Distinguishing Time-Varying Factor Models

Time-varying factor models have been widely used to model changing relationships among economic and financial variables. The existing literature usually specifies the time-varying factor loadings as deterministic functions of time or unit root processes. This paper proposes two consistent tests to distinguish these two specifications based on a randomization approach. By setting the null hypothesis as either specification, we show that the proposed test statistics follow an asymptotic chi-squared distribution under the respective null hypotheses and diverge to infinity in probability under the respective alternatives. Simulation studies reveal that both test statistics perform reasonably well in finite samples. We apply the proposed tests to the U.S. macroeconomic and global macroeconomic and financial datasets. The results suggest that the time-varying factor loadings as deterministic functions of time should be adopted for these two applications.

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Publication Details

Journal
Journal of Business and Economic Statistics
Published
2024-08-26
DOI
https://doi.org/10.1080/07350015.2024.2395424
Citations
3
Primary Topic
Complex Systems and Time Series Analysis
Type
article
Field-Weighted Citation Impact
3.39

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article

Distinguishing Time-Varying Factor Models

Zhonghao Fu, Liangjun Su, Xia Wang
3 citations
Journal of Business and Economic Statistics
Complex Systems and Time Series Analysis
3.39
article

Distinguishing Time-Varying Factor Models

Zhonghao Fu, Liangjun Su, Xia Wang
article en
3 citations

Abstract

Time-varying factor models have been widely used to model changing relationships among economic and financial variables. The existing literature usually specifies the time-varying factor loadings as deterministic functions of time or unit root processes. This paper proposes two consistent tests to distinguish these two specifications based on a randomization approach. By setting the null hypothesis as either specification, we show that the proposed test statistics follow an asymptotic chi-squared distribution under the respective null hypotheses and diverge to infinity in probability under the respective alternatives. Simulation studies reveal that both test statistics perform reasonably well in finite samples. We apply the proposed tests to the U.S. macroeconomic and global macroeconomic and financial datasets. The results suggest that the time-varying factor loadings as deterministic functions of time should be adopted for these two applications.

Journal of Business and Economic StatisticsVol. 43(3)
Fudan University (CN), Renmin University of China (CN), Shanghai University of International Business and Economics (CN), Tsinghua University (CN)
National Natural Science Foundation of China
Decent work and economic growth
Openalex Percentile: Top 6%
Complex Systems and Time Series Analysis
3.39
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