| 000 -LEADER |
|---|
| fixed length control field |
02280nam a2200265Ia 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
DE-boiza |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20191107121337.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
191008 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
0-262-03272-4 |
| 040 ## - CATALOGING SOURCE |
|---|
| Transcribing agency |
IZA |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Clements, Michael P. |
| 9 (RLIN) |
190 |
|
|---|
| Personal name |
Hendry, David F. |
| 9 (RLIN) |
3514 |
| 245 #0 - TITLE STATEMENT |
|---|
| Title |
Forecasting Non-Stationary Economic Time Series |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Date of publication, distribution, etc. |
1999, |
| Name of publisher, distributor, etc. |
MIT Press, |
| Place of publication, distribution, etc. |
Cambridge, Mass et al., |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
362 pages |
| 340 ## - PHYSICAL MEDIUM |
|---|
| Location within medium |
C3 02 |
| 440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE |
|---|
| Title |
Zeutehn Lecture Book Series |
| 9 (RLIN) |
5504 |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Economies evolve and are subject to sudden shifts precipitated by legislative changes, economic policy, major discoveries, and political turmoil. Macroeconometric models are a very imperfect tool for forecasting this highly complicated and changing process. Ignoring these factors leads to a wide discrepancy between theory and practice. In their second book on economic forecasting, Michael P. Clements and David F. Hendry ask why some practices seem to work empirically despite a lack of formal support from theory. After reviewing the conventional approach to economic forecasting, they look at the implications for causal modeling, present a taxonomy of forecast errors, and delineate the sources of forecast failure. They show that forecast-period shifts in deterministic factors—interacting with model misspecification, collinearity, and inconsistent estimation—are the dominant source of systematic failure. They then consider various approaches for avoiding systematic forecasting errors, including intercept corrections, differencing, co-breaking, and modeling regime shifts; they emphasize the distinction between equilibrium correction (based on cointegration) and error correction (automatically offsetting past errors). Finally, they present three applications to test the implications of their framework. Their results on forecasting have wider implications for the conduct of empirical econometric research, model formulation, the testing of economic hypotheses, and model-based policy analyses. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
economy |
| 9 (RLIN) |
146 |
|
|---|
| Topical term or geographic name entry element |
forecast |
| 9 (RLIN) |
590 |
|
|---|
| Topical term or geographic name entry element |
time series analysis |
| 9 (RLIN) |
269 |
| 653 ## - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
forecast failure |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| Uniform Resource Identifier |
<a href="https://mitpress.mit.edu/books/forecasting-non-stationary-economic-time-series">https://mitpress.mit.edu/books/forecasting-non-stationary-economic-time-series</a> |
| Link text |
Publisher's website |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Koha item type |
Monography |
| Source of classification or shelving scheme |
|
