Meklēšanas opcijas
Sākums Medijiem Noderīga informācija Pētījumi un publikācijas Statistika Monetārā politika Euro Maksājumi un tirgi Karjera
Ierosinājumi
Šķirošanas kritērijs
Latviešu valodas versija nav pieejama

Paul McNelis

28 April 2004
WORKING PAPER SERIES - No. 352
Details
Abstract
This paper applies linear and neural network-based "thick" models for forecasting inflation based on Phillips-curve formulations in the USA, Japan and the euro area. Thick models represent "trimmed mean" forecasts from several neural network models. They outperform the best performing linear models for "real-time" and "bootstrap" forecasts for service indices for the euro area, and do well, sometimes better, for the more general consumer and producer price indices across a variety of countries.
JEL Code
C12 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Hypothesis Testing: General
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation