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A Miserable Pandemic

Jacob Hess
June 26, 2021

The economic disruption caused by the COVID-19 pandemic has been widespread across the United States, but individual states have seen very different conditions over the past year and a half. We construct a state "misery index" to build a simple measure of these conditions. The "misery index" is an economic indicator used to gauge the economic condition of people in a country. It was created by Arthur Okun, a US economist in the 1960s that served as the chairman of the Council of Economic Advisers for Lyndon B. Johnson in 1968 and 1969. Okun's misery index was a very simple measure calculated by adding the unemployment rate and the annualized inflation rate, two indicators that describe the health of the consumer. The highest recorded misery index value in the US was in June 1980 at 21.98; the lowest ever recorded was in July 1953 at a super low 2.97.

The traditional misery index described by Okun cannot be created for the individual states for 2020 because state inflation data is not available for the year. Instead, we construct a misery index using the state unemployment rate, a traditional component, and the differential between the state's quarterly GDP and the national quarterly GDP. Using data from the Bureau of Labor Statistics and the Bureau of Economic Analysis, index values for the four quarters of 2020 are calculated.

The average misery index reading across all fifty states was 5.9%, very close to a median value of 5.5%. Values ranged from a minimum of -2.3% in South Dakota and a maximum of 12.5% in Hawaii, two states with big differences in how they handled the pandemic. There was a negative correlation of R = -0.52 between the misery index and the number of COVID-19 cases per 100,000 population; however, there were several outliers which dampened the correlation. The top four outliers in either directions have been labeled in the plot.

Many states with the lowest misery indexes have some of the highest total COVID-19 cases per capita (data as of December 2020): South Dakota ranks 2nd in total cases per capita, Utah ranks 7th, Nebraska ranks 6th, and Iowa ranks 5th. This likely reflects that these states were willing to exchange a better economic outcome for a less desirable public health outcome. Hawaii, Vermont, Oregon, Washington, and Washington DC were in the top six for lowest total cases per capita and had misery indexes above the overall average. Vermont was a noticeable outlier with the lowest total cases per capital and 12th lowest misery index. North Dakota was an outlier in the other direction as the state with the highest cases per capita but an elevated misery index compared to the trend.

Extending from the concept of the correlation identified above, the next plot points out that the severity of containment measures of individual states were positively correlated with a state's misery index at R = 0.69. This trend was slightly clearer with less obvious outliers. Vermont again sticks out as the state that was able to limit economic damage while maintaining above-average restriction levels. This time, Connecticut was close behind. There was a small cluster of states, Mississippi, Oklahoma, and Florida, that had misery indexes around the average despite having some of the lowest containment index values in the country. Nevada was another that drifted off trend. Florida and Nevada stick out as distinct underperformers since they are hotspots for domestic tourism, a sector that was especially impacted by the pandemic.

In fact, almost every state that has a large leisure and hospitality sector (data from regional employment data) experienced a higher misery index (with the exception of South Dakota which was a positive surprise). Nevada, Florida, and Hawaii stick out in this trend with all three states having misery indexes above the average while boasting the largest leisure and hospitality sectors relative to overall employment. Montana and Wyoming aren't obvious outliers, but since they ranked lower on the restrictions index, they should have lower misery indexes. Overall, the correlation is only slightly positively correlated at R = 0.31, but there isn't much variation in other states' leisure and hospitality sector sizes.

The misery index constructed using the unemployment rate and the differential between a state's quarterly GDP and the national quarterly GDP points to various trends during the pandemic. States with more miserable economic outcomes tended to have less miserable public health outcomes. This comes partly from the fact that states with a higher misery index also had higher containment measures which caused workplaces to shut down and movement to be restricted. Another factor that was relevant was the size of the leisure and hospitality sector in states. The top 7 states with the largest share of leisure and hospitality had above-average misery index values.

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