Autoregression models for unemployment rate
Artykuł w czasopiśmie
| Status: | |
| Autorzy: | Rzymowski Witold, Surowiec Agnieszka |
| Rok wydania: | 2011 |
| Wersja dokumentu: | Drukowana |
| Język: | angielski |
| Wolumen/Tom: | 2 |
| Strony: | 262 - 273 |
| Efekt badań statutowych | NIE |
| Materiał konferencyjny: | NIE |
| Publikacja OA: | NIE |
| Abstrakty: | angielski |
| The Least Absolute Relative Error Estlmatlon Method (LAREEM) was compared with the most Important method ofthe Least Sguares (LSM): The autoregression models. aiso with perlodic components, for the unemployment ratę In Poland In years 1990-2010 are tested. The algorithm which is used to calculate the structure parametersis based on subgradlent method. The purpose o/ these inve5tigations was toflnd the best model to predict as well as possible the unemployment rate in the future. Some models with perlodic components can predict the unemployment ratę in Poland for next month with relaVve error less than3%. |
