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HAM PETROL FİYATLARI VE DÖVİZ KURU: MARKOV-GEÇİŞ HATA DÜZELTME MODELİ

Year 2018, Volume: 3 Issue: 1, 339 - 347, 31.03.2018
https://doi.org/10.29106/fesa.405987

Abstract

Petrol piyasasında ki olağanüstü fiyat dalgalanmaları küresel ekonomi
üzerinde etkili olmaktadır.  
Bretton Woods’un
çöküşüyle birlikte petrol fiyatları ve döviz kurlarında uzun süreli salınımlar meydana
gelmiştir.  Petrol
fiyat şokları dolayısıyla enerji piyasasında meydana gelen dengesizlikteki
artış döviz kurlarına yönelik ilgiyi arttırmaktadır. Petrol arzı
şoklarının ekonomi üzerindeki etkilerinin genellikle dış kaynaklı olması ve
fiyatlardaki a
şırı değişimler hem petrol
ithal/ihraç eden ülkelerdeki politika üreticilerini hem de uluslararası
yatırımcıları etkilemektedir.
Krizin kapsamı ve süresi
ile ilgili belirsizlik arttıkça, petrol fiyatlarındaki dalgalanmaların yükselen
piyasalar üzerindeki etkilerinin incelenmesi önemli hale gelmektedir. Ekonomik
büyümenin enerji büyümesiyle ilişkili olması nedeniyle gelişmekte olan ülkeler
petrol fiyatlarındaki değişimlere karşı daha korunmasızdır. Gelişmiş ekonomiler
ve petrol ihraç eden ülkeler genellikle literatürde incelenmesine rağmen,
gelişmekte olan
ülkelerin kuruna odaklanarak petrol fiyatları ile döviz kuru arasındaki doğrusal
olmayan ilişkiyi açıklamaya çalışan çok fazla çalışma bulunmamaktadır. Makale
kapsamında, 1980:01-2017:06 aylık dönemleri için ham petrol fiyat seviyeleri ve
döviz kuru arasındaki ilişki Markov geçiş vektör hata düzeltme modeli
çerçevesinde incelenmektedir. 

