Original Paper

AStA Advances in Statistical Analysis

, Volume 97, Issue 3, pp 239-270

First online:

Open Access This content is freely available online to anyone, anywhere at any time.

Goodness-of-fit testing for the marginal distribution of regime-switching models with an application to electricity spot prices

  • Joanna JanczuraAffiliated withHugo Steinhaus Center, Institute of Mathematics and Computer Science, Wrocław University of Technology Email author 
  • , Rafał WeronAffiliated withInstitute of Organization and Management, Wrocław University of Technology

Abstract

This paper complements a recently published study (Janczura and Weron in AStA-Adv Stat Anal 96(3):385–407, 2012) on efficient estimation of Markov regime-switching models. Here, we propose a new goodness-of-fit testing scheme for the marginal distribution of such models. We consider models with an observable (like threshold autoregressions) as well as a latent state process (like Markov regime-switching). The test is based on the Kolmogorov–Smirnov supremum-distance statistic and the concept of the weighted empirical distribution function. The motivation for this research comes from a recent stream of literature in energy economics concerning electricity spot price models. While the existence of distinct regimes in such data is generally unquestionable (due to the supply stack structure), the actual goodness-of-fit of the models requires statistical validation. We illustrate the proposed scheme by testing whether commonly used Markov regime-switching models fit deseasonalized electricity prices from the NEPOOL (US) day-ahead market.

Keywords

Regime-switching Energy economics Goodness-of-fit Weighted empirical distribution function Kolmogorov–Smirnov test