This project aims to quantify the relationship between a set of macroeconomic indicators
and the unemployment rate (is the percentage of unemployed workers in the labor force).
Specifically, a simple multiple linear regression model is fit to monthly data from 2000 to 2019 to
predict unemployment rate by the following predictors: Consumer Price Index (CPI), Leading
Indicators OECD, China / U.S. Foreign Exchange Rate, Trade Balance, Effective Federal Funds
Rate, S&P 500, Dow Jones Industrial Average, Federal Minimum Hourly Wage for Nonfarm
Workers for the United State, Crude Oil Price, U.S. Inflation Rate, and NASDAQ Composite. The
multiple linear regression model was refined using ANOVA and hypothesis testing. The adequacy
of the refined multiple linear regression model is justified by a high R
(0.95) of the fitted model
and normally distributed residual.