A tale of two metrics: Polling and financial contributions as a measure of performance

TL;DR

This paper analyzes the dynamics of campaign performance in the 2020 Democratic primaries by comparing polling and financial contributions, using joinpoint regression to identify key change points related to candidate support.

Contribution

It introduces the application of joinpoint regression to political campaign data, revealing how campaign events influence voter support and funding patterns.

Findings

Joinpoint regression identifies major campaign events affecting support.

Polling and financial data show both similarities and differences in candidate dynamics.

The method provides insights into voter behavior and campaign success points.

Abstract

Campaign analysis is an integral part of American democracy and has many complexities in its dynamics. Experts have long sought to understand these dynamics and evaluate campaign performance using a variety of techniques. We explore campaign financing and standing in the polls as two components of campaign performance in the context of the 2020 Democratic primaries. We show where these measures exhibit represent similar dynamics and where they differ. We focus on identifying change points in the trend for all candidates using joinpoint regression models. We find how these change points identify major events such as failure or success in a debate. Joinpoint regression reveals who the voters support when they stop supporting a specific candidate. This study demonstrates the value of joinpoint regression in political campaign analysis and it represents a crossover of this technique into the political domain building a foundation for continued exploration and use of this method.