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Presidential Elections Forecast
My forecast relies on the historical data of the popular data in every state
Acknowledgment
Thanks to Asma Barakat for helping me in gathering the needed data for this research!
Introduction
Many factors affect the election results as the COVID-19, impeachment, economy, unemployment rate, natural disasters’ response, climate change, foreign policy, people’s loyalty to their party, debates, presidents’ heights, and plenty of other factors. In this article, I will focus solely on historical data of the popular vote in every state.
Model
The programming language used in the modeling and analysis is SAS 9.4. The model used is the PROC UNIVARIATE.
Results
To test my model, I predicted the 2016 elections and compared the results to the actual values. Collectively, the algorithm shows that Trump would win in 2016, which actually happened. Also, it forecasts that he will win the 2020 elections. However, by inspecting the state's results, I found that the code predicted 11 states wrong, further details below.
How far in history should we collect the data?
This model relies solely on people’s loyalty to their parties. It does not include any other factors. We gathered the popular vote percentages for every party since 1960.