Estymowane modele równowagi ogólnej: zastosowanie metody dekompozycji funkcji do oceny zależności między parametrami postaci strukturalnej i zredukowanej

The paper presents the application of high dimensional model representation to characterise the relationship between structural and reduced form coefficients of estimated general equilibrium models. The function representation is considered a state-dependent regression that is estimated non-parametrically, based on Monte Carlo sample, and generated from the probability distribution of structural parameters. The estimation method consists of recursive filtering and smoothing algorithms, derived from the Kalman filter, enhanced with special data re-ordering, to capture strong variability of the parameters in the state-dependent regression. The estimated function decomposition is used to build sensitivity indices. The methodology presented is illustrated with an example from the literature.