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Comment On ‘To Criticize The Critics’, By Peter C.B. Phillips, Christopher A. Sims
Comment On ‘To Criticize The Critics’, By Peter C.B. Phillips, Christopher A. Sims
Cowles Foundation Discussion Papers
In his paper “To Criticize the Critics” (1991), Peter Phillips discusses Bayesian methodology for time series models. The main point that Uhlig and I set out to make, however, was that careful consideration of the implications of the likelihood principle suggests that much of the recent work under the “unit root” label in the econometrics literature is being incorrectly interpreted in practice. We pointed out that time series models with possible unit roots are one of the few domains within which the implications of a likelihood principle approach to inference are difference, even in the large samples, from those of …
The Spurious Effect Of Unit Roots On Exogeneity Tests In Vector Autoregressions: An Analytical Study, Hiro Y. Toda, Peter C.B. Phillips
The Spurious Effect Of Unit Roots On Exogeneity Tests In Vector Autoregressions: An Analytical Study, Hiro Y. Toda, Peter C.B. Phillips
Cowles Foundation Discussion Papers
This paper analyzes whether inclusion of a statistically independent random walk in a vector autoregression can result in spurious inference. The problem was raised originally by Ohanian (1988). In a Monte Carlo simulation based on the VAR’s estimated by Sims (1980b, 1982), Ohanian found that block exogeneity of the genuine variables with respect to an artificially generated random walk variable was rejected too often. In the present paper we attempt a full analytical study of this problem. It can be shown that if the genuine variables are nonstationary, the Wald statistic for testing the block exogeneity hypothesis does not have …
Exactly Unbiased Estimation Of First Order Autoregressive/Unit Root Models, Donald W.K. Andrews
Exactly Unbiased Estimation Of First Order Autoregressive/Unit Root Models, Donald W.K. Andrews
Cowles Foundation Discussion Papers
This paper is concerned with the estimation of first-order autoregressive/unit root models with independent identically distributed normal errors. The models considered include those without an intercept, those with an intercept, and those with an intercept and time trend. The autoregressive (AR) parameter alpha is allowed to lie in the interval (-1,1], which includes the case of a unit root. Exactly median-unbiased estimators of the AR parameter alpha are proposed. Exact confidence intervals for this parameter are introduced. Corresponding exactly median-unbiased estimators and exact confidence intervals are also provided for the impulse response function and the cumulative impulse response. An unbiased …