Smith meet Jones

A while ago I wrote up a smorgasbord of policies that I thought could increase US economic growth, at least for a few decades, in "Economic Growth" (pdf, html here.) Noah Smith took me to task in a Bloomberg View column, complaining that I confused growth with levels,

...I want to focus on one bad argument that Cochrane uses. Most of the so-called growth policies Cochrane and other conservatives propose don't really target growth at all, just short-term efficiency. By pretending that one-shot efficiency boosts will increase long-term sustainable growth, Cochrane effectively executes a bait-and-switch.

As it turns out, the difference between "growth" and "level" effects in growth theory and facts is not so strong. Many economists remember vaguely something from grad school about permanent "growth" effects being different and much larger than "level" effects.  It turns out that the distinction is no longer so clear cut; "growth" is smaller and less permanent than you may have thought, and levels are bigger and longer lasting than you may have thought.

Along the way, I offer one quantitative exercise to help think just how much additional growth the US could get from the sort of free-market policies I outlined in the essay.

Part I Growth and Levels 

A quick reply: China.

China removed exactly the sort of "level" or "inefficiency" economic distortions that free-market economists like myself (and Adam Smith) recommend. What happened? Here is a plot of China's per capita GDP, relative to the US (From World Bank). In case you've been sleeping under a rock somewhere, China took off.

(Note: This blog gets picked up in several places that mangle pictures and equations. If you're not seeing the above picture or later equations, come to the original.)

Now, in the "growth" vs "level," or "frontier" vs. "development" dichotomy, China experienced  a pure "level" effect. Its GDP increased by removing barriers to "short-term" efficiency, not by any of the "long-term" growth changes (more R&D, say) of growth theory.

But "temporary" "short-run" or "catch-up" growth can last for decades.  And it can be highly significant for people's well-being. From 2000 to 2014, China's GDP per capita grew by a factor of 7, from $955 per person to $7,594 per person, 696%, 14.8% annual compound growth rate (my, compounding does a lot). And they're still at 15% of the US level of GDP per person. There is a lot of "growth" left in this "level" effect!

Lots and lots of people, even "liberals" in Noah's other false dichotomy, use the word "growth" to describe what happened to China, and would not belittle policies that could make the same thing happen here.

Part II. How much better can the US do? 

But can liberalization policies have the same effect for us? Yes, you may say, China had scope for a big "catchup" growth effect. But the US is a "frontier" country. China can copy what we're doing. There is nobody for us to copy. Big increases in levels, which look like growth for a while, are over for us.

But are they? We know how much better China's economy can be, because we see the US. We see how much better North Korea's could be, because we see South Korea. (Literally, in this case.) How much better could the US be, really, if we removed all the distortions as in my growth essay?

To think about this issue, I made the following graph of GDP per capita versus the World Bank's
"Distance to Frontier" overall measure of government interference:

The distance to frontier score...shows the distance of each economy to the “frontier,” which represents the best performance observed on each of the indicators across all economies in the Doing Business sample since 2005.

The individual measures are things like

Starting a Business, Dealing with Construction Permits, Getting Electricity, Registering Property, Getting Credit, Protecting Minority Investors, Paying Taxes, Trading Across Borders, Enforcing Contracts, Resolving Insolvency

(I used GDP data for 2013, and distance for 2014. That gave the largest number of countries.)

The US is $52,000 per year and a distance score of 82. China is $7,000 and a score of 63. The diagonal line is an OLS regression fit.

The distance to frontier measure is highly correlated with GDP per capita. It tracks enormous variation in performance, from the abject poverty of $1,000 per year through the US and beyond.

The correlation would be stronger if not for the outliers. In red, Libya and Venezuela are arguably countries with temporarily higher GDP than the quality of their institutions will allow for long. In green, Rwanda and Georgia may have reasons for temporarily low GDP among improving institutions. Cuba and North Korea are missing. Luxembourg, Kuwait, have obvious stories. And I did not weight by population; large countries seem to be closer to the line.

Update: An attempt at nicer graph art. The countries are weighted by population. The dashed line is a weighted least squares fit, weighted by population. China is red, US is blue. Better?

One might dismiss the correlation a bit as reverse causation. But look at North vs. South Korea, East vs. West Germany, and the rise of China and India. It seems bad policies really can do a lot of damage. And the US and UK had pretty good institutions when their GDPs were much lower. (Hall and Jones 1999 control for endogeneity in this sort of regression by using instrumental variables.)

Too much growth commentary, I think, confounds "frontier" with "perfect." The US has good institutions, but not perfect ones. It takes forever to get a building permit in Lybia. It takes 2 years or more to get one in Palo Alto. It could take 10 minutes. We are not completely uncorrupt. Our tax code is not perfect. Property rights in the US are not ironclad. A lawsuit might take 10 years in Egypt. But it still could take 3 years here. (Disclaimer, all made-up numbers.) And so forth.

