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Information Journal Paper

Title

DETECTING OF TURNING POINTS IN BUSINESS CYCLES OF IRANIAN ECONOMY THROUGH AUTOREGRESSIVE MARKOV SWITCHING MODEL

Pages

  1-25

Abstract

 This study was to investigate, TURNING POINTS in BUSINESS CYCLEs in the economy of Iran using seasonal date during (1981:1-2008:2). To make it practical AUTOREGRESSIVE MARKOV SWITCHING MODEL by Hamilton (1989) was used. Today this approach is used in many advanced countries in order to identify and dating of cycle. Results showed that in that period in three junctures four records happened. The longest records are during [1991:2-1998:2], with the duration of 7 seasons. In addition to that results showed that in under discussion period every time a record happens in countries for about 1.74 seasons. While the appearance of every Boom in under discussion period in the economy of Iran continued 6.66 seasons.

Cites

References

Cite

APA: Copy

HOJABR KIANI, K., & MORADI, A.. (2011). DETECTING OF TURNING POINTS IN BUSINESS CYCLES OF IRANIAN ECONOMY THROUGH AUTOREGRESSIVE MARKOV SWITCHING MODEL. ECONOMIC MODELLING, 5(2 (14)), 1-25. SID. https://sid.ir/paper/176375/en

Vancouver: Copy

HOJABR KIANI K., MORADI A.. DETECTING OF TURNING POINTS IN BUSINESS CYCLES OF IRANIAN ECONOMY THROUGH AUTOREGRESSIVE MARKOV SWITCHING MODEL. ECONOMIC MODELLING[Internet]. 2011;5(2 (14)):1-25. Available from: https://sid.ir/paper/176375/en

IEEE: Copy

K. HOJABR KIANI, and A. MORADI, “DETECTING OF TURNING POINTS IN BUSINESS CYCLES OF IRANIAN ECONOMY THROUGH AUTOREGRESSIVE MARKOV SWITCHING MODEL,” ECONOMIC MODELLING, vol. 5, no. 2 (14), pp. 1–25, 2011, [Online]. Available: https://sid.ir/paper/176375/en

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