Info

The following are just a few of the visualizations that I created in R in the Labor Economics course that I took at UCSB during the Summer 2022 quarter. This course served as my first introduction to R, and we mainly only used it to create these simple charts using data from the FRED (Federal Reserve Economic Data) website’s API (using the quantmod library).

Visualizations/Metrics

The labor market participation rate. From the FRED website: “The Labor Force Participation Rate is defined by the Current Population Survey (CPS) as ‘the number of people in the labor force as a percentage of the civilian noninstitutional population […] the participation rate is the percentage of the population that is either working or actively looking for work.’” Additionally, you can see that the gender variable is facet-wrapped in ggplot to display the difference in change between female and male labor force participation over time. As you can see, female labor force participation has largely increased and trended upwards since the 1950’s, while the inverse is true for males.

The unemployment rate. This is simply defined as the number of all people unemployed as a percentage of the labor force. As you can see, there has been many spikes of relatively high unemployment throughout the past decades, with the most notable one occurring in 2020 as a result of the Covid-19 pandemic.

Weekly initial claims. From the FRED website: “An initial claim is a claim filed by an unemployed individual after a separation from an employer. The claim requests a determination of basic eligibility for the Unemployment Insurance program.” This graph in particular shows the weekly claims over the prior ~11 weeks at the time that this assignment was assigned to us in class (2022).

Payroll employment change (in the thousands, seasonally adjusted). From the FRED website: “[Payroll employment] … is a measure of the number of U.S. workers in the economy that excludes proprietors, private household employees, unpaid volunteers, farm employees, and the unincorporated self-employed.” This measure can provide us with information pertaining to the overall health of the economy as it relates to employment. Changes in employment can tell us things about how businesses may be growing or declining, or how much disposable income may be increasing or decreasing, all of which impact the overall economy.

Employment change (seasonally adjusted). This graph displays the difference between the establishment and household surveys. As you can see, the red bars (establishment survey) are identical to the previous metric above (payroll employment change). According to the Bureau of Labor Statistics: “The household survey has no duplication of individuals, because individuals are counted only once, even if they hold more than one job. In the establishment survey, employees working at more than one job and thus appearing on more than one payroll are counted separately for each appearance.” In other words, the payroll survey counts the number of jobs, while the household survey counts the number of employed people.

The Beveridge curve. This curve describes the relationship between the unemployment rate and the vacancy rate (the number of unfilled jobs expressed as a proportion of the labour force). In this case, the two variables are expressed on the axes in logarithmic scale to display/cover all of the given datapoints compactly. Additionally, there is an added OLS (Ordinary Least Square) regression line plotted over the graph to further display the relationship/correlation between the two variables.