A Time Series Analysis of Unemployment Rates

Application Background

Our dataset comes from the Federal Reserve Economic Data (FRED). According to the Federal Reserve website, the Fed “conducts the nation’s monetary policy to promote maximum employment, stable prices, and moderate long-term interest rates in the U.S economy.” The particular dataset we are looking at comes from the U.S. Bureau of Labor Statistics, and it measures the monthly unemployment rate of people in the United States Labor Force. According to Bureau of Labor Statistics, an individual is considered to be unemployed if:

1. They do not have a job
2. Have actively looked for work in the prior four weeks
3. And are currently available for work

It is important to analyze economic data such as the changes in the unemployment rate because it tells us the state of the economy at any given time. From a statistical standpoint, unemployment data indicates trends in certain occupations and/or occupational sectors. One of the goals of the Federal Reserve is to promote maximum employment, which means that they try to be proactive in keeping unemployment rates as low as possible and brace for sudden peaks in unemployment rates. They study and record patterns in order to prevent a spike in unemployment and promote maximum employment. Trends in unemployment help us understand periods of recession because they tend to rise after a recession period begins. We can use the trends we see in unemployment to better understand the business cycle, which portrays upward and downward movements of Gross Domestic Product (GDP), and potentially forecast long-term trend. Because of the relationship between unemployment and GDP, we can possibly use the trends in unemployment data to potentially prevent and prepare for the effects of a recession as GDP is a known economic indicator of when the country is in a recession or approaching a recession period.

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