Add to ORKGThe chapter deals with parametric models for the measurement of the business cycle in economic time series. It presents univariate methods based on parametric trend{cycle decom- positions and multivariate models featuring a Phillips type relationship between the output gap and inflation and the estimation of the gap using mixed frequency data. We finally address the issue of assessing the accuracy of the output gap estimates
The output gap and inflation forecast are important factors to analyze current state of the economy ...
This paper uses a Bayesian dynamic index model to extract common trends and cycles from large datase...
Abstract Over the last decades, the estimation of the slack in the economy has become an essential p...
The chapter deals with parametric models for the measurement of the business cycle in economic time ...
The continued increase in availability of economic data in recent years and, more importantly, the p...
This thesis studies structural time series model (STM) and its application. A STM decomposes a time ...
Defence date: 12 September 2011Jury Members: Prof. Massimiliano Marcellino, EUI, Supervisor Prof. ...
Abstract: We propose a bivariate structural time series framework to decompose GDP and the unemploym...
Determining turning points in the business cycle is a difficult problem. Making sensible predictions...
The continued increase in availability of economic data in recent years and, more impor-tantly, the ...
Professor Zellner has greatly contributed to econometrics in many aspects. This paper c...
We propose a model diagnostic device to compare different linear and non linear parametric time seri...
This article proposes a multivariate bandpass filter based on the trend plus cycle decomposition mod...
Potential output plays a central role in monetary policy and short-termmacroeconomic policy making. ...
One basic problem in business cycle studies is how to deal with nonstationary time series. Trend-cyc...
The output gap and inflation forecast are important factors to analyze current state of the economy ...
This paper uses a Bayesian dynamic index model to extract common trends and cycles from large datase...
Abstract Over the last decades, the estimation of the slack in the economy has become an essential p...
The chapter deals with parametric models for the measurement of the business cycle in economic time ...
The continued increase in availability of economic data in recent years and, more importantly, the p...
This thesis studies structural time series model (STM) and its application. A STM decomposes a time ...
Defence date: 12 September 2011Jury Members: Prof. Massimiliano Marcellino, EUI, Supervisor Prof. ...
Abstract: We propose a bivariate structural time series framework to decompose GDP and the unemploym...
Determining turning points in the business cycle is a difficult problem. Making sensible predictions...
The continued increase in availability of economic data in recent years and, more impor-tantly, the ...
Professor Zellner has greatly contributed to econometrics in many aspects. This paper c...
We propose a model diagnostic device to compare different linear and non linear parametric time seri...
This article proposes a multivariate bandpass filter based on the trend plus cycle decomposition mod...
Potential output plays a central role in monetary policy and short-termmacroeconomic policy making. ...
One basic problem in business cycle studies is how to deal with nonstationary time series. Trend-cyc...
The output gap and inflation forecast are important factors to analyze current state of the economy ...
This paper uses a Bayesian dynamic index model to extract common trends and cycles from large datase...
Abstract Over the last decades, the estimation of the slack in the economy has become an essential p...