Baseball’s ERA Statistic and the Unemployment Rate Have the Same Problems
Neither is perfect, and that’s fine.
The overlap in the baseball-economics Venn diagram is larger than most realize. Many prominent economists, including former Federal Reserve Chairman Ben Bernanke, are huge baseball fans. Chairman Bernanke’s staff even created a baseball card celebrating his “statistics” upon retirement from the Board of Governors:
Most economists are drawn to both a career in economics and interest in baseball for the same reason: Statistics. Economic statistics (also known as economic indicators) can be similar to statistics in baseball when it comes to shortcomings. Some are known as ‘surface-level’ statistics like the unemployment rate (U-3) or the consumer price index (this is the price index used to calculate inflation rates), while others dig deeper into the economy like the multiple manufacturing indexes (PMI, ISM) or the Case-Shiller home price index. Baseball deals with the same issue of having surface-level statistics and other that dig a bit deeper. The question becomes, is this a bad thing?
Take for example a pitcher’s earned-run average (ERA). A straight-forward statistic calculated by taking the number of earned runs a pitcher allows on average per 9 innings pitched. This statistic, which began being collected in 1912 by the National League, is one of many used to rate a pitcher’s effectiveness on the mound. Is it perfect? No. When you dig deeper, you realize that ERA doesn’t account for important details like poor defense, how well the pitcher does at home versus on the road, or just plain old luck.
To try and control for these factors, baseball statisticians have invented other measures of pitchers’ performance. Two (of many) examples are ERA+ and WHIP. ERA+ adjusts ERA by taking into account the pitcher’s ballpark and which league he belongs to and spits out a number. Anything above 100 indicates the pitcher is above average, whereas below 100 is below average. WHIP stands for walks and hits per inning pitched, telling the observer on average how many walks and hits a pitcher gives up each inning on average, even if they don’t score a run.
If most people agree there are better statistics available for use, why not use them on an everyday basis rather than showing a pitcher’s ERA every time they enter the game? The answer is simple: for the ordinary fan, ERA does a good job. ERA+ and WHIP are available for anyone wanting to dig deeper and do a more thorough analysis.
Economics runs into the same problem. The official unemployment rate in the United States, released on a monthly basis by the Bureau of Labor Statistics (BLS), is calculated by taking the number of people who are classified as unemployed as a percentage of the overall labor force. In order for someone to be unemployed they must have been actively searching for a job over the past 4 weeks. In order for someone to be in the labor force they must be over the age of 16 and either employed or unemployed. The unemployment rate is a surface-level statistic meant to shine light on one tiny aspect of the labor market.
When you learn more about the unemployment rate, you understand its shortcomings. The official number does not count individuals who give up looking for employment because they feel the labor market has nothing to offer them (these individuals are known as discouraged workers). The unemployment rate also does not include those individuals who are working part-time but want to be working full-time (these individuals are known as working part-time for economic reasons).
To give a more complete picture of the unemployment situation in the US, the BLS publishes 5 additional measures that dig deeper into the data and add more information, much like ERA+ or WHIP does for baseball. These are summarized in Table A-15: Alternative Measures of Labor Underutilization of the monthly jobs report. The most detailed measure of unemployment is known as U-6. This statistic includes discouraged workers, people working part-time for economic reasons, and also those who are marginally attached to the labor force (Persons marginally attached to the labor force are defined by the BLS as “those who currently are neither working nor looking for work but indicate that they want and are available for a job and have looked for work sometime in the past 12 months.”) Below shows these statistics since 1994 when collection on these measures began:
As you can see, the official unemployment rate doesn’t tell the whole story of the labor market. Just like a pitcher’s ERA does not tell you everything about his effectiveness. But at the end of the day, the official unemployment rate, like ERA, is a simple statistic to start your understanding. Instead of bashing simple statistics like these and others, it’s time to fully understand the value of both surface-level stats and those that dig deeper.
I leave you with a warning: If you plan on having a discussion about ranking pitchers by their effectiveness on the mound, or a President on their impact on the economy, make sure you have a deeper understanding of pros and cons of the statistics you use. Because trolls don’t just live under bridges these days.
