Predicting the 2024 US Presidential Election
Political forecasting is looking into the political future, and its corollary election forecasting is seeing into the future of voting behavior. The most popular method of election forecasting is pre-election polls. There is also election forecasting using statistical models.
I built a political economy and security model which has predicted that Kamala Harris will win the 2024 US Presidential Election. This is a regression model which simply means I use several issues that are important to voters to predict the election outcome. The political economy and security is a statistical model which uses political, economic and security data from academic, not for profit, official sources, and polls to forecast the election. The research question the model answers is: “What is the probability of the Democratic Party candidate or the Republican Party candidate winning the 2024 Presidential Election?
The issues used to predict the Harris win are the annualized net difference in Democratic and Republican voters trust in the government to do what is right, annualized consumer price index, the annualized number of immigrants as a proportion of the population, and the annualized prison population growth rate from 1952-2023. The outcome is party in power candidate in the White House (Democrat/Republican).
The model argues that voters will reward the Democratic party in power in the White House with an election victory when there is a decrease in the difference between Democratic voters and Republican voters trust in the government to do what is right, there is an increase in inflation that the Democrats frame as resulting from corporate greed rather than government spending, and voters feel physically safe and secure because of lower rates of immigration into the country and lower rates of incarceration. This argument was confirmed by the model’s output which means that the Democratic Party candidate Kamala Harris will win the election. The model correctly predicts the political party candidate in the White House 90.63% of the time so the model has a very high rate of accuracy. The election will be a very close one.
Christopher A.D. Charles Ph.D. is a Full Professor of Political and Social Psychology at the University of the West Indies, Mona. He is also a member of the executive council of the political forecasting group in the American Political Science Association.
