SMU SOE Online Job Talk Practice (Dec 13, 2021, 4.00pm-5.30pm): Unified Factor Model Estimation and Inference under Short and Long Memory

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TOPIC:

UNIFIED FACTOR MODEL ESTIMATION AND INFERENCE UNDER SHORT AND LONG MEMORY

ABSTRACT This paper studies a panel linear regression model with interactive fixed effects wherein regressors, factors and idiosyncratic error terms are all stationary but with potential long memory. The setup involves a new factor model formulation for which weakly dependent regressors, factors and innovations are embedded as a special case. Standard methods based on principal component decomposition and least squares estimation, as in Bai (2009), are found to suffer bias correction failure because the order of magnitude of the bias is determined in a complex manner by the memory parameters. To cope with this failure and to provide a simple implementable estimation procedure, frequency domain least squares estimation is proposed. The limit distribution of this frequency domain approach is established and a hybrid selection method is developed to determine the number of factors. Simulations show that the frequency domain estimator is robust to short memory and outperforms the time domain estimator when long range dependence is present. An empirical illustration of the approach is provided, examining the long-run relationship between debt and economic growth. Click here to view the speaker's CV.		This job talk practice will be held virtually via Zoom. Click here to join Zoom meeting Meeting ID: 926 6047 2519 Passcode: 131221
		PRESENTER Shuyao Ke Singapore Management University
		RESEARCH FIELDS Econometric Theory Financial Econometrics Macroeconomics
		DATE: 13 December 2021 (Monday)
		TIME: 4.00pm - 5.30pm

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