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Simulation Encompassing: Testing Non‐nested Hypotheses *
Author(s) -
Lu Maozu,
Mizon Grayham E.,
Monfardini Chiara
Publication year - 2008
Publication title -
oxford bulletin of economics and statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.131
H-Index - 73
eISSN - 1468-0084
pISSN - 0305-9049
DOI - 10.1111/j.1468-0084.2008.00530.x
Subject(s) - wald test , test statistic , mathematics , statistics , statistic , nested set model , monte carlo method , covariance , covariance matrix , statistical hypothesis testing , econometrics , computer science , data mining , relational database
This paper considers simulation‐based procedures to compute the Wald encompassing and the Cox test statistics for non‐nested models. These simulation estimation procedures are applied to both the encompassing contrast and its covariance matrix in the case of a Wald non‐nested test statistic, and both the numerator and the denominator in the Cox test statistic. The proposed procedures are illustrated by the example of comparing a linear with a log‐linear model. Monte Carlo studies are conducted for both examples and the results indicate that with simulated covariance matrices, the small sample behaviour of both test statistics is close to that of their asymptotic distributions.