The Effect of the Minimum Wage on Employment and Unemployment

In a comment on my blog post about the proposed $15 federal minimum wage, frequent (and careful) commenter KevinDC quotes my statement:

Here’s what they found. The vast majority of studies, 79.3 percent, found that a higher minimum wage led to less employment.

He then comments:

I like the precise wording here by using the term “less employment.” One thing I’ve tried explaining to people is that is possible for increases in the minimum wage to decrease employment without increasing unemployment, because economists are bad at naming things in a way that make intuitive sense to people outside the field. (“Public goods? Obviously that means goods provided by the public sector, right?” “Market failure? That’s whenever I personally don’t like a market outcome, isn’t it?”) So, even in the case where  particular study doesn’t find increased unemployment after a minimum wage hike, that doesn’t actually mean that the increase in the minimum wage didn’t decrease employment.

Well said, Kevin.

I want to add that the CBO study I cited makes this distinction also. Here’s a key paragraph:

Taking those factors into account, CBO projects that, on net, the Raise the Wage Act of 2021 would reduce employment by increasing amounts over the 2021–2025 period. In 2025, when the minimum wage reached $15 per hour, employment would be reduced by 1.4 million workers (or 0.9 percent), according to CBO’s average estimate. In 2021, most workers who would not have a job because of the higher minimum wage would still be looking for work and hence be categorized as unemployed; by 2025, however, half of the 1.4 million people who would be jobless because of the bill would have dropped out of the labor force, CBO estimates. Young, less educated people would account for a disproportionate share of those reductions in employment.

 

 

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890 Thousand Excess Deaths Due to Covid and Lockdowns

We find that shocks to unemployment are followed by statistically significant increases in mortality rates and declines in life expectancy. We use our results to assess the long-run effects of the COVID-19 economic recession on mortality and life expectancy. We estimate the size of the COVID-19-related unemployment to be between 2 and 5 times larger than the typical unemployment shock, depending on race/gender, resulting in a 3.0% increase in mortality rate and a 0.5% drop in life expectancy over the next 15 years for the overall American population. We also predict that the shock will disproportionately affect African-Americans and women, over a short horizon, while white men might suffer large consequences over longer horizons. These figures translate in [to] a staggering 0.89 million additional deaths over the next 15 years.

This is from Francesco Bianchi, Giada Bianchi, and Dongho Song, “The Long-Term Impact of the COVID-19 Unemployment Shock on Life Expectancy and Mortality Rates,” NBER Working Paper No. 28304, December 2020.

An excerpt:

For the overall population, the increase in the death rate following the COVID-19 pandemic implies a staggering 0.89 and 1.37 million excess deaths over the next 15 and 20 years, respectively. These numbers correspond to 0.24% and 0.37% of the projected US population at the 15- and 20-year horizons, respectively. For African- Americans, we estimate 180 thousand and 270 thousand excess deaths over the next 15 and 20 years, respectively. These numbers correspond to 0.34% and 0.49% of the projected African- American population at the 15- and 20-year horizons, respectively. For Whites, we estimate 0.82 and 1.21 million excess deaths over the next 15 and 20 years, respectively. These numbers correspond to 0.30% and 0.44% of the projected White population at the 15- and 20-year horizons, respectively. These numbers are roughly equally split between men and women.

Francesco Bianchi is an economist at Duke University, Giada Bianchi is an MD in the Division of Hematology, Department of Medicine, Brigham and Women’s Hospital Harvard Medical School, and Dongho Song is an economist at the Johns Hopkins University’s Carey Business School.

The authors write:

We interpret these results as a strong indication that policymakers should take into consideration the severe, long-run implications of such a large economic recession on people’s lives when deliberating on COVID-19 recovery and containment measures. Without any doubt, lockdowns save lives, but they also contribute to the decline in real activity that can have severe consequences on health.

I’m not sure why they are confident that there is zero doubt that lockdowns save lives. They admit in the last quoted sentence above that lockdowns “contribute to the decline in real activity that can have severe consequences on health.” What if lockdowns are responsible for half of the bad unemployment consequences, and voluntary actions in response to the fear of getting the virus are responsible for the other half? Then, assuming a linear relationship between unemployment and fatalities, the lockdowns would be responsible for half of 0.89 million to 1.37 million deaths, which translates to between 450,000 deaths and 685,000 deaths. Can they really be confident that lockdowns saved at least 450,000 lives?

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Great News on Employment and Unemployment

On the first Friday of October I laid out the somewhat good news on employment and unemployment for September. This Friday (today), the news is fantastic!

1. The number of people employed increased by 2.243 million. A typical increase in normal times is between 0.2 and 0.3 million, so this is 7 to 10 times as large.

2. The employment to population ratio increased from 56.6 percent to 57.4 percent, a large increase.

3. The number of people unemployed fell from 12.580 million to 11.061 million, a drop of 1.519 million.

4. The unemployment rate fell from 7.9 percent to 6.9 percent.

5. The unemployment rate for people in every single category: black, white, men, women, teenagers, Asian, and Hispanic or Latino, fell. For many of those groups it fell by more than 1 percentage point.

