The Economic Cost of Shutting Down "Non-essential" Businesses

THE ESTIMATES BELOW WERE MADE CIRCA MARCH 20, 2020.  Updated estimates are available here, complete with additional cost categories and references and based on important new data.

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We are currently fighting a war against the COVID-19 virus.  The war presents an obvious and massive tradeoff between “guns” – activities whose primary purpose is war production – and “butter,” which refers to the normal activities of households and businesses.  Without any improvement in our techniques for fighting the war, the sacrifices by households and businesses will be staggering and historically unprecedented.

This document enumerates and quantifies the sacrifices using two novel methods.  The results suggest that negative 50 percent is an optimistic projection for the annualized growth rate of U.S. GDP in 2020 Q2 if the nonessential businesses were not allowed to operate during that quarter.  GDP losses, while massive, nonetheless understate the true costs of the sacrifices that households and businesses are making, which I estimate to total almost $10,000 per household per quarter.  This is why better techniques for fighting the war are incredibly valuable.

Government officials around the world have ordered businesses shut and families to stay in their homes except for essential activities.  My purpose here is to enumerate and quantify the real economic costs of fighting the war in this way.  This document estimates the opportunity costs of lockdown relative to a normally functioning economy, which is the relevant comparison for the purposes of policy decisions such as medical innovation (or, possibly, a statistical sampling effort) that could end the lockdown earlier. 

To be clear, the cost-enumeration exercise can be consistent with a conclusion that the war is worth fighting – that depends on quantifying the benefits, which are surely significant given the value that people place on health and longevity.  Although this document does not address the question of whether a lockdown is better than no policy response, it offers some of the essential ingredients for such an analysis.  No policy response would itself involve economic contraction during the period of time in which no treatment or vaccine is available.

The lockdown method of fighting the war on the virus directly affects how people allocate their time.  That includes what they do, where they do it, and with whom.  Because normal time allocation includes elements of saving and capital accumulation, such as learning skills, the economic effects of the war are felt into the future as stocks of physical and human capital are reduced.  For enumeration purposes, I distinguish market production activities from all other activities, especially because market production is counted in conventionally-measured GDP whereas leisure activities are not.  Although I refer to the non-market activities as “leisure,” they include religious gatherings and forms of effort such as student effort in school and effort put toward housework.  Both market production and leisure activities are significantly affected by lockdown.

A.  Net Costs Associated with Market Production

Lockdown reduces the amount and effectiveness with which people work.  The effects of this can be measured on either the production side of the national accounts, as the value of goods and services not produced, or the income side as reductions in total incomes.  Either approach yields the same result, up to measurement error.[1]  However, the incidence – the distribution of impact across industries, occupations, and income groups – is different from the production and income perspectives.

Momentarily putting aside costs associated with leisure activities, the lockdown can be analogized with a change in the number of holidays and weekends (“nonwork days”).  A well-studied, albeit obscure, element of national income accounting is the adjustment for the fact that the number of nonwork days normally varies from year to year.[2]  A normal year has about 251 working days and about 114 nonworking days.[3]  The national accountants have found that adding a nonwork day to the year reduces the year’s real GDP by about 0.1 percent and have been applying this estimate to both the production and real income accounts.[4]  Adding a nonwork day to a quarter would therefore reduce the quarter’s unadjusted real GDP by about 0.4 percent.

Extrapolating from this finding, removing all of the working days from a quarter is 62 or 63 times this, or 25 percent.[5]  In other words, if seasonally-adjusted GDP 2020-Q2 would have been $5.5 trillion at a quarterly rate (see Table 1), then changing all of that quarter’s working days to the functional equivalent of a weekend or holiday would reduce the quarter’s GDP to $4.2 trillion.[6]  Applying the same approach to 2020-Q1, with a lockdown occurring for one-eighth of the quarter, 2020-Q1 real GDP (in 2020-Q2 prices) would be $5.4 trillion.  The quarter-over-quarter growth rate of seasonally-adjusted real GDP would, expressed at annual rates, therefore be -10 percent in Q1 and -63 percent in Q2.[7]  The Q2 growth rate would be less negative to the extent that a lockdown was in place for only part of the quarter or for part of the country.

[Table 1 contains POINT ESTIMATES, not worst-case scenarios.  If these costs are to be netted against health benefits, then those benefits should be POINT ESTIMATES too.  Worst-case scenario health benefits should be compared with worst-case scenario costs, which far exceed what I provided].

Lockdown is not exactly the functional equivalent of changing workdays to weekends or holidays.  On one hand, a segment of the workforce will engage in telework during lockdown that they would not perform on a normal weekend or holiday.  Other segments or regions will be exempt from shutdown.  This by itself suggests that the $4.2 trillion estimate is too pessimistic.  On the other hand, much of the normal weekend activity such as restaurants, entertainment, and religious activities is not occurring during lockdown.  This by itself suggests that the $4.2 trillion estimate is too optimistic.

