An evaluation of real-time forecasting performance across 10 western U.S. States

Article type: Research Article

Authors: Phillips, Keith R.^a | Lopez, Joaquin^{a; *}

Affiliations: [a] Federal Reserve Bank of Dallas, San Antonio, TX 78204, USA

Correspondence: [*] Corresponding author: Joaquin Lopez was an economic analyst at the Federal Reserve Bank of Dallas when this article was written but currently is a Ph.D. student at the University of Chicago. Tel.: +1 210 978 1409; E-mail: [email protected]. The views expressed here are those of the authors and do not necessarily reflect those of the Federal Reserve Bank of Dallas or the Federal Reserve System

Abstract: The recent financial crisis and economic downturn has emphasized the importance of accurate sub-national forecasting models. To judge which models work best, researchers have emphasized the importance of looking at the true real-time performance of models and not simply an analysis of out-of-sample results. In this study we utilize real-time forecasts from the Western Blue Chip Economic Forecast to analyze and evaluate a host of different forecasters and models across time and 10 U.S. states to see if some models and forecasters consistently outperform others. We use the forecast accuracy criteria established by the Blue Chip publication. To evaluate accuracy we develop a scoring procedure based on the number of years that the forecaster/model was closest to actual relative to what we would expect just by random chance. We also utilize standard measures such as the Root Mean Square Error and Theil's inequality coefficient and test the statistical significance of the best forecasts. We then take a closer look at one model that has proven to be very accurate.

Keywords: Econometric models, regional data, benchmarking, and seasonal adjustment

DOI: 10.3233/JEM-2009-0318

Journal: Journal of Economic and Social Measurement, vol. 34, no. 2-3, pp. 119-132, 2009