[題目] Testing for Structural Changes in Large Dimensional Factor Models via Discrete Fourier Transform

[主講人] 王霞，中山大學嶺南學院

[主持人] 章勇輝，中國人民大學經濟學院

[時間] 2019年9月20日16:00

[地點] 明德主樓729會議室

[摘要] We propose a new test for structural changes in large dimensional factor models via a discrete Fourier transform (DFT) approach. If structural changes exist, the conventional principal component analysis will fail to estimate common factors and factor loadings consistently. The estimated residuals will contain information about structural changes. Therefore, we can compare the DFT of the residuals with the null (zero) spectrum implied by no structural change. The proposed test is powerful against both smooth structural changes and abrupt structural breaks with possibly unknown number of breaks and unknown break dates in factor loadings. It can detect a class of local alternatives at the rate T^{-1/2} N^{-1/2}, where T and N are the numbers of time periods and cross-sectional units. As a result, the test is asymptotically more efficient than the existing tests in the factor model literature. Moreover, it is easy to implement and tuning parameter-free. And our test is robust to serial dependence and cross-sectional dependence of unknown form. Monte Carlo studies demonstrate its reasonable size and excellent power in detecting structural changes of unknown types in factor loadings. In an application to Stock and Watson`s (2012) U.S. macroeconomic data, we find significant and robust evidence against time-invariant factor loadings.

[主講人簡介] 王霞，2013年畢業于廈門大學王亞南經濟研究院，現為中山大學嶺南學院副教授。主要研究興趣包括：理論計量經濟學，時間序列分析，宏觀經濟與貨幣政策，曾在Journal of Econometrics、International Economic Review、Econometric Theory、 Journal of Business & Economic Statistics、《經濟研究》、《管理科學學報》等國內外核心期刊發表論文20余篇。