A second method uses the production side alone.  Labor is reduced by the number of “non-essential” employees, which has been about 30 percent during Federal shutdowns.[8]  In some of the industries, real capital will continue to be used, albeit by fewer employees.  Other industries will not use their capital, although it may be repurposed, such as a hotel being used as a hospital ward.  To be conservative, I assume that few industries increase their labor-capital ratio.[9]  The reduction in capital input is therefore somewhere between 0 and 30 percent; I assume 15 percent.  History has repeatedly shown that labor is more important in the production process than capital, so that by the second method real GDP is reduced 26 percent.[10]

The estimates above assume no black markets.  But, as seen with border patrol and the war on drugs, any government regulation attempting to block valuable gains from trade will result in black market activity.  Businesses will also work the gray area, lobbying and distorting their operations to have more activities declared “essential.”

Black-market activity is far less productive than legitimate activity, which is why it does not come close to replacing the “non-essential” sales that were banned.  But it still has value, which is why the best welfare effects of shutdown may be less pessimistic than analysis assuming zero black market.[11]  I assume that black markets replace 25 percent of the gains from trade, based on studies of illegal drugs.[12]  However, value generated in black markets is typically not measured as part of GDP.  Indeed, black markets compete with legitimate markets for the factors of production and by this channel would reduce measured real GDP even more than would occur without black markets (Fleming, Roman and Farrell 2000).

Table 1 shows only averages, but the distribution of costs is unequal.  Revealed preference -- that fact that the demand for social insurance increases in these situations -- suggests that the inequality itself is a cost large enough that people are willing to tolerate even further increases in the average costs (i.e., further decreases in GDP) in order to mitigate the costs for those disproportionately affected.

Although the national income accounts were designed on the basis of the principles of welfare economics, GDP growth is not exactly a benefit and GDP reduction is not exactly a welfare cost because valuable activities and assets such as home production, elements of human capital accumulation, and environmental quality are not yet recognized in the official national accounts (Hartwick 1990, Nordhaus and Kokkelenberg 1999, Jorgenson 2010).  However, as discussed further below, the GDP losses cited above prove to reasonably approximate more comprehensive welfare losses.

B.  Net Costs Associated with Nonmarket Activities

The nonmarket/home sector is affected by lockdown through two basic channels, as shown in Table 1.  The first channel is discussed above: the nonmarket sector has additional labor that has been forced out of the market sector.  The second channel is that the nonmarket sector becomes less productive, both for the nonmarket time that normally exists as well as the additional nonmarket time coming from the market sector, because even in their nonwork activities people are restricted in terms of where they go and how they associate with others.  The percentage change in the value created in the nonmarket sector combines the two channels and is approximately the sum of the (positive) percentage change in labor input and the (negative) percentage change of nonmarket productivity.[13]

An important example of the second channel is the time allocation of children and young adults who would normally be enrolled in school and now spend their time at home.  Their learning from normal face-to-face interactions with teachers and fellow students is not fully reflected in GDP, but is nonetheless valuable.  In other cases, as with religious gatherings, entertainment, and tourism, lockdowns reduce the value of these activities by limiting how people can congregate and the market inputs that can be used as part of the leisure activity.

Because the national accounts are based on the principles of welfare economics, GDP would ideally capture value created or destroyed in both the market and nonmarket sectors.  Measurement challenges have so far limited the scope of conventional GDP measures to the market sector.  Conventional GDP measures therefore miss the value of additional nonmarket time added by the shutdown (the first channel) as well as the reduced productivity of nonmarket time (the second channel).  This section provides estimates of the two, which can be added to the GDP losses from Section I.B to arrive at a welfare loss of shutdown as compared to normal economic activity.

To estimate the nonmarket value of added labor, I use the short run of the neoclassical growth model, which is essentially a labor supply and demand framework.  The average nonmarket value of time is below the after-tax real wage that would normally prevail, but above the marginal value of time with a shutdown, which I estimate to be 49 percent of the former.[14]   With a 48 percent marginal tax rate (inclusive of implicit taxes on labor income), the total nonmarket value of the extra time is about $7 billion per day (see Table 1), or about 30 percent of the reduction in real GDP.  Simply put, about two-thirds of the $22 billion daily GDP loss is a welfare loss, even without considering any productivity change in the nonmarket sector.

Full-time schooling, where there are normally about 73 million children and young adults enrolled, is the part of the non-market sector’s productivity loss that is easiest to quantify.  Their time and efforts, which are known as “foregone earnings” and not counted in conventional GDP measures, are combined with direct schooling costs such as the education industry’s payroll and capital expenses because the students, their parents, or their community value the results of schooling.  The direct costs were $370 billion in 2018.  Various studies, such as Breton’s (2013) estimate that foregone earnings are about 102 percent of the direct costs, which would be $377 billion in 2018, or about $4.5 per hour that the average student was in school.  Assuming that some schooling will still occur during lockdown, I take the loss of student output attributable to their time and effort to be half, or about $2.25 per hour that they would have been in school.

