Evaluating Probability Forecasts for GDP Declines Using Alternative Methodologies

Posted: 12 Jul 2012

See all articles by Kajal Lahiri

Kajal Lahiri

State University of New York (SUNY) at Albany, College of Arts and Sciences, Economics

Jiazhuo George Wang

affiliation not provided to SSRN

Date Written: July 11, 2012

Abstract

Evaluation methodologies for rare events from meteorology, psychology and medical diagnosis are used to examine the value of probability forecasts of real GDP declines during the current (Q0) and each of the next four quarters (Q1-Q4) using data from the Survey of Professional Forecasters. We study the quality of these probability forecasts in terms of calibration, resolution, odds ratio, the relative operating characteristic (ROC), and alternative variance decompositions. Only the shorter-term forecasts (Q0-Q2) are found to possess significant skill in terms of all measures considered, even though they are characterized by excess variability and lack of calibration.

The battery of diagnostic statistics cataloged in this paper should be useful for evaluating regression models with binary dependent variables, particularly when the event of interest is relatively uncommon.

Keywords: Binary prediction, Rare events, Survey of Professional Forecasters, Subjective probability, Calibration, Resolution, Skill score, Relative Operating Characteristics, Odds ratio, Recession

JEL Classification: B22, C11, C22, C53

Suggested Citation

Lahiri, Kajal and Wang, Jiazhuo George, Evaluating Probability Forecasts for GDP Declines Using Alternative Methodologies (July 11, 2012). International Journal of Forecasting, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2103892

Kajal Lahiri (Contact Author)

State University of New York (SUNY) at Albany, College of Arts and Sciences, Economics ( email )

Department of Economics
1400 Washington Avenue
Albany, NY 12222
United States
518-442 4758 (Phone)
518-442 4736 (Fax)

HOME PAGE: http://www.albany.edu/~klahiri

Jiazhuo George Wang

affiliation not provided to SSRN ( email )

Here is the Coronavirus
related research on SSRN

Paper statistics

Abstract Views
319
PlumX Metrics