/A_Panel_Data_Analysis_to_Forecast_US_Presidential_Elections

In this paper I will initially retrace the path marked by Ray C. Fair with his long lasting series of presidential elections forecasts exploiting the same variables he uses but enriching the model with panel data. Exploiting the Fixed Effects estimation I will then add new variables that, according to our intuition, could lead to an overall improvement of the model and test for them applying the LASSO algorithm for model selection. I will finally infer the results and explore the possible challenges in disentangling causality from correlation

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