Forecast accuracy and uncertainty in applied econometrics: a recommendation of specific-to-general predictor selection
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DOI: 10.1007/s00181-010-0378-3
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Citations
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Cited by:
- Rossen Anja, 2016.
"On the Predictive Content of Nonlinear Transformations of Lagged Autoregression Residuals and Time Series Observations,"
Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(3), pages 389-409, May.
- Rossen Anja, 2016. "On the Predictive Content of Nonlinear Transformations of Lagged Autoregression Residuals and Time Series Observations," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(3), pages 389-409, May.
- Rossen, Anja, 2011. "On the predictive content of nonlinear transformations of lagged autoregression residuals and time series observations," HWWI Research Papers 113, Hamburg Institute of International Economics (HWWI).
- Rossen, Anja, 2014. "On the predictive content of nonlinear transformations of lagged autoregression residuals and time series observations," HWWI Research Papers 157, Hamburg Institute of International Economics (HWWI).
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More about this item
Keywords
Model selection; Forecasting; Specification testing; Lagrange multiplier tests; Forecast combination; C22; C51;All these keywords.
JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
Statistics
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