Dec 7, 2020

Gov 1347: Election Analytics - Narrative

Gov 1347 Election 2020

The fall semester is wrapping up and this will be my final blog post for Gov 1347. After 10 blogs, I can't help but stop and appreciate just how much I've learned in the past three months and all the fun I had writing these. So, even though this chapter is coming to an end, I'm excited to see what my next blog post might entail. For this final Gov 1347 post, I will be evaluating and testing the post-election narrative that COVID-19 was the main cause of Trump's loss to Biden. I'll start with a comparison of the 2020 and 2016 election results. Then, I'll pull in county-level data and evaluate connections between the 2020 election and covid. Read More...

Nov 21, 2020

Gov 1347: Election Analytics - Post-Election Reflection

Gov 1347 Election 2020

It is now almost two weeks and a half past election day 2020. Joe Biden is now the president-elect, however President Trump will not concede and is instead contesting the election. It is unlikely that the results of the election will be changing, as there does not appear to be any solid evidence of widespread voter fraud. So, I will be going ahead with my post-election analysis and reflection. I'll specifically be exploring how my models performed and try to brainstorm what caused any errors in my models. At the end, I will address some things I think would be useful to explore in forecasting future election. Read More...

Nov 1, 2020

Gov 1347: Election Analytics - Final Prediction

Gov 1347 Election 2020

With election night rounding the corner, it is time for me to make one final attempt to forecast the 2020 presidential election. For my final forecast, I decided to use two different types of models: a multiple linear regression model for my two-party popular vote forecast and a binomial logistic regression model for my electoral college forecast. These models are very similar to the ones created in the Harvard Political Review's forecast that I co-authored. However, I extend the electoral college model to use a binomial logistic regression to try and do a better job of accounting for fundamental uncertainty. Read More...

Oct 24, 2020

Gov 1347: Election Analytics - Shocks

Gov 1347 Election 2020

This week, I'm looking at shocks and how they affect elections. 2020 has been full of shocks, from the COVID-19 virus to the death of Justice Ruth Bader Ginsburg. In this blog, I'll look and discuss the effect of the COVID-19 virus. I'll also be creating an updated state prediction model. Read More...

Oct 17, 2020

Gov 1347: Election Analytics - Demographics

Gov 1347 Election 2020

This week, I am looking at the demographic breakdown of individual states. Using the change in demography, I create models for each state predicting two-party popular vote. I then compare these models to a control model that uses polls and incumbency to predict two-party popular vote. I also begin to explore the use of the caret package in this blog, specifically for cross-validation. Read More...

Oct 11, 2020

Gov 1347: Election Analytics - Advertising

Gov 1347 Election 2020

This week, I am diving into TV advertising spending done by presidential candidates. I start by looking at the historical rise of TV advertising in presidential elections. Then, I'll present spending data by presidential candidates on TV ads in the past few elections. This data will be used to create a model to try to predict the 2020 electoral map solely based on the proportion of TV ad dominance by each candidate and the party of each candidate. Read More...

Oct 4, 2020

Gov 1347: Election Analytics - Incumbency

Gov 1347 Election 2020

This week, I am looking at incumbency and the unique position that incumbents have in presidential elections. I'll start off by evaluating some of the advantages that incumbents have and then build a few models that use incumbency. At the end, I compare my models to the Time For Change Model and then make predictions for the 2020 election. Read More...

Sep 27, 2020

Gov 1347: Election Analytics - Polls

Gov 1347 Election 2020

This week, I am be looking at polls and incorporating them into prediction models alongside a measure of the economy. I'll begin with comparing the different grades of polls and looking at the polls from 2016 and 2020. Then, I'll take a dive into state polls and create a model to try and predict the election outcome in Florida for 2020. Read More...

Sep 19, 2020

Gov 1347: Election Analytics - The Economy

Gov 1347 Election 2020

This week, I am building predictive models for US presidential elections using the following economic variables: Gross Domestic Product (GDP), Real Disposable Income (RDI), and Unemployment. For each model, I'll apply data from 2020 to evaluate its accuracy and then focus on incumbency. I wrap up by modeling state level unemployment data and comparing it to the model which uses national level unemployment data. Read More...

Sep 12, 2020

Gov 1347: Election Analytics - Introduction

Gov 1347 Election 2020

For the first blog, I'll be exploring past election results to find any trends in the data. More specifically, I'll be looking at incumbency, the electoral college, and swing states. Read More...