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CEIS: CENTRE FOR ECONOMIC & INTERNATIONAL STUDIES Vincenzo Atella - Director "Unbundling the Incumbent: Evidence from UK Broadband" CEIS Working Paper No. 331 MATTIA NARDOTTO, University of Cologne - Department of Economics Email:
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TOMMASO M. VALLETTI, Imperial College Business School, University of Rome II - Department of Financial and Quantitative Economics, Centre for Economic Policy Research (CEPR) Email:
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FRANK VERBOVEN, KU Leuven - Faculty of Business and Economics (FEB) Email:
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We consider the impact of a regulatory process forcing an incumbent telecom operator to make its local broadband network available to other companies (local loop unbundling, or LLU). Entrants are then able to upgrade their individual lines and offer Internet services directly to customers. Employing a very detailed dataset covering the whole of the UK, we find that, over the course of time, many entrants have begun to take advantage of unbundling. LLU entry only had a positive effect on broadband penetration in the early years, and no longer in the recent years as the market reached maturity. In contrast, LLU entry continues to have a positive impact on the quality of the service provided, as entrants differentiate their products upwards compared to the incumbent. We also assess the impact of competition from an alternative form of technology (cable) which is not subject to regulation, and what we discover is that inter-platform competition has a positive impact on both penetration and quality. "On the Selection of Common Factors for Macroeconomic Forecasting" CEIS Working Paper No. 332 ALESSANDRO GIOVANNELLI, University of Rome II Email:
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TOMMASO PROIETTI, University of Rome II - Department of Economics and Finance Email:
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We address the problem of selecting the common factors that are relevant for forecasting macroeconomic variables. In economic forecasting using diffusion indexes the factors are ordered, according to their importance, in terms of relative variability, and are the same for each variable to predict, i.e. the process of selecting the factors is not supervised by the predictand. We propose a simple and operational supervised method, based on selecting the factors on the basis of their significance in the regression of the predictand on the predictors. Given a potentially large number of predictors, we consider linear transformations obtained by principal components analysis. The orthogonality of the components implies that the standard t-statistics for the inclusion of a particular component are independent, and thus applying a selection procedure that takes into account the multiplicity of the hypotheses tests is both correct and computationally feasible. We focus on three main multiple testing procedures: Holm’s sequential method, controlling the family wise error rate, the Benjamini-Hochberg method, controlling the false discovery rate, and a procedure for incorporating prior information on the ordering of the components, based on weighting the p-values according to the eigenvalues associated to the components. We compare the empirical performances of these methods with the classical diffusion index (DI) approach proposed by Stock and Watson, conducting a pseudo-real time forecasting exercise, assessing the predictions of 8 macroeconomic variables using factors extracted from an U.S. dataset consisting of 121 quarterly time series. The overall conclusion is that nature is tricky, but essentially benign: the information that is relevant for prediction is effectively condensed by the first few factors. However, variable selection, leading to exclude some of the low order principal components, can lead to a sizable improvement in forecasting in specific cases. Only in one instance, real personal income, we were able to detect a significant contribution from high order components. "Euro-Dollar Polarization and Heterogeneity in Exchange Rate Pass-Throughs within the Euro Zone" CEIS Working Paper No. 333 MARIAROSARIA COMUNALE, Bank of Lithuania - Economics Department Email:
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This paper provides an empirical study of the asymmetrical spillovers of the euro-US dollar exchange rate on the inflation in the euro zone, dividing the sample in two groups of countries: core and periphery. Then we test if the euro-US dollar exchange rate is still able to give a different impact on the groups’ performance as in the past US dollar-deutschmark polarization phenomenon studying the intra-euro area differences in exchange rate pass-through (ERPT), as an important element of inflation dynamics.
Using a dynamic panel data framework based on an exchange rate pass-through model, we estimate the elasticities of the two groups by system IV-GMM and the common correlated effects mean group estimator, which deals with the presence of cross-sectional dependence.
We conclude that the euro-US dollar is still an important factor, but not the only key factor, in determining the asymmetry in HICP inflation between core and periphery. The nominal effective exchange rate instead is an important driver for the inflation, but only considering the euro zone as a whole.
The EMU seems to not have insulated enough some member countries from nominal external shocks. The nominal effective exchange rate is also a factor to take into account in order to analyze the recent low inflation in the euro zone, even if the size of the ERPT is relatively small. | | ^top
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