Marxist Perspectives on White House Staff Turnover

The labor theory of value (a.k.a., law of value) is an aspect of Marxist theory that still thrives in the marketplace of ideas.  It values anything and everything according to how much labor went into it.

Therefore, for example, Ben Rhodes contributed at least thrice more to the Federal government than, say, Brian Blase because Rhodes served 96 months in the Obama White House (as Deputy National Security Advisor) while Blase served only 29 (as Special Assistant to President Trump for Healthcare Policy).

But let's look at why Rhodes' tenure was 96 months whereas Blase's was 29.  Chapter 23 of Rhodes' memoirs explains that as of 2014 (roughly 70 months in), he expected that his policy accomplishments were still unfinished.

• Normalizing relations with Cuba (to my personal benefit) did not begin until the 71st month; the President's trip to Cuba was in the 86th month.
• The Iran deal was not reached until the 78th month.
• Intervention in Libya (26th month) may have felt like a policy success at the time (Chapter 18 quotes President Obama as saying "In Libya, everything went right--we saved thousands of lives, we didn't have a single casualty...").

Brian Blase's important policy accomplishments came sooner.  He led three (sic) Federal agencies to coauthor three transformative Federal deregulatory actions that were celebrated in the White House Rose Garden in Blase's 29th month.

• Allowing more small businesses to form Association Health Plans (17th month; creating an annual net benefit of $13 billion for some of the reasons discussed earlier).
• Expanding Short-Term Limited Duration health Insurance plans (19th month; creating an annual net benefit of $12 billion for some of the reasons discussed earlier).
• Creating individual-coverage Health Reimbursement Accounts (29th month; CEA has not yet quantified a net benefit).
• Contributing to the Administration's effort to set the Affordable Care Act's individual mandate penalty to zero (11th month; creating an annual net benefit of $20 billion as discussed earlier).
• Other not yet quantified policy achievements such as fixing the Affordable Care Act's formula for the Premium Adjustment Percentage.

Indeed, these health insurance deregulations accomplished in 29 months have, as a share of national income, net benefits that are more than half of the legendary deregulation of airlines that began during the Carter Administration, which took more than twice the time that health insurance deregulation did.

Another example is Andrew Bremberg, who served 24 months as President Trump's Director of the Domestic Policy Council.  He had many accomplishments during that time, the most legendary being his leadership of the Administration and the 115th Congress to deregulate by way of the Congressional Review Act.

• Measured in terms of economic impact, this work was prolific.
• 16 separate pieces of legislation deregulated education, mining, retirement accounts, and more.  They are expected to increase annual real incomes by more than $40 billion.
• All of this was achieved in only 15 months.

COS General Kelly (17 months) is another example.  He came early in the Administration when more efficient operating procedures were needed and, as in earlier Administrations (this one had its first-year middle-east policy dictated by leaks), leaks needed to be reduced.  Like Doug Collins did for the Jordan-era Chicago Bulls, General Kelly improved the organization.  With Kelly's accomplishments in place, it was time for a different set of talents.  Mulvaney is the White House's Phil Jackson with both political successes (i.e., winning elections himself) and an impressive analytical mind.

Undoubtedly there are Trump Administration officials with both short tenures and short accomplishments.  But the above is enough to show how misleading are the turnover statistics.

You might assert that Blase and Bremberg had easier jobs than Rhodes did because the former were "merely" undoing actions of a previous Administration.  That assertion certifies mastery of the labor theory of value.

[The labor theory of value has endured since Marx.  Other important parts of Marxist theory did not, but made a comeback recently.  I will write about those next.]

Who recognizes economic history first: politicians or economists?

Figure 1 is the familiar chart showing the “Laffer curve” relationship between a tax rate and the net revenue from the tax.  A small tax on, say, wireless internet service is expected to provide more revenue (point B) than would be obtained without any tax on wireless internet service (point A).  It is conceivable that the wireless internet tax rate could get so high that further increases in the rate actually reduce revenue (point C) as consumers take steps to evade taxation altogether.  At point C, economics gets really interesting because many of the difficult public policy marginal tradeoffs disappear.

When it comes to various taxes in the United States, at least, we economists typically expect that the operative point is B.  E.g., the Federal payroll tax is probably at a point where further increases in the rate would raise at least some revenue, albeit less than static scores that make little distinction between points A and B.

