Approximate Asymptotic Distribution Functions for Unit-Root and Cointegration Tests

James MacKinnon

Journal of Business & Economic Statistics, 1994, vol. 12, issue 2, 167-76

Abstract: Monte Carlo experiments and response surface regressions are used to calculate approximate asymptotic distribution functions for a number of well-known unit root and cointegration test statistics. These allow empirical workers to calculate approximate P values for these tests. The results of the paper are based on an extensive set of Monte Carlo experiments, which yield finite-sample quantiles for several sample sizes. Response surface regressions are then used to obtain asymptotic quantiles for a large number of different test sizes. Finally, approximate distribution functions with simple functional forms are estimated from these asymptotic quantiles.

Date: 1994
References: Add references at CitEc
Citations: View citations in EconPapers (192)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Working Paper: Approximate Asymptotic Distribution Functions for Unit Roots and Cointegration Tests (1992)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bes:jnlbes:v:12:y:1994:i:2:p:167-76

Ordering information: This journal article can be ordered from
http://www.amstat.org/publications/index.html

Access Statistics for this article

Journal of Business & Economic Statistics is currently edited by Jonathan H. Wright and Keisuke Hirano

More articles in Journal of Business & Economic Statistics from American Statistical Association
Bibliographic data for series maintained by Christopher F. Baum (baum@bc.edu).