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Canonical correlation analysis of stochastic trends via functional approximation

2024/11/29 by Franchi, Massimo, Georgiev, Iliyan, Paruolo, Paolo
#Econometrics (econ.EM) #FOS: Computer and information sciences #FOS: Economics and business #Methodology (stat.ME)

paper · doi:10.48550/arxiv.2411.19572

Abstract

This paper proposes a novel approach for semiparametric inference on the number s of common trends and their loading matrix ψ 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 ψ 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 ψ are T-consistent, mixed-Gaussian and efficient, so that Wald tests on ψ are asymptotically Normal or χ2. 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≥ 10 p and p≤ 300. An empirical analysis of 20 exchange rates illustrates the methods.

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