Higher order approximations for Wald statistics in time series regressions with integrated processes |
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| Affiliation: | 1. Department of Economics, University of Illinois at Urbana-Champaign, 1206 South Sixth Street, Champaign, IL 61820, USA;2. Cowles Foundation for Research in Economics, Yale University, P.O. Box 208281, New Haven, CT 06520, USA; University of Auckland & University of York;1. Brookings Institution, United States.;2. Center for International Development Harvard University, United States;3. CESifo and IZA, Germany;4. Interamerican Development Bank, United States;5. UNCTAD, Switzerland;6. University of Chile, School of Economics and Business. Dept of Management Ctrl & I.S., Chile;1. Test Evaluation Research Group, University of Birmingham, Birmingham, UK;2. NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, Birmingham, UK;3. Nottingham Clinical Trials Unit, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK;4. Centre for Prognosis Research, School of Primary, Community and Social Care, Keele University, Staffordshire, UK;5. Exeter Test Group, College of Medicine and Health, University of Exeter, Exeter, UK |
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| Abstract: | Asymptotic expansions are developed for Wald test statistics in time series regressions with integrated processes. These expansions provide an opportunity to reduce size distortion in testing by suitable bandwidth selection, and automated rules for doing so are calculated. A band spectral regression and the associated Wald test are also considered. Both the first order and second order properties of the estimator are studied. |
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