Convention bump model

The convention-bump model, developed by Jim Campbell, predicts the two-party popular vote based on the state of the economy and the candidates’ standing in polls before and after the conventions.

Variable description

Table 1: Overview of variables used in the convention-bump model
Variable Description Value
PRE-CONVENTION POLL Incumbent party’s candidate two-party support in polls before the parties’ first convention 52.2
NET CONVENTION BUMP Change in incumbent party’s candidate two-party support polls from before the first convention to after the second convention 0.4
GDP Annualized real GDP growth rate in the second quarter (April–June) of 2016 as indicated by the Bureau of Economic Analysis’ second estimate released at the end of August 1.1
A Constant 51.2
V Incumbent share of the two-party presidential vote

Vote equation

The regression model’s vote equation reads as:

V = A + b1 PRE-CONVENTION POLL + b2 NET CONVENTION BUMP + b3 GDP

2016 forecast

Jim Campbell presented the 2016 forecast of the convention bump model at the APSA meeting in Philadelphia. The model predicts Clinton to gain 51.2% of the two-party vote, compared to 48.8 for Trump.

Past performance

On average across the three elections since 2004, the trial-heat model missed the final results by 2.7 percentage points.

References

Campbell, J. (2012). Forecasting the Presidential and Congressional Elections of 2012: The Trial-Heat and the Seats-in-Trouble Models. PS: Political Science & Politics, 45(4), 630-634.