The local linear trend and global linear trend models embody extreme assumptions about trends. According to the local linear trend formulation the level and growth rate are allowed to rapidly adapt to changes in the data path. On the other hand, the global linear trend model makes no allowance for structural change. In this paper we introduce a new model that, as well as encompassing the global linear trend and local linear trend models, allows for a range of "in between" cases. The theoretical properties of the autocovariance and forecast functions for this model suggest that it should be useful when neither a local linear trend nor a global linear trend is appropriate. A comparison of forecasting performance using real time series provide...
A study of business cycles does not require trend estimation and elimination, but a study of growth ...
The paper considers stochastic linear trends in series with a higher than annual frequency of observ...
This thesis suggests a general approach for estimating the trend of a univariate time series. It beg...
The local linear trend and global linear trend models embody extreme assumptions about trends. Accor...
The global linear trend with autocorrelated disturbances is a surprising omission from the M1 compet...
SUMMARY Many different approaches have been proposed to deal with the signal extraction problem in g...
This paper considers various asymptotic approximations to the finite sample distribution of the esti...
We discuss some challenges presented by trending data in time series econometrics. To the empirical ...
textabstractWe develop a formal statistical approach to investigate the possibility that leading ind...
textabstractWe compare the forecasting performance of linear autoregressive models, autoregressive m...
cRoyal Economic Society 2006Summary: The application of a partially linear model to global and hemis...
Trend detection is model-dependent. We analyze this for auto-correlated temperature time series. By ...
Leading, coincident and lagging indicators have long been used to analyze and assess the current sta...
Abstract: A knowledge of the level of trend ination is key to many current policy decisions and seve...
This paper examines growth forecasts of models that allow for cross-country interactions and/or a ti...
A study of business cycles does not require trend estimation and elimination, but a study of growth ...
The paper considers stochastic linear trends in series with a higher than annual frequency of observ...
This thesis suggests a general approach for estimating the trend of a univariate time series. It beg...
The local linear trend and global linear trend models embody extreme assumptions about trends. Accor...
The global linear trend with autocorrelated disturbances is a surprising omission from the M1 compet...
SUMMARY Many different approaches have been proposed to deal with the signal extraction problem in g...
This paper considers various asymptotic approximations to the finite sample distribution of the esti...
We discuss some challenges presented by trending data in time series econometrics. To the empirical ...
textabstractWe develop a formal statistical approach to investigate the possibility that leading ind...
textabstractWe compare the forecasting performance of linear autoregressive models, autoregressive m...
cRoyal Economic Society 2006Summary: The application of a partially linear model to global and hemis...
Trend detection is model-dependent. We analyze this for auto-correlated temperature time series. By ...
Leading, coincident and lagging indicators have long been used to analyze and assess the current sta...
Abstract: A knowledge of the level of trend ination is key to many current policy decisions and seve...
This paper examines growth forecasts of models that allow for cross-country interactions and/or a ti...
A study of business cycles does not require trend estimation and elimination, but a study of growth ...
The paper considers stochastic linear trends in series with a higher than annual frequency of observ...
This thesis suggests a general approach for estimating the trend of a univariate time series. It beg...