Learning does not stop at graduation.  Post-graduation workers learn on the job, which shifts the composition of their compensation toward skill acquisition and away from the cash and other fringe benefits that are part of conventionally measured GDP (Rosen 1972).  Although the market sector may be the physical location of this learning, I count the foregone earnings as “nonmarket” because it is usually unmeasured.  I estimate the value of foregone earnings using the cross-section age-earnings profile and the average of two estimates of the age-training profile (Mulligan 1998).  During a shutdown, this learning does not occur for 30 percent of the workforce, although (as with market production) I assume that about one-third of its value is replaced with nonmarket activity.  The net opportunity cost associated with on-the-job training (OJT) is therefore about $107 billion at an annual rate, as shown in Table 1.

The normal population has even more adults not in the labor force than full-time students, not to mention all of the time that workers normally spend outside of work.  If a shutdown also reduced the hourly value of their time by $2.25 for 2000 hours per year for those out of the labor force and for 500 hours per year for those who work, that would be a loss of $767 billion at an annual rate.

C.  The Incidence of the Net Costs

The massive costs of shutting down “non-essential” activities are not shared equally among Americans.  Some workers are still able to draw a normal salary even while their industry is inactive.  Others work in industries such as parts of healthcare that are booming as a result of the pandemic.  Because the aggregate reduction in the value of what is produced must equal the aggregate reduction in total income, the costs of lockdown will fall disproportionately on the remainder of the population that are not in these circumstances.

Public programs are being created and expanded with the intention of helping some of those who are disproportionately bearing the costs.  Redistribution policy may help distribute the aggregate costs more fairly, but in no way can it reduce the aggregate cost.  Even while these policies assist those who are not working because of the pandemic, they do not replace the work and production that the workers would have been doing.  Instead, redistribution itself has its own aggregate costs, for example, by reducing incentives to work and incentives of workers to shift into industries that need them most (Mulligan 2012).

D.  Bibliography

Barro, Robert J., José F. Ursúa, and Joanna Weng. "The Coronavirus and the Great Influenza Pandemic: Lessons from the “Spanish Flu” for the Coronavirus’s Potential Effects on Mortality and Economic Activity." NBER working paper, no. 26866 (March 2020).

Breton, Theodore R. "Were Mankiw, Romer, and Weil right? A reconciliation of the micro and macro effects of schooling on income." Macroeconomic Dynamics 17 (2013): 1023–1054.

Christian, Michael S., and others. Human capital accounting in the United States: 1994 to 2006. BEA, 2010.

Council of Economic Advisers. Mitigating the Impact of Pandemic Influenza through Vaccine Innovation. Executive Office of the President, September 2019.

DiMasi, Joseph A., Henry G. Grabowski, and Ronald W. Hansen. "Innovation in the pharmaceutical industry: new estimates of R&D costs." Journal of health economics 47 (2016): 20–33.

Eichenbaum, Martin S., Sergio Rebelo, and Mathias Trabandt. "The Macroeconomics of Epidemics." googlegroups.com. March 23, 2020. https://fb8280a8-a-62cb3a1a-s-sites.googlegroups.com/site/mathiastrabandt/home/downloads/EichenbaumRebeloTrabandt_EpidemicsMacro.pdf?attachauth=ANoY7coRODwA_z1gJoSLHsTEXF0IQcWOQbFP5bfX9cHSypuO2NuwJPyq7T2A4p2wdppOl0jWVgmAzN4-16-irT7vZqkwvBs8_8PNb3hs0ZJmZtr.

European Central Bank. "The impact of the number of working days on euro area GDP in 2004." Monthly Bulletin, June 2004: 51-63.

Fleming, Matthew H., John Roman, and Graham Farrell. "The shadow economy." Journal of International Affairs, 2000: 387–409.

Hartwick, John M. "Natural resources, national accounting and economic depreciation." Journal of Public Economics 43 (1990): 291–304.

Jaffe, Sonia, Robert Minton, Casey B. Mulligan, and Kevin M. Murphy. Chicago Price Theory. Princeton University Press (ChicagoPriceTheory.com), 2019.

Jorgenson, Dale W. "A new architecture for the US national accounts." Review of Income and Wealth 55 (2009): 1–42.

Jorgenson, Dale W. "Human capital and the national accounts." Survey of Current Business 90 (2010): 54–56.

Katz, Eric. "Agencies Paid Federal Employees $3.7 Billion Not to Work During Recent Shutdowns." govexec.com. September 17, 2019. https://www.govexec.com/pay-benefits/2019/09/agencies-paid-federal-employees-37-billion-not-work-during-recent-shutdowns/159936/.

Mulligan, Casey B. The Redistribution Recession. New York: Oxford University Press (redistributionrecession.com), 2012.

