The Role of Ancillarity in Inference for Non-stationary Variables
AbstractSome examples of the regression method are compared with likelihood-based inference. It is shown that, although the asymptotic theory is distinctly different for ergodic and nonergodic processes, the likelihood methods lead to the result that asymptotic inference can be conducted in the same way for the two cases by appealing to classical conditioning arguments from statistics using the notion of S-ancillarity or strong exogeneity. It is pointed out that the Fisher information can be considered a measure of the conditional variance of the maximum likelihood estimator given the available information in the sample. Copyright 1995 by Royal Economic Society.
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Bibliographic InfoArticle provided by Royal Economic Society in its journal The Economic Journal.
Volume (Year): 105 (1995)
Issue (Month): 429 (March)
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- Arvid Raknerud, 2001. "A State Space Approach for Estimating VAR Models for Panel Data with Latent Dynamic Components," Discussion Papers 295, Research Department of Statistics Norway.
- Søren Johansen, 2010.
"An Extension of Cointegration to Fractional Autoregressive Processes,"
10-28, University of Copenhagen. Department of Economics.
- Søren Johansen, 2011. "An extension of cointegration to fractional autoregressive processes," CREATES Research Papers 2011-06, School of Economics and Management, University of Aarhus.
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