So, the big question is, just how much greater "level" -- and how much China-like "growth" on the way -- could the US achieve by improving our good but imperfect institutions?

The Distance to Frontier measure is relative to the best country on each dimension in the World Bank sample. So a score of 100 is certainly possible. I labeled that by a hypothetical country, "Frontierland" (FRO) in the graph.

Perhaps we can do better. Even the best countries in the world are not perfect. Let's call the best possible institutions Libertarian Nirvana (LRN). How good could it be? If the US is currently 82, and the union of best current practices 100, let's consider the implications of a 110 guesstimate.

Country	Code	Distance	GDP/N	% > US	20 year growth
China	CHN	61	$7,000
United States	USA	82	$53,000
Frontierland	FRO	100	$163,000	209	5.6
Libertarian Nirvana	LRN	110	$398,000	651	14.8

The table shows China and the US along with my hypothetical new countries. Frontierland generates $163,000 of GDP per capita, 209% better than the US. If it takes 20 years to adjust, that means 5.6% per year compound growth. Libertarian Nirvana generates $398,000 of GDP per capita, 651 percent better than the US, a level effect which if achieved in 20 years generates 14.8% compound annual growth along the way.

These numbers seem big. But there are no black boxes here. You see the graph, I'm just fitting the line.  And China just did achieve nearly 20 years of 14% growth, and a 700% improvement.

In a sense, the numbers are conservative. The US is above the regression line in the graph. By the regression line, our GDP per capita should only be $33,000 per capita. I extrapolated the regression line, not the current state of the US.

Summary: It is surprising that bad policies, bad institutions, bad ease of doing business, can do quite so much damage. Harberger triangles just don't seem to add up to the difference between $1,000  and $53,000 GDP per capita. But the evidence -- especially the basically controlled experiments of the Koreas and Germanys -- is pretty strong.

The converse must therefore also be true. If bad institutions and policies can do so much damage, better ones may also be able to do a lot of good.

This is admittedly simplistic. Growth theory does distinguish between "ideas" produced by the "frontier" country, that are harder to improve, and "misallocation", "development" of more efficiently using existing ideas. As traditional macroeconomics thinks about aggregate demand easily raising GDP until we run in to aggregate supply,  there is a point of superb efficiency beyond which you can't go without more ideas. I don't know where that point is. But uniting the existing best practices around the world in Frontierland is surely a lower bound, and an extra 10 percent doesn't seem horribly implausible.

Lots of other new research suggests that level inefficiencies are sizeable. For example, Chang-Tai Hsieh and Pete Klenow measure misallocation -- the extent to which low productivity plants should contract and high productivity plans should expand, largely by just moving people around (yes, I'm simplifying). They report from this source "Full liberalization, by this calculation, would boost aggregate manufacturing TFP by 86%–115% in China, 100%–128% in India, and 30%–43% in the United States." And this is just from better matches. They're not even talking about policies that raise TFP at all plants, like removing regulatory barriers.

Likewise, Michael Clemens argues that opening borders -- again better matching skills and opportunities -- would roughly double world GDP. That too is (as far as I can tell) based only on "level" calculations, not the "scale" effects of better ideas that growth theory (below) would adduce. But you'd get a lot of "growth" on the way to doubling the level!

Part III. Smith, meet Jones; Growth effects are smaller than you thought

Conversely, it turns out that "growth" effects are vanishing from growth theory. Levels are all we have -- but big levels, that take decades of "transitory" growth to achieve.

The crucial references here are Chad Jones' 2005 "Growth and Ideas" and 1995 "R&D based models of economic growth" and 1999 "Sources of U.S. Economic Growth in a World of Ideas" My discussion will pretty freely plagiarize.

Suppose output is produced using labor \(L_Y\) and a stock of ideas \(A\) by \[ Y = A^\sigma L_Y \] New ideas are likewise produced from labor and old ideas, \[ \dot{A} = \delta L_A A^\phi \] where \(L_A\) is the number of people working on ideas, often (but too narrowly, in my view) called "researchers." To keep it simple, suppose a fraction \(s\) of the labor force works in research, \(L_A= s L\) and that population \(L\) grows at the rate \(n\). The classic Romer, Grossman and Helpman, and Aghion and Howitt models specify \(\phi = 1\). Then we have \[ \frac{\dot{A}}{A} = \delta s L \] and growth in output per capita is \[ g_Y \equiv \frac{\dot{Y}}{Y} -\frac{\dot{L}}{L} = \sigma \delta s L. \] Here you see the new growth theory promise: an increase in the fraction of the population doing research \(s\) can raise the permanent growth rate of output per capita! This is a "growth effect" as opposed to those boring old "level effects" of standard efficiency-improving microeconomics.

