Change, demographic and intellectual

 New post over at grumpy-economist.com substack

Fiscal Narratives for US Inflation

An essay on substack; interpreting US inflation history via fiscal theory, prepared as comments for a session at the AEA meetings. 

Bond risk premiums -- certainty found and lost again

This is a second post from a set of comments I gave at the NBER Asset Pricing conference in early November at Stanford.  Conference agenda here. My full slides here. First post here, on new-Keynesian models

I  commented on "Downward Nominal Rigidities and Bond Premia" by François Gourio  and Phuong Ngo. The paper was about bond premiums. Commenting made me realize that I thought I understood the issue, and now I realize I don't at all. Understanding term premiums still seems a fruitful area of research after all these years.  

I thought I understood risk premiums

The term premium question is, do you earn more money on average holding long term bonds or short-term bonds? Related, is the yield curve on average upward or downward sloping? Should an investor hold long or short term bonds? 

New-Keynesian models, a puzzle of scientific sociology

This post is from a set of comments I gave at the NBER Asset Pricing conference in early November at Stanford.  Conference agenda here. My full slides here. There was video, but sadly I took too long to write this post and the NBER took down the conference video. 

I was asked to comment on "Downward Nominal Rigidities and Bond Premia" by François Gourio  and Phuong Ngo. It's a very nice clean paper, so all I could think to do as discussant is praise it, then move on to bigger issues. These are really comments about whole literatures, not about one paper. One can admire the play but complain about the game. 

The paper implements a version of Bob Lucas' 1973 "International evidence" observation. Prices are less sticky in high inflation countries. The Phillips curve more vertical. Output is less affected by inflation. The Calvo fairy visits every night in Argentina. To Lucas, high inflation comes with variable inflation, so people understand that price changes are mostly aggregate not relative prices, and ignore them. Gourio and Ngo use a new-Keynesian model with downwardly sticky prices and wages to express the idea.  When inflation is low, we're more often in the more-sticky regime. They use this idea in a model of bond risk premia. Times of low inflation lead to more correlation of inflation and output, and so a different correlation of nominal bond returns with the discount factor, and a different term premium. 

I made two points, first about bond premiums and second about new-Keynesian models. Only the latter for this post. 

This paper, like hundreds before it, adds a few ingredients on top of a standard textbook new-Keynesian model. But that textbook model has deep structural problems. There are known ways to fix the problems. Yet we continually build on the standard model, rather than incorporate known ways or find new ways to fix its underlying problems. 

Problem 1: The sign is "wrong" or at least unconventional.

Interest rates and inflation part 2: Losing faith in VARs

(This post continues part 1 which just looked at the data. Part 3 on theory is here) 

When the Fed raises interest rates, how does inflation respond? Are there "long and variable lags" to inflation and output?  

There is a standard story: The Fed raises interest rates; inflation is sticky so real interest rates (interest rate - inflation) rise; higher real interest rates lower output and employment; the softer economy pushes inflation down. Each of these is a lagged effect. But despite 40 years of effort, theory struggles to substantiate that story (next post), it's had to see in the data (last post), and the empirical work is ephemeral -- this post.  

The vector autoregression and related local projection are today the standard empirical tools to address how monetary policy affects the economy, and have been since Chris Sims' great work in the 1970s. (See Larry Christiano's review.) 

I am losing faith in the method and results. We need to find new ways to learn about the effects of monetary policy. This post expands on some thoughts on this topic in "Expectations and the Neutrality of Interest Rates," several of my papers from the 1990s* and excellent recent reviews from Valerie Ramey and  Emi Nakamura and Jón Steinsson, who  eloquently summarize the hard identification and computation troubles of contemporary empirical work.

Maybe popular wisdom is right, and economics just has to catch up. Perhaps we will. But a popular belief that does not have solid scientific theory and empirical backing, despite a 40 year effort for models and data that will provide the desired answer, must be a bit less trustworthy than one that does have such foundations. Practical people should consider that the Fed may be less powerful than traditionally thought, and that its interest rate policy has different effects than commonly thought. Whether and under what conditions high interest rates lower inflation, whether they do so with long and variable but nonetheless predictable and exploitable lags, is much less certain than you think. 

New York Times on HANK, and questions

By the standards of mainstream media coverage of technical economics, Peter Coy's coverage of HANK (Heterogeneous Agent New Keynesian) models in the New York Times was actually pretty good. 

1) Representative agents and distributions. 

