We produce predictions of Norwegian GDP. To this end, we estimate a Bayesian dynamic factor model on a panel of fourteen variables (all followed closely by market operators) ranging from 1990 to 2011. By means of a pseudo real-time exercise, we show that the Bayesian dynamic factor model performs well both in terms of point forecast and in terms of density forecasts. Results indicate that our model outperforms standard univariate benchmark models, that it performs as well as the Bloomberg survey, and that it outperforms the predictions published by the Norges Bank in its Monetary Policy Report.SCOPUS: ar.jinfo:eu-repo/semantics/publishe
In this paper, a generalized dynamic factor model is utilized to produce short-term forecasts of rea...
We estimate a Bayesian VAR (BVAR) for the UK economy and assess its performance in forecasting GDP g...
In this thesis, we used financial indicators to construct a Financial Conditions Index (FCI) aimed a...
We assess the forecast ability of Norges Bank’s regional survey for inflation, GDP growth and the un...
Abstract: We use state space methods to estimate a large dynamic factor model for the Norwegian eco...
This paper finds that asset prices on Oslo Stock Exchange is the single most important block of data...
The topic of this master thesis is forecasting of Norwegian quarterly GDP growth. We aim to research...
In this paper we describe Norges Bank's system for averaging models (SAM) which produces model-based...
We de fine and forecast classical business cycle turning points for the Norwegian economy. When defi...
This thesis analyzes the nowcasting of quarterly GDP growth for nine European economies using a dyna...
We review several methods to define and forecast classical business cycle turning points in Norway. ...
In recent years, factor models have received increasing attention from both econometricians and prac...
Gross domestic product is a measure of overall economic activity. It is therefore regarded as one of...
This paper considers the problem of forecasting in dynamic factor models using Bayesian model averag...
This paper compares the out-of-sample forecast accuracy of policymakers, private banks and three cla...
In this paper, a generalized dynamic factor model is utilized to produce short-term forecasts of rea...
We estimate a Bayesian VAR (BVAR) for the UK economy and assess its performance in forecasting GDP g...
In this thesis, we used financial indicators to construct a Financial Conditions Index (FCI) aimed a...
We assess the forecast ability of Norges Bank’s regional survey for inflation, GDP growth and the un...
Abstract: We use state space methods to estimate a large dynamic factor model for the Norwegian eco...
This paper finds that asset prices on Oslo Stock Exchange is the single most important block of data...
The topic of this master thesis is forecasting of Norwegian quarterly GDP growth. We aim to research...
In this paper we describe Norges Bank's system for averaging models (SAM) which produces model-based...
We de fine and forecast classical business cycle turning points for the Norwegian economy. When defi...
This thesis analyzes the nowcasting of quarterly GDP growth for nine European economies using a dyna...
We review several methods to define and forecast classical business cycle turning points in Norway. ...
In recent years, factor models have received increasing attention from both econometricians and prac...
Gross domestic product is a measure of overall economic activity. It is therefore regarded as one of...
This paper considers the problem of forecasting in dynamic factor models using Bayesian model averag...
This paper compares the out-of-sample forecast accuracy of policymakers, private banks and three cla...
In this paper, a generalized dynamic factor model is utilized to produce short-term forecasts of rea...
We estimate a Bayesian VAR (BVAR) for the UK economy and assess its performance in forecasting GDP g...
In this thesis, we used financial indicators to construct a Financial Conditions Index (FCI) aimed a...