But here you also see the fatal flaw pointed out by Jones. The growth rate of output should increase with the level of population. As world population increased from 2 billion in 1927 to 7 billion today, growth should have increased from 2% to 7% per year, per capita. The growth rate of output per capita should itself be growing exponentially! Substituting, we should see \[ g_Y = \sigma \delta s L_0 e^{nt} \] The problem is deep. The model with \(\phi = 1\) gets all sorts of scale effects wrong. Not only has the population increased over the last century, the fraction engaged in R&D has increased dramatically. Integration, by which two economies merge and effectively double their populations, should double their growth rates. Yet frontier growth rates are quite steady, if anything declining since the 1970s.

Jones' solution is simple: How about \(\phi < 1\)? Let's think hard about returns to scale in idea-production

If \(\phi > 0\), then the number of new ideas a researcher invents over a given interval of time is an increasing function of the existing stock of knowledge. We might label this the standing on shoulders effect: the discovery of ideas in the past makes us more effective researchers today. Alternatively, though, one might consider the case where \(\phi < 0\), i.e. where the productivity of research declines as new ideas are discovered. A useful analogy in this case is a fishing pond. If the pond is stocked with only 100 fish, then it may be increasingly difficult to catch each new fish. Similarly, perhaps the most obvious new ideas are discovered first and it gets increasingly difficult to find the next new idea.

Or, maybe \(\phi=0\) is a useful benchmark: each hour of work produces the same number of new ideas. But  \(\phi=1\) is a strange case; each hour of effort produces the same increase in the growth rate of new ideas.

Solving the model for \(\phi \lt 1 \) the idea accumulation equation is \[ \frac{\dot{A}}{A} = \delta s L_0 e^{nt} A^{\phi-1} \] Let's look for a constant growth rate solution \(A_t = A_0e^{g_At}\), \[ g_A= \delta s L_0 e^{nt} A_0^{\phi-1} e^{(\phi-1){g_At}} \] This will only work if the exponents cancel, \[n+(\phi-1)g_A = 0 \] \[g_A = \frac{n}{1-\phi} \] The steady state output per capita growth is then \[ g_Y = \sigma g_A = \frac{\sigma n}{1-\phi}\] This change solves the problem: It's still an endogenous growth model, in which growth is driven by the accumulation of non-rivalrous ideas. There are still externalities, and doing more idea-creation might be a good idea itself. But now the model predicts a sensible steady growth in per-capita income.

The model no longer has "growth effects." Jones:

Changes in research intensity no longer affect the long-run growth rate but, rather, affect the long-run level of income along the balanced-growth path (through transitory effects on growth). Similarly, changes in the size of the population affect the level of income but not its long-run growth rate. Finally, the long-run growth rate

On reflection, this distinction isn't really a big deal. The model behaves smoothly, for any finitely long period of time or data, as \(\phi\) approaches one. The "level" effects get larger, and the period of temporary "growth" in transition dynamics to a new level gets longer. Even a century's worth of steady growth can't easily distinguish between values of \(\phi\) a bit below one, and the limit \(\phi=1\) of permanent growth effects.

This should remind you of the great unit root debate. A model \(y_t = \phi y_{t-1} + \varepsilon_t\) with \( \phi=1\) has a unit root, and shocks have permanent effects. A model with \( \phi < 1\) is stationary, with only transitory responses to shocks. But \(\phi=0.99\) behaves for a century's worth of data almost exactly like \(\phi=1\). So the difference between "permanent" and "transitory", like the difference between "growth" and "level" really is not stark.

So where are we? There is no magic difference between permanent growth effects and one-time level increases. All we have are distortions that change the level of GDP per capita.

The big question remains: how bad are the distortions? Which ones have large effects and which are tolerable small effects? Endogenous growth theory still suggests that distortions which interfere with idea production, including embodiment of new ideas in productivity-raising businesses, will have much larger effects than, say, higher sales taxes on tacos. Just why is the correlation between bad government and bad economies so strong?  My essay just suggested getting rid of all the distortions we could find.

Part IV. Needless politicization 

As I hope this extensive post shows, these questions are not political, and the subject of much deep current research.

Noah chooses to make this political. The quote again,

...I want to focus on one bad argument that Cochrane uses. Most of the so-called growth policies Cochrane and other conservatives propose don't really target growth at all, just short-term efficiency. By pretending that one-shot efficiency boosts will increase long-term sustainable growth, Cochrane effectively executes a bait-and-switch.

"Bad argument" may just mean that Noah is unaware of Jones' and related work. "Cochrane and other conservatives" is telling. Look at my profile. You don't find that word.  Open borders, drug legalization, and so forth are not well described as "conservative." I emailed Noah last time he used the word, so his inaccuracy is intentional.

"Pretending" "bait-and-switch" are unsubstantiated charges of intentional deception. And to call permanent increases in efficiency "short-term" is itself a bit of a stretch.