Yes, it starts with the usual misunderstanding about "representative agents," that models assume we are all the same. Some of this is the standard journalist's response to all economic models: we have simplified the assumptions, we need more general assumptions. They don't understand that the genius of economic theory lies precisely in finding simplified but tractable assumptions that tell the main story. Progress never comes from putting more ingredients and stirring the pot to see what comes out. (I mean you, third year graduate students looking for a thesis topic.) 

But in this case many economists are also confused on this issue. I've been to quite a few HANK seminars in which prominent academics waste 10 minutes or so dumping on the "assumption that everyone is identical." 

There is a beautiful old theorem, called the "social welfare function." (I learned this in graduate school in fall 1979, from Hal Varian's excellent textbook.) People can have almost arbitrarily different preferences (utility functions), incomes and shocks, companies can have almost arbitrarily different characteristics (production functions),  yet the aggregate economy behaves as if there is a single representative consumer and representative firm. The equilibrium path of aggregate consumption, output,  investment, employment, and the prices and interest rates of that equilibrium are the same as those of an economy where everyone and every firm is the same, with a "representative agent" consumption function and "representative firm" production function.  Moreover, the representative agent utility function and representative firm production function need not look anything like those of any particular individual person and firm. If I have power utility and you have quadratic utility, the economy behaves as if there is a single consumer with something in between. 

Defining the job of macroeconomics to understand the movement over time of aggregates -- how do GDP, consumption, investment, employment, price level, interest rates, stock prices etc. move over time, and how do policies affect those movements -- macroeconomics can ignore microeconomics. (We'll get back to that definition in a moment.) 

Inflation and debt across countries

Peder Beck-Friis and Richard Clarida at Pimco have a nice blog post on the recent inflation, including the above graph.  I have wondered, and been asked, if the differences across countries in inflation lines up with the size of the covid fiscal expansion. Apparently yes. 

Papers: Dew-Becker on Networks

I've been reading a lot of macro lately. In part, I'm just catching up from a few years of book writing. In part,  I want to understand inflation dynamics, the quest set forth in "expectations and the neutrality of interest rates," and an  obvious next step in the fiscal theory program. Perhaps blog readers might find interesting some summaries of recent papers, when there is a great idea that can be summarized without a huge amount of math. So, I start a series on cool papers I'm reading. 

Today: "Tail risk in production networks" by Ian Dew-Becker, a beautiful paper. A "production network" approach recognizes that each firm buys from others, and models this interconnection. It's a hot topic for lots of reasons, below.  I'm interested because prices cascading through production networks might induce a better model of inflation dynamics. 

(This post uses Mathjax equations. If you're seeing garbage like [\alpha = \beta] then come back to the source  here.) 

To Ian's paper: Each firm uses other firms' outputs as inputs. Now, hit the economy with a vector of productivity shocks. Some firms get more productive, some get less productive. The more productive ones will expand and lower prices, but that changes everyone's input prices too. Where does it all settle down? This is the fun question of network economics. 

Ian's central idea: The problem simplifies a lot for large shocks. Usually when problems are complicated we look at first or second order approximations, i.e. for small shocks, obtaining linear or quadratic ("simple") approximations. 

On the x axis, take a vector of productivity shocks for each firm, and scale it up or down. The x axis represents this overall scale. The y axis is GDP. The right hand graph is Ian's point: for large shocks, log GDP becomes linear in log productivity -- really simple. 

Why? Because for large enough shocks, all the networky stuff disappears. Each firm's output moves up or down depending only on one critical input. 

Bob Lucas and his papers

My first post described a few anecdotes about what a warm person Bob Lucas was, and such a great colleague. Here I describe a little bit of his intellectual influence, in a form that is I hope accessible to average people.

The “rational expectations” revolution that brought down Keynesianism in the 1970s was really much larger than that. It was really the “general equilibrium” revolution. 

Macroeconomics until 1970 was sharply different from regular microeconomics. Economics is all about “models,” complete toy economies that we construct via equations and in computer programs. You can’t keep track of everything in even the most beautiful prose. Microeconomic models, and “general equilibrium” as that term was used at the time, wrote down how people behave — how they decide what to buy, how hard to work, whether to save, etc.. Then it similarly described how companies behave and how government behaves. Set this in motion and see where it all settles down; what prices and quantities result. 

Lessons from Sargent and Leeper

At the AEI fiscal theory event last Tuesday Tom Sargent and Eric Leeper made some key points about the current situation, with reference to lessons of history. 

