Improving Causal Models for Election Forecasting: Further Evidence on the Golden Rule of Forecasting

10 Pages Posted: 1 Sep 2014

See all articles by Andreas Graefe

Andreas Graefe

Macromedia University of Applied Sciences

J. Scott Armstrong

University of Pennsylvania - Marketing Department

Kesten C. Green

University of South Australia - UniSA Business School; Ehrenberg-Bass Institute for Marketing Science

Date Written: August 26, 2014

Abstract

The Golden Rule of Forecasting counsels forecasters to be conservative when making forecasts. We tested the value of three of the four Golden Rule guidelines that apply to causal models: modify effect estimates to reflect uncerainty; use all important variables; and combine forecasts from diverse models. These guidelines were tested using out-of-sample forecasts from eight US presidential election forecasting models across the 15 elections from 1956 to 2012. Moderating effect sizes via equalizing regression coefficients reduced the error relative to the original model forecasts by 5%. Including all 25 variables from the eight models in a single equal-weights index model reduced error by 46%, and combining forecasts from the eight models reduced error by 36%.

Keywords: Econometrics, election forecasting, equalizing, equal weights, index method, political economy models, regression

Suggested Citation

Graefe, Andreas and Armstrong, J. Scott and Green, Kesten C., Improving Causal Models for Election Forecasting: Further Evidence on the Golden Rule of Forecasting (August 26, 2014). APSA 2014 Annual Meeting Paper. Available at SSRN: https://ssrn.com/abstract=2451666

Andreas Graefe (Contact Author)

Macromedia University of Applied Sciences ( email )

Sandstrasse 9
Munich, Bavaria 80337
Germany

HOME PAGE: http://www.andreas-graefe.org

J. Scott Armstrong

University of Pennsylvania - Marketing Department ( email )

700 Jon M. Huntsman Hall
3730 Walnut Street
Philadelphia, PA 19104-6340
United States
215-898-5087 (Phone)
215-898-2534 (Fax)

HOME PAGE: http://marketing.wharton.upenn.edu/people/faculty/armstrong.cfm

Kesten C. Green

University of South Australia - UniSA Business School ( email )

GPO Box 2471
Adelaide, SA 5001
Australia
+61 8 83012 9097 (Phone)

HOME PAGE: http://people.unisa.edu.au/Kesten.Green

Ehrenberg-Bass Institute for Marketing Science ( email )

Australia

HOME PAGE: http://www.marketingscience.info/people/KestenGreen.html

Register to save articles to
your library

Register

Paper statistics

Downloads
72
Abstract Views
602
rank
331,183
PlumX Metrics