Inference about predictive ability
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Citations
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Cited by:
- Pablo Pincheira, 2008. "Combining Tests of Predictive Ability Theory and Evidence for Chilean and Canadian Exchange Rates," Working Papers Central Bank of Chile 459, Central Bank of Chile.
- Daniel Buncic, 2012.
"Understanding forecast failure of ESTAR models of real exchange rates,"
Empirical Economics, Springer, vol. 43(1), pages 399-426, August.
- Daniel Buncic, 2009. "Understanding forecast failure of ESTAR models of real exchange rates," EERI Research Paper Series EERI_RP_2009_18, Economics and Econometrics Research Institute (EERI), Brussels.
- Buncic, Daniel, 2009. "Understanding forecast failure in ESTAR models of real exchange rates," MPRA Paper 13121, University Library of Munich, Germany.
- Buncic, Daniel, 2009. "Understanding forecast failure of ESTAR models of real exchange rates," MPRA Paper 16526, University Library of Munich, Germany.
- Clements, Michael P. & Smith, Jeremy, 2002. "Evaluating multivariate forecast densities: a comparison of two approaches," International Journal of Forecasting, Elsevier, vol. 18(3), pages 397-407.
- Gabriela De Raaij & Burkhard Raunig, 2005. "Evaluating density forecasts from models of stock market returns," The European Journal of Finance, Taylor & Francis Journals, vol. 11(2), pages 151-166.
- Robledo, Carlos W. & Zapata, Hector O. & McCracken, Michael, 2001. "New Mse Tests For Evaluating Forecasting Performance: Empirics And Bootstrap," 2001 Annual meeting, August 5-8, Chicago, IL 20686, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
- Michael P. Clements & David F. Hendry, 2005. "Guest Editors’ Introduction: Information in Economic Forecasting," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(s1), pages 713-753, December.
- Haider, Adnan & Hanif, Muhammad Nadeem, 2007. "Inflation Forecasting in Pakistan using Artificial Neural Networks," MPRA Paper 14645, University Library of Munich, Germany.
- Clark, Todd E. & McCracken, Michael W., 2001.
"Tests of equal forecast accuracy and encompassing for nested models,"
Journal of Econometrics, Elsevier, vol. 105(1), pages 85-110, November.
- Todd E. Clark & Michael McCracken, 1999. "Tests of Equal Forecast Accuracy and Encompassing for Nested Models," Computing in Economics and Finance 1999 1241, Society for Computational Economics.
- Todd E. Clark & Michael W. McCracken, 2000. "Tests of Equal Forecast Accuracy and Encompassing for Nested Models," Econometric Society World Congress 2000 Contributed Papers 0319, Econometric Society.
- Todd E. Clark & Michael W. McCracken, 1999. "Tests of equal forecast accuracy and encompassing for nested models," Research Working Paper 99-11, Federal Reserve Bank of Kansas City.
- Stanislav Anatolyev, 2007.
"Inference about predictive ability when there are many predictors,"
Working Papers
w0096, Center for Economic and Financial Research (CEFIR).
- Stanislav Anatolyev, 2007. "Inference about predictive ability when there are many predictors," Working Papers w0096, New Economic School (NES).
- Nakamura, Emi, 2005. "Inflation forecasting using a neural network," Economics Letters, Elsevier, vol. 86(3), pages 373-378, March.
- Clements, Michael P. & Franses, Philip Hans & Swanson, Norman R., 2004.
"Forecasting economic and financial time-series with non-linear models,"
International Journal of Forecasting, Elsevier, vol. 20(2), pages 169-183.
- Michael P. Clements & Philip Hans Franses & Norman R. Swanson, 2003. "Forecasting economic and financial time-series with non-linear models," Departmental Working Papers 200309, Rutgers University, Department of Economics.
- Rosario Dell'Aquila & Elvezio Ronchetti, 2004. "Robust tests of predictive accuracy," Metron - International Journal of Statistics, Dipartimento di Statistica, ProbabilitĂ e Statistiche Applicate - University of Rome, vol. 0(2), pages 161-184.
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More about this item
JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2001-10-29 (Econometrics)
- NEP-ETS-2001-10-29 (Econometric Time Series)
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