Political Party Identification: Predicting Party Affiliations based on Age and Economic Outlook. My research captures three variables used in determining the performance of the current and past ruling parties. Through the associations determined, I will develop a linear regression model based on the ages of respondents, and economic outlook over the past twelve months to determine the individual’s party affiliation. I will run correlations between each of the independent variables and the dependent to ascertain whether as postulated, older, more conservative Americans are more likely to be associated with the more conservative Republican Party; and whether either Democrats or Republicans have a more biased outlook of the economic situation in the country.
Based on the outcome, it will be possible to determine which party has a higher likelihood of winning the 2016 Presidential elections based statistical evidence. The dependent variable for this research is party affiliation (PID_X). It will be determined using respondents’ perceived economic status of the country between the time of the survey and the previous one year (ECON_ECPAST_X), which is the first independent variable for this study. Age (DEM-AGEGRP_IWDATE), the other independent variable, will serve as a moderating factor for the relationship between party affiliation and economic outlook.
Hypothetically, by older people being more conservative and more pro-Republican, age could be a source of unaccounted-for bias, which advised the decision to use it as a moderating factor. This way, the bias will be eliminated, and obtain a fairer prediction of party affiliation based on economic outlook.