Even the New York Times, and many respectable "liberal" economists use the words "growth" to describe what has happened in China and to describe what "short-term" level effects could do for the US. From the Hilary Clinton Campaign website,

Hillary understands that in order to raise incomes, we need strong growth, fair growth, and long-term growth. And she has a plan to get us there.

Strong growth
Provide tax relief for families. Hillary will cut taxes for hard-working families to increase their take-home pay...

Unleash small business growth. ..She’s put forward a small-business agenda to expand access to capital, provide tax relief, cut red tape, and help small businesses bring their goods to new markets.

...Hillary’s New College Compact will invest $350 billion so that students do not have to borrow to pay tuition at a public college in their state. ..

Boost public investment in infrastructure and scientific research. ... Hillary has called for a national infrastructure bank... She will call for reform that closes corporate tax loopholes and drives investment here, in the U.S. And she would increase funding for scientific research at agencies like the National Institutes of Health and the National Science Foundation.

Lift up participation in the workforce—especially for women...

No, that's not my essay, nor the Bush 4% growth website. There is the word "growth," all over the place, but only the scientific research might count as raising growth in the Noah Smith classificiation. Yet he does not include her among  "conservative" economists displaying "bad arguments," "pretending," or "bait and switching."

Enough. Shoehorning interesting economics into partisan political "conservative" vs. "liberal" categories is not a useful way to understand the issues here.


 

Zoning and inequality

I am always pleased when economists normally thought of on different ends of the political spectrum come to the same conclusions. So it is with zoning laws; traditionally a target of free-market and libertarian thinkers. Now joined by Jason Furman, Obama administration CEA chair. From a recent speech,

..excessive or unnecessary land use or zoning regulations... impede mobility and thus contribute to rising inequality and declining productivity growth.

How?

...zoning regulations and other local barriers to housing development allow a small number of individuals to capture the economic benefits of living in a community, thus limiting diversity and mobility. ...

Zoning and other land use regulations, by restricting the supply of housing and so increasing its cost, may make it difficult for individuals to move to areas with better-paying jobs and higher-quality schools. Barriers to geographic mobility reduce the productive use of our resources and entrench economic inequality.

and later

High-productivity cities—like Boston and San Francisco—have higher-income jobs relative to low-productivity cities. Normally, these higher wages would encourage workers to move to these high-productivity cities—a dynamic that brings more resources to productive areas of the country, allows workers in low-productivity areas to earn more, improves job matches and competes away any above-market wages (another type of economic rents) in the high-productivity cities. But when zoning restricts the supply of housing and renders housing more expensive—even relative to the higher wages in the high productivity cities—then workers are less able to move, particularly those who are low income to begin with and who would benefit most from moving. As a result, existing income inequality across cities remains entrenched and may even be exacerbated, while productivity does not grow as fast it normally would.

Moreover,

zoning restrictions are not distributed randomly but instead tend to be more prevalent in high-income communities... This fact, coupled with the income gains for the rich over the past four decades, have worked toward pricing middle- and lower-income families out of the communities with the best schools.

The speech reviews a good deal of academic evidence. For example:

An indirect way to gauge the impact of land use restrictions and other supply constraints for buildable land, including the local topography, is to compare the sales price of houses to the cost of materials and labor to build the structure. ... As Figure 1 from Gyourko and Molloy (2015) shows, the gap between real house prices and construction costs has grown over time,

The differences across places are large and growing:

Gyourko et al. (2013) shows how the real home price distribution has widened over the last several decades, coinciding with increased variation in land use restrictions....

The answer to lots of people who want to live in the same space, especially urban environments, is to build up. Indeed,

A variety of changes...have led to growing demand for multifamily, rental, shared occupancy, and home modifications.

but alas,

multi-family housing units are ... most often the target of regulation...

Another limit: In most places the ironclad rule is one family per lot, meaning one structure per lot. No granny flats. Then granny has to move in to a nursing home, paid for by medicare or medicaid.

As the Baby Boomer generation ages into retirement, many more elderly Americans will require modifications to the homes they currently live in or may opt for shared occupancy with another family, often their own. Both of these practices would benefit from changes in zoning policies in some areas of the country so as to make home modification and shared occupancy feasible for a larger number of seniors

"The consequences of zoning are much broader and include:"

• Greater environmental damage: when strict zoning policies cap a city’s density, they ensure that the city’s residents must on average occupy more land than they otherwise would and travel greater distances to and from work as well, both of which increase carbon production, all else equal (Glaeser, 2011)

To say nothing of horrible traffic, need for more roads, and all the other pollutants as well as carbon, plus pointless waste of time.

All of this is familiar where I live in Palo Alto. Like most places in the bay area, my city council is agonizingly green, progressive, and  anti-inequality Yet it presides over a rigid zoning system that produces exactly the opposite result: poor people are excluded, young techies who want to live in apartments commute from San Francisco.  Granny flats are forbidden. Horrible traffic flows by single family houses on large lots, costing two to three million dollars and more just for the land.

