14:00 鈥� 15:00 鈥� Massimo Franchi
Title: Canonical correlation analysis of stochastic trends via functional approximation
Abstract: This paper proposes a novel approach for semiparametric inference on the number s of common trends and their loading matrix 蠄 in I(1)/I(0) systems. It combines functional approximation of limits of random walks and canonical correlations analysis, performed between the p observed time series of length T and the first K discretized elements of an L2 basis. Tests and selection criteria on s, and estimators and tests on 蠄 are proposed; their properties are discussed as T and K diverge sequentially for fixed p and s. It is found that tests on s are asymptotically pivotal, selection criteria of s are consistent, estimators of 蠄 are T -consistent, mixed-Gaussian and efficient, so that Wald tests on 蠄 are asymptotically Normal or 蠂2. The paper also discusses asymptotically pivotal misspecification tests for checking model assumptions. The approach can be coherently applied to subsets or aggregations of variables in a given panel. Monte Carlo simulations show that these tools have reasonable performance for T 鈮� 10p and p 鈮� 300. An empirical analysis of 20 exchange rates illustrates the methods. Joint work with I. Georgiev and P. Paruolo.
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