The above are all data from the Bureau of Labor Statistics household survey.

The data from the establishment survey are also good, especially in the details.

1. Private employment rose by 906,000.

2. Leisure and hospitality, one of the sectors hardest hit by both the pandemic and the lockdowns, rose by 208,000.

3. Government employment fell by 268,000.

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Building an Inclusive Recovery in the Middle East and Central Asia

By Jihad Azour and Joyce Wong Countries in the Middle East and Central Asia face with COVID-19 a public health emergency unlike any seen in our lifetime, along with an unprecedented economic downturn. The pandemic is exacerbating existing economic and social challenges, calling for urgent action to mitigate the threat of long-term damage to incomes […]

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Chart of the WeekUnemployment in Today’s Recession Compared to the Global Financial Crisis

By Ippei Shibata There has been much discussion in recent months about how workers who transitioned to working from home—and those who were deemed “essential”—are less affected by the layoffs and job losses brought on by lockdowns than are workers in “social” jobs that require closer human interaction, like restaurant workers. However, our new IMF […]

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The COVID-19 Gender Gap

By Kristalina Georgieva, Stefania Fabrizio, Cheng Hoon Lim, and Marina M. Tavares The COVID-19 pandemic threatens to roll back gains in women’s economic opportunities, widening gender gaps that persist despite 30 years of progress. Well-designed policies to foster recovery can mitigate the negative effects of the crisis on women and prevent further setbacks for gender […]

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The Fantastic Unemployment Numbers!

 

Possibly because of the long weekend and possibly because the unemployment numbers don’t make Donald Trump look bad, there hasn’t been as much commentary as I had expected on the June unemployment numbers.

Here’s mine: They are fantastic!

Here’s the BLS release.

Now for some highlights.

Nonfarm payroll employment rose by 4.8 million in June. I’m not sure  but I’m pretty sure that this is a record increase. The previous, month, May, it was a whopping 2.5 million. So June’s number is almost double May’s increase.

The unemployment rate fell from 13.3 percent in May to 11.1 percent in June, a drop of 2.2 percentage points.

The number of people unemployed fell by a whopping 3.2 million. I think that’s a record drop also.

The labor force participation rate rose by 0.7 percentage point.

The employment to population ratio rose by 1.8 percentage points.

In thinking that the major recovery would not start until the added $600 per week federal unemployment ended (it ends at the end of July), I was too pessimistic.

I do think, though, that if Congress had not passed that benefit in March and had Donald Trump not signed the legislation, the unemployment rate today would be in high single digits, not low double digits.

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Cooking Official Statistics Is Not Easy, for Now

After the Bureau of Labor Statistics announced a drop in the unemployment rate—from 14.7% in April to “only” 13.3% in May—a friend emailed me to share his suspicion that the unexpectedly low figure was a propagandist lie. The probability of that is not zero, I explained to him, but it is extremely low.

These data are gathered (through a monthly survey of 70,000 households), assembled, analyzed, and summarized by bureaucrats from the Census Bureau and the BLS, many of whom are professional statisticians. Bureaucrats could of course be co-opted or corrupted by political leaders, as they were in Argentina and Greece not so long ago. But there are reasons why this is less likely to happen in America.

Any attempt at political interference in official statistical data (which would probably be a crime under federal law) could be resisted or blocked at many points in the process. Successful conspiracies involving a large number of people are rare because, like in the Prisoner Dilemma game, anyone has an incentive to defect before anyone else does. A political manipulation at the last stage would be visible to many who have participated in the process. (The BLS Commissioner apparently only sees the report once it is completed.) Any success at political manipulation would quite certainly be followed by some resignations. High-level bureaucrats have an incentive to preserve the value of their personal brands. A professional statistician suspected of having acquiesced to data fraud may be unable to find another job in his field. Moreover, a political manipulation would be interpreted as meaning that US statistical agencies having become of the Greek or Argentine sort. The credibility of all federal statistical agencies would suffer—and may take decades to recover. Treasury yields would probably increase as creditors would suspect that the federal deficit and debt numbers, for example, are cooked too.

Another part of the difficulty would be to reconcile false unemployment statistics with other numbers calculated by other federal statistical agencies, like the Bureau of Economic Analysis (at the Commerce Department), which will, at the end of July, provide a first estimate of second-quarter GDP. And note that cooking a number one month may require cooking it again the following month and so forth, increasing the probability of the fraud being discovered.

Think also of the Department of Labor’s Inspector General, who may investigate any suspicion of statistical manipulation. It is true that federal Inspectors General may now be scared of investigating political malversations after President Trump removed five of them in different agencies over the past few months. But who knows, the Department of Labor Inspector General may still investigate out of personal integrity or because his legal responsibilities require it.

Fortunately, then, lying is not always easy in a government limited by the rule of law and constrained by numerous centers of power. We could say that, like in Rudyard’s delicious novel The Man Who Would Be King (1888), even the king cannot do everything he wants.

