Macroeconomic Forecasting under Regime Switching, Structural Breaks and High-dimensional Data
Macro-economische voorspellingen bij wisselende economische omstandigheden, structurele veranderingen en hoog-dimensionale data
Macroeconomic time series are not constant over time. Recent years have again emphasized that growth and decline periods alternate, with different dynamics characterizing each period. Such instabilities increase the complexity of econometric models and complicate the construction of accurate forecasts. In addition, more and more macroeconomic indicators are available that might, or might not, have an effect on a specific variable of interest.
In current data sets, the number of predictors tends towards the available number of observations. As a consequence, forecast uncertainty increases further. In this thesis, new shrinkage and dimension reduction techniques are developed that reduce the uncertainty that is inherent to modeling unstable time series or using a large number of possibly relevant predictors.
|, , ,|
|R. Paap (Richard) , A. Pick (Andreas)|
|Erasmus University Rotterdam|
|Tinbergen Instituut Research Series|
|Organisation||Department of Econometrics|
Boot, T. (2017, February 17). Macroeconomic Forecasting under Regime Switching, Structural Breaks and High-dimensional Data (No. 678). Tinbergen Instituut Research Series. Erasmus University Rotterdam. Retrieved from http://hdl.handle.net/1765/95500