Approximately normal tests for equal predictive accuracy in nested models / Todd E. Clark and Kenneth D. West.
| Author/creator | Clark, Todd E. |
| Other author | West, Kenneth D. (Kenneth David) |
| Other author | Federal Reserve Bank of Kansas City. Research Division. |
| Format | Electronic |
| Publication Info | Kansas City [Mo.] : Research Division, Federal Reserve Bank of Kansas City, |
| Supplemental Content | Full text available from NBER Working Papers |
| Series | RWP ; 05-05 Research working paper (Federal Reserve Bank of Kansas City : Online) ; 05-05. UNAUTHORIZED |
| Summary | "Forecast evaluation often compares a parsimonious null model to a larger model that nests the null model. Under the null that the parsimonious model generates the data, the larger model introduces noise into its forecasts by estimating parameters whose population values are zero. We observe that the mean squared prediction error (MSPE) from the parsimonious model is therefore expected to be smaller than that of the larger model. We describe how to adjust MSPEs to account for this noise. We propose applying standard methods (West (1996)) to test whether the adjusted mean squared error difference is zero. We refer to nonstandard limiting distributions derived in Clark and McCracken (2001, 2005a) to argue that use of standard normal critical values will yield actual sizes close to, but a little less than, nominal size. Simulation evidence supports our recommended procedure." |
| General note | Title from PDF file (viewed on Dec. 30, 2005). |
| General note | "November 2005." |
| Bibliography note | Includes bibliographical references. |
| Access restriction | Available only to authorized users. |
| Other forms | Also available in print. |
| Technical details | Mode of access: World Wide Web |
| Genre/form | Electronic books. |
| LCCN | 2005301035 |
Availability
| Library | Location | Call Number | Status | Item Actions |
|---|---|---|---|---|
| Electronic Resources | Access Content Online | ✔ Available |