KONJONKTÜRÜN DÖNÜM NOKTALARININ TAHMİNİ İÇİN BİR PROBİT MODELİ: TÜRKİYE ÖRNEĞİ

Bu çalışmanın amacı Türkiye’de konjonktür dalgalarının dönüm noktalarının tahminidir. Çalışmada dönüm noktasının tanımının ardından, literatürde kullanılan yöntemler ve bu yöntemlerin Türkiye’ye uygunluğu incelenmiştir. Türkiye için en uygun tahmin yönteminin Probit modelleri olduğu tespit edilmiştir. Diğer tahmin yöntemlerinin konjonktürün resesyon ve genişleme fazlarını, aynı yapının farklı anları varsayması ve Türkiye’deki işsizlik serileri gibi bazı serilerin sağlıklı olmaması bu tercihte önemli rol oynamıştır.

Anahtar Kelimeler:

Konjonktür dalgalarının dönüm noktaları, Probit modelleri, Konjonktür dalgaları

This paper aims to predict the turning points of Turkish business cycles for the period of 1987:Q4–2004:Q2. After defining a turning point and possible estimation methods it has been developed a probit model for estimating the probability of a turning point. The model performs better than some other methods for predicting turning points. Because other estimation methods suppose that the underlying structure of the economy does not change from a recession to an expansion. In these models the underlying structure is stable and can be described, or at least approximated, by a linear probabilistic model.

Keywords:

Turning points of the business cycles, Probit Models, Business cycles,

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BOLDIN, Micheal D. (1994), “Data turning point in the business cycle,” The Journal of Business, 67(1), 97-137.
BOLDIN, Micheal D. (1992), “Using Switching Models to Study Business Cycle Asymmeties: Overview of Methodology and Application,” Federal Reserve Bank Of New York, Research paper, (9211) New York.
BURNS, Arthur F. ve Mıtchell C. WESLEY (1946), “Measuring Business Cycles,” New York: National Bureau of Economic Research.
ESTRELLA, Arturo ve Gikas HARDOUVELIS (1991), “The Term Structure as a Predictor of Real Economic Activity,” Journal of Finance, (46) 555–76.
ESTRELLA, Arturo ve Frederic S. MISHKIN (1998), “Predicting U.S. Recessions: Financial Variables as Leading Indicators,” The Review of Economics and Statistics, (80), 45–61.
HAMİLTON, James (1989), “A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle,” Econometrica, (57), 357–84.
KAMINSKY, Graciela. ve Carmen M. REINHART (1996), “The Twin Crises: Causes of Banking And Balance of Payments Problems,” International Finance Discussion Paper,(544),1996.
KASMAN, K. Saadet, Adnan KASMAN ve Evrim TURGUTLU (2005), “Fisher Hypothesis Revisited: A Fractional Cointegration Analysis” Dokuz Eylül University Faculty of Business Department of Economics, Discussion Paper series, 04(05), October 2005.
KLING, John. L. (1987), “Predicting the Turning Points of the Business and Economic Time Series,” The Journal of Business, 60(2), 201-238.
MOORE, Geoffrey H. ve Victor ZARNOWITZ (1986), “The Development and Role of the National Bureau of Economic Research's Business Cycle Chronologies,” The American business cycle: Continuity and change içinde, University of Chicago Press, Chicago.
NEFTÇİ, N. Salih (1982), “Optimal Prediction of Cyclical Downturns” Journal of Economic Dynamics and Control, 4(3), 225-241.
NEGRO, D. Marco (2001), Federal Reserve Bank Of Atlanta , Economic Review (2), 1-12 .
STOCK, James ve Mark WATSON (1989), “New Indexes of Coincident and Leading Indicators,” O. Blanchard ve S. Fischer (der.) NBER Macroeconomic Annual içinde, 351–94.
WECKER, F. William (1979), “Predicting the Turning Points of a Time Series” The Journal of Business, (52), 35-50.