Author: Gerhard Fenz
Publisher:
ISBN:
Category : Austria
Languages : en
Pages : 36
Book Description
An Unobserved Components Model to Forecast Austrian GDP
Policy Analysis and Forecasting in the World Economy
Author: Francis Vitek
Publisher: International Monetary Fund
ISBN: 1475599560
Category : Business & Economics
Languages : en
Pages : 77
Book Description
This paper develops a structural macroeconometric model of the world economy, disaggregated into thirty five national economies. This panel unobserved components model features a monetary transmission mechanism, a fiscal transmission mechanism, and extensive macrofinancial linkages, both within and across economies. A variety of monetary policy analysis, fiscal policy analysis, spillover analysis, and forecasting applications of the estimated model are demonstrated, based on a Bayesian framework for conditioning on judgment.
Publisher: International Monetary Fund
ISBN: 1475599560
Category : Business & Economics
Languages : en
Pages : 77
Book Description
This paper develops a structural macroeconometric model of the world economy, disaggregated into thirty five national economies. This panel unobserved components model features a monetary transmission mechanism, a fiscal transmission mechanism, and extensive macrofinancial linkages, both within and across economies. A variety of monetary policy analysis, fiscal policy analysis, spillover analysis, and forecasting applications of the estimated model are demonstrated, based on a Bayesian framework for conditioning on judgment.
Forecasting Austrian GDP Using the Generalized Dynamic Factor Model
Author: Martin Schneider
Publisher:
ISBN:
Category : Austria
Languages : en
Pages : 48
Book Description
Publisher:
ISBN:
Category : Austria
Languages : en
Pages : 48
Book Description
Regime-dependent Nowcasting of the Austrian Economy
Author: Ines Fortin
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
We nowcast and forecast Austrian economic activity, namely real gross domestic product (GDP), consumption and investment, which are available at a quarterly frequency. While nowcasting uses data up to (and including) the quarter to be predicted, forecasting uses only data up to the previous quarter. We use a large number of monthly indicators to construct early estimates of the target variables. For this purpose we use different mixed-frequency models, namely the mixed-frequency vector autoregressive model according to Ghysels (2016) and mixed data sampling approaches, and compare their forecast and nowcast accuracies in terms of the root mean squared error. We also consider traditional benchmark models which rely only on quarterly data. We are particularly interested in whether explicitly considering different regimes improves the nowcast. Thus we examine regime-dependent models, taking into account business cycle regimes (recession/non-recession) or financial/economic uncertainty regimes (high/low uncertainty) driven by global and Austrian economic and financial uncertainty indicators. We find that taking explicit account of regimes clearly improves nowcasting, and different regimes are important for GDP, consumption and investment. While the recession/non-recession regimes seem to be important to nowcast GDP and consumption, high/low global financial uncertainty regimes are important to nowcast investment. Also, some variables seem to be important only in certain regimes, like tourist arrivals in the non-recession regime when nowcasting consumption, while other variables are important in both regimes, like order books in the high and low global financial uncertainty regimes when nowcasting investment. In addition, nowcasting indeed provides a value added to forecasting, and the new information available in the first month seems to be most important. However, sometimes also the forecast performs quite well, and then it mostly comes from a mixed-frequency model. So monthly information seems to be helpful also in forecasting, not only in nowcasting. Finally, we do not find a clear winner among the different mixed-frequency models.