The statutory Federal corporate rate is an interesting case, especially three years ago when it was well above rates elsewhere in the world.  Arguably cutting that rate increased Federal revenue as at point C (combined revenues from payroll, personal income, and corporate income).  But other reasonable experts could opine that point B was and is the operative point for the corporate tax rate.  And even these opposing experts would likely agree that the operative point (B or C) is above point A where the tax is abolished.

My only point here is that we would be at a unique chapter in economic history if a tax were obviously at point C or beyond.  So turn now to Figure 2, especially its point D where the government receives more revenue by abolishing the tax.  This was the case with the Affordable Care Act’s tax on uninsurance (a.k.a., individual mandate tax).

(I cannot say for sure how the path evolves between points A and D, e.g., perhaps the path never crosses above the horizontal axis, but that issue is not important for what follows.)

The first chapter of my ACA book explained what was happening, using the story of Pastor Ben Winslett who described how the ACA “has placed an enormous financial burden on normal, everyday people quite literally forcing us onto government assistance we didn’t need before.”  In other words, the individual mandate penalized people for turning down government assistance!  Mick Mulvaney explains here.

The government saves money by reducing the punishment it imposes on people who turn down subsidies because more people turn down the subsidies.

You don’t have to believe me.  Look at Jonathan Gruber’s 2010 analysis of repealing the individual mandate, where he projected (p. 4) that repealing it would reduce Federal spending by about $46 billion per year, while sacrificing much less than that in terms of mandate collections.  Or the Congressional Budget Office projection that repealing the mandate would reduce Federal spending by about $34 billion per year, while sacrificing much less than that in terms of mandate collections.  I (and the current CEA) think that those two estimates are exaggerated, but if Gruber and CBO stand by their qualitative analysis then all four of us must agree that point D is the operative point.

Having a tax at point D easily makes the highlights of economic history. Neither my book (which focused on the subsidies and the employer mandate), Gruber’s report, nor the CBO’s report put their findings on the individual mandate in the context of a Laffer curve let alone follow up with an estimate of the massive economic damage that comes with pushing a tax down to point D.  It should be no surprise that, in doing the necessary work, the current CEA found massive net benefits of moving from point D to point A even after considering the various benefits of expanding health insurance coverage.

President Trump and Congressional Republicans recognized the historical damage done by the individual mandate well before economists did, even while it is economists who specialize in such matters.  President Trump reached the (important and correct) conclusion sooner because he reasons differently on issues like this.  Simulated annealing is a close analogy that I’ll write about later.  He did not get ahead of us by “playing 3 dimensional chess” or drawing Figure 2: that would be the kind of deductive reasoning that is prevalent in economics and proved slower at reaching the answer.  Many critiques of the President assume that deduction is the only method and thereby entirely miss the point of simulated annealing, which is that he would try both criticizing the mandate and (albeit briefly) praising it and then closely monitor the feedback.  I suspect that members of Congress did something similar (President Obama also recognized -- just privately until he left office -- that there was more to the individual mandate than the technocrats were telling him).

Health regulation is just one area of Federal policy where some of the most interesting economic history is happening now….

Critiques of Single-payer: Why Did They Take So Long to be Discovered?

It is now routine for Democrats to be asked in town halls, debates, etc. "Who here would abolish their private health insurance in favor of a government-run plan?"  But why did it take so long to pose this question to advocates of "single-payer" health systems?

As a matter of economics, it should be obvious that the health insurance market would not be served by a single seller unless there were tremendous barriers to entry.  E.g., criminalizing any private enterprise that attempts to sell or otherwise provide health insurance.  Without stark penalties, regardless of the details of government plans, there would be gains from trade between private insurers and at least a small segment of consumers if not more.  With private insurers, the market is no longer "single payer" (as long as "single" refers to "one"). 

For this reason, bills in Congress proposing to transform the U.S. market into single payer outlaw private health insurance.  Take Senator Bernie Sanders 2013 (sic) American Health Security Act's "enactment of a Medicare-for-All Single Payer Health Care System" by "Requir[ing] each state health security program to prohibit the sale of health insurance in that state...."

Why didn't Mrs. Clinton ever raise this point when Senator Sanders was campaigning against her for the 2016 Democratic nomination?

