At our recent forecast update conference, we reported that the COVID-19 recession slammed California’s economy leading to a 9% loss in jobs in 2020 versus a milder loss of 6.7% in the U.S.
In a recent article of mine published in COVID Economics, I showed that California suffered more job losses because of its aggressive COVID-19 lockdown policies. As measured by the Oxford University index, California’s 2020 annual average daily stringency score was 60.4 versus 50.2 for the U.S. That stringency score of 60.4 ranked California as the 6th highest of all 50 states.
The close relationship between higher stringency scores and higher job losses can be seen by dividing the 50 states into five groups of 10 states each in order of stringency. For example, the ten states with the lowest Oxford University stringency scores (18.4 – 36.1) experienced an average job loss of 5.1%. The next highest stringency group of states (36.5 – 40.0) had an average job loss of 6.0%; followed by states (40 – 43) with an average job loss of 8.1%; followed by states (44 – 48) with an average job loss of 8.3 percent; followed by states (49 – 61) with an average job loss of 10.4%.
These findings provide strong statistical support that California’s higher job losses than the nation in 2020 were caused by its more restrictive mandates. Rigorous support of this conclusion is provided by using more sophisticated statistical procedures (multiple regression analyses) that show the exact relationship between stringency scores and jobs. Specifically, my findings show that as states become more restrictive as measured by their Oxford stringency scores, job losses in those more restrictive states increase. Not only that, but the degree of job losses increases at an increasing rate.
This statistical finding suggests that as states like California become increasingly aggressive in imposing mandates (like closing K-12 schools), the economic loss for those states is exponentially greater than those states that followed a more moderate policy. Texas, for example, had a stringency score of 50.5 (close to the national average of 50.2) and, as a result, experienced an average job loss of 4.8% versus California’s 9%.
If California’s stringency were closer to the national average of 50.2, my empirical findings suggest that California would have saved about 370,000 jobs, a total similar to the population of Anaheim, California’s 10th largest city.
These job losses in California did not occur only in low-paying job sectors like leisure and hospitality. Our recent update of the Chapman-UCI innovation index through the third quarter of 2020 shows that just as COVID-19 hit California harder in overall job losses, it also led to lower job growth in innovation industries in California as compared to the U.S.
California’s aggressive strategy in mandating harsher stringency regulations is reflected not only in lost jobs but also in lower real gross state product – the most comprehensive measure of a state’s economic output. My empirical findings show that real gross state product was about a half percent lower because California’s stringency score was 10 points higher than the average score for all states. That translates to a loss of $87 billion in real gross state product.
Even more startling are my findings that reveal the economic cost per life saved associated with California’s more aggressive policies. After holding all other explanatory factors constant, the economic cost per life saved in California was $1.4 million, about 30% higher than the $1.1 million average cost per life saved for the nation.
It should be noted that my research showed that increasing stringency saved lives. No doubt, higher stringency scores are associated with lower COVID-19 death rates. But unlike jobs and gross state product, where the economic costs increased exponentially with higher scores, the COVID-19 death rate decreased at a diminishing rate.
By pushing past the average stringency score of 50, California’s job and income losses rose rapidly while the number of lives saved diminished. That, in turn, suggests that the sweet spot in terms of optimal stringency strategy is to stay closer to the national average rather than push the boundaries.
James L. Doti is president emeritus and professor of economics at Chapman University.
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