The speech was nice until the "solutions" part, for example,

First, the Department of Housing and Urban Development (HUD) instituted substantially greater transparency through its Affirmatively Furthering Fair Housing (AFFH) rule,...

I didn't make that one up. Daffy Duck should apply to head this initiative.

The Fair Housing Act of 1968 required any group receiving federal housing funds, as well as federal agencies overseeing such programs, to actively work toward increasing fair housing and equal opportunity. ...the new HUD rule, finalized this year, will give communities new tools to quantify the remaining inequities in local housing markets and achieve greater clarity in setting goals for the future. As a central part of this initiative, HUD will provide publicly open data and mapping tools to community members and local leaders, so that they can assess conditions in their housing markets.

I'm not holding my breath.  Palo Alto's strict zoning did not occur  because nobody has zillow and google maps and so can't figure out what's going on. And they have a slew of programs that are "actively" "working toward" "increasing fair housing."

Oh and of course more cheap credit. Hmm, how can that go wrong

The Multifamily Risk-Sharing Mortgage program, a partnership between HUD and the Treasury,...

This is not a criticism of Jason. He is, after all, CEA chair, so his job is to finish speeches with what great stuff the Administration is doing. That the result is almost a parody of ineffective nanny-state bureaucratic paper shuffling is not his fault.

And his silence on "affordable housing" mandates is doubly praiseworthy. One might have expected an Administration speech on this topic to cheer that morass. Silence is, sometimes, golden.

So let's cheer the common ground: Free markets have strong forces that reduce inequality.  Much inequality is the result of restrictions -- many state and local, and many undertaken by the most well-meaning people, unfortunately unburdened by a sense of the proper limitations of government action and the value of property rights.

Markets also have forces to get around heavy restrictions. The golden goose can leave; to LA or to Austin TX.

Fixed-income comments

A month ago,  I attended the SF Fed/Bank of Canada conference on fixed income. I had the chance to comment on Michael Bauer and Jim Hamilton's "Robust Bond Risk Premia.” My comments here.

As usual when faced with a really nice paper, I used most of my discussion time to survey the field and give my views on current facts and challenges, which is why my comments might be interesting to blog readers.

Some highlights: I reran regressions of bond returns in the style of Joslin, Priebsch, and Singleton, forecasting returns with the first  three principal components of yields, and growth and inflation. Here are the results:

First row: the slope factor forecasts returns with the usual 18% R2. Second row: Inflation and growth do not forecast returns at all. Third row: in combination with the first three principal components, the R2 rises to 0.26 by adding growth and inflation. Inflation now becomes a significant predictor, and its presence raises the coefficient and t statistic on the level and slope factors. This is an interesting OLS puzzle.

If you plot inflation, you see it is mostly a downward trend in this sample period. So, it occurred to me, what if I used a trend instead? The last two rows of the table add a trend. Indeed, with the trend, growth and inflation disappear. In fact, we can drop growth, inflation, and the third principal component, forecast returns with amazing t statistics and an R2 of 0.62, which must be an all time high.

What's going on here? Is the trend just picking up a trend in returns? Here is a plot of expected returns (a + b x_t) and actual returns (r_t+1) for four of the models in Table 1.

The point: the trend is not just picking up a trend in returns. And the 62% R2 is not a pathology of one big outlier, a trend, or something else.  Instead, the trend serves to filter the level factor, and to a lesser extent the slope factor. The message is not "a trend seems to forecast a trend in returns" but "the cyclical variations picked up by detrended level and slope factors seem to forecast returns."

So what does this all mean? Is this proof growth and inflation don't work because they are driven out by trends? No, the trend is after all a proxy for something economic.  (This is roughly Cieslak and Povala's point, who get over 50% R2 in a longer sample with smoothed inflation.) Is this all a big econometric goof, because serially correlated right hand variables are a mistake? No, and my comments go into this at length. Bauer and Hamilton's point is this econometric problem, but they don't get close to t statistics of 10. OLS cares about serial correlation of the residuals, but not of the right hand variables.  In the end, it's a interpretation issue, not an econometric one.

The biggest point of my comments: It's time to get past forecasting returns one at a time. Classic finance got past "is AT&T a good investment?" in the 1960s, after all, and moved on to portfolios and covariances. Here, the more interesting outstanding question is the factor structure of expected returns  -- do expected returns on all bonds move together over time? -- and the risk premium question -- what are the factors, covariance with which drives that variation in expected returns?

To this question, perhaps we should take a lesson from the VAR literature of the 1980s, and stop worrying tremendously about equation by equation parsimony in forecasting. Instead, accept that forecasting regressions will be a somewhat overfit, but put our attention in the cross-equation structure of forecasts.

To be specific, the next graph shows the expected returns of bonds with maturity 1-10 years -- the fitted value of each bond's return-forecasting regression. The graph is clear: these are not 10 different series. The expected returns on all bonds move in lockstep. There is a strong one-factor structure in expected returns.