Nordhaus, William D., and Edward C. Kokkelenberg. Nature’s Numbers. National Academy Press Washington, DC, 1999.

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[1] Adding the opportunity costs of production to the reductions in incomes would be double counting.

[2] Leap years also create variation in the total number of days.

[3] A year has 52 weeks plus an additional one or two days, for a total of between 104 and 106 weekend days.  There are ten Federal holidays.

[4] European Central Bank (2004).  Note that 0.1 percent is much less than 1/251; the estimate implies that the average nonworking day has two-thirds the GDP of a working day.

[5] The exact number of working days that 2020 Q2 would have normally had is irrelevant for this calculation because the national accountants adjust for its deviation from 251/4.

[6] This is the sum of Table 1’s first row with its addendum row.

[7] This assumes a baseline annual growth rate of 2 percent and applies it one for one.  The formula for the annualized growth rate in Q2 is . 

[8] Katz (2019).  The non-essential share has not yet been measured for government-mandated private-sector shutdowns, which is why the holiday-weekend method should receive more weight.  Given that I obtain almost the same result for the two methods, their weighting is not critical to the analysis.

[9] Using their labor is different than keeping the labor on the payroll.  An unused worker still on the payroll does not contribute to current output.

[10] Barro, Ursúa and Weng (2020) estimate that, if the COVID-19 epidemic were a scaled version of the 1918 Spanish Flu, real GDP would fall less than eight percent.  The authors note that the current pandemic is unique in that “countries have been pursuing a policy of lowering real GDP,” which are the lockdowns that are the subject of this document.  Looking at the current pandemic, Eichenbaum, Rebelo, and Trabandt (2020) estimate that aggregate consumption and GDP (their model has no investment) will fall up to 20 percent.

[11] But government regulators can hardly defend their shutdown regulations on the grounds that they will not be obeyed!  Moreover, black markets add another social cost by eroding respect for law and order.

[12] The war on drugs increases the retail price (and unit cost to suppliers) by a roughly a factor of four and reduces the quantity consumed by a factor of two (Jaffe, et al. 2019, Figure 12-1).  Illegal drug sellers have had many years to accumulate organizational and other capital that lockdown violators did not.  On the other side, drug war enforcers have had many years that lockdown enforcers have not.

[13] The approximation is exact when the changes are measured in logarithms rather than percentages.

[14] This assumes a wage elasticity of labor supply of 1/2 (0.49 = 0.7²).

Will write soon on the real economy

What is happening to the real economy right now is straightforward from the perspective of the supply and demand for labor and capital.  This perspective shows how the real-economy costs are massive, and largely unnecessary, especially to the extent that they continue more than a week or two.  (I discussed the political economy of this here).

This perspective shows how the recovery will look.

This perspective shows why equities are so much cheaper, beyond what is "justified" by reductions in the future dividend stream (hint: Irving Fisher, but as I have written in the past, do not interpret "interest rate" as the yield on Treasury Bills or Fed Funds but rather as the profit rate on real capital). 

I will write up the details soon.

COVID-19 policy: your costs will be ignored unless you speak up

It is a fact that, despite requirements to the contrary, Federal health professionals do not consider the costs of health-enhancing rules and regulations in their normal course of operations.  Jerry Ellig has documented this fact in his regulatory report cards where he shows that the cost-benefit analysis from HHS (the Federal department making health policy) consistently ranks as one of the worst agencies in terms of considering costs as part of its regulatory impact analysis.  (Using other Federal agencies as a benchmark is an incredibly low bar!).

This HHS tradition is not new (Ellig's latest report card was prepared in 20116), and continues even into the current administration, as I witnessed first hand.  For example, when HHS is of a mind to reduce the number of people uninsured, they impose any cost on taxpayers and consumers in pursuit of getting people signed up for insurance and furthermore pretend that those costs are so negligible as to be unworthy of counting.

We can safely assume that HHS continues this approach to COVID-19.  They want to minimize the rate of new infections.  It won't matter to them how much of our money that costs.  It won't matter how much human capital our children and young adults lose.

Although it was not true in the past with health insurance, opioids, and other matters, perhaps this time they are doing the right things.  If so, it is the blind squirrel story, because they are ignoring costs.

The only way for Federal health decisions to reflect costs is for YOU TO SPEAK UP.  HHS reports to elected officials, who can and often do listen to their constituents.  President Trump certainly does listen (I know that first hand).  But they will not hear unless PEOPLE SPEAK UP.

Cass Sunstein, whom I admire, has nonetheless made a big mistake by perpetuating the myth that "Technocrats have triumphed,” which is his way of asserting that Americans are now ruled over by nonpartisan career professionals who carefully balance costs and benefits.  This depiction of balancing costs and benefits is absurd, especially as regards to health policy, which is the single biggest area of Federal regulation.

What I never anticipated is that it would become so obvious to so many regular people how health policy is conducted without regard to the costs they bear.

