Undergraduate Research Blog Post #2

 

Discuss the progress you have made so far. 

Since the initial blog post we have been analysing past research papers as well as other academic reviews in order to have a thorough literature review. This led to a vast amount of variables and a large pile of data, which we are currently in the process of fine tuning to only the essential variables for the parsimonious model.

Provide insights and reflections on the data you have obtained so far. 

The primary tool that I will be using to create a model will be STATA, thus I had to get well acquainted with STATA over the course of time since the previous blog post. I have begun testing various simple models in order to insure accuracy and allow the data to be presented in the most efficient format possible. I plan to finish the variable-related work over the break and we hope to test the model early next semester; while consulting the most recent economic resources and statistics available.

Include any questions raised from the data you collected. 

Given that the result of the election has already been decided this will be slightly unorthodox, we have to make sure that the data is not affected in any way by this. Further, the more we continue to streamline the data the more the data is leaning to a few essential variables such as certain states, population vote v. general vote, historical precedence, etc. The significance of the work can be seen simply by removing the unnecessary factors from the data.

Undergraduate Research Blog Post #1

Please describe the title and purpose of your project as well as the goals and objectives of your research.

The title of the research paper is ‘2016 US Presidential Election: Socio-Economic Determinants and an Economic Outlook’; the main purpose of the project is to investigate the various factors that would affect the outcome of the election, produce a prediction and then evaluate the post-election economy given the result. Given the peculiarity of this election I wanted to incorporate as many factors as possible and many current models seem to neglect the affect that demographic variables have on predictions. We will also include panel data taken over past elections from 1972-2012, historical precedent plays an important role and this along with the numerous other factors will help predict the election for us. Given that the election result will be available before we conclude research we will be able to see if the model predicted the correct outcome; this is where we go into the strictly economic part of the research. We will then create an economic forecast based on the policies of the elected candidate and we will continue to analyse this up until May 2017 when our economic forecast can be evaluated.

Highlight what you expect to achieve or learn from this project.

I wanted to conduct research first and foremost because I would be working with Dr. Morreale, I have been enrolled advanced economics classes but this was an opportunity to gain some practical knowledge that would not normally be accessible to me. I have not yet truly been immersed in a long-term research project, so examining data and ensuring that it is processed and presented accurately and correctly is a skill that I want to perfect. Given that STATA will be an integral tool for me as I continue to take more advanced classes, the exposure and technical expertise that the research project will allow me to have is invaluable. I strive to expand my academic horizons as much as possible and this research project will go some way to achieving that; the final presentation and showcase event are allow unique experiences that I wanted to be a part of.

Explain what methods you will use to answer your research questions.

I will be analysing Polls and evaluating past election result but the primary tool that I will be using to create a model will be STATA and I will likely use other data based software such as excel. We will be using regression modelling throughout the process of predicting the election and we will consult national economic resources and statistics for the economic forecast.