The intriguing error in employment data made by the BLS over the past three months does not change my opinion. As my co-blogger David Henderson explained, an error by interviewers led to misclassify the workers furloughed due to the coronavirus as employed instead of “unemployed on temporary layoff” as they should have been. Without this error, the correct unemployment rate would have been closer to 20% in April and to 16% in May, as opposed to the published figures of 14.7 and 13.3%. This big error blunts the impact of the pandemic and especially of government measures to combat it.

The notification of this error in the BLS’s June 5 report covering May (available at https://www.bls.gov/bls/news-release/empsit.htm#2020) reads as follows:

However, there was also a large number of workers who were classified as employed but absent from work. As was the case in March and April, household survey interviewers were instructed to classify employed persons absent from work due to coronavirus related business closures as unemployed on temporary layoff. However, it is apparent that not all such workers were so classified. BLS and the Census Bureau are investigating why this misclassification error continues to occur and are taking additional steps to address the issue.

If the workers who were recorded as employed but absent from work due to “other reasons” (over and above the number absent for other reasons in a typical May) had been classified as unemployed on temporary layoff, the overall unemployment rate would have been about 3 percentage points higher than reported (on a not seasonally adjusted basis). However, according to usual practice, the data from the household survey are accepted as recorded. To maintain data integrity, no ad hoc actions are taken to reclassify survey responses.

(The constraint of maintaining data integrity exists to prevent intentional manipulation.)

A notice similar to the one above appeared in the report for April (published May 8) as well as in the report for March (published April 3); see also https://www.bls.gov/bls/news-release/empsit.htm#2020 for these reports. The same data collection error was committed three months in a row.

Let’s hope the BLS and the Census Bureau continue investigating until they find how the error happened. And let’s hope that their Inspectors General are (still) ready to do their own investigations if necessary.

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The Bad and the Great News about Unemployment in May

 

My economist friend Jack Tatom wrote the following on Facebook and gave me permission to share. For background, see my “Why the Drop in Unemployment Did Not Surprise Me,” June 5. It’s pretty involved and you might have to pause at various points to take it in, but it’s by far the best explanation I’ve seen. Here goes:

On Friday, June 5, the Bureau of Labor Statistics (BLS) announced the Employment Situation for May showing that the nation’s unemployment rate had declined in May from 14.7 percent to 13.3 percent, a shock to many who had expected a fall in employment of over 9 million and a rise in the unemployment rate to 20 percent. I was not among the shocked. I had expected employment to rise very sharply due to a reduction in the number unemployed.

The BLS added a footnote to their May report that indicates there had been an error in data submitted by survey takers who had counted many people as employed instead of as unemployed. The latter was the explicit instruction BLS had given for the treatment of furloughed workers who did not work during the previous week. According to the BLS, had the surveys been correctly completed, the April unemployment rate would have been shown as 19.7 percent and the rate would have fallen to 16.3 percent in May. [DRH note: Note that that still is a large fall in the unemployment rate; I believe it’s the largest one-month fall in recorded U.S. history.]

So, what happened and what does this mean? First of all, it means that in both months unemployment and the unemployment rate were higher than previously thought. That’s the bad news. The 20 percent unemployment rate expected for May nearly occurred in April. The good news is that this data shows the turnaround in the economy was actually bigger than the official data indicate. The official reported data show a decline of 1.4 percentage points in the unemployment rate; the actual decline that the BLS indicates occurred is more than twice as large as the official data shows.

Based on the data released, my calculations indicate approximately 7.7 million furloughed workers were “mistakenly” treated as employed in April but should have been treated as unemployed. Instead of the 18.1 million reported in Table A-11 of the Employment Situation for April, the correct number was about 25.8 million. In May, the Table A-11 shows a 15.3 million on-furloughed reduction in the overall number unemployed. Using the revised data based on the footnote to the BLS report, it now appears that the decline in unemployment in May due to falling numbers of unemployed workers on temporary layoffs was 5.7 million workers instead of the officially reported 2.7 million. This larger return of furloughed workers to employment again accounted for more than all of the approximately 5.0 million increase in overall employment implied by the footnote. Five million more workers returning to work in May is dramatically more than the continuing decline expected a week ago by others or even the 2.1 million official gain reported on Friday. That is not good news; it is great news.

What about the decline in employment expected by nearly all analysts and the press? Buried in all these numbers is a decline in employment for workers who were not on furlough that was swamped by the return of formerly furloughed workers. In the official data, the reduction of unemployed and furloughed workers was 2.7 million, but the reduction in the unemployed was 2.1 million. The difference is others who were not furloughed but added to the number unemployed. When the corrected measures are used, furloughed workers declined by 5.7 million, larger by about 0.7 million than the overall approximate number of 5 million reduction in overall unemployment (different from official measures due to rounding error). So there was a decline in employment in May that was overwhelmed by the return of furloughed workers observed in April and back in employment by May.

Where do we go from here? Depends on to whom “we” refers. The BLS official view is not to tamper with suspected errors in the collected surveys. So, whether BLS will adjust the official data in the future remains to be seen. But where the economy goes is more certain. Given the opening of states’ economies in late May and early June, the accelerating opening of businesses suggests even larger increases in employment and declines in the unemployment rate in June and the rest of the summer.

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