Subsidizing Addiction

In both 2015 and 2016, U.S. life expectancy fell from the previous year. A single-year drop had not happened in 22 years, and two consecutive drops had not occurred in more than 50 years. This sharp reversal in the national trend toward longer lives is widely understood to be connected to the opioid epidemic that began in the 1990s. The best kept secret about the epidemic, however, is how much of it – arguably most of it – resulted from Federal policy changes initiated by both Democrats and Republicans.

Opioids include prescription drugs like oxycodone as well as illicitly manufactured drugs like heroin and fentanyl. Since 2000, the Federal government has increased subsidies on both types of opioids and cut taxes on illicit opioids.

Medical professional organizations like the American Pain Society have been criticized for recommending more aggressive opioid prescription practices and downplaying addiction risks. But the effects of their recommendations would have been less severe without the Federal dollars that supported them. Beginning in 2000, the Veterans Health Administration (part of the Federal government) mandated that pain be seen as “the 5th Vital Sign,” which meant that pain would be routinely screened for and documented primarily based on patient self-assessments. Years later, the new Secretary of Veterans Affairs would report that veterans were twice as likely to die from opioid overdose than the general population.

This new approach would soon enter into civilian practice too, with three phases of financial encouragement from the Centers for Medicare and Medicaid Services. CMS has long conditioned hospital reimbursement under its massive Medicare and Medicaid programs on hospital quality assessments by the Joint Commission on Accreditation of Healthcare Organizations, another accreditation organization, or state survey agencies. In 2001, pain management became part of the accreditation process, putting billions of CMS dollars at stake. The second phase of incentives began in 2007, when CMS began withholding two percent from full reimbursement if a hospital failed to participate in the patient survey known as HCAHPS; hospitals and doctors discovered that their performance on the survey improved if opioids were liberally prescribed. The third phase began in 2012, when CMS implemented the “valued-based purchasing” (VBP) requirement provided for by the Affordable Care Act, which tied hospital reimbursement even more strongly to the HCAHPS survey. CMS would spend the next seven years taking steps to reduce these financial incentives for aggressive opioid prescribing.

Federal subsidies benefiting opioid consumers were probably even larger. In 2006, Medicare began to cover prescription drugs pursuant to its new “Part D” program. Although most Medicare enrollees are elderly, many of their prescriptions ended up in the hands of nonelderly people. Citing a family physician from Ohio, Sam Quinones’s book Dreamland asserts that “seniors realized they could subsidize their retirement by selling their prescription Oxys [a potent opioid] to younger folks. Some of the first Oxy dealers, in fact, were seniors who saw the value of the pills in their cabinets. ‘It’s like hitting the Lotto if your doctor will put you on OxyContin…. People don’t even think twice about selling.’” The White House Council of Economic Advisors (CEA) estimates that three-fourths of the growth in prescribed opioids between 2001 and 2010 were financed by government programs.

The 2010 Affordable Care Act requires health plans (especially Medicare) to cover “benzos” – prescription tranquilizers like Valium and Xanax. Benzos are part of the opioid crisis because they are the other half of the risky opioid-benzo cocktail that is favored by many opioid abusers. The tranquilizers enhance the feelings connected to opioid consumption, including the consumption of heroin and fentanyl. In other words, unlike the 2006 Medicare subsidies, which apply only to prescription opioids, the ACA’s benzo subsidies increase the demand for illicit opioids too.

In 2013, Attorney General Eric Holder took a step toward ending the war on drugs by instructing Federal attorneys that they should not prosecute low-level drug offenders. As I explain in my recent paper, this amounts to a tax cut on illicit opioids that would presumably reduce their street prices.

As far as I can tell, these policies went ahead because much of the Federal government did not grasp the full extent of the opioid epidemic. The Federal Register (the daily publication of US government agencies), reveals the Federal priorities at the time. Every 10,000 pages published between 2009 and 2016 had only six documents mentioning “opioid,” “opioids,” or “opiate.” In contrast, the same 10,000 pages had nearly 40 documents mentioning “climate change.” As recently as 2013 – the third consecutive year in which the death rate was almost triple normal levels – the Congressional Record mentions “climate change” 27 times more often than “opioid” or “opioids.”

Regardless of whether the government increases subsidies or cuts taxes, the result is lower prices paid by the opioid consumer, making opioid addiction more affordable. The CEA’s recently released 2020 Economic Report of the President estimates that, adjusted for inflation, out-of-pocket prices for prescription opioids fell by a factor of five between 2001 and 2010. (CEA’s price data is graphed below.) More recently, the quality-adjusted price of illicit opioids fell by at least a factor of two.

Studies have shown that opioids and other addictive substances obey the law of demand: lower prices mean more demand. If nothing else, the reduced prices for opioids have sharply increased the number of people who can afford an opioid addiction. CEA estimates that lower prescription opioid prices explain 31 to 83 percent of the increase in the death rate from 2001 to 2010 involving prescription opioids. This estimate does not include the additional effects of subsidies for benzos or hospitals, or the effects of reduced heroin prices since 2010.