Tom's comments updated his excellent paper with George Hall "Three World Wars" (at pnas,  summary essay in the Hoover Conference volume). Tom and George liken covid to a war: a large emergency requiring immense expenditure. We can quibble about "require" but not the expenditure. 

(2008 was a little war in this sense as well.) Since outlays are well ahead of receipts, these huge temporary expenditures are financed by issuing debt and printing money, as optimal tax theory says they should be. 

In all three cases, you see a ratcheting up of outlays after the war. That's happening now, and in 2008, just as in WWI and WWII. 

After WWI and WWII, there is a period of primary surpluses -- tax receipts greater than spending -- which helps to pay back the debt. This time is notable for the absence of that effect. 

We see that most clearly by plotting the primary deficits directly. The data update since Tom and George's original paper (dots) makes that clear. To a fiscal theorist, this is a worrisome difference. We are not following historical tradition of regular, full employment, peacetime surpluses. 

The two world wars were also financed by a considerable inflation. The important consequence of inflation is that it inflates away government debt. Essentially, we pay for part of the war by a default on debt, engineered via inflation. 

FTPL Videos

 Two great videos just dropped related to fiscal theory. 

The first is an "Uncommon Knowledge" interview with Peter Robinson. We start with fiscal theory and move on far and wide. Peter is a great interviewer, and the Uncommon Knowledge production team put together a great video of it. Pick your link: Video at Hoover (best, in my view); Hoover event page with podcast, links and more info, Youtube, Twitter, Facebook. 

Second, Michael Strain at AEI moderated a great panel discussion on fiscal theory with me, Robert Barro, Tom Sargent and Eric Leeper. Three of the founding fathers of fiscal theory offer thoughtful comments, and Michael had provocative questions. I start with a 20 minute presentation, with slides, so this is the most compact "what is the fiscal theory" video to date. It's at the AEI event page or Youtube 

Mulligan and the demand for opioids

This is another post from an Economic Policy Working Group meeting at Hoover, in which simple undergraduate supply and demand analysis, creatively applied, leads to a surprising result.  

Casey Mulligan presented "Prices and Policies in Opioid Markets." Paper, slides and video of the presentation.  (Updated link now works) 

Once prescription opioids became an evident crisis, the government took steps to restrict the supply, raising the price. Yet opioid consumption and overdoses went up. Explain that Mr. Chicago economist! 

Here's the clever answer: 

There are two ways to buy opioids, 1) legally or semi-legally; i.e. get opioids that come from pharmaceutical companies and are prescribed to someone by a doctor or 2) illegally. 

There is a fixed cost of entering the illegal market. .".Avoiding theft, acquiring self-dosing skills, or overcoming fear of needles. ...establishing a trusting relationship with a drug dealer...." But the cost per dose of illegal drugs is typically less than for legal drugs. 

So, imagine a drug user starting at B. At that price for legal (red) and illegal (black) drugs, the user chooses legal drugs at point B. Now raise the price of legal drugs, as shown by the arrow. If the user stayed with legal drugs, he or she would use less. But now there is an option, incur the fixed cost and buy illegal drugs on the black line. At the higher price for legal drugs that makes sense. But since the marginal cost of illegal drugs is lower, once the user has overcome the fixed cost, he or she uses more. 

Raise the price, and they consume more (of a substitute). 

Short and long run minimum wage

On Wednesday, Erik Hurst presented a lovely paper, "The Distributional Impact of the Minimum Wage in the Short and Long Run," written with Elena Pastorino, Patrick Kehoe, and Thomas Winberry, at the Hoover Economic Policy Working Group seminar. Video (a great presentation) and slides here. 

This is a beautiful and detailed model, which won't try to summarize here. I write to pass on one central graph and insight. 

Suppose there is some "monopsony power," at the individual firm level. Don't argue about that yet. Erik and coauthors  put it in, so that there is a hope that minimum wages can do some good, and it is the central argument made by minimum wage proponents. In the paper it comes because people are uniquely suited to a particular job for personal reasons. Professors don't like to move, they've figured out the ropes at their current university, so the dean can get away with paying less than they could get elsewhere. Why this applies to MacDonalds relative to the Taco Bell next door is a good question, but again, the point is to analyze it not to argue about it. 

"Labor demand" here is the marginal product of labor. (\(f'(N)\) It's what labor demand would be in a competitive market. The monopsnists' demand is lower). Monopsony means that the "marginal cost of labor" rises with the number of employees. There is a core of people that really love the job that you can hire at low cost. As you expand, though, you have to hire people who aren't that attached to this particular job, so you have to pay more. And you have to pay everyone else more too, (by reasonable assumption -- no individually negotiated wages), so the average cost of labor rises. 

