE), than the other sparse and dense methods or naïve benchmark, at different forecasts horizons and sample sizes. "The Societal Benefits of Money and Interest Bearing Debt"
CEIS Working Paper No. 453 LUIS F. ARAUJO, Michigan State University - Department of Economics
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LEO FERRARIS, Universidad Carlos III de Madrid
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A long standing issue in monetary theory is whether money and interest bearing debt may both play a beneficial role in facilitating transactions. This paper identifies in the misallocation of liquidity a key element to provide an answer. In a search model of money, we show that there exists an equilibrium which resembles a liquidity trap, in which debt and money are used interchangeably to trade goods and debt carries no interest, and a Pareto superior equilibrium in which money is used to trade goods and interest bearing debt to reshuffle misallocated liquidity. Monetary policy has no effect in the liquidity trap, and a liquidity effect in the Pareto superior equilibrium. | | ^top
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