References

  • Abed, R.E.L., Amor, T.H., ve Nouira, R. (2016), Asymmetric effect and dynamic relationships between oil prices shocks and exchange rate volatility: Evidence from some selected MENA countries. Middle East Economic Association, 15th The International Conference Doha, Qatar, March, 1-24.
  • Amano, R. ve Norden S. (1998), Exchange Rates and Oil Prices, Review of International Economics, Vol. 6, No. 4, pp. 683–94.
  • Balke, N.S.ve Fomby, T.B. (1997), Threshold Cointegration. International Economic Review, 38(3), 627-645.
  • Beckmann, J. ve Czudaj, R. (2012), Oil Price and U.S. Dollar Exchange Rates Dynamics, University of Duisburg- Essen, Department of Economics.
  • Breitenfellner, A. and Cuaresma J. C. (2008), Crude Oil Prices and the Euro-Dollar Exchange Rate: A Forecasting Exercise. University of Innsbruck, Working Papers in Economics and Statistics, No. 2008-08.
  • Coudert, V., Mignon, V. ve Penot, A. (2008), Oil Price and the Dollar, Energy Studies Review, Vol. 15, No. 2, pp. 45–58.
  • Dempster, A.P., Laird, N.M. ve . Rubin, D.B (1977), Maximum Likelihood Estimation from Incomplete Data via the EM Algorithm. Journal of the Royal Statistical Society, 39 (Series B), 1–38.
  • Dewachter, H. (1997), Sign Predictions of Exchange Rate Changes: Charts as Proxies for Bayesian inferences,Weltwirtschaftliches Archiv, Vol. 133, pp. 39–55. Diebold, F. X., Lee, J.-H. ve Weinbach, G. C., (1994), Regime switching with time-varying transition probabilities. In C. Hargreaves (ed.) Nonstationary Time Series Analysis and Cointegration, pp. 283–302, Oxford: Oxford University Press.
  • Durland, J. M. ve McCurdy, T. H., (1994).,Duration-dependent transitions in a Markov model of U.S. GNP growth. Journal of Business and Economic Statistics 12, 279–288.
  • Enders, W. ve Dibooglu, S. (2001), Long-run Purchasing Power Parity with Asymmetric Adjustment, Southern Economic Journal, Vol. 68, No. 2, pp. 433–45.
  • Engel, C. ve Hamilton, J. (1990), Long Swings in the Dollar: Are They in the Data and do Market Know It?, American Economic Review, Vol. 80, pp. 687–713.
  • Ehrmann, M., Ellison, M. ve Valla N., (2003). Regime-dependent impulse response functions in a Markov-switching vector autoregression model. Economics Letters 78, 295–299.
  • Evans, M. ve . Lewis, K (1995), ‘Do Long-term Swings in the Dollar Affect Estimates of the Risk Premia?’, Review of Financial Studies, Vol. 8, pp. 709–42.
  • Fan, J ve Yao, Q., (2003). Nonlinear Time Series: NonparametrPsaric and Parametric Methods. New York: Springer.
  • Filardo, A. J., (1994). Business-cycle phases and their transitional dynamics. Journal of Business and Economic Statistics 12, 299–308.
  • Filardo, A. J. ve Gordon, S. F., (1998). Business cycle durations. Journal of Econometrics 85, 99–123
  • Ghysels, E,. (1994), On the periodic structure of the business cycle. Journal of Business and Economic Statistics 12, 289–298.
  • Granger, C. W. J., (1996), Can we improve the perceived quality of economic forecasts? Journal of Applied Econometrics 11, 455-473.
  • Hamilton, J. (1989), A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle, ,Econometrica, Vol. 57, pp. 357–84.
  • Hamilton, J. D., (1994). Time Series Analysis. Princeton, NJ: Princeton University Press.
  • Hansen, B. E.(2001), The new econometrics of structural change: dating breaks in U.S. labor productivity. The Journal of Economic Perspectives 15, 117–128.
  • Hansen, B.E. ve Seo, B. (2002), Testing for Two-Regime Threshold Cointegration in Vector Error-Correction Models. Journal of Econometrics, 110(2), 293-318.
  • Huang, Y. ve Guo F. (2007), The Role of Oil Price Shocks on China’s Real Exchange Rate, China Economic Review, Vol. 18,pp. 403–16.
  • Ihle, R. ve Cramon-Taubadel, S. ,(2008),A Comparison of Threshold Cointegration and Markov-Switching Vector Error Correction Models in Price Transmission Analysis. Proceedings of the NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management, St. Louis, MO.
  • Indjehagopian, J., F. Lantz ve Simon, V.,(2000), Dynamics of Heating Oil Market Prices in Europe, Energy Economics, Vol. 22, No. 2, pp. 225–52.
  • Kaminsky, G. (1993), Is There a Peso Problem? Evidence from the Dollar/Pound Exchange Rate, 1976–1987, American Economic Review, Vol. 83, pp. 450–72.
  • Kilian, L. ve Taylor, M. P. (2003), Why is it so Difficult to Beat the Random Walk Forecast of Exchange Rates. Journal of International Economics, 60(1), 85-107.
  • Kim, M.-J. ve Yoo, J.-S., (1995), New index of coincident indicators: A multivariate Markov switching factor model approach. Journal of Monetary Economics 36, 607– 630.
  • Krolzig, H.-M., 1997. Markov Switching Vector Autoregressions Modelling: Statistical Inference and Application to Business Cycle Analysis. Berlin: Springer.
  • Krolzig, H.-M.,(1999), Statistical analysis of cointegrated VAR processes with Markovian regime shifts. Working Paper # 1113, Computing in Economics and Finance 1999, Society for Computational Economics
  • Krolzig, H.-M., Marcellino, M. ve Mizon, G. E., (2002.), A Markov-switching vector equilibrium correction model of the UK labor market. Empirical Economics 27, 233-254.
  • Krolzig, H.-M., (2006), Impulse response analysis in Markov switching vector autoregressive models. Economics Department, University of Kent. Keynes College.
  • Lindgren, G., (1978), Markov regime models for mixed distributions and switching regressions. Scandinavian Journal of Statistics 5, 81-91.
  • Lizardo, R., ve Mollick A., (2010), Oil Price Fluctuations and U.S. Dollar Exchange Rates, Energy Economics 32, no. 2: 399–408.
  • Lo, M.C. ve Zivot E. (2001), Threshold Cointegration and Nonlinear Adjustment to the Law of One Price. Macroeconomic Dynamics, 5(4), 533-576.
  • Perron, P. (2006), Dealing with Structural Breaks. Palgrave Handbook of Econometrics 1, 278–352.
  • Reboredo, J.C. (2012), Modelling Oil Price and Exchange Rate Co-Movements. Journal of Policy Modeling, 34(3), 419-440.
  • Saikkonen, P. (1992), Estimation and Testing of Cointegrated Systems by an Autoregressive Approximation. Econometric Theory, 8(1), 1-27.
  • Saikkonen, P. ve . Luukkonen R,(1997), Testing Cointegration in Infinite Order Vector Autoregressive Processes. Journal of Econometrics, 81(1), 93-126.
  • Teräsvirta, T, (1994), Specification, Estimation and Evaluation of Smooth Transition Autoregressive Models, Journal of the American Statistical Association, 89(425), 208-218.
  • Zalduendo, J. (2006), Determinants of Venezuelas Equilibrium Real Exchange Rate, IMF Working Paper, WP-0674.
  • Zhang, Y., Y, Fan, H. T.ve Wei Y., (2008), Spillover Effect of US Dollar Exchange Rate on Oil Prices, Journal of Policy Modeling, Vol. 30, No. 6, pp. 973–91.
Year 2018, Volume: 3 Issue: 1, 339 - 347, 31.03.2018
https://doi.org/10.29106/fesa.405987