Why didn't Joe Crowley raise this point when campaigning against AOC in 2018?

One possible answer is overconfidence in victory.  But overconfidence did not stop Clinton supporters from calling Sanders a socialist during the 2016 primary, or Clinton positioning herself as a defender of capitalism.  Why not make it more concrete to regular people and alert the 180 million consumers of private health insurance that their product would become illegal?

I think part of the answer is that few people actually read the single-payer bills in Congress (I observed the same with the "stimulus" law and with the ACA) or think through the economics of how single payer can operate even in principle.

From the first day I arrived at White House CEA, I told anyone who would listen: "Medicare for All bills in Congress will outlaw the sale of private health insurance and outlaw the provision of health insurance as part of employment."  They thought I was kidding.  Because capable politicians do not give such gifts to their opponents, what I said could not be true.  I began carrying the relevant bill sections in my jacket pocket for the benefit of the doubting Thomases; only after that did the President's speeches (which are preread by EOP staff) begin to include the disturbing and incredible truths about "Medicare for All" (an earlier alarm bell was here).

It turns out that I have a talent for finding rock-solid facts that journalists would vigorously deny (see Jim Acosta here, noting that the President wrote about "the Democrat proposal 'Medicare for All'", which USA today shortened to "Democrats" in its byline).  A few months later, journalists finally stopped denying the plain text of the Medicare for All bill and began querying Democrats as to whether they support the abolition of private health insurance.

(Medicare for All bills also adhere remarkably closely to Marxist theory, but that is primarily of academic interest so I will post on it later.)

[For those interested in the technicalities, Medicare for All outlaws any private insurance (individual or employer) that covers any normal medical service.  Specifically (from page 421 the 2019 Economic Report of the President, referring to the 2017 bills): “medically necessary or appropriate”

• hospital services,

• ambulatory patient services,

• primary and preventive services,

• prescription drugs,

• medical devices,

• biological products,

• mental health services,

• substance abuse treatment,

• laboratory/diagnostic services,

• reproductive care,

• maternity care,

• newborn care,

• pediatrics,

• oral health services,

• audiology services,

• vision services, or short-term rehabilitative and habilitative services and devices (sections 107 and 201 of the “Medicare for All” Act of 2017 and section 104 of the House bill).

The House bill (section 102) goes further with

• dietary and nutritional therapies,

• long-term care,

• palliative care,

• chiropractic services,

• and podiatric care.

The 2019 bills further add to this list. 

]

A Brief Summary of Activities in President Trump's Council of Economic Advisers

From July 2018 to June 2019, I served as Chief Economist of the Council of Economic Advisers (CEA). My primary responsibilities were preparing public reports, supervising senior economists and interacting with various groups in the White House and in the relevant agencies on a wide range of topics.  As CEA engaged in topics, they were picked up by Kevin Hassett (especially tax and trade), Tom Philipson (esp. health, infrastructure, student loans), Rich Burkhauser (esp. labor, immigration, and social programs), or me (Affordable Care Act, socialism, regulation, wage growth, macro aspects of trade).  On some of the topics I worked serially or in tandem with Tom (health insurance regulation, Medicare Part D, the Rx CPI, opioid prices) and in tandem with Rich (TROIKA).

The large majority of my time was in various stages of preparing Administration reports for the public, most of which were CEA products although OMB publishes the TROIKA results and the agencies publish rulemaking documents (which CEA sometimes edits).

Typical activities: Supply and Demand

The pace and daily execution of my work closely resembled academic research and economics consulting in litigation matters.  This is probably unusual in the history of the CEA, but was the result of three practices:

• anticipating the needs of POTUS and EOP economic principals,[1]
• fitting questions into the catalog of economic theory so that established methods and literatures could be used to quickly obtain reliable answers,[2] and
• using already-published CEA reports to facilitate accurate and consistent execution of new tasks.

Much public policy discussion is devoid of economics and thereby obscures evaluation of current Federal policies.  Invariably these were policy areas where EOP principals most valued CEA’s work.  Socialism and Medicare for All (see also their updates in the in 2019 Economic Report of the President) are good examples where CEA was able to initiate or at least bend the conversation by assembling results from economic research.

