Premium
Forecasting the World Economy in the Short Term
Author(s) -
Jakaitiene Audrone,
Dees Stephane
Publication year - 2012
Publication title -
the world economy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.594
H-Index - 68
eISSN - 1467-9701
pISSN - 0378-5920
DOI - 10.1111/j.1467-9701.2011.01433.x
Subject(s) - benchmark (surveying) , aggregate (composite) , ranking (information retrieval) , econometrics , consensus forecast , economics , term (time) , computer science , economic forecasting , task (project management) , world economy , machine learning , geography , materials science , physics , management , geodesy , quantum mechanics , composite material , political science , law
(1433) Audrone Jakaitiene and Stephane Dees Forecasting the world economy is a difficult task given the complex interrelationships within and across countries. This paper proposes a number of approaches to forecast short‐term changes in selected world economic variables and aims, first, at ranking various forecasting methods in terms of forecast accuracy and, second, at checking whether methods forecasting directly aggregate variables (direct approaches) outperform methods based on the aggregation of country‐specific forecasts (bottom‐up approaches). Overall, all methods perform better than a simple benchmark for short horizons (up to 3 months ahead). Among the forecasting approaches used, factor models appear to perform the best. Moreover, direct approaches outperform bottom‐up ones for real variables, but not for prices. Finally, when country‐specific forecasts are adjusted to match direct forecasts at the aggregate levels (top‐down approaches), the forecast accuracy is neither improved nor deteriorated (i.e. top‐down and bottom‐up approaches are broadly equivalent in terms of country‐specific forecast accuracy).