Univariate spectral analysis is used to model seasonally unadjusted quarterly unemployment rate data for Australia, 1978(2) to 2002(3). Data are tested for three categories: persons, males and females. Dynamic out-of-sample forecasts are made for 8 quarters using spectral analysis models evaluated against ARIMA model counterparts. It is found that the spectral analysis models achieve higher levels of forecasting accuracy than ARIMA counterparts, including turning point forecast accuracy. These results emerge in spite of weaker in-sample explanatory power of the spectral models against the ARIMA models. It is concluded the results suggest that the spectral model is ultimately better attuned to the various cyclical forces of the past unfoldin...
A quantitative model is presented linking the rate of inflation and unemployment to the change in th...
This paper presents a comparison of forecasting performance for a variety of linear time series mod...
Predicting the unemployment rate is one of the most important applications for economists and policy...
Predicting the unemployment rate is one of the most important applications for economists and policy...
We document evolving patterns in the inflation-unemployment relationship in Australia in the frequen...
In this paper, we assess the usefulness of constant gain least squares (CGLS) when forecasting the u...
Time series data comprises several components; Trend, Seasonal variations, cyclical variations and i...
We use a nonlinear, nonparametric method to forecast the unemployment rates. We compare these foreca...
Purpose: Unemployment rate prediction has become critically significant, because it can be used by g...
In this thesis I wish to model and forecast ination in both univariate and multivariate settings. On...
In this paper we compare the accuracy of unemployment rates forecasts of eight Central and Eastern E...
Abstract In contrast to recent forecasting developments, 'Old School' forecasting techniqu...
We construct a dynamic error correction model of the Australian labour market using a macroeconomic ...
Spectral density matrices provide a complete summary of the second order dynamics of a multivariate ...
In this paper we propose the use of a threshold autoregressive conditional heteroakedastic model to...
A quantitative model is presented linking the rate of inflation and unemployment to the change in th...
This paper presents a comparison of forecasting performance for a variety of linear time series mod...
Predicting the unemployment rate is one of the most important applications for economists and policy...
Predicting the unemployment rate is one of the most important applications for economists and policy...
We document evolving patterns in the inflation-unemployment relationship in Australia in the frequen...
In this paper, we assess the usefulness of constant gain least squares (CGLS) when forecasting the u...
Time series data comprises several components; Trend, Seasonal variations, cyclical variations and i...
We use a nonlinear, nonparametric method to forecast the unemployment rates. We compare these foreca...
Purpose: Unemployment rate prediction has become critically significant, because it can be used by g...
In this thesis I wish to model and forecast ination in both univariate and multivariate settings. On...
In this paper we compare the accuracy of unemployment rates forecasts of eight Central and Eastern E...
Abstract In contrast to recent forecasting developments, 'Old School' forecasting techniqu...
We construct a dynamic error correction model of the Australian labour market using a macroeconomic ...
Spectral density matrices provide a complete summary of the second order dynamics of a multivariate ...
In this paper we propose the use of a threshold autoregressive conditional heteroakedastic model to...
A quantitative model is presented linking the rate of inflation and unemployment to the change in th...
This paper presents a comparison of forecasting performance for a variety of linear time series mod...
Predicting the unemployment rate is one of the most important applications for economists and policy...