Abstract

References

  • Abed, R.E.L., Amor, T.H., ve Nouira, R. (2016), Asymmetric effect and dynamic relationships between oil prices shocks and exchange rate volatility: Evidence from some selected MENA countries. Middle East Economic Association, 15th The International Conference Doha, Qatar, March, 1-24.
  • Amano, R. ve Norden S. (1998), Exchange Rates and Oil Prices, Review of International Economics, Vol. 6, No. 4, pp. 683–94.
  • Balke, N.S.ve Fomby, T.B. (1997), Threshold Cointegration. International Economic Review, 38(3), 627-645.
  • Beckmann, J. ve Czudaj, R. (2012), Oil Price and U.S. Dollar Exchange Rates Dynamics, University of Duisburg- Essen, Department of Economics.
  • Breitenfellner, A. and Cuaresma J. C. (2008), Crude Oil Prices and the Euro-Dollar Exchange Rate: A Forecasting Exercise. University of Innsbruck, Working Papers in Economics and Statistics, No. 2008-08.
  • Coudert, V., Mignon, V. ve Penot, A. (2008), Oil Price and the Dollar, Energy Studies Review, Vol. 15, No. 2, pp. 45–58.
  • Dempster, A.P., Laird, N.M. ve . Rubin, D.B (1977), Maximum Likelihood Estimation from Incomplete Data via the EM Algorithm. Journal of the Royal Statistical Society, 39 (Series B), 1–38.
  • Dewachter, H. (1997), Sign Predictions of Exchange Rate Changes: Charts as Proxies for Bayesian inferences,Weltwirtschaftliches Archiv, Vol. 133, pp. 39–55. Diebold, F. X., Lee, J.-H. ve Weinbach, G. C., (1994), Regime switching with time-varying transition probabilities. In C. Hargreaves (ed.) Nonstationary Time Series Analysis and Cointegration, pp. 283–302, Oxford: Oxford University Press.
  • Durland, J. M. ve McCurdy, T. H., (1994).,Duration-dependent transitions in a Markov model of U.S. GNP growth. Journal of Business and Economic Statistics 12, 279–288.
  • Enders, W. ve Dibooglu, S. (2001), Long-run Purchasing Power Parity with Asymmetric Adjustment, Southern Economic Journal, Vol. 68, No. 2, pp. 433–45.
  • Engel, C. ve Hamilton, J. (1990), Long Swings in the Dollar: Are They in the Data and do Market Know It?, American Economic Review, Vol. 80, pp. 687–713.
  • Ehrmann, M., Ellison, M. ve Valla N., (2003). Regime-dependent impulse response functions in a Markov-switching vector autoregression model. Economics Letters 78, 295–299.
  • Evans, M. ve . Lewis, K (1995), ‘Do Long-term Swings in the Dollar Affect Estimates of the Risk Premia?’, Review of Financial Studies, Vol. 8, pp. 709–42.
  • Fan, J ve Yao, Q., (2003). Nonlinear Time Series: NonparametrPsaric and Parametric Methods. New York: Springer.
  • Filardo, A. J., (1994). Business-cycle phases and their transitional dynamics. Journal of Business and Economic Statistics 12, 299–308.
  • Filardo, A. J. ve Gordon, S. F., (1998). Business cycle durations. Journal of Econometrics 85, 99–123
  • Ghysels, E,. (1994), On the periodic structure of the business cycle. Journal of Business and Economic Statistics 12, 289–298.
  • Granger, C. W. J., (1996), Can we improve the perceived quality of economic forecasts? Journal of Applied Econometrics 11, 455-473.
  • Hamilton, J. (1989), A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle, ,Econometrica, Vol. 57, pp. 357–84.
  • Hamilton, J. D., (1994). Time Series Analysis. Princeton, NJ: Princeton University Press.
  • Hansen, B. E.(2001), The new econometrics of structural change: dating breaks in U.S. labor productivity. The Journal of Economic Perspectives 15, 117–128.
  • Hansen, B.E. ve Seo, B. (2002), Testing for Two-Regime Threshold Cointegration in Vector Error-Correction Models. Journal of Econometrics, 110(2), 293-318.
