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Flexible Estimation of Copulas: An Application to the US Housing Crisis
Author(s) -
Ho Anson T. Y.,
Huynh Kim P.,
JachoChávez David T.
Publication year - 2015
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.2437
Subject(s) - copula (linguistics) , econometrics , nonparametric statistics , estimator , replicate , parametric statistics , gaussian , computer science , economics , mathematics , statistics , physics , quantum mechanics
Summary Zimmer (‘The role of copulas in the housing crisis’, Review of Economics and Statistics 2012; 94 : 607–620) provides an interesting case study of the pitfalls of using parametric copulas to understand the US housing crisis in the latter part of 2000s. The original study by Zimmer (2012) employs a finite‐mixture copula to illustrate that the symmetry of the Gaussian copula may not be tenable, especially for US housing price data during the time period from 1975:Q2 to 2009:Q1. We undertake a replication of his study in a wide sense. First, we replicate the study by incorporating revised data and then extending the dataset to include the most recent data. Second, we implement a nonparametric copula estimator recently proposed by Racine (‘Mixed data kernel copulas’, Empirical Economics forthcoming) to the parametrically filtered data used in Zimmer (2012). Our replication finds that the application of the nonparametric copula to the same and extended filtered data provides an alternative flexible specification for copulas. However, the overall cautionary message of the flexible‐form copula espoused in Zimmer (2012) remains. Copyright © 2015 John Wiley & Sons, Ltd.