FORECASTING ROMANIAN GDP USING A BVAR MODEL 1
Petre Caraiani
Abstract
Open-access reader
Petre Caraiani
Abstract
Open-access reader
In this study I use the Bayesian VAR framework to forecast the dynamics of output for the Romanian economy. I estimate several versions of Bayesian VARs and compare them in terms of forecasting statistics with two standard models, the OLS and the unrestricted VAR, as well as with a naïve forecast. The findings confirm that the BVAR approach outperforms the standard models. The best BVAR model is used for forecasting quarterly GDP in the short run. The results show that the recovery will be slow and that the output gap will continue to be negative for a few quarters even after the economy starts to grow.
OpenAlex reports 24 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
In this study I use the Bayesian VAR framework to forecast the dynamics of output for the Romanian economy. I estimate several versions of Bayesian VARs and compare them in terms of forecasting statistics with two standard models, the OLS and the unrestricted VAR, as well as with a naïve forecast. The findings confirm that the BVAR approach outperforms the standard models. The best BVAR model is used for forecasting quarterly GDP in the short run. The results show that the recovery will be slow and that the output gap will continue to be negative for a few quarters even after the economy starts to grow.
Key concepts: Bayesian vector autoregression, Economics, Econometrics, Romanian, Bayesian probability, Statistics, Mathematics, Linguistics