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
Book Description
We nowcast and forecast Austrian economic activity, namely real gross domestic product (GDP), consumption and investment, which are available at a quarterly frequency. While nowcasting uses data up to (and including) the quarter to be predicted, forecasting uses only data up to the previous quarter. We use a large number of monthly indicators to construct early estimates of the target variables. For this purpose we use different mixed-frequency models, namely the mixed-frequency vector autoregressive model according to Ghysels (2016) and mixed data sampling approaches, and compare their forecast and nowcast accuracies in terms of the root mean squared error. We also consider traditional benchmark models which rely only on quarterly data. We are particularly interested in whether explicitly considering different regimes improves the nowcast. Thus we examine regime-dependent models, taking into account business cycle regimes (recession/non-recession) or financial/economic uncertainty regimes (high/low uncertainty) driven by global and Austrian economic and financial uncertainty indicators. We find that taking explicit account of regimes clearly improves nowcasting, and different regimes are important for GDP, consumption and investment. While the recession/non-recession regimes seem to be important to nowcast GDP and consumption, high/low global financial uncertainty regimes are important to nowcast investment. Also, some variables seem to be important only in certain regimes, like tourist arrivals in the non-recession regime when nowcasting consumption, while other variables are important in both regimes, like order books in the high and low global financial uncertainty regimes when nowcasting investment. In addition, nowcasting indeed provides a value added to forecasting, and the new information available in the first month seems to be most important. However, sometimes also the forecast performs quite well, and then it mostly comes from a mixed-frequency model. So monthly information seems to be helpful also in forecasting, not only in nowcasting. Finally, we do not find a clear winner among the different mixed-frequency models.
Use and Misuse of Unobserved Components in Economic Forecasting
Author: AgustÃn Maravall
Publisher:
ISBN:
Category : Economic forecasting
Languages : en
Pages : 48
Book Description
Publisher:
ISBN:
Category : Economic forecasting
Languages : en
Pages : 48
Book Description
Unobserved Components Models for Quaterly German GDP
Unobserved Components Models for Quarterly German GDP
Author: Gebhard Flaig
Publisher:
ISBN:
Category : Business cycles
Languages : en
Pages : 18
Book Description
Publisher:
ISBN:
Category : Business cycles
Languages : en
Pages : 18
Book Description
Why Did We Fail to Predict GDP During the Last Cycle?
Author: Martin Schneider
Publisher:
ISBN:
Category : Austria
Languages : en
Pages : 14
Book Description
Literaturverz. S. 13.
Publisher:
ISBN:
Category : Austria
Languages : en
Pages : 14
Book Description
Literaturverz. S. 13.
Univariate Unobserved-Component Model with a Non-Random-Walk Permanent Component
Author: Zhiwei Xu
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
In this note, we revisit the univariate unobserved-component (UC) model of U.S. GDP by relaxing the traditional random-walk assumption of the permanent component. Since our general UC model is unidentified, we investigate the upper bound of the contribution of the transitory component, and find the GDP fluctuation is dominated by the permanent component.
Publisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
In this note, we revisit the univariate unobserved-component (UC) model of U.S. GDP by relaxing the traditional random-walk assumption of the permanent component. Since our general UC model is unidentified, we investigate the upper bound of the contribution of the transitory component, and find the GDP fluctuation is dominated by the permanent component.
Policy Analysis and Forecasting in the World Economy
Author: Francis Vitek
Publisher: International Monetary Fund
ISBN: 1475504187
Category : Business & Economics
Languages : en
Pages : 77
Book Description
This paper develops a structural macroeconometric model of the world economy, disaggregated into thirty five national economies. This panel unobserved components model features a monetary transmission mechanism, a fiscal transmission mechanism, and extensive macrofinancial linkages, both within and across economies. A variety of monetary policy analysis, fiscal policy analysis, spillover analysis, and forecasting applications of the estimated model are demonstrated, based on a Bayesian framework for conditioning on judgment.
Publisher: International Monetary Fund
ISBN: 1475504187
Category : Business & Economics
Languages : en
Pages : 77
Book Description
This paper develops a structural macroeconometric model of the world economy, disaggregated into thirty five national economies. This panel unobserved components model features a monetary transmission mechanism, a fiscal transmission mechanism, and extensive macrofinancial linkages, both within and across economies. A variety of monetary policy analysis, fiscal policy analysis, spillover analysis, and forecasting applications of the estimated model are demonstrated, based on a Bayesian framework for conditioning on judgment.