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The Investigation of Inflation and Phillips Curve for Turkey with Unobserved Component Model

Yıl 2020, , 64 - 72, 24.06.2020
https://doi.org/10.18026/cbayarsos.525385

Öz

Unobserved component models; which are directly formulated in terms of the unobservable components that represent important characteristics of series such as trend, cyclical, seasonal and irregular components. The so-called models provide us to interpret in terms of each components, to obtain unobserved variables and to predict by preserving the originality of the series.
In this study, inflation, which is one of the basic macroeconomic variables, was examined by using the patterns of unobserved component models and statistical theories based on the so-called models. Then, Phillips Curve was predicted. Unobserved variables such as the output gap and the natural unemployment rate required for the Phillips Curve estimation were also obtained based on the method in question. In the analysis, the data of GDP, unemployment and inflation for Turkey were used the period for 1998: Q1- 2016: Q2. The findings showed that the Phillips curve isn’t valid for Turkey.

Kaynakça

  • COMMANDEUR, J. ve KOOPMAN, S. J. (2007). An Introduction to State Space Time Series Analysis. Oxford: Oxford University Press.DURBIN, J. ve KOOPMAN, S. J. (2012). Time Series Analysis by State Space Methods. Oxford: Oxford University Press.COMMANDEUR, J. ve KOOPMAN, S. J. (2007). An Introduction to State Space Time Series Analysis. Oxford: Oxford University Press.DURBIN, J. ve KOOPMAN, S. J. (2012). Time Series Analysis by State Space Methods. Oxford: Oxford University Press.EĞILMEZ, M. (2016). GSYH Hesaplaması Değişti, Kişi Başına Gelirimiz Arttı. http:// www.mahfiegilmez.com/2016/12/gsyh-hesaplamas-degisti-kisi-basna.html, (12.12.2016).FOMBY, T. (2008). The Unobservable Components Model. Working Paper. 1–42.HARVEY, A.C. (1989). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge: Cambridge University Press.HARVEY, A. C. (2011). Modelling The Phillips Curve With Unobserved Components. Applied Financial Economics. 21(1):7–17. KALMAN, R.E. (1960). A new Approach to Linear Filtering and Prediction Problems. Journal of Basic Engineering. 82(1): 35-45.KOTIA, A. (2013). An Unobserved Components Phillips Curve for India Re-examining output inflation dynamics in India. Working Paper. Oxford University.KUŞTEPELI, Y. (2005). A Comprehensive Short-Run Analysis of a (possible) Turkish Phillips Curve. Applied Economics. 37(5): 581-591LEE, J. ve NELSON, C. R. (2007). Expectation Horizon and The Phillips Curve: The Solution to An Empirical Puzzle. Journal of Applied Econometrics. 22(1): 161-178. MACHADO, V.G. ve PORTUGAL, M.S. (2014). Phillips Curve in Brazil : An Unobserved Components. Estudos Econômicos. 44(4): 787–814.MANKIW, N. G. (2010). Macroecenomics. New York: Worth Publishers.MERGNER, S. (2009). Applications of State Space Models in Finance. Göttingen: Universitätsverlag GöttingenNASON, J. M. ve SMITH, G. W. (2008). Identifying The New Keynesian Phillips Curve. Journal of Applied Econometrics. 23(5):525-551.NELSON, C. ve PLOSSER, C.I. (1982). Trends and Random Walks in Macroeconomic Series. Journal of Monetary Economics. 10:139-162.ÖĞÜNÇ, F. ve ECE, D. (2004). Estimating Output gap for Turkey: Unobserved Components . Applied Economics Letters. 11:177-182.ÖZBEK, L.ve ÖZLALE, U. (2005). Employing the Extended Kalman filter in Measuring The Output Gap. Journal of Economic Dynamics and Control. 29(9):1611–1622. ÖZBEK, L. (2017). Kalman Filtresi. Ankara: Akademisyen Kitabevi.PHILLIPS, A.W. (1958). The Relation Between Unemployment and the Rate of Change of Money Wages in the United Kingdom:1861-1957. Economica. 25(100): 283-99.PROIETTI, T. (2002). Forecasting with Structural Time Series Models. A Companion to Economic Forecasting. 1–31. RUDD, J. ve WHELAN, K. (2007). Modeling Inflation Dynamics: A Critical Review of Recent Research. Journal of Money, Credit and Banking. 39(1): 155-170.US, V. (2014). Estimating NAIRU for The Turkish Economy Using Extended Kalman Filter Approach. Central Bank Review. 14: 63–94.YILDIRIM, K., KARAMAN, D. ve TAŞDEMIR, M. (2014). Makro Ekonomi. İstanbul: Seçkin Yayıncılık.

Türkiye için Enflasyonun ve Phillips Eğrisinin Gözlenemeyen Bileşen Modelleri ile İncelenmesi

Yıl 2020, , 64 - 72, 24.06.2020
https://doi.org/10.18026/cbayarsos.525385

Öz

Gözlenemeyen bileşen modelleri; trend, konjonktürel, mevsimsel ve düzensiz bileşenler gibi serilerin önemli özelliklerini temsil eden gözlenemeyen bileşenleri açısından doğrudan formülize edilen modellerdir. Söz konusu modeller; her bir bileşene ayrı ayrı ekonomik yorum getirmeyi, gözlenemeyen değişkenleri elde etmeyi ve serilerin orijinalliklerini koruyarak tahminleme yapmayı mümkün kılmaktadır. Çalışmada temel makroekonomik değişkenlerden biri olan enflasyon bileşenleri açısından; gözlenemeyen bileşen model kalıpları ve dayandığı istatistiksel teoriler kullanılarak incelenmiş ve Phillips Eğrisi tahminlenmesi yapılmıştır. Phillips Eğrisi tahmini için gerekli olan çıktı açığı ve doğal işsizlik oranı gibi gözlenemeyen değişkenler de söz konusu yönteme dayanarak elde edilmiştir. Analizlerde, 1998:Q1-2016:Q2 dönemi için Türkiye GSYH, işsizlik ve enflasyon verileri kullanılmıştır. Elde edilen bulgular, Türkiye için Phillips eğrisinin geçerli olmadığını göstermiştir.

Kaynakça

  • COMMANDEUR, J. ve KOOPMAN, S. J. (2007). An Introduction to State Space Time Series Analysis. Oxford: Oxford University Press.DURBIN, J. ve KOOPMAN, S. J. (2012). Time Series Analysis by State Space Methods. Oxford: Oxford University Press.COMMANDEUR, J. ve KOOPMAN, S. J. (2007). An Introduction to State Space Time Series Analysis. Oxford: Oxford University Press.DURBIN, J. ve KOOPMAN, S. J. (2012). Time Series Analysis by State Space Methods. Oxford: Oxford University Press.EĞILMEZ, M. (2016). GSYH Hesaplaması Değişti, Kişi Başına Gelirimiz Arttı. http:// www.mahfiegilmez.com/2016/12/gsyh-hesaplamas-degisti-kisi-basna.html, (12.12.2016).FOMBY, T. (2008). The Unobservable Components Model. Working Paper. 1–42.HARVEY, A.C. (1989). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge: Cambridge University Press.HARVEY, A. C. (2011). Modelling The Phillips Curve With Unobserved Components. Applied Financial Economics. 21(1):7–17. KALMAN, R.E. (1960). A new Approach to Linear Filtering and Prediction Problems. Journal of Basic Engineering. 82(1): 35-45.KOTIA, A. (2013). An Unobserved Components Phillips Curve for India Re-examining output inflation dynamics in India. Working Paper. Oxford University.KUŞTEPELI, Y. (2005). A Comprehensive Short-Run Analysis of a (possible) Turkish Phillips Curve. Applied Economics. 37(5): 581-591LEE, J. ve NELSON, C. R. (2007). Expectation Horizon and The Phillips Curve: The Solution to An Empirical Puzzle. Journal of Applied Econometrics. 22(1): 161-178. MACHADO, V.G. ve PORTUGAL, M.S. (2014). Phillips Curve in Brazil : An Unobserved Components. Estudos Econômicos. 44(4): 787–814.MANKIW, N. G. (2010). Macroecenomics. New York: Worth Publishers.MERGNER, S. (2009). Applications of State Space Models in Finance. Göttingen: Universitätsverlag GöttingenNASON, J. M. ve SMITH, G. W. (2008). Identifying The New Keynesian Phillips Curve. Journal of Applied Econometrics. 23(5):525-551.NELSON, C. ve PLOSSER, C.I. (1982). Trends and Random Walks in Macroeconomic Series. Journal of Monetary Economics. 10:139-162.ÖĞÜNÇ, F. ve ECE, D. (2004). Estimating Output gap for Turkey: Unobserved Components . Applied Economics Letters. 11:177-182.ÖZBEK, L.ve ÖZLALE, U. (2005). Employing the Extended Kalman filter in Measuring The Output Gap. Journal of Economic Dynamics and Control. 29(9):1611–1622. ÖZBEK, L. (2017). Kalman Filtresi. Ankara: Akademisyen Kitabevi.PHILLIPS, A.W. (1958). The Relation Between Unemployment and the Rate of Change of Money Wages in the United Kingdom:1861-1957. Economica. 25(100): 283-99.PROIETTI, T. (2002). Forecasting with Structural Time Series Models. A Companion to Economic Forecasting. 1–31. RUDD, J. ve WHELAN, K. (2007). Modeling Inflation Dynamics: A Critical Review of Recent Research. Journal of Money, Credit and Banking. 39(1): 155-170.US, V. (2014). Estimating NAIRU for The Turkish Economy Using Extended Kalman Filter Approach. Central Bank Review. 14: 63–94.YILDIRIM, K., KARAMAN, D. ve TAŞDEMIR, M. (2014). Makro Ekonomi. İstanbul: Seçkin Yayıncılık.
Toplam 1 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm İktisadi ve idari Bilimler Sayısı
Yazarlar

Eda Yalçın Kayacan 0000-0002-1616-9121

Şenay Üçdoğruk Birecikli 0000-0002-1616-9121

Yayımlanma Tarihi 24 Haziran 2020
Yayımlandığı Sayı Yıl 2020

Kaynak Göster

APA Yalçın Kayacan, E., & Üçdoğruk Birecikli, Ş. (2020). Türkiye için Enflasyonun ve Phillips Eğrisinin Gözlenemeyen Bileşen Modelleri ile İncelenmesi. Manisa Celal Bayar Üniversitesi Sosyal Bilimler Dergisi, 18(2), 64-72. https://doi.org/10.18026/cbayarsos.525385