Numerical distribution functions of fractional unit root and cointegration tests
AbstractWe calculate, by simulations, numerical asymptotic distribution functions of likelihood ratio tests for fractional unit roots and cointegration rank. Because these distributions depend on a real-valued parameter b which must be estimated, simple tabulation is not feasible. Partly due to the presence of this parameter, the choice of model specification for the response surface regressions used to obtain the numerical distribution functions is more involved than is usually the case. We deal with model uncertainty by model averaging rather than by model selection. We make available a computer program which, given the dimension of the problem, q, and a value of b, provides either a set of critical values or the asymptotic P value for any value of the likelihood ratio statistic.
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Bibliographic InfoPaper provided by Queen's University, Department of Economics in its series Working Papers with number 1240.
Length: 12 pages
Date of creation: May 2012
Date of revision:
fractional unit root; fractional cointegration; likelihood ratio test; model averaging; numerical CDF; response surface regression;
Other versions of this item:
- James G. MacKinnon & Morten Ørregaard Nielsen, 2010. "Numerical distribution functions of fractional unit root and cointegration tests," CREATES Research Papers 2010-59, School of Economics and Management, University of Aarhus.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C16 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Econometric and Statistical Methods; Specific Distributions
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2010-08-06 (All new papers)
- NEP-ECM-2010-08-06 (Econometrics)
- NEP-ETS-2010-08-06 (Econometric Time Series)
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