MIDAS ve MF-VAR Modelleri ile GSYH Ön Tahmini

Abstract

Küreselleşen dünya ekonomisi ve yaşanan teknolojik gelişmeler, ekonominin konjonktürel durumunun tespiti doğrultusunda uygun ekonomi politikalarının olabildiğince erken zamanda üretilme zorunluluğunu ortaya çıkarmıştır. Bu amaçla Eurostat öncülüğünde başlatılan çalışmaların başında, ekonominin mevcut durumu hakkında bilgi sağlayan temel göstergelerden olan GSYH ön tahmin çalışmaları yer almaktadır. Ön tahmin uygulamaları ile üç aylık GSYH'nin eldeki mevcut veriler kullanılarak ekonometrik modeller aracılığıyla nihai tahmin döneminden daha erken zamanda hesaplanmasına imkan sağlanmıştır. Bu çalışmada da GSYH çeyreklik büyüme oranının referans dönemin sona ermesinden 45 gün sonra elde edilmesine yönelik Türkiye uygulaması gerçekleştirilmiştir.

t+45 anında GSYH'nin ön tahmininin hesaplanma aşamasında ilk olarak, iktisadi teori çerçevesinde GSYH ile ilişkili 28 tane gösterge belirlenerek göstergelerin zaman serisi özellikleri incelenmiştir. Ön tahmin hesabında, farklı frekanslı verilerde yer alan tüm bilgiyi kullanarak aynı anda modellenmesine olanak sağlayan Almon Polinomlu MIDAS regresyon modelleri ile göstergelerin dinamik etkilerinin denklem sisteminde incelendiği MF-VAR modelleri kullanılmıştır. Belirtilen iki farklı modelden ön tahminler elde edilmiş olup modellerin karşılaştırmalı analizi gerçekleştirilmiştir. Tahmin uzunluklarının tahmin performansına etkisini de değerlendirmek amacıyla örneklem dışı tahminlerde 1 yıllık süreyi kapsayan 4 çeyrek dönem için tahminler elde edilerek RMSE değerleri incelenmiştir. Sonuç olarak kısa ve uzun dönem tahminlerinde MIDAS modellerinin MF-VAR modellerinden daha iyi performansa sahip olduğu ileri sürülebilir.

Keywords

• Büyüme Oranı
• Gayrisafi Yurt İçi Hasıla
• MF-VAR Modelleri
• MIDAS Modelleri
• Ön Tahmin

GDP Flash Estimate with MIDAS and Mixed Frequency VAR

Abstract

The globalized world economy and the technological developments experienced have revealed the necessity of producing appropriate economic policies as early as possible in line with the determination of the economic situation. For this purpose, the flash estimate studies of GDP, one of the basic indicators that provide information about the current state of the economy, are among the initiatives started under the leadership of Eurostat. With the flash estimate applications, the quarterly GDP has been provided to be calculated earlier than the final estimation period by using econometric models. In this study GDP quarterly growth rate for Turkey at about 45 days after the end of the reference period were carried out. At the stage of calculating the flash estimate of GDP at t+45; 28 related indicators were determined within the framework of economic theory and the time series characteristics of the indicators were examined in the first instance. In the flash estimate calculation, Almon Polynomial MIDAS regression models, which allow simultaneous modeling using all the information in different frequency data, and MF-VAR models in which the dynamic effects of the indicators are examined in the equation system were used. Flash estimates were obtained from the two different models mentioned and comparative analysis of the models was performed. In order to evaluate the effect of forecast lengths on forecast performance, RMSE values were obtained by obtaining forecasts for 4 quarters covering a 1 year period in out-of-sample forecasts. As a result, it can be argued that MIDAS models perform better than MF-VAR models in short and long term estimations.

Keywords

• Growth Rate
• Gross Domestic Product
• MF-VAR Models
• MIDAS Models
• Flash Estimate

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