Thus, the monopsonies firm chooses to hire fewer people \(N_m\),  produce less, and pay them a wage \(W_n\) below their marginal product.  ("Average cost of labor" is really the labor supply curve, call it \(w=L(N)\). Then \(\max (f(N)-wN\) s.t. \(w=L(N)\) yields \(f'(N)=w+NL'(N)\). The "marginal cost of labor" in the graph is this latter quantity: the wage you pay the last worker, plus all workers times the extra wage you must pay them all. Disclaimer: the equations are me reverse-engineering the graph.) 

Now, add a minimum wage. As the minimum wage rises above \(W_m\), we initially see a rise in the number of workers, and their incomes. The firm moves along the arrow as shown. (\(\max f(N)-wN\) s.t. \( w \ge L(N)\), \( w \ge w^\ast\) gives \(w^\ast = L(N)\) .) 

Keep raising the minimum wage, though. Once we get past the point that labor supply ("average cost of labor") requires a wage greater than the marginal product of labor, the firm turns around and hires fewer people: 

Gramm, Early and the Unfixable Problem

Phil Gramm and John Early have a new WSJ oped, based on their smashing new book. Both are based on an astounding fact: The numbers used by the Census Bureau, and countless following researchers, to define income inequality and poverty do not include taxes, which reduce income of the rich, and transfers, which increase income of the poor. The latter, obviously, matters to just how many Americans fall in the Census Bureau's definition of poverty.

Specifically, in the oped, the new refundable tax credit cannot, by arithmetic, do anything to alleviate measured child poverty because 

"the income numbers used to calculate the official poverty rates don’t count refundable tax credits as income to the recipients. "

This is wonderful for advocates of ever larger transfer programs, as it creates a problem that can never be measured to be fixed! 

The more general issue 

The Census Bureau fails to count two-thirds of all government transfer payments to households in the income numbers it uses to calculate not only poverty levels but also income inequality and income growth. In addition to not counting refundable tax credits, which are paid by checks from the U.S. Treasury, the official Census Bureau measure doesn’t count food stamps, Medicaid, the Children’s Health Insurance Program, rent subsidies, energy subsidies and health-insurance subsidies under the Affordable Care Act. In total, benefits provided in more than 100 other federal, state and local transfer payments aren’t counted by the Census Bureau as income to the recipients

The book goes on to show how this startling omission overturns just about everything you've heard from the hyperventilating classes about income inequality. Granted, spending zillions on rotten health insurance that people value much less than a dollar per dollar is not quite the same as cash, but there are lots of cash or cash equivalent transfers in there. 

A question I do not know the answer to: Do means-tested programs count as "income" the transfers from other means-tested programs? If a program is only available to, say, those with less than $50,000 per year income, does that figure include any other means-tested programs?  Even the ones that send cash, rather than in-kind transfers such as rent, energy, and health insurance subsidies? I suspect largely no. If not, the incentives for means-tested programs are far worse than even they appear. Facts welcome.

One might easily respond that ok, but evil capitalism created wider pre-tax pre-transfer inequality, and only by the grace of larger and larger transfers has some measure of stability been restored. Well, which is the cause and which is the effect -- wider pre-tax pre-transfer inequality, or the large expansion of means-tested programs, all of which add to the stupendous marginal tax rates facing Americans with less opportunity? The book goes on to argue convincingly the latter. I'll cover that later. Noting here, they anticipate the argument. 

How much do interest rates help?

So if the Fed raises interest rates, how much and how soon will that help inflation? For another project, I went back to Valerie Ramey's classic review. Here is her replication and update of two classic estimates: 

Two estimates of the effect of monetary policy shocks. Top:  Christiano et al. (1999) identification. 1965m1–1995m6 full specification: solid black lines; 1983m1–2007m12 full specification: short dashed blue lines; 1983m1–2007m12, omits money and reserves: long-dashed red lines. Light gray bands are 90% confidence bands. Bottom: Romer and Romer monetary shock. Coibion VAR 1969m3–1996m12: solid black lines; 1983m1–2007m12: short dashed blue lines; 1969m3–2007m12: long- dashed red lines. Source: Ramey (2016)

The left side tells us what the federal funds rate typically does after the Fed raises it. The right shows the effect of the rate rise on the level of the CPI. Inflation is the slope of the curve. The horizontal axis is quarters. The top panel uses a vector autoregression. The bottom panel uses the Romer and Romer reading of the Fed minutes to isolate a monetary policy shock. 