Without the new subsidies supporting opioid addiction, the number of fatalities from opioid overdoses would be significantly lower, and maybe it wouldn’t even be called an “epidemic.”

Challenger Sanders v Challenger Trump

Sanders and Trump both side with flyover country rather than the Washington bubble.  This approach is valuable on election days, albeit creating much personal inconvenience on the days in between.

As part of this, both will speak some of the truisms that are supposed to be off limits.  E.g., Trump's "American carnage" in his inaugural address (if you think that was not a truism, look here).  Or Sanders' admiration of the Cuban literacy campaign (as impressive as it was for literacy results, it was even more impressive as a political move, helping to cement Castro's power for many decades).

A difference between Sanders and Trump on this is that Trump simultaneously says the politically incorrect while expanding the boundaries of his brand.  He says the truth in a way that goads his opponents into vigorously denying that very truth.  "American carnage" is one example among many.  This is one of Trump's valuable skills for operating in our world where ideas do not have copyrights.  By contrast, when Sanders says something true he says it in a way in which competitors can adopt it for themselves.

Sanders is fundamentally an ideologue, whereas neither Trump nor voters are.  This allows Trump to take on political opponents, and even appreciate their strengths, without personally insulting their voters.  Sanders seems tied to a lot of dogma around social policy.  As long as Sanders has to repeat that Trump is supposedly "racist, sexist, homophobic, xenophobic" etc., he is in imminent danger of the basket-of-deplorables trap: describing half of America as the same or at least having them hear it that way.  I doubt Sanders realizes how similar he sounds to Mrs. Clinton on this subject.

As of 2016, neither Trump nor Sanders showed much allegiance to a political party.  This removes some constraints on their quest for electoral victory, but discards some of the value that party brings, such as credibly lengthening the planning horizon.  That value has to be replaced by something.  Trump helped replace it with his list of judge candidates.  And with long-horizon political aspirations for Ivanka and others.  I don't yet see what will be Sanders' replacement.

Trump is smarter.  Take the controversies that the two ignite.  By insisting that fracking be banned, Sanders seems unaware that Pennsylvania is a swing state.  By more easily acknowledging accomplishments of Castro than of Trump, Sanders seems unaware that Florida is a swing state filled with people who voted for Trump but not Castro.

(also an interesting exposition of "identification in difference-in-differences").

Today Trump is POTUS and has results to showcase.  POTUS Trump will be bragging about promises kept while Sanders through backchannels will be telling people not to worry that his promises will be kept.  But my purpose here is to compare them as challenger candidates.

Look at all of those CEA charts!

(Fox News shows CEA charts from "the brand new economic report from the White House" while the Secretary of Labor provides narrative).

The Economic Impact of Sanders’ Radical Agenda

If fully implemented, but otherwise implemented wisely, Senator Sanders’ agenda for the economy would reduce real GDP and consumption by 24 percent.  Real wages would fall more than 50 percent after taxes.  Employment and hours would fall 16 percent combined.  There would be less total healthcare, less childcare, less energy available to households, and less value added in the university sector.  Although it is more difficult to forecast, the stock market would likely fall more than 50 percent.

Previous analysis of Medicare for All

When I was at CEA, we used an extension of the neoclassical growth model to assess the economic impact of “Medicare for All” (M4A), which we charitably interpreted as 100 percent public financing of the health sector, with (in Chapter 8 of the 2019 ERP) nobody consuming less healthcare and many consuming more than in the baseline.  We also charitably assumed that the public financing would occur with taxes that have minimum efficiency loss per dollar collected.

Arguably the Laffer curve for payroll and consumption taxes is not high enough to finance M4A, but at CEA we charitably assumed that the tax base is inelastic enough to rule out this possibility.  As reported in the 2019 Economic Report of the President, we concluded that payroll tax rates would increase 14 percentage points and tax payments would increase an average of $18,000 per household per year.  Real national income and GDP would fall 9 percent.  Real national income net of taxes and health spending would fall 19 percent.  These result from M4A by itself, and are a best-case scenario.

Considering Sanders’ Agenda More Fully: Factors of Production

My purpose here is to consider Sanders’ agenda more fully, including free public college, free childcare, and a full transformation of the energy sector.  I will also consider the fact, confirmed repeatedly in history, that nationalizing industries will reduce their productivity.  Overall productivity will also decline somewhat as the economy is reregulated (including perhaps a $15 minimum wage and regulating employee-management relations) enough to be put on the pre-2016 regulatory growth path.  A Federal jobs guarantee or a student loan bailout would also not be pretty, but I have not yet quantified it.

I assume that what is currently household spending on public college tuition and on daycare (1.75 percent of aggregate consumption) will become “free” and that these resources will see their utilization increase by the same percentage as healthcare.  Under the assumption that a Sanders administration would provide Federal assistance to nonrich households that are burdened by the high energy prices that come with the Green New Deal, I also expand the Federal budget for that purpose by another two percent of baseline consumption.

