| Abstract |
This paper proposes a sieve method to estimate state-varying factor models where the factor loadings vary over certain state variables. We propose a two-step estimation procedure to estimate the parameters of interest. In the first step we obtain a preliminary consistent estimate of the factors and factor loadings via nuclear norm regularization (NNR). In the second step, we conduct the post-NNR iterative least squares estimation of the factors, and factor loadings and establish the asymptotic properties of the estimators. Based on the estimation theory, we propose a test for the null hypothesis of constant factor loadings. We study the asymptotic properties of test statistics under the null and local and global alternatives. Monte Carlo simulations suggest that the proposed estimation and testing methods work well in finite samples. This paper is co-authored with Sainan Jin and Xia Wang. |
| About the speaker |
Liangjun Su is the C.V. Starr Chair Professor of Economics, School of Economics and Management, Tsinghua University. He got PhD in Economics in 2004 from the University of California, San Diego, and has been worked at Peking University and Singapore Management University. Liangjun is a productive researcher. So far, he has published around 100 papers, and most of them are at top econometric or statistical journals, such as Econometrica, Journal of Econometrics, Econometric Theory, JASA, JBES, etc. He has been one of Elsevier Highly Cited Chinese Researchers continuously in the past four years. Currently he is a Co-Editor of Econometric Theory and an Associate Editor of Journal of Econometrics.
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