Finance 101: Expected return = covariance of return with something, times risk premium. What's that something? In this context, the bonds whose expected return moves most over time should have returns that covary proportionally more with some factor. What is it? The next picture plots how much each bond moves with the common factor shown in Figure 11 against the covariance of the 10 bond returns with innovations in the bond principal components, growth, and inflation.

Again, the pattern is pretty clear: time-varying expected return corresponds completely with covariances with the level factor. Covariances with the other factors are all about zero, and do not vary in the same way as expected returns.

In sum, this simple exploration shows a pretty strong pattern: 1) There is a strong one-factor model of expected returns -- expected returns on bonds of all maturity move together over time. 2) There is a strong one-factor model of risk: the single time-varying risk premium in all bonds corresponds to covariance with a single factor, innovations to the level of interest rates.

This is all very simplified of course. The point: This kind of characterization of the joint behavior of bonds of various maturities -- and later of bonds, stocks, and foreign exchange -- seems like a more interesting unanswered question than the precise identity of forecasting variables for each security, taken in isolation.

These points are a bit of a rehash of older papers, Decomposing the yield curve and more generally  Discount Rates. But they are also an extension --- the "Decomposing the yield curve" point holds using the JPS forecasters and factors, and updated data.  This kind of inquiry needs a lot more work.

A wise comment

Scott Sumner passes on a wise comment from his blog:

...the main problem in America is that the public, including its highly educated members, is social-scientifically ignorant. Most people I talk to about policy do not even realize that there is anything non-trivial about policy analysis. They want the government to make sure that four phases of rigorously designed RCTs be performed before drugs are made available to the public, for fear of unintended consequences of intervening on a complex system like the human body, yet they think they understand the consequences of highly complex interventions on human societies by introspection alone. Not only do they think they understand the consequences of alternative policy choices, but they're so confident that their understanding is right and that its truth is so obvious that the only explanation for disagreement is evil intentions.  

When I point out that on virtually every policy issue, at least somewhat compelling arguments for many conflicting points of view have been made by relevant experts, people usually react in disbelief or denial, or immediately retreat to questioning the motives of these experts ("of course they say that, they're on the payroll of Big Business" or whatever). These patterns of speech and behavior are uniformly distributed across the political spectrum, even if intelligence and knowledge of well-established facts is not. Even many experts in particular areas of social science evince no awareness of the lack of expert consensus on almost anything in their field, and give the impression of unanimity to an unknowing public.

(Emphasis in the original.) The rush to bulverism (evil intentions or corruption of people who disagree) is particularly noticeable in economic commentary.  Uncertainty about policy is especially strong in macroeconomics and finance.  That doesn't mean anything goes. Many arguments do violate basic budget constraints or suffer other obvious logical flaws.

How do you know economists have a sense of humor? We use decimal points.

Hounded out of business II

Nathaniel Popper at the New York Times Dealbook, writes "Dream of New Kind of Credit Union Is Extinguished by Bureaucracy" It's a worthy addition to the series of anecdotes on how regulation, especially discretionary actions of regulators, are killing investment and businesses.

Again, we collect anecdotes as a challenge to measurement. There is no data series on numbers of businesses driven away by regulation. Yet.

This is a good anecdote, as it illustrates a too little reported underbelly of financial regulation.

Mr. Kahle saw how hard it was for the employees at his firm to obtain loans, and more broadly, how the existing financial system had helped contribute to the financial crisis. He thought he could do things differently, and he aimed to prove it when he began applying to open a credit union in early 2011.

Since then, the credit union has faced a barrage of regulatory audits and limitations on its operations, ...Now, Mr. Kahle is giving up on his dream of creating a new kind of bank, ...

...the troubles faced by his Internet Archive Federal Credit Union point to how difficult it can be to try out anything new in the heavily regulated industry.
After an 18-month application process, regulators let the Internet Archive Federal Credit Union open in 2012, but with restrictions that did not allow it to offer basic banking products, such as debit cards and online banking.

Mr. Modell said that during the 18-month application process, he and Mr. Kahle made 4,756 changes to their application and made it through only because of Mr. Kahle’s wealth.  “I could afford to say yes at every turn — every time they made some weird demand,” Mr. Kahle said. 

When they did get their charter from the N.C.U.A. in August 2012 — the first new credit union chartered that year — the Internet Archive Federal Credit Union was limited by the regulators to loans of $5,000 or less, and it could generally serve only people in a small area around New Brunswick, N.J., where the credit union was located.

It's a wonder that the US is still only in the mid 40s on the world bank's list of how hard it is to start a new business.  But just getting going, with restrictions that make profitability essentially impossible, is only the beginning.

it [the credit union] has faced a steady stream of official exams since: 11 in 14 months. In August, the credit union, by its own count, spent 187 hours dealing with regulators and only 61 hours dealing with customers.