Probably the best tool is the empirical counterpart of the supply and demand picture.  That is, measuring both price and quantity using the best methods available in the academic literature.  CEA is desperately needed to perform this function.  The current CEA already has 11 instances of those pictures in its Economic Reports of the President, as compared to only 8 for all of the combined other Presidential Administrations in U.S. history.[3]  This may seem to be a trivial enterprise, but the “best” in our profession fail at it regularly (see below and here and here).

With the labor market, for example, the public policy community is familiar with methods for measuring quantities (employment, hours, unemployment etc.) but unfamiliar with measuring prices (i.e., wages).  CEA measured wages with attention to composition issues, human capital, taxes, etc., and thereby helped change the factually incorrect narrative that real wages were “stagnating.”

Prescription drugs are another important example.  The typical narrative (including at HHS, which sees itself as the drug-price regulator) was that prescription drug prices were increasing faster than general inflation, as they had for decades. But, with attention to the institutional details of the supply chain, CEA found that the best measures showed an increase in quantities of prescriptions at the same time that prices have been falling over the past two years or so.

With the decades-long opioid epidemic, public policy discussions still ignore prices altogether: another opportunity where CEA made a valuable contribution by following standard economic practice.  (More on this tragic and ongoing story in later posts).

CEA’s trade team executed these methods repeatedly as various tariff rates were changed.

CEA took a similar approach to the Affordable Care Act, where we found that Trump Administration reforms were significantly reducing health insurance prices measured according to a cost of living index.  CEA’s public report on this issue presented the dual of the cost-of-living index, namely cost-benefit analysis.  This spawned many other regulatory impact analyses by CEA that laid the foundation for its report on the economic effects of the Trump Administration’s deregulation portfolio.  I worked closely with Don Kenkel (now the CEA Chief Economist) on these issues throughout the year.

One Economics

I looked carefully and critically at the headline calculations of all CEA reports released during the year (beyond the 12 reports or ERP sections that I edited), as well as the corporate tax reports released at the end of 2017.  The essential methods and sources for these calculations proved to be consistent across reports including, but not limited to, tax, immigration, health, socialism, and regulation.

A three-good version of the neoclassical growth model with taxes was another workhorse that links industry-specific analysis with macroeconomic analysis.  The three goods are leisure and two consumption goods (but see below).  CEA used that to look at Medicare for All (health consumption vs other consumption), tariffs (tariffed goods vs other goods), and dozens of regulations (regulated good vs other consumption goods). We also used it to look at business tax reform and investment regulation, where there is just one consumption good but two capital goods (corporate vs noncorporate).  We typically focused on the steady state and took a broad view of “taxation” that encompasses other market distortions.  We derived quantitative rules of thumb (such as the well-known marginal excess burden of taxation) for the effects of a single sector’s distortion on the aggregate supplies of labor and capital.

I frequently used automated economic reasoning (run with Mathematica with an add-on from the web) to confirm, refine, and extend our reasoning about the three-good model and other applications of logic and economic theory that went beyond the simplest supply-and-demand framework.  I will be adding these examples (which embed hundreds of automatically assembled and decided Tarski formulas) to the library of SAT/quantifier-elimination applications that I maintain with computer scientists.

Working in a Large Organization

The Executive Office of the President (EOP, of which CEA is one of several components), not to mention the entire Federal government, is a large organization with components far more inter-reliant than the components of a university. Professors joining CEA need to be aware that staff meetings are critical for keeping information flowing to the parts of the EOP that need it.  As you attend EOP meetings in your subject area, be prepared to share headlines with the rest of the CEA staff at the staff meetings and listen to others to assess who in CEA or outside CEA might be of help for the next task that arrives.

The EOP has a staff hierarchy for the same reasons, although many employees adhere to it so rigidly that there is a role for organizational entrepreneurs who cross some of those boundaries, which is a role I took on in much of my work.  Otherwise meetings of principals (a.k.a., cabinet-level positions) and deputies (report directly to principals) may not have anyone present who knows first hand the details of the meetings’ subject.  I presume that this is also a problem in large private organizations, but more acute in government where leaks are more of a constraint on determining who is invited to meetings (see, e.g., this memoir’s discussion of leaks in the Obama White House).

CEA Chairman Hassett and COS DJ Nordquist assembled an amazing team of economists.  I also worked closely with six other components of the Federal government: the Office of Management and Budget (OMB), the National Economic Council (NEC), the Office of Information and Regulatory Affairs (OIRA, technically part of OMB), the Domestic Policy Council (DPC), the Department of Labor (DOL), and the Department of Health and Human Services (HHS).

Every day working in the EOP was a pleasure (Mick Mulvaney = Phil Jackson; the Kelly-Collins analogy is imperfect). It is difficult saying goodbye to so many excellent EOP colleagues but by design CEA has high turnover so that others outside can come in with fresh ideas and energy.

[In returning to the University of Chicago, I return to publishing under my own name and take sole responsibility for the analysis and conclusions.  As such, the Federal government is not consulted on my writings.]

---

[1] E.g., measuring wage growth properly, exposing misconceptions about single-payer systems, highlighting the consequences of deregulation from autos to prescription drugs.

[2] A forthcoming blog post will list more than 50 results from Chicago Price Theory (forthcoming, Princeton University Press) that appear in public CEA reports.

[3] CEA, which is tasked with preparing the Economic Report of the President, dates back “only” to 1946.

Lou Dobbs knew what we were doing

Remembering Alan Krueger

Sadly Princeton Professor and former CEA chair Alan Krueger passed away this weekend.  Many younger economists were inspired by his insistence that economics is an empirical subject: no matter how good a theory sounds, it is not valuable unless it is confirmed with data.  He was 100% correct about that.

Another of his many contributions was his editorship of Journal of Economic Perspectives which, unlike most academic journals, publishes accessible economic analyses of important topics, including our shared interest in intergenerational mobility (he proved to be an excellent editor on this piece).

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Inflation has little to do with the Unemployment Rate

Copyright, TheHill.com

The April unemployment rate, released Friday, showed the headline unemployment rate below 4 percent, which has rarely happened in the past 48 years. But a low unemployment rate does not necessarily mean high inflation.

A conventional wisdom, sometimes known as the Phillips curve, holds that low unemployment creates inflation as employers increasingly bid against each other for workers and pass on some of their labor costs to consumers.

One problem with the theory is that low unemployment is not synonymous with high employment. Aside from identifying Americans as either working or being unemployed, federal government statisticians also put adults into a third category: out of the labor force (OLF).

In other words, "unemployed" is just one of two not-working categories, so that both employment and unemployment can fall at the same time if enough people are switching from unemployed to out of the labor force.

The official distinction between unemployed and OLF is whether the not-working person is actively looking for work. This distinction helps to prevent confusing a retiree or a full-time student with a laid-off head of household who is eagerly looking for a new job.

But a number of people are on the margin of looking for work and could be classified either way. During President Obama's first term, the federal government was actively assisting out-of-work people with temporary cash, health and mortgage assistance but only if they said that they were looking for work. That by itself inflated the measured unemployment rate above what it would have been.

When the temporary assistance programs began to expire during 2010 and 2011, that's exactly when the unemployment rate started falling. Some of that drop was a result of additional employment, but an important part of it was just a shift to the OLF form of not working.

To further add to the statistical distortion, the headline unemployment rate is measured as a share of people in the labor force rather than a share of population. When 3.9 percent of the labor force is unemployed, that means that an even lesser percentage of the adult population is unemployed because a great many adults are not in the labor force.

Increases in the number of people classified as OLF can, therefore, reduce the headline unemployment rate without changing the number of people who actually are unemployed.

The chart below shows unemployment (blue) and OLF (red) on the same scale, which is a fraction of the adult population (I have subtracted 28 points from OLF so that the two series come together around 2010).

Around 2010, the two started moving in opposite directions, and this trend continued until about 2016. By that point, unemployment was historically low, in comparison with the population, but employment was not historically high.

What had really changed between 2010 and 2016 was the propensity of people who are out of work to say that they are actively looking.

The most recent year has been different, with unemployment falling yet no real increase in OLF. But that change is fairly small in comparison to the changes from 2010 to 2016.

The other problem with the Phillips curve theory is that it has been backward many times in history; there have been times of rapid economic growth at the same time that inflation was low or even negative.

The takeaway: If you want to understand what is happening with inflation, look somewhere else than the unemployment rate.