Top pane (VAR): Multiplying by 10, a 2 percentage point rise in the funds rate (blue dash) might lower cumulative inflation by one percentage point in three years (12 quarters), before it runs out of steam. The black line is the most hopeful, but it is essentially the 1980 experience. Still, multiplying by 5, a 2 percentage point rise in the funds rate only lowers inflation half a percent in those first three years (12 quarters), though after 10 years (40 quarters) you get a full percentage point reduction in the price level.

Bottom panel (Narrative): In  the black and red lines that include the 1980 shock, a 3% rise in interest rate produces no noticeable decline in inflation for the first three years. 10 years later, the price level is a decent 4 percent lower, but that is 0.4% per year reduction in inflation. The blue lines that exclude 1980 show a plausible longer-lasting shock, but 1% higher interest rate only produces 1% lower price level in 10 years, m 0.1% per year. 

The problem is the ephemeral Phillips curve, which I emphasized in my WSJ oped. In the VARs, the Fed is pretty good at inducing a recession. Here are the Romer-Romer shocks' effects on output and unemployment: 

It's just that inducing recessions is not particularly effective at lowering inflation. 

And I cherry picked good looking graphs. Many estimates don't find any effect on inflation, or even a positive one: 

No theory today, just the facts. This is the empirical basis for the idea that the Fed can swiftly stop inflation by raising interest rates. The underlying machinery does the best that 50 years on the topic has been able to do to separate causation from correlation, and to isolate the Fed's actions from other influences on inflation. Perfect, no, but this is what we have. 

Perhaps counting on the Fed to stop inflation all by itself is not such a great idea. And I don't have in mind more jawboning and WIN buttons. 

Update: A few Twitter commenters say that we really don't get much out of "normal times" and we have to look to big "regime shifts." 1980 is an example, and the results with and without 1980 are telling. But that is perhaps the point. If so, then it will take a "regime shift" to tame inflation not the usual "tools." 

  

AEA P&P, a measure of an organization

The American Economics Association papers and proceedings are out. This is a selection of the selection of papers presented at the AEA annual meetings. It tells you a lot about where the economics profession is--what papers are submitted--and also where the AEA as our (so far) premier professional organization is--what papers got included -- and perhaps more interestingly, where it isn't. 

Here are the papers. The AEA put the sessions in random order; I reorganized by rough topic. Of course many of the topics have intersectional elements so this isn't perfect either. Comments below, but you should read the raw data first and find your own inferences. 

AEA DISTINGUISHED LECTURE

On the Dynamics of Human Behavior: The Past, Present, and Future of Culture, Conflict, and Cooperation

Race

RACE, GENDER, AND FINANCIAL WELL-BEING

• Black Land Loss: 1920−1997
• Intersectionality and Financial Inclusion in the United States
• At the Intersection of Race, Occupational Status, and Middle-Class Attainment in Young Adulthood
• Child-to-Parent Intergenerational Transfers, Social Security, and Child Wealth Building

RACISM IN THE UNITED STATES: EVIDENCE FROM ECONOMIC HISTORY

• Media Access and Consumption in the Civil Rights Era
• On the Impact of Federal Housing Policies on Racial Inequality
• Sundown Towns and Racial Exclusion: The Southern White Diaspora and the "Great Retreat"
• Discrimination, Segregation, Integration, and Expropriation

Is the Fed new-Keynesian?

(Update: This post turned in to "inflation past present and future")

I realize that the title of my last post, Is the Fed Fisherian? was not as clear as it could be. The model I used to understand the Fed's forecast was, in fact, completely standard new-Keyenesian. The new-Keynesian model has the Fisherian property -- a permanent interest rate rise raises inflation, at least eventually -- but that is not its core feature. A clearer description is, is the Fed new-Keynesian -- and thereby, only incidentally, Fisherian. 

Beyond clearing that up, today I want to add unemployment. In part, I am motivated by a new working paper by Alex Domash and Larry Summers, warning that the Fed will have to raise interest rates to stop this inflation, and doing so will cause a recession. They also point out that scenario in the past, most notably 1980. 

So what model can account for the Fed's rosy employment scenario? It turns out that the little new-Keynesian model from the last post accounts for its unemployment views as well. And that the same model accounts for its inflation, unemployment, and funds rate forecasts together makes it more credible that this is a reasonable model of how the Fed thinks.  

