I. Introduction; II. The Encompassing Principle; III. Data and Out-of-Sample Forecasts; IV. The Encompassing Algorithm; V. Results; A. Does the Algorithm Work?; B. Which Significance Level to Use?; VI. Comparisons With Other Methods; VII. Conclusions; Appendix; I. Data; Appendix Tables; 1. Description of Data; 2. Relative Performance of Algorithm Forecasts; 3. A Comparison of Forecast Combination Methods; Figure; 1. Relative Performance of Algorithm Forecasts; References
Summary
The paper proposes an algorithm that uses forecast encompassing tests for combining forecasts. The algorithm excludes a forecast from the combination if it is encompassed by another forecast. To assess the usefulness of this approach, an extensive empirical analysis is undertaken using a U.S. macroecoomic data set. The results are encouraging as the algorithm forecasts outperform benchmark model forecasts, in a mean square error (MSE) sense, in a majority of cases
Bibliography
Includes bibliographical references (page 21)
Notes
Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. http://purl.oclc.org/DLF/benchrepro0212 MiAaHDL
English
digitized 2010 HathiTrust Digital Library committed to preserve pda MiAaHDL
