SMU SOE Seminar (April 3, 2023): Inference in a Stationary/Nonstationary Autoregressive Time-Varying-Parameter Model

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TOPIC:

INFERENCE IN A STATIONARY/NONSTATIONARY AUTOREGRESSIVE TIME-VARYING-PARAMETER MODEL

ABSTRACT Autoregressive models — stationary or nonstationary — are workhorse models in econometric time series. This paper considers nonparametric estimation and inference in autoregressive (AR) models with deterministically time-varying parameters. A key feature of the proposed approach is to allow for time-varying stationarity in some time periods, time-varying nonstationarity (i.e., unit root or local-to-unit root behavior) in other periods, and smooth transitions between the two. We allow for all parameters of the model to be time-varying, not just the AR parameter. The estimation of the AR parameter at any time point is based on the local LS regression method, where the relevant initial condition is endogenous. We introduce a new method to eliminate the impact of the endogenous initial condition on the asymptotics, and obtain limit distributions after proper normalization for the AR parameter when it is unit root, local-to-unity, and stationary/stationary-like. Asymptotic properties for t-statistics are also established. These are used to construct confidence intervals for the AR parameter at any specified point in time. This confidence interval has correct uniform asymptotic coverage probability regardless of the time-varying stationarity/nonstationary behavior of the observations. Click here to view the CV.
		PRESENTER Ming Li National University of Singapore
		RESEARCH FIELDS Econometric Theory
		DATE: 3 April 2023 (Monday)
		TIME: 4pm - 5.30pm
		VENUE: Meeting Room 5.1, Level 5 School of Economics Singapore Management University 90 Stamford Road Singapore 178903

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