MARC details
| 000 -LEADER |
|---|
| fixed length control field |
01901nam a22002537a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
ZW-GwMSU |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20240320134502.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
240320b |||||||| |||| 00| 0 eng d |
| 022 ## - INTERNATIONAL STANDARD SERIAL NUMBER |
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| International Standard Serial Number |
02664666 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
MSU |
| Language of cataloging |
English |
| Transcribing agency |
MSU |
| Description conventions |
rda |
| 050 00 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
HB139.T52 ECO |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Lieil, Robert P. |
| Relator term |
author |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
On the recoverability of forecasters' preferences |
| Statement of responsibility, etc. |
created by Robert P. Lieil and Maxwell B. Stinchcombe |
| 264 1# - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Cambridge: |
| Name of producer, publisher, distributor, manufacturer |
Cambridge University Press, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2013. |
| 336 ## - CONTENT TYPE |
|---|
| Source |
rdacontent |
| Content type term |
text |
| Content type code |
txt |
| 337 ## - MEDIA TYPE |
|---|
| Source |
rdamedia |
| Media type term |
unmediated |
| Media type code |
n |
| 338 ## - CARRIER TYPE |
|---|
| Source |
rdacarrier |
| Carrier type term |
volume |
| Carrier type code |
nc |
| 440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE |
|---|
| Title |
Econometric Theory |
| Volume/sequential designation |
Volume 29, number 3 |
| 520 3# - SUMMARY, ETC. |
|---|
| Summary, etc. |
We study the problem of identifying a forecaster’s loss function from observations on forecasts, realizations, and the forecaster’s information set. Essentially different loss functions can lead to the same forecasts in all situations, though within the class of all continuous loss functions, this is strongly nongeneric. With the small set of exceptional cases ruled out, generic nonparametric preference recovery is theoretically possible, but identification depends critically on the amount of variation in the conditional distributions of the process being forecast. There exist processes with sufficient variability to guarantee identification, and much of this variation is also necessary for a process to have universal identifying power. We also briefly address the case in which the econometrician does not fully observe the conditional distributions used by the forecaster, and in this context we provide a practically useful set identification result for loss functions used in forecasting binary variables. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Forecasting model |
| Form subdivision |
Theory of preferences |
| General subdivision |
Economic forecast |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Stinchcombe, Maxwell B. |
| Relator term |
co author |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| Uniform Resource Identifier |
https://doi.org/10.1017/S0266466612000461 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Journal Article |