The credit union’s other ideas for expansion were also shot down. In 2014, the Internet Archive Federal Credit Union tried to team up with an organization for migrant workers, the Farmworker Support Committee, to offer bank accounts and cheaper money transfers, but the idea was eventually rejected by an N.C.U.A. examiner.

And when the regulators turn against you, they know how to turn the screws:

Mr. Modell and Mr. Kahle said the red flags raised by the N.C.U.A. examiners had been over small discrepancies and record-keeping issues — and often turned out to be factually wrong.

“None of the compliance issues listed in the report were correct,” the credit union wrote in an appeal sent to the N.C.U.A. in May, after the agency lowered the credit union’s regulatory rating.

The N.C.U.A. sent its examiners on an increasingly frequent basis and requested more and more monthly reports from Mr. Modell... By mid-2014, the credit union had made less than $50,000 in loans and Mr. Kahle suggested to Mr. Modell that it was time to give up

And this business seems pretty much a poster child of benevolent capitalism:

“The original vision of this thing — of helping nonprofit workers, or helping the poor — they will not allow it,” Mr. Kahle said.

Given the bad press payday lenders get, this is doubly sad. The quantifiable result:

the number of credit unions in the United States has been shrinking each year since the crisis. There are around 6,300 credit unions, down from 7,000 in 2012 and 8,400 in 2007.

The larger backdrop would be amusing if it were not tragic. While the monetary policy part of the Fed has wanted stimulus and more lending, the regulatory apparatus has apparently been busy making sure banks don't lend, at least to anyone who needs the money, new banks don't start, and financial innovations don't emerge.

Update: LabMD CEO Michael J. Dougherty has a blog and a book.

Spot insurance markets

Obamacare/ ACA was in the news last week. Some relevant summaries, and comment below.

United Health pulling out of the Obamacare exchange market

UnitedHealth reported one problem after another: An expensive risk pool that lacks the younger and healthier consumers who are supposed to buy overpriced plans to cross-subsidize everyone else....People join the exchanges before they incur large medical expenses—insurers are required under ObamaCare to cover anyone who applies—and then drop out after they receive care. The collapse of the ObamaCare co-ops is recoiling through the market.

... Commercial insurers are being displaced by Medicaid managed-care HMOs, with their ultra-narrow physician networks and closed drug formularies.

From the WSJ blog,

...Health plans say they have had more sick people, and fewer healthy people, sign up under the new rules than they need to keep prices stable. ...It’s also cited as a factor in some insurers’ decisions to withdraw products from the market or offer more limited choices of providers this year. Health Care Service Corp., which owns Blue Cross and Blue Shield plans in five states, already has pulled out in selling through HealthCare.gov in New Mexico, and yanked its preferred-provider organization offerings in Texas.

From Rising rates pose challenge to health law

Federal officials are pushing people to evaluate their options and consider switching plans to try to keep costs in check, in a message regularly summarized as “shop and save.”

In about half of the states using HealthCare.gov, people in popular plans can pay lower premiums in 2016 than they did in 2015—as long as they are willing to switch to a plan with a different insurer, usually with a narrower network of doctors and a higher deductible. 

A story:

Kimono England...said... Their health plan’s decision to withdraw its “preferred provider organization” product this year tipped her over the edge.

She said she now has only a narrow provider-network option that doesn’t include her local doctors,...she decided to enroll in a Christian health-care sharing ministry, in which members agree to pay each other’s health bills... since the ministry won’t pay for an expensive specialty shot her husband needs four times a year they are thinking of buying a health plan just to cover him.

The move by the England family would mean that five people with relatively low medical costs exit the insurance risk pool, and one person with large expenses remains—bad news for the insurance industry.

Also,  Mary Kissel interview of Holman Jenkins (video)

Comments:

Let's beyond the standard headlines -- "Millions more covered!" "But they're all medicaid or high subsidy!" (For example here.) "Premiums going up!" "Not if you shop!" and so forth.

Health "insurance" seems to be moving to a spot market, in which large numbers of people change plans, sign up, or leave every year, and in which large numbers of companies change their plans and coverage every year.

The churn on the individual side and its spiraling costs was a predictable (and widely predicted) response to the ACA, which addressed preexisting conditions by mandating insurers to cover anyone at the same price. The joke around the passage of the ACA was that health insurance would consist of a cell phone, which you use to buy coverage on the way to the hospital.

Yes, open enrollment is only once a year, but it's not really a constraint. Most conditions involve years of care, and you can wait six months to ramp up big expenses. A binding non-insurance penalty close to the cost of insurance was never going to pass.

Moreover, the problem is not so much insurance vs. no insurance, it's the right to move around between plans. Buy a bronze high deductible policy one year. If you get sick, move to a gold low deductible big network policy the next year.

