Food for Thought

The fear should not be that markets are irrational, but rather that markets are perfectly rational, yet chronically unstable.

Fragile Finance - A Look at Macroprudential Regulation

Modern finance is fragile, so what should we do?

Last year, Olivier Jean Blanchard wrote a "Seoul paper" on macro and financial issues, calling for a rethinking of the way macroeconomic policy is conducted.  In the old approach:

We thought of monetary policy as having one target, inflation, and one instrument, the policy rate. So long as inflation was stable, the output gap was likely to be small and stable and monetary policy did its job. We thought of fiscal policy as playing a secondary role, with political constraints sharply limiting its de facto usefulness. And we thought of financial regulation as mostly outside the macroeconomic policy framework.

This shift was significant, as previous financial regulation was primarily concerned with the micro picture.  But with the realization that there are serious systemic risks that permeate markets, interest has shifted to trying to look at financial regulation from a macro perspective.  Since then, macroprudential policy has been integrated into the G-20 framework and there is a large and growing literature on how to implement it.

This is an especially thorny issue because we're not quite sure what we're looking at.  Unlike monetary policy, macroprudential policy does not have the equivalent of a DSGE for analysis.  Moreover, what measures of risk should be used?  Capital ratios?  Loan-to-value ratio?  Does one follow a rule based approach or allow for more discretion?  This has been the fundamental problem with more formal analyses of macroprudential policy, as "both theoretical and empirical work linking the financial sector to the macroeconomy is far from a stage where it can be operationalized and used for risk analysis and policy simulations."  There simply isn't enough data to thoroughly analyze macroprudential effects.

A recent study has suggested that certain macroprudential policies, such as caps on loan to value ratios or dynamic provisioning have been effective in reducing the procyclicality of credit growth.  As debt is very fragile and promotes unpredictable complexity, any way to reduce its use in times of economic growth is good to hear.  Ideally, debt can be limited to digging oneself out of holes, and not trying to get to extreme heights of economic euphoria.

Note that this kind of regression analysis, although it is dealing with debt, which increases the probability of black swans, is still appropriate because it's looking at the growth of debt versus the growth of GDP.  Models aren't dependent on the exact magnitude of these parameters, rather we use changes in the parameters to determine if a given policy is appropriate.

However, this macroprudential approach is not without concerns.  It is not sufficient, and safety net policies will still be necessary.  Additionally, capital controls in and of themselves may have severe harm for long run economic growth.  As we're dealing with systemic risk, it may be that the regulations to limit systemic risk only ends up replicating it elsewhere, in industries that are not as easily regulated.  This would be even more worrisome, as previously known risks go on to evolve into unknown unknowns: the realm of Extremistan.

In spite of this, I feel that macroprudential policy will be increasingly important for the future, especially if we move to a more nominally stable NGDP targeting regime.  When aggregate demand is stabilized, the largest welfare costs will arise from aggregate supply shocks.  And as the financial sector is one of the critical industries for system wide credit, the question of how to regulate finance is fundamentally an aggregate supply issue.  In the market monetarist framework of Scott Sumners, macroprudential policy will be critical for shaping the composition of NGDP growth in a post market monetarist world.  This will be also very important for developing nations, as they are disproportionately harmed by large swings in real growth.  A massive drop in export and natural resource demand can let their capital stock deteriorate, damaging their prospects for development.  This move towards "increasing transaction costs" in order to improve global finance echoes Dani Rodrik's arguments for a more sustainable version of global trade.  Much as a better trade does not equal more integration, better finance may not entail more transnational capital flows.  And without stable and robust finance, there shall be neither stable nor robust growth.  That forms the basis of macroprudential regulation.

Correlations Across Time: How Stable are the Curves?

What is the Philips curve, and how do we know it's there?   It was originally discovered by Irving Fisher in 1926 when he noted the negative correlation between inflation and unemployment.  Of course, he was not the first to realize this connection between prices and employment, as Hume commented on this exact issue almost 200 years before:

In my opinion, it is only in the interval or intermediate situation, between the acquisition of money and the rise in prices, that the increasing quantity of gold or silver is favourable to industry. . . . The farmer or gardener, finding that their commodities are taken off apply themselves with alacrity to the raising of more. . . . It is easy to trace the money in its progress through the whole commonwealth; where we shall find that it must first quicken the diligence of every individual, before it increases the price of labour

For this reason, Milton Friedman often said that modern macroeconomics has made it just one derivative past Hume.  Instead of just focusing on the first derivative and changes in the price level, we now look at the second derivative and changes in the inflation rate.

Robert Hall took this one step further in his 1986 exposition on efficient monetary policy and, instead of looking at one more derivative, looked at one more parameter.  Instead of just looking at the levels of unemployment and inflation, he theorized on the relationship between the volatility of the two variables.  He hypothesized the existence of an efficient policy frontier, a trade-off between price stability and unemployment stability that would prevent both variables from settling down in the face of periodic random shocks.

But have either of these correlations held throughout time?  The Philip's curve worked originally very well in the 1960's to 1980's, but then broke down as stagflation struck and expected inflation shifted the "stable" Philip's curve.  Thus, there seems to be a severe issue with measuring the Philip's curve; where should one start and end the observation window?  The analysis can easily become utterly meaningless, as:

To see how meaningless correlation can be outside of Mediocristan, take a historical series involving two variables that are patently from Ex­ tremistan, such as the bond and the stock markets, or two securities prices, or two variables like, say, changes in book sales of children's books in the United States, and fertilizer production in China; or real-estate prices in New York City and returns of the Mongolian stock market. Measure correlation between the pairs of variables in different subperiