Pregled bibliografske jedinice broj: 1113541
Forecasting Croatian quarterly real GDP with monthly monetary aggregate M1 data: A mixed frequency approach (MIDAS)
Forecasting Croatian quarterly real GDP with monthly monetary aggregate M1 data: A mixed frequency approach (MIDAS) // Conference Proceedings of the 9th International Scientific Conference “Tourism, Innovations and Entrepreneurship – TIE 2019” / Benazić, M. ; Blažević Burić, S. ; Tijanić, L. ; Laporšek, S. ; Wołowiec, T. (ur.).
Pula: Sveučilište Jurja Dobrile u Puli, 2020. str. 365-380 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
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Naslov
Forecasting Croatian quarterly real GDP with
monthly monetary aggregate M1 data: A mixed
frequency approach (MIDAS)
Autori
Benazić, Manuel
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Conference Proceedings of the 9th International Scientific Conference “Tourism, Innovations and Entrepreneurship – TIE 2019”
/ Benazić, M. ; Blažević Burić, S. ; Tijanić, L. ; Laporšek, S. ; Wołowiec, T. - Pula : Sveučilište Jurja Dobrile u Puli, 2020, 365-380
ISBN
978-953-8278-54-9
Skup
9th International Scientific Conference "Tourism, Innovations and Entrepreneurship" (TIE 2019)
Mjesto i datum
Poreč, Hrvatska, 26.09.2019. - 27.09.2019
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
business cycles, MIDAS approach, mixed frequency data, monetary policy
Sažetak
Forecasting macroeconomic variables such as gross domestic product (GDP), consumption, investments etc. is one of the most important tasks in predicting business cycles. Problems arise from the fact that many macroeconomic indicators are available only as lower frequency data and forecasting models generally require data to be of the same frequency. For example, GDP data is sampled quarterly, money and inflation are sampled monthly, while most interest rate data is sampled daily. Mixed Data Sampling (MIDAS) regression estimation technique overcomes these problems, enabling data sampled at different frequencies to be used in the same regression. Therefore, in this paper, Croatian quarterly real GDP is forecasted using monthly monetary aggregate M1 data and the MIDAS approach with the Beta and Almon weighting methods. An estimated MIDAS model using the Beta weighting method shows that monthly monetary aggregate M1 has an overall positive effect on quarterly real GDP, but the effect disappears quickly in lags. On the other hand, the estimated MIDAS model using the Almon weighting method shows that the overall effect of monthly monetary aggregate M1 on quarterly real GDP is also positive and decreasing in lags. However, in contrast with the Beta weights estimate, the lag coefficients show a linear pattern. In addition, computed static forecasts from MIDAS models show that monthly monetary aggregate M1 can be used for predicting Croatian quarterly real GDP.
Izvorni jezik
Engleski
Znanstvena područja
Ekonomija