The tragedy here is what was lost. Yes, individual insurance had big problems. But before the ACA, there were millions of people who bought insurance when they were healthy; that paid guaranteed-renewable premiums in a large stable health insurance companies, so that when they got sick, they would still have good affordable health insurance. Sure, it didn't work for people who moved across state lines, who got jobs with employer-provided group plans, and many suffered various snafus. But for many self-employed people and small business owners outside the big company - big government nexus, it actually worked ok.

Those relationships are all gone now. If ever we do move back to long-lasting, individual insurance, that you buy when healthy so that it covers you when sick, the millions of people who did the right thing and bought in to the system are now gone.

It's more surprising, at least to me, that annual chaos is breaking out on both sides.  Plans are discontinued, companies leave the market, coops come and go bankrupt, networks change, and many of us have the pleasure of annually sorting through health insurance policies, trying to figure out which ones cover the doctors, hospitals, and medications we are using or might need next year, all likely to do it again in the next year.

Our "federal officials" are not only not bemoaning this chaos -- they're encouraging it! "Shop and save." Shop because your plan got canceled, they changed your network, they vastly raised your premiums, and so forth. Save because they won't pay your claims.

I guess Americans need something to do between Thanksgiving and New Years. Together with shopping for cell phone contracts, cable and internet bundles, and figuring out our frequent flyer programs, this should keep us all plenty busy. Winter in the Republic of Paperwork.

Will the supply churn continue? One view of this is simply that companies need time to adapt. They made optimistic assumptions about their pools, find they're losing money and have to adjust. In time, we will again see stable offerings by stable companies.

Maybe, but I doubt it. If people keep playing games, moving to high cost policies when they get sick, health insurance for those of us not getting subsidies will be astronomically expensive. It ceases being insurance.

A different view is that the supply churn is the industry's way of solving the problem. By changing networks and coverage each year, by canceling policies frequently, by companies forming, dissolving, entering and leaving markets,  they keep us on our toes. A stable wide network plan with reasonable cost will attract too many sick people. So, the answer is, keep it unstable.  The same kind of price discrimination by complexity that pervades airlines, cell phones, and credit card contracts, might pull in healthy people who don't have time to spend three weeks a year finding out what doctors are covered by what plan.

Related, I suspect the industry is finding a way to segment the market. There are really four separate health insurance systems: 1) Expanded Medicaid. 2) Highly subsidized premiums based on income. 3) Non-subsidized individual policies. 4) Employer provided insurance for high income people with full time jobs. The first three were supposed to be parts of the same market, but it's fragmenting, with medicaid and subsidized plans giving out low cost low quality care.

This is not a grand conspiracy theory. Like most outcomes in economics, it's not obvious any of the participants understand what's going on, and an evolutionary process settles on outcomes that "work" in the regulatory environment and don't lose catastrophic amounts of money.

Health insurance really does not work as a spot market, of course.

The answer? For those who haven't been reading this blog very long (collections here and here), it is straightforward: Lifelong, deregulated, guaranteed-renewable, individual insurance, bought when you're healthy, carried along from state to state and job to job, with employers contributing premiums rather than setting up group plans. Deregulation of supply, so that for most procedures you can just pay cash and not be rooked by made up prices.

Early Fisherism

John Taylor has an interesting blog post with a great title, "Staggering Neo-Fisherian Ideas and Staggered Contracts." John goes back to a paper he wrote in 1982 for the Jackson Hole conference, on the issue of that time, how to lower inflation. He presented simulations of a model with staggered wage setting, which I reproduce below.

So as far back as 1982, here is a model in which lower interest rates correspond with lower inflation, both in the short run and the long run.  John's model has money in it, so the mechanics are a pre-announced monetary contraction.

Sargent's famous "Ends of four big inflations"  tells an even more radical story.

On solving the governments' fiscal problems, inflation ends instantly. Sargent and Wallace alas do not have interest rate data, but from the inflation data it's pretty plausible that interest rates fell like a stone when the fiscal reforms are implemented. They have money stock measures -- and the ends of these inflations did not have any monetary tightening at all. Money stock measures all expanded substantially as inflation ended.

I've been having an interesting back and forth with a correspondent about Milton Friedman's views. In  "Do higher interest rates raise or lower inflation?" I quoted Friedman's 1968 address, and said he believed that an interest rate peg is unstable. Not so fast says my correspondent, and passed on a lovely memo written by Milton Friedman -- better still once owned by Anna Schwartz. (Yes I checked that it's ok to post this)

and later

As I read this quote, Friedman emphasizes that lower interest rates come only with lower inflation in the long run, so there is some Fishery theory here. But in the short run, if the Fed lowers money growth, then interest rates will first rise but then decline as inflation declines. So the implied short run relationship goes the other way.

As I read it, then, Friedman says it is possible to target interest rates. But to do so requires particularly active money growth policy to offset the instability that would result from simply announcing a fixed interest rate.

That leads to a very interesting question, how the same interest rate path could be supported by different money growth paths.