The Fed, it seems is new-Keyensian. That makes some sense; their models are new-Keynesian. We shall see if those models are right. 

I start today by plotting again the Fed's projections, this time including unemployment. As well as inflation going away on its own without a period of high interest rates, you see inflation gently converge to the Fed's view of a long-run 4% natural rate. Is there a model behind this rosy scenario? Yes. 

Brazilian Inflation

This marvelous plot comes from an interesting article, The Monetary and Fiscal History of Brazil, 1960-2016 by Joao Ayres, Marcio Garcia, Diogo A. Guillén, and Patrick J. Kehoe. The article is part of the Becker-Friedman Institute Project, complete with a big and now easily available data collection effort, and forthcoming book. 

If you want a deep historical and economic analysis of fiscal and monetary interactions, this is an amazing resource. And it summarizes historical episodes that North Americans just might want to know more about soon! 

(HT Ricardo Reis who pointed it out in a great discussion last week, that I will post as soon as it's available.) 

Infrastructure and jobs

William Gropper, Construction of the Dam, 1938

To many on the left, it's always 1933. Building "roads and bridges" will "create jobs," soaking up the mass army of unemployed desperate for work that they seem to see. 

Driving around though, I notice that we build roads with big machines, not lots of people. And construction jobs are high-skill jobs, not people with shovels. "Shovel-ready" itself is a misnomer. Nobody uses shovels on a construction site anymore, they use a backhoe. Neither you, reading this, nor I, nor an unemployed Wal-Mart greeter or bartender could do much of anything useful on a road construction site. 

On a lark, I went to the Bureau of Labor Statistics to see just how many people are employed on roads and bridge construction. 

	Latest	Feb-Mar change
Total nonfarm	144,120.0	916
Construction of buildings	1,689.3	17.8
Heavy and civil engineering construction	1,062.9	27.3
Water and sewer system construction	183.8
Oil and gas pipeline construction	134.9
Power and communication system construction	211.3
Highway street and bridge construction	338.3
Specialty trade contractors	4,714.2	65.0

For perspective, total nonfarm employment is 144 million people, up nearly a million in the last month. That's a lot, usually 200,000 is a good month. Well, we're recovering fast from the pandemic. In case you didn't hear the pounding of nails, building construction employees 1.6 million people, with 4.7 million more in the trades. (We're not so much building new housing as building in new places.) 

Total unemployment is 9.7 million right now, down from 23 million at its peak. 

Roads and bridges employ 338,000 people. The total is a half of this month's gain alone.  We could use some water construction here in California, though it's not going to happen, and with only 184,000 people employed there looks to be room to expand. 135,000 are building oil and gas pipelines. Uh-oh.

Inequality mirage?

David Splinter and Gerald Auten gave last week's Hoover Economic Policy Working Group seminar, summarizing their past and some work in progress on the distribution of income.  Link in case the above embed does not work. A recent paper. Splinter's web page. 

Splinter and Auten are very even handed, just-the-facts, economists. I'll pass on their facts. Grumpy interpretations are my own. 

It is a fact generally accepted that income inequality has grown a lot recently, and this is a "problem" to be "solved." So what if the great inequality crisis simply isn't true? Let's leave aside whether income is a good measure (it isn't), let's just look at the fact, has income inequality substantially increased? 

No. Here is the headline result. In their careful redoing of the numbers, the top 1% share of income has barely budged since the 1970s. (And, by the way, if you think the mid 1970s economy was the great happy prosperity we should try to reestablish, you're too young to remember the 1970s.)

Now we get in to a deep under the hood exercise about costing up income, and where did Piketty and Saez go wrong. The video has some of that. The papers have more, and a long list of back and forth, including comparisons with many other studies. I'll name just a few.

Omitted income.   Piketty Saez leave out many kinds of income. Auten Splinter attribute all national income to somebody.  Before 1986 many wealthy people were incorporated.  Leaving out corporate income biases the early shares down. Auten Splinter fix that. Pre-tax and transfer income! Who cares about pre-tax income! Auten Splinter calculate income after taxes at the top -- lower -- and including transfers at the bottom -- higher. Demographics. Marriage rates have fallen, so Auten Splinter calculate income by individuals. Benefits! They include benefits like employer-provided health insurance.

One can quibble, but one can quibble. At least this cornerstone "fact" of political debate is a lot less sure than it looks. 

If the rich aren't getting richer, the poor aren't getting poorer: