Tests of Non-Causality Under Markov Assumptions for Qualitative Panel Data

For many years, social scientists have been interested in obtaining testable definitions of causality [C. W. Granger (1969)]. Recent works include those of G. Chamberlain (1982) and J. P. Florens and M. Mouchart (1982). The present paper first clarifies the results of these latter papers by considering a unifying definition of non-causality. Then, log-likelihood ratio (LR) tests for non-causality are derived for qualitative panel data under the minimal assumption that one series is Markov. LR tests for the Markov property are also obtained. Both test statistics have closed forms. These tests thus provide a readily applicable procedure for testing non-causality on qualitative panel data. Finally, the tests are applied to French Business Survey data in order to test the hypothesis that price changes from period to period are strictly exogenous to disequilibria appearing within periods.