  • Huang, Y. ve Guo F. (2007), The Role of Oil Price Shocks on China’s Real Exchange Rate, China Economic Review, Vol. 18,pp. 403–16.
  • Ihle, R. ve Cramon-Taubadel, S. ,(2008),A Comparison of Threshold Cointegration and Markov-Switching Vector Error Correction Models in Price Transmission Analysis. Proceedings of the NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management, St. Louis, MO.
  • Indjehagopian, J., F. Lantz ve Simon, V.,(2000), Dynamics of Heating Oil Market Prices in Europe, Energy Economics, Vol. 22, No. 2, pp. 225–52.
  • Kaminsky, G. (1993), Is There a Peso Problem? Evidence from the Dollar/Pound Exchange Rate, 1976–1987, American Economic Review, Vol. 83, pp. 450–72.
  • Kilian, L. ve Taylor, M. P. (2003), Why is it so Difficult to Beat the Random Walk Forecast of Exchange Rates. Journal of International Economics, 60(1), 85-107.
  • Kim, M.-J. ve Yoo, J.-S., (1995), New index of coincident indicators: A multivariate Markov switching factor model approach. Journal of Monetary Economics 36, 607– 630.
  • Krolzig, H.-M., 1997. Markov Switching Vector Autoregressions Modelling: Statistical Inference and Application to Business Cycle Analysis. Berlin: Springer.
  • Krolzig, H.-M.,(1999), Statistical analysis of cointegrated VAR processes with Markovian regime shifts. Working Paper # 1113, Computing in Economics and Finance 1999, Society for Computational Economics
  • Krolzig, H.-M., Marcellino, M. ve Mizon, G. E., (2002.), A Markov-switching vector equilibrium correction model of the UK labor market. Empirical Economics 27, 233-254.
  • Krolzig, H.-M., (2006), Impulse response analysis in Markov switching vector autoregressive models. Economics Department, University of Kent. Keynes College.
  • Lindgren, G., (1978), Markov regime models for mixed distributions and switching regressions. Scandinavian Journal of Statistics 5, 81-91.
  • Lizardo, R., ve Mollick A., (2010), Oil Price Fluctuations and U.S. Dollar Exchange Rates, Energy Economics 32, no. 2: 399–408.
  • Lo, M.C. ve Zivot E. (2001), Threshold Cointegration and Nonlinear Adjustment to the Law of One Price. Macroeconomic Dynamics, 5(4), 533-576.
  • Perron, P. (2006), Dealing with Structural Breaks. Palgrave Handbook of Econometrics 1, 278–352.
  • Reboredo, J.C. (2012), Modelling Oil Price and Exchange Rate Co-Movements. Journal of Policy Modeling, 34(3), 419-440.
  • Saikkonen, P. (1992), Estimation and Testing of Cointegrated Systems by an Autoregressive Approximation. Econometric Theory, 8(1), 1-27.
  • Saikkonen, P. ve . Luukkonen R,(1997), Testing Cointegration in Infinite Order Vector Autoregressive Processes. Journal of Econometrics, 81(1), 93-126.
  • Teräsvirta, T, (1994), Specification, Estimation and Evaluation of Smooth Transition Autoregressive Models, Journal of the American Statistical Association, 89(425), 208-218.
  • Zalduendo, J. (2006), Determinants of Venezuelas Equilibrium Real Exchange Rate, IMF Working Paper, WP-0674.
  • Zhang, Y., Y, Fan, H. T.ve Wei Y., (2008), Spillover Effect of US Dollar Exchange Rate on Oil Prices, Journal of Policy Modeling, Vol. 30, No. 6, pp. 973–91.
There are 42 citations in total.

Details

Primary Language Turkish
Subjects Business Administration
Journal Section Araştırma Makaleleri
Authors

Mehmet Kenan Terzioğlu

Publication Date March 31, 2018
Submission Date March 14, 2018
Acceptance Date March 20, 2018
Published in Issue Year 2018 Volume: 3 Issue: 1

Cite

APA Terzioğlu, M. K. (2018). HAM PETROL FİYATLARI VE DÖVİZ KURU: MARKOV-GEÇİŞ HATA DÜZELTME MODELİ. Finans Ekonomi Ve Sosyal Araştırmalar Dergisi, 3(1), 339-347. https://doi.org/10.29106/fesa.405987