Even if without any productivity loss or increased utilization in healthcare, college, and daycare, this means that the Sanders agenda would be expanding the Federal budget by 13.25 percent of baseline consumption.  Including 19 percent additional utilization of these “free” goods and services, tax rates on labor income must increase by 23.5 percentage points (it would be more but the Sanders agenda does expand the tax base by eliminating the exclusion for employer-sponsored health insurance).  GDP falls by 16 percent (this does not yet consider productivity losses -- that comes below).

The simple, correct, but perennially forgotten, idea is that it matters when we spend other people's money on other people.  Nationalizing an industry's revenue is NOT merely a matter of relabeling the dollars that people spend on that industry.  Moving the revenue over to the public purse removes all individual incentive to economize on the amount of spending and to ensure that the spending goes to the highest value activities.  The data matches the theory very well on this.

Considering Sanders’ Agenda More Fully: Productivity

The Sanders agenda puts the economy so close to the top of its Laffer curve that there is no additional revenue to finance the additional inputs into healthcare, college, and daycare that would be needed if those industries suffered any productivity loss.  If their productivity fell by 25 percent, which is optimistic as nationalizations go (see Chapter 8 of the 2019 ERP), then the output of those industries would have to be cut by 25 percent.  To be clear, the result would be less healthcare, less college, and less daycare.

The Sanders agenda will reregulate the economy.  I optimistically (i.e., charitably to the Sanders agenda) project the regulation to be a return to the pre-2016 regulatory trend plus cutting energy productivity in half.  CEA estimated that the pre-2016 trend was to reduce productivity by 0.16 percent per year (see Chapter 3 of the 2020 ERP), which would be 1.3 percent by 2024.  I also assume that a President Sanders would undo President Trump’s deregulatory agenda and his corporate tax cut and thereby reduce productivity by another 3.3 percent.  Taking energy as 3 percent of the economy, the climate change part of the Sanders agenda would (again, optimistically) reduce productivity by 3 percent.  Adding these to the productivity losses in the nationalized industries, that is 10.9 percent less productivity.

Overall, real GDP and consumption would fall 24 percent.  Employment and hours would fall 16 percent combined.  Real wages would fall 11 percent before taxes.  After-tax real wages would fall 51 percent.

This is akin to the Great Depression of the 1930s, except that the Great Depression was eventually followed by a recovery whereas the Sanders agenda (I assume) does not involve eventually putting policies back to the way President Trump had them.  Therefore the stock market would fall at least what it did in 1929, which was almost 50 percent.

Don’t Take Sanders Literally

As an academic exercise, I have taken Sanders literally.  That is not a good forecast of what his policies would be.  If nothing else, his promises are so damaging that the rest of our political system would water them down.  Indeed, Sanders surrogates such as AOC have been saying as much to assure (sic) nervous voters.

None of this denies that Sanders, whose candidacy I have followed for five years, is compelling.  Marxism itself is powerfully irresistible, surviving over a century in the marketplace for ideas.  But it's more than that.  Outside the Washington bubble, there is a demand for disruption rooted in real substance.  Not as much as in 2016, but still there.  People also understandably admire how Sanders' episodes of honesty are so frequent by the standards of conventional politicians.  My favorite example is his 2016 economics white paper, which openly acknowledges the existence of serious people with the opposite view (see especially footnotes 21 and 36), which is exactly the view I express above.


[Appendix on climate effects:

My GDP estimates do not include any climate damage.  M4A is a big part of the Sanders agenda, and has nothing to do with environment.  As shown in Chapter 4 of the 2020 ERP, banning fracking, which is part of the Sanders agenda, makes climate change worse.   To the extent that worse climate means less GDP for the U.S. (climate change is mostly a world GDP effect rather than U.S. GDP?), that would add to the GDP impact I calculated.  On the other hand, other parts of the Sanders agenda might help with climate change.  Also, whaat's above looks at economic impacts in a 5-10 year time frame, whereas effects through climate change will take decades.]

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Is the Grand Canyon Just a Ditch?

[Originally posted at economics21.org]

The myriad deregulatory actions of the Trump administration are generating considerable cost savings, savings that even conservative critics of regulatory overreach are underestimating. Like the Grand Canyon, the vast scale of these deregulatory efforts (and their results) is hard to fathom.

In just three years the administration has reversed hundreds of regulations, many of which drone on for hundreds of pages. And it’s done so without fear or favor. Many of the regulations reversed had been written and implemented at the behest of special interests, including large banks, trial lawyers, major health insurance companies, big tech companies, labor unions, and foreign drug manufacturers. 

Even officials within the administration underestimate what has been achieved because they tend to grasp only their specific part of the overall picture. Still, I’ve been surprised to see a group of conservatives confidently conclude that the Trump administration “has achieved little” on deregulation. This, sadly, is akin to a human being encountering the immensity of the Grand Canyon only to conclude that it is “just a ditch.”

