Publisher:
University of Pavia, Department of Economics and Quantitative Methods, Pavia
This paper aims to construct a high-frequency coincident indicator of economic activity for Lombardy and for the provinces of Milan and Pavia, by using the dynamic factor model approach introduced by Stock e Watson (1998a e 1998b). The principal...
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ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
Signature:
DS 157 (2012,158)
Inter-library loan:
No inter-library loan
This paper aims to construct a high-frequency coincident indicator of economic activity for Lombardy and for the provinces of Milan and Pavia, by using the dynamic factor model approach introduced by Stock e Watson (1998a e 1998b). The principal component analysis is first used to summarize the information contained in a large dataset in a limited number of common factors capable of capturing the main features of local business fluctuations. The EM (Expectation Maximization) algorithm then allows to compute the desired territorial indicators by taking into account the official annual data on regional GDP or provincial valueadded growth.
