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  • Testing for common nonlinearities in a real tolar - euro exchange rate model
    Kavkler, Alenka ; Böhm, Bernhard
    This empirical investigation applies the common nonlinearities techniques to small models of the real exchange rate, decomposed into its three components, domestic prices, foreign prices and the ... nominal exchange rate. Five most important foreign trade partners of Slovenia are included in the study, namely Germany, Italy, France, Austria and Croatia. The canonical correlations approach for modelling multiple equation systems with common nonlinear components of a smooth transition type is discussed. The coefficients in a smooth transition regression model are assumed to be nonlinear continuous functions of a properly chosen transition variable. The obtained model thus captures structural changes in the relationship between the observed economic variables. With the help of the canonical correlations technique a simple test for testing for common nonlinear components in a multiple equation system can be derived. Knowledge about common nonlinear components helps us interpret the relationships between different economic variables and also simplifies the specification and estimation of the equation system, since in this case reduction in the dimension of nonlinear components is possible. It was shown by Anderson and Vahid that the test for common nonlinearities is related to the test statistic for overidentifying restrictions in the generalized method of moments framework and that both tests have the same asymptotic distribution. A single common nonlinear component is detected only in the real exchange rate model of the Slovenian Tolar versus the Austrian Schilling, respectively Euro, and the obtained nonlinear logistic smooth transition vector autoregressive (LSTVAR) model is discussed.
    Vir: Proceedings of the 2nd International Workshop on Micro and Macro Models in Economics, September 2006, Bratislava, Slovak Republic (Str. 65-84)
    Vrsta gradiva - prispevek na konferenci
    Leto - 2006
    Jezik - angleški
    COBISS.SI-ID - 9077788

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