The daily grind of repealing excessive regulation does not always grab headlines. I don’t blame commentators for being unaware of some, or even most, of the deregulation that has occurred. That is why the Council of Economic Advisers (CEA)—where, until recently, I served as chief economist—dedicated a great deal of manpower preparing a comprehensive and rigorous assessment of deregulation since 2017. That report, released in June, concluded that the past three years of deregulation is comparable to, and probably exceeds, any deregulatory episode in modern U.S. history. That includes the historic deregulations of airlines, trucking, railroads, and energy that were initiated during the Carter administration.

Argue with the CEA report, if you want. Or read David R. Henderson’s summary of the report. But don’t claim that the Grand Canyon is a just a ditch until you have a cursory look at the CEA’s map.

The CEA began with the surprisingly difficult task of identifying the deregulations that were reducing household and business costs the most. You would think that government numbers could be used to make this assessment, but they are notoriously inaccurate. A Competitive Enterprise Institute study of the 53,838 federal rules finalized between 2001 and 2014 found that only 246 of them (less than 1%) quantified regulatory costs. Lurking in the other 53,592 are some very costly regulations to be discovered by some other method.

Instead, the CEA selected the top 21 regulations based on measures of attention from the public, as expressed by actions in Congress or comments submitted to the regulatory agency during the regulatory process. The CEA then performed a rigorous economic analysis of the selected regulations to estimate their costs and benefits. The arithmetic motivating this procedure is that a sum of the hundreds of costs savings (the entire deregulatory portfolio) is made up largely by the elements of the sum of cost savings from the regulations with the largest costs.

The attention metric led to some interesting discoveries. Take the 2016 prohibition of “junk” health insurance plans (i.e., plans that families like and purchase, in large part because the plans are cheaper than the plans endorsed by bureaucrats) that the Trump administration reversed in 2018. Whereas the typical regulation receives zero comments, this one received thousands. At the same time, the regulators assessed no cost for the rule because the rule was (with a bit of circularity) designated to be “economically insignificant.” Such designation is not supposed to be used unless there is no material adverse effect on a sector of the economy. It is absurd to deny any material adverse effect from a prohibition of a product that two million people would be purchasing (as estimated by the nonpartisan Congressional Budget Office). The CEA estimated that the annual cost of this regulation was $13 billion, which is 130 times the monetary threshold for “economic significance.”

It’s hard to understand the intention of the regulators who designated the rule to be “economically insignificant.” Were they unaware that the rule was getting thousands of comments? Did they think that people bothered to comment on something insignificant? Was it a technical error? Or was it a deliberate attempt to jam through a regulation without revealing much about its costs? Regardless of which answer is correct, we have yet another reason to doubt the cost estimates provided by regulatory agencies.

A similar phenomenon is revealed in the chart below, reproduced from another CEA report on prescription drug prices. It shows something historically unusual happening to prescription drug prices, as measured by the Consumer Price Index calculated by the Bureau of Labor Statistics. Much of the change has to do with deregulation of the entry of generic drugs. The Food and Drug Administration had such a burdensome approval process for generic manufacturers that in some instances only one company was making a generic. A handful of lucky, or well connected, companies were able to sell a drug they did not invent at a price about as high as that charged when the inventor held the monopoly. President Trump’s FDA changed that.

Figure 1 CPI for Prescription Drugs, Jan 1970 to Sep 2019. Source: CEA October 2019.

A little arithmetic helps to assess orders of magnitude (CEA calculations are much more detailed). If prescription drug prices had continued to increase at 4% per year after 2016, that would put them 8% higher after two years. In fact, after deregulation, they fell about 2% over two years, and therefore were roughly 10% below the previous trend. With the average household spending about $2,700 annually on prescriptions—including the taxes they pay to support government programs purchasing prescriptions—that is an annual savings of $270 per household.

These examples, repealing the costly regulation of generic drugs and health insurance, are but two of many such efforts by the Trump administration since 2017. This paragraph, from the CEA report’s conclusion, gives a sense for the broad swath of deregulation:

Since 2017, consumers and small businesses have been able to live and work with more choice and less Federal government interference. They can purchase health insurance in groups or as individuals without paying for categories of coverage that they do not want or need. Small businesses can design compensation packages that meet the needs of their employees, enter into a genuine franchise relationship with a larger corporation, or seek confidential professional advice on the organization of their workplaces. Consumers have a variety of choices as to less expensive wireless and wired Internet access. Small banks are no longer treated as “too big to fail” (they never were) and subject to the costly regulatory scrutiny that goes with that designation.

All told, the CEA report estimates that over the next five to 10 years, the deregulatory efforts of the Trump administration will increase annual real incomes in the United States by $3,100 per household. 

That’s no ditch. 

Running Government Like a Businsess