Mixed Frequency Data Dynamic Models in Macroeconomic Forecasting
Journal Title: Zarządzanie i Finanse - Year 2015, Vol 13, Issue 4
Abstract
The aim of the study was to find out whether the use of mixed frequency data dynamic models can improve the accuracy of quarterly forecasts of selected macroeconomic variables. The research tools were the MIDAS, AR-MIDAS, DFM, ARIMA and VAR models with quarterly forecasts as reference points. The study used a simulation of eight (ex ante) forecasting sessions. To that end, it was necessary to use variables from the real-time database. Yet, due to the limited access to such databases, the study focused on U.S. GDP. The results indicate that the AR-MIDAS class model, which directly incorporates the latest available monthly information as well as „classic” VAR model provided significantly more accurate forecasts of GDP then DFM and ARIMA models. Comparing AR‑MIDAS and VAR forecasts (which were equally accurate in terms of Diebold‑Mariano test) only the previous model proved to be able to provide accurate forecasts of all turning points which occurred within the sample. This unique feature enables to recommend AR-MIDAS as a now‑casting or short term forecasting tool.
Authors and Affiliations
Lech Kujawski
Keywords
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