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A New Structural Break Test for Panels with Common Factors

Huanjun Zhu, Vasilis Sarafidis () and Mervyn Silvapulle

No 2019-07-09, Working Papers from Wang Yanan Institute for Studies in Economics (WISE), Xiamen University

Abstract: This paper develops new tests against a structural break in panel data models with common factors when T is fixed, where T denotes the number of observations over time. For this class of models, the available tests against a structural break are valid only under the assumption that T is ‘large’. However, this may be a stringent requirement; more commonly so in datasets with annual time frequency, in which case the sample may cover a relatively long period even if T is not large. The proposed approach builds upon existing GMM methodology and develops Distance-type and LM-type tests for detecting a structural break, both when the breakpoint is known as well as when it is unknown. The proposed methodology permits weak exogeneity and/or endogeneity of the regressors. In a simulation study, the method performed well, both in terms of size and power, as well as in terms of successfully locating the time of the structural break. The method is illustrated by testing the so-called ‘Gibrat’s Law’, using a dataset from 4,128 financial institutions, each one observed for the period 2002-2014.

Keywords: Method of moments; unobserved heterogeneity; break-point detection; fixed T asymptotics. (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2019-07-09
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