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Inference in linear time series models with some unit roots. (English) Zbl 0724.62087
Summary: This paper considers estimation and hypothesis testing in linear time series models when some or all of the variables have unit roots. Our motivating example is a vector autoregression with some unit roots in the companion matrix, which might include polynomials in time as regressors. In the general formulation, the variable might be integraded or cointegrated of arbitrary orders, and might have drifts as well.
We show that parameters that can be written as coefficients on mean zero nonintegrated regressors have jointly normal asymptotic distributions, converging at the rate \(T^{1/2}\). In general, the other coefficients (including the coefficients on polynomials in time) will have nonnormal asymptotic distributions. The results provide a formal characterization which t or F tests - such as Granger causality tests - will be asymptotically valid, and which will have nonstandard limiting distributions.

62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
62E20 Asymptotic distribution theory in statistics
62F03 Parametric hypothesis testing
62F10 Point estimation
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