IDENTIFYING THE INDUSTRY BUSINESS CYCLE USING THE MARKOV SWITCHING APPROACH IN CENTRAL AND EASTERN EUROPE Cover Image

IDENTIFYING THE INDUSTRY BUSINESS CYCLE USING THE MARKOV SWITCHING APPROACH IN CENTRAL AND EASTERN EUROPE
IDENTIFYING THE INDUSTRY BUSINESS CYCLE USING THE MARKOV SWITCHING APPROACH IN CENTRAL AND EASTERN EUROPE

Author(s): Cristian Stanciu, Mihai Niţoi, Cristi Marcel Spulbar
Subject(s): Economy
Published by: Editura Universitaria Craiova
Keywords: business cycle; Markov Switching model; Romanian economy; transition economies

Summary/Abstract: In this article we use a Markov Switching model with two lags to identify and to compare the business cycle in Romania, Czech Republic, Hungary and Poland using data on industrial production for the 1991-2011 period. We use a model with two regimes that reflect the economic expansions and contractions. The Markov Switching models have been widely used in order to detect and to date the business cycle turning points. However, it should be pointed out that the industrial production may have a little bit different dynamics than the quarterly gross domestic product which is the main measure of economic activity. Based on the smoothed regime probabilities the model track three recessionary periods of the Romanian economy in 1991, 1997 and 2009 and two recessionary periods for the other countries in 1991 and 2009. Mean yoy growth of IPI is 5.01% during expansion periods, while it switches to -18.6% during contraction periods for the Romanian economy. In comparison, mean yoy growth of IPI is 7.25% during expansion periods, while it switches to -13.4% during contraction periods for the Poland economy. Furthermore, in Romania, the duration of the three recessions in months was 25, 25 and 9 months. In Poland, the duration of the two recessions was 16 and 10 months. The results of the study may be used in order to compare the business cycle in Central and Eastern European countries with the Euro Area business cycle.

  • Issue Year: 2012
  • Issue No: 2
  • Page Range: 293-300
  • Page Count: 8
  • Language: English