| 000 -LEADER |
|---|
| fixed length control field |
01471nam a22001457a 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
220429b ||||| |||| 00| 0 eng d |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Rossi, Barbara |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Forecasting in the presence of instabilities: How we know whether models predict well and how to improve them |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc |
Journal of Economic Literature |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
59(4), Dec, 2021: p.1135-1190 |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
This article provides guidance on how to evaluate and improve the forecasting ability of models in the presence of instabilities, which are widespread in economic time series. Empirically relevant examples include predicting the financial crisis of 2007–08, as well as, more broadly, fluctuations in asset prices, exchange rates, output growth, and inflation. In the context of unstable environments, I discuss how to assess models' forecasting ability; how to robustify models' estimation; and how to correctly report measures of forecast uncertainty. Importantly, and perhaps surprisingly, breaks in models' parameters are neither necessary nor sufficient to generate time variation in models' forecasting performance: thus, one should not test for breaks in models' parameters, but rather evaluate their forecasting ability in a robust way. In addition, local measures of models' forecasting performance are more appropriate than traditional, average measures. – Reproduced |
| 773 ## - HOST ITEM ENTRY |
|---|
| Main entry heading |
Journal of Economic Literature |
| 906 ## - LOCAL DATA ELEMENT F, LDF (RLIN) |
|---|
| Subject DIP |
ECONOMIC DEVELOPMENT |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Item type |
Articles |
