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Media type:
E-Article
Title:
The Estimation of Threshold Models in Price Transmission Analysis
Contributor:
Greb, Friederike;
von Cramon-Taubadel, Stephan;
Krivobokova, Tatyana;
Munk, Axel
Published:
Wiley, 2013
Published in:
American Journal of Agricultural Economics, 95 (2013) 4, Seite 900-916
Language:
English
DOI:
10.1093/ajae/aat006
ISSN:
0002-9092;
1467-8276
Origination:
Footnote:
Description:
The threshold vector error correction model is a popular tool for the analysis of spatial price transmission. In the literature, the profile likelihood estimator is the preferred choice for estimating this model. Yet, in many settings this estimator performs poorly. In particular, if the true thresholds are such that one or more regimes contain only a small number of observations, if unknown model parameters are numerous, or if parameters differ little between regimes, the profile likelihood estimator displays large bias and variance. Such settings are likely when studying price transmission. We analyze the weaknesses of the profile likelihood approach and propose an alternative regularized Bayesian estimator, which was developed for simpler but related threshold models. Simulation results show that the regularized Bayesian estimator outperforms profile likelihood in the estimation of threshold vector error correction models. Two empirical applications demonstrate the relevance of this new estimator for spatial price transmission analysis.