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Please use this identifier to cite or link to this item: http://hdl.handle.net/2108/355

Title: Measuring core inflation by multivariate structural time series models
Authors: Proietti, Tommaso
Keywords: common trends
dynamic factor analysis
homogeneity
exponential smoothing
Wiener Kolmogorov filter
Issue Date: May-2006
Publisher: CEIS
Series/Report no.: CEIS Tor Vergata Research Paper; 83
Abstract: The measurement of core in°ation can be carried out by optimal signal extraction techniques based on the multivariate local level model, by imposing suitable restrictions on its parameters. The various restrictions correspond to several specialisations of the model: the core inflation measure becomes the optimal estimate of the common trend in a multivariate time series of inflation rates for a variety of goods and services, or it becomes a minimum variance linear combination of the inflation rates, or it represents the component generated by the common disturbances in a dynamic error component formulation of the multivariate local level model. Particular attention is given to the characterisation of the optimal weighting functions and to the design of signal extraction filters that can be viewed as two sided exponentially weighted moving averages applied to a cross-sectional average of individual inflation rates. An empirical application relative to U.S. monthly inflation rates for 8...
URI: http://ssrn.com/abstract=905287
http://hdl.handle.net/2108/355
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