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.
|Table 1: Overview of variables used in the convention-bump model|
||Incumbent party’s candidate two-party support in polls before the parties’ first convention||52.2|
||Change in incumbent party’s candidate two-party support polls from before the first convention to after the second convention||0.4|
||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|
|V||Incumbent share of the two-party presidential vote|
The regression model’s vote equation reads as:
V = A + b1
PRE-CONVENTION POLL + b2
NET CONVENTION BUMP + b3
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.
On average across the three elections since 2004, the trial-heat model missed the final results by 2.7 percentage points.
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.