Modeling Business Cycles In The Romanian Economy Using The Markov Switching Approach
AbstractI use the Markov Switching AR approach to model the business cycles in Romanian economy for the 1991-2008 period using monthly data on industrial production. The time series used allows for a comparison with previous dating of Romanian business cycles. Generally, the MS-AR performs well, confirming the previous finding about turning points in business cycles during the transition period. At the same time, it suggests that the ongoing recession started earlier than conventionally thought and that it may last more than a year and a half.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Institute for Economic Forecasting in its journal Romanian Journal for Economic Forecasting.
Volume (Year): (2010)
Issue (Month): 1 (March)
Contact details of provider:
Postal: Casa Academiei, Calea 13, Septembrie nr.13, sector 5, Bucureşti 761172
Phone: 004 021 3188148
Fax: 004 021 3188148
Web page: http://www.ipe.ro/
More information through EDIRC
business cycles; Markov switching; nonlinear methods; transition economies; mathematical methods;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
- E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Purica, Ionut & Caraiani, Petre, 2009. "Second Order Dynamics Of Economic Cycles," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 6(1), pages 36-47, March.
- Albu, Lucian Liviu, 2001. "Evolution Of Inflation-Unemployment Relationship In The Perspective Of Romania’S Accession To Eu," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 5-23, December.
- Durland, J Michael & McCurdy, Thomas H, 1994.
"Duration-Dependent Transitions in a Markov Model of U.S. GNP Growth,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 12(3), pages 279-88, July.
- J. Michael Durland & Thomas H. McCurdy, 1993. "Duration Dependent Transitions in a Markov Model of U.S. GNP Growth," Working Papers 887, Queen's University, Department of Economics.
- Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
- Caraiani, Petre, 2004. "Nominal And Real Stylized Facts Of The Business Cycles In Romanian Economy," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 1(4), pages 121-132, December.
- Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
- Cristi SPULBAR & Mihai NITOI & Cristian STANCIU, 2012. "Identifying The Industry Business Cycle Using The Markov Switching Approach In Central And Eastern Europe," Management and Marketing Journal, University of Craiova, Faculty of Economics and Business Administration, vol. 0(2), pages 293-300, November.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Corina Saman).
If references are entirely missing, you can add them using this form.