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Erscheinungsjahr: 
2001
Schriftenreihe/Nr.: 
SFB 373 Discussion Paper No. 2001,103
Verlag: 
Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes, Berlin
Zusammenfassung: 
This paper develops a new econometric tool for evolutionary autoregressive models where the AR coefficients change smoothly over time. To estimate the unknown functional form of time-varying coefficients, we propose a mdified local linear smoother. The asymptotic normality and variance of the new estimator are derived by extending Phillips and Solo device to the case of evolutionary linear processes. As an application for statistical inference, we show how Wald tests for stationarity and misspecification could be formulated based on finite-dimensional distributions of the kernel estimates. We also examine the finite sample performance of the method via numerical simulations. As an empirical illustration, the method is applied to the real data of US stock returns.
Schlagwörter: 
Autoregressive models
Evolutionary linear processes
Local linear fits
Locally-stationary processes
Phillips and Solo device
Time-varying coefficients
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Dokumentart: 
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