Add to ORKGThis review provides an overview of forecasting methods that can help researchers forecast in the presence of non-stationarities caused by instabilities. The emphasis of the review is both theoretical and applied, and provides several examples of interest to economists. We show that modeling instabilities can help, but it depends on how they are modeled. We also show how to robustify a model against instabilities
We propose a new methodology to identify the sources of models' forecasting performance. The methodo...
When the assumption of constant parameters fails, the in-sample fit of a model may be a poor guide t...
Forecasting has always been at the forefront of decision making and planning. The uncertainty that s...
This review provides an overview of forecasting methods that can help researchers forecast in the pr...
This article provides guidance on how to evaluate and improve the forecasting ability of models in t...
Addresses the problems confronting forecasting in economies subject to structural breaks. Discusses ...
To explain which methods might win forecasting competitions on economic time series, we ...
To explain which methods might win forecasting competitions on economic time series, we consider for...
Economic forecasting may go badly awry when there are structural breaks, such that the relationships...
This chapter describes the issues confronting any realistic context for economic forecasting, which ...
To forecast at several, say h, periods into the future, a modeller faces two techniques: iterating o...
This chapter assesses forecasts constructed using dynamic factor models for their reliability in the...
We revisit the concept of unpredictability to explore its implications for forecasting strategies in...
A structural break is viewed as a permanent change in the parameter vector of a model. Using taxonom...
We revisit the concept of unpredictability to explore its implications for forecasting strategies in...
We propose a new methodology to identify the sources of models' forecasting performance. The methodo...
When the assumption of constant parameters fails, the in-sample fit of a model may be a poor guide t...
Forecasting has always been at the forefront of decision making and planning. The uncertainty that s...
This review provides an overview of forecasting methods that can help researchers forecast in the pr...
This article provides guidance on how to evaluate and improve the forecasting ability of models in t...
Addresses the problems confronting forecasting in economies subject to structural breaks. Discusses ...
To explain which methods might win forecasting competitions on economic time series, we ...
To explain which methods might win forecasting competitions on economic time series, we consider for...
Economic forecasting may go badly awry when there are structural breaks, such that the relationships...
This chapter describes the issues confronting any realistic context for economic forecasting, which ...
To forecast at several, say h, periods into the future, a modeller faces two techniques: iterating o...
This chapter assesses forecasts constructed using dynamic factor models for their reliability in the...
We revisit the concept of unpredictability to explore its implications for forecasting strategies in...
A structural break is viewed as a permanent change in the parameter vector of a model. Using taxonom...
We revisit the concept of unpredictability to explore its implications for forecasting strategies in...
We propose a new methodology to identify the sources of models' forecasting performance. The methodo...
When the assumption of constant parameters fails, the in-sample fit of a model may be a poor guide t...
Forecasting has always been at the forefront of decision making and planning. The uncertainty that s...