Time series models of GDP: a reappraisal
AbstractWe propose a model diagnostic device to compare different linear and non linear parametric time series models of real GDP business cycle.The comparison appears of remarkable economic importance since different models have very different implications in term of long run persistence of negative shocks on the level of aggregate output.On the basis of the proposed diagnostic six popular models of real GDP are compared in a Monte Carlo simulation.We find that SETAR models and three stages Markov-switching models significantlly overperform the other statistical representation of the series.Since the SETAR form of non linearity is far easier to handle for both estimation and testing we argue in their favour.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 36389.
Date of creation: 2010
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SETAR models; ARMA models; Markov-switching models; impulse response functions; residual based misspecification tests; busyness-cycle stylized facts;
Find related papers by JEL classification:
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
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