SMU SOE Online Job Talk Practice (Nov 17, 2021, 4.00pm-5.30pm): Analysis of Large Real Estate Prices Data: A High-Order Spatiotemporal Autoregression Approach

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ABSTRACT Real estate prices arrive sequentially on different housing units over time in a large volume. In this paper, we propose a high-order spatiotemporal autoregressive model with unobserved cluster and time heterogeneity. When the numbers of clusters (C) and time segments (T) are finite and the errors are iid, quasi maximum likelihood method is used for model estimation and inference. In the presence of unknown heteroskedasticity, or C and/or T is large, an adjusted quasi score method is proposed for model estimation and inference. Methods for constructing the space-time connectivity matrices are proposed. Monte Carlo experiments are performed for assessing the finite sample properties of the proposed methods. An empirical application is presented using the housing transaction data in Beijing. We find that the estimation of the spatiotemporal interaction effects are largely affected after controlling for cluster heterogeneity at the community level. 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: 948 0594 6499 Passcode: 171121
		PRESENTER Yifan Wu Singapore Management University
		RESEARCH FIELDS Urban Economics Real Estate Economics Finance Spatial Econometrics
		DATE: 17 November 2021 (Wednesday)
		TIME: 4.00pm - 5.30pm