Campaign Narrative
History of the District New Hampshire’s 2nd District is currently represented by Ann Kuster McLane, a five-term incumbent who was just elected to a sixth term. She represents roughly 680,000 people, a population that is overwhelmingly white (88.1%) with a high high-school graduation rate but a college graduation rate of only 37%, compared to 42% of Americans. The median household income is $77,432, compared to the national median of $70,784.
Election Reflection
This blog is part of a series related to Gov 1347: Election Analytics, a course at Harvard University taught by Professor Ryan D. Enos. Introduction This election cycle led to some expectations being met and some surprises. A “red wave,” somewhat like the one predicted in my model, was unsuccessful, however the Republicans still won the House. Some safe House districts, like Colorado-3 with incumbent Lauren Boebert, became extremely tight races and Republicans won in places like New York that no Democrat expected to lose.
Final Prediction
This blog is part of a series related to Gov 1347: Election Analytics, a course at Harvard University taught by Professor Ryan D. Enos. Introduction This post has been a long time coming. A culmination of all of my analytical work and experimentation with R this semester, this post will describe and evaluate my final predictive model for the 2022 Election. For the last ten weeks, I have been building models to try to predict the election, using new dependent variables as we study them.
Blog 7: Shocks
This blog is part of a series related to Gov 1347: Election Analytics, a course at Harvard University taught by Professor Ryan D. Enos. Introduction This week in Election Analytics, two weeks out from the election, we are talking about “shocks,” or significant events that have the capacity to change the outcome of an election. It has been established that voters evaluate incumbents based on past performance, but when reviewing shocks, do voters take them into account when making decisions?
Blog 6: The Ground Game
This blog is part of a series related to Gov 1347: Election Analytics, a course at Harvard University taught by Professor Ryan D. Enos. Introduction This week in Election Analytics, we are talking about the ground game, or the impact that campaign operations on the ground have on election outcomes. First, looking at the literature, there are a lot of opinions and research about different goals of the ground game, but most of them focus on persuasion, convicing a registered voter to vote for your preferred candidate, or mobilization, getting a campaign’s supporters out to vote.
Blog 5: The Air War
This blog is part of a series related to Gov 1347: Election Analytics, a course at Harvard University taught by Professor Ryan D. Enos. This week, Gov 1347 is looking at the Air War: the neverending battle between campaigns to capture potential voters’ attention via television advertisements. There are different theories about the impact of campaign ads on voting preferences but both Gerber et al. and Huber and Arceneaux, our authors for the week, have discovered through their research that ads have little to no effect on voter mobilization.
Blog 4: Incumbency
This blog is part of a series related to Gov 1347: Election Analytics, a course at Harvard University taught by Professor Ryan D. Enos. Introduction This week in Election Analytics, we will be incorporating incumbency and expert predictions into our existing models. Incumbency is widely considered to have an impact in elections. In recent years, analysts have looked deeper into this, identifying two types of incumbent impact: President’s Party and district-level incumbency.
Blog Post 3: Polling
This blog is part of a series related to Gov 1347: Election Analytics, a course at Harvard University taught by Professor Ryan D. Enos. Introduction This week in Election Analytics, the subject of discussion is Polling. How do polls impact election predictions? Are they reliable? How should they be weighed when compared to other factors like the fundamentals, or economy-based predictions? Before diving into my model and this week’s adjustments, let’s break down the work of some more experienced pollsters.
Blog Post 2
This blog is part of a series related to Gov 1347: Election Analytics, a course at Harvard University taught by Professor Ryan D. Enos. Introduction This week in Election Analytics, we are talking about the economy. We are not the first to do this. It has long been theorized that the economy has an tremendous impact on election results, to the point that some predictors, like Yale professor Ray Fair, rely solely on economic variables in developing their models.
Election Analytics: Blog Post 1
This blog is part of a series related to Gov 1347: Election Analytics, a course at Harvard University taught by Professor Ryan D. Enos. Introduction My name is Meredith Zielonka and I’m a sophomore at Harvard College studying Government, hopefully with a subfield specialization in data science. This semester, I will be assembling a blog in order to track the evolution of my predictions regarding the results of the 2022 midterms.