Econometrics; R Program; Data Mining; Economic Indicators
Econometrics and Datamining using R Programming
I provide an analysis of Rhode Island economic conditions by comparing economic variables in the state to other states in New England and the country as a whole. I learned the programming language R to complete the analysis using published economic statistics. Statistics provided from the Bureau of Economic Analysis (BEA) show quarterly or annual trends which can assist the researcher in predicting future trends. This data includes figures such as real personal income, real GDP, per capita real GDP, regional price parities, housing prices, and total full-time and part-time employment by state; additionally, industry statistics can be analyzed by employment, wage and salary data. The main focus of this project is to bring data from various economic web sites into R Studio to represent these categories as easy-to-interpret figures and graphs. These figures and graphs highlight the connections between various industry, employment, and GDP data to draw conclusions as to which sectors of the economy are affecting others. Doing this for each state in New England will then give the researcher a comparison of data on a regionally-based scale against which to compare Rhode Island.
Since this project aims to also analyze reaction to these economic trends, datamining will be used to search for related hashtags on social media platforms. By datamining, a programmer can extract keywords (such as state names and economic factors) that positively or negatively argue for the trends of current policy. Relating this project to policy making, I further the experiment by interviewing representatives within the Rhode Island State House Judicial Committee to understand their viewpoint on the current Rhode Island economic situation.