Non-causality in bivariate binary time series |
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Authors: | Rocco Mosconi Raffaello Seri |
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Institution: | 1. Dipartimento di Ingegneria Gestionale, Politecnico di Milano, P.za Leonardo da Vinci 32, 20133 Milano, Italy;2. Dipartimento di Economia, Università degli Studi dell’Insubria, via Ravasi 2, 21100 Varese, Italy |
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Abstract: | In this paper we develop a dynamic discrete-time bivariate probit model, in which the conditions for Granger non-causality can be represented and tested. The conditions for simultaneous independence are also worked out. The model is extended in order to allow for covariates, representing individual as well as time heterogeneity. The proposed model can be estimated by Maximum Likelihood. Granger non-causality and simultaneous independence can be tested by Likelihood Ratio or Wald tests. A specialized version of the model, aimed at testing Granger non-causality with bivariate discrete-time survival data is also discussed. The proposed tests are illustrated in two empirical applications. |
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Keywords: | C50 C33 C35 |
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