Post-Election Campaign Narrative
1. Introduction The district I chose to focus on was my home district in Nevada – Congressional District 3. The results of the midterms in Nevada proved that it still continues to be a swing state. While Congresswoman Susie Lee has guarded her seat for 3 consecutive cycles at this point (including the 2022 midterm elections), this district is known to be notoriously tight, and I was interested in observing a diverse and competitive district.
Post-Election Reflection
## Loading required package: ggplot2 ## Loading required package: lattice ## ## Attaching package: 'caret' ## The following objects are masked from 'package:Metrics': ## ## precision, recall 1. A recap of model(s) and predictions The specified prediction model in section (1) is a multivariate regression model that estimates the popular vote share of Democratic Party for House Representative elections using the past five House Representative election results from 2012 to 2020.
Final Election Prediction
#Updated Model When predicting the 2022 midterm elections, I decided to create a linear regression model based on variables from 3 categories: 1) expert predictions, 2) economic indicators, and 3) demographic variables. Included in expert predictions are three variables that are coded as dummy variables: whether it is a close election or not, whether voters are Lean, Likely, or Safe Democrats, and whether or not the President is a Democrat or not.
Ground Game
Do Expert Predictions predict turnout? In my district-level two-party vote share predictions, I incorporated turnout, incumbency and expert predictions to predict turnout and understand the relationship between expert predictions and ground campaigns with turnout as well as ad spending in turnout. I broke down my analysis into 2 different types of models, testing different variables that I found to be relevant. We have learned in class that with all the campaigning during an election, it is useful to adjust predictions based on the information acquired up until the day before the election.
Expert Predictions and Incumbency
## Part 1: Can we trust expert predictions? Expert predictions have long been a method to assure voters of order in a volatile political climate. We have come to a point where we trust models from big media sources and academics that are based on a small number of elections with reliable data along with a couple of heavy handed assumptions. But as Enos and Hersh show in their 2015 paper, “Campaign Perceptions of Electoral Closeness: Uncertainty, Fear and Over-Confidence”, political campaign operatives tend to be overconfident in their candidates’ performance, skewing the perception of the closeness of an election.
Introduction Part 1: U.S.
Describing Trends in the Popular Vote In this first blog, I will attempt to answer two questions: 1) How competitive are midterm elections in the U.S.? 2) Which states vote blue/red and how consistently? Based on all midterm elections from 1950 to 2018, I will use visualizations to address these questions. In the Decline of Competition and Change in Congressional Elections in Congress Responds to the Twentieth Century, Professors Campbell and Juerk claim that without competition, elections are meaningless.
Introduction Part 2: Illinois
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