Yıl 2020, Cilt 04 , Sayı 1, Sayfalar 1 - 9 2020-08-31

Forecasting Monthly Inflation: A MIDAS Regression Application for Turkey

Kadir KARAGÖZ [1] , Suzan ERGÜN [2]


Forecasting the short-term price movements is especially important in terms of developing adequate monetary policies during inflationary periods. For countries such as Turkey where inflation targeting policy were adopted and relatively high inflation rates are observed, making short term forecasting using daily data will allow decision processes to react more rapidly. In Turkey, several methods are used by the Central Bank and academicians for estimating the inflation rate. However, in all these methods, covariates are used from the same frequency (mostly monthly) in modelling the inflation rate. In this study, it has been tried to develop a model which can be used in the forecasting of inflation rate by using MIDAS method which allows the series to be used in the same regression equation from different frequency. In the set regression equation, commercial credit interest rate (weekly), TL / US Dollar parity (daily), gold gram price (daily) and oil price (daily) data are used as variables which have the potential to determine the monthly producer price level (PPI) by increasing the input costs. Considering the AIC and SIC criteria, it was found that the best performing model out of four alternatives was the weighted equation according to the Almon polynomial distributed lags method. The in-sample predictive success of the model was found satisfactory.
Inflation forecasting, Mixed data sampling, MIDAS, Turkey
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Birincil Dil en
Konular Matematik
Bölüm Articles
Yazarlar

Orcid: 0000-0002-4436-9235
Yazar: Kadir KARAGÖZ (Sorumlu Yazar)
Kurum: MANİSA CELÂL BAYAR ÜNİVERSİTESİ
Ülke: Turkey


Orcid: 0000-0002-8447-972X
Yazar: Suzan ERGÜN
Kurum: İNÖNÜ ÜNİVERSİTESİ
Ülke: Turkey


Tarihler

Yayımlanma Tarihi : 31 Ağustos 2020

Bibtex @araştırma makalesi { forecasting653098, journal = {Turkish Journal of Forecasting}, issn = {}, eissn = {2618-6594}, address = {Giresun Üniversitesi Fen Edebiyat Fakültesi İstatistik Bölümü, Güre Yerleşkesi, 28100 Merkez, Giresun}, publisher = {Giresun Üniversitesi}, year = {2020}, volume = {04}, pages = {1 - 9}, doi = {}, title = {Forecasting Monthly Inflation: A MIDAS Regression Application for Turkey}, key = {cite}, author = {Karagöz, Kadir and Ergün, Suzan} }
APA Karagöz, K , Ergün, S . (2020). Forecasting Monthly Inflation: A MIDAS Regression Application for Turkey . Turkish Journal of Forecasting , 04 (1) , 1-9 . Retrieved from https://dergipark.org.tr/tr/pub/forecasting/issue/57892/653098
MLA Karagöz, K , Ergün, S . "Forecasting Monthly Inflation: A MIDAS Regression Application for Turkey" . Turkish Journal of Forecasting 04 (2020 ): 1-9 <https://dergipark.org.tr/tr/pub/forecasting/issue/57892/653098>
Chicago Karagöz, K , Ergün, S . "Forecasting Monthly Inflation: A MIDAS Regression Application for Turkey". Turkish Journal of Forecasting 04 (2020 ): 1-9
RIS TY - JOUR T1 - Forecasting Monthly Inflation: A MIDAS Regression Application for Turkey AU - Kadir Karagöz , Suzan Ergün Y1 - 2020 PY - 2020 N1 - DO - T2 - Turkish Journal of Forecasting JF - Journal JO - JOR SP - 1 EP - 9 VL - 04 IS - 1 SN - -2618-6594 M3 - UR - Y2 - 2020 ER -
EndNote %0 Turkish Journal of Forecasting Forecasting Monthly Inflation: A MIDAS Regression Application for Turkey %A Kadir Karagöz , Suzan Ergün %T Forecasting Monthly Inflation: A MIDAS Regression Application for Turkey %D 2020 %J Turkish Journal of Forecasting %P -2618-6594 %V 04 %N 1 %R %U
ISNAD Karagöz, Kadir , Ergün, Suzan . "Forecasting Monthly Inflation: A MIDAS Regression Application for Turkey". Turkish Journal of Forecasting 04 / 1 (Ağustos 2020): 1-9 .
AMA Karagöz K , Ergün S . Forecasting Monthly Inflation: A MIDAS Regression Application for Turkey. TJF. 2020; 04(1): 1-9.
Vancouver Karagöz K , Ergün S . Forecasting Monthly Inflation: A MIDAS Regression Application for Turkey. Turkish Journal of Forecasting. 2020; 04(1): 1-9.
IEEE K. Karagöz ve S. Ergün , "Forecasting Monthly Inflation: A MIDAS Regression Application for Turkey", Turkish Journal of Forecasting, c. 04, sayı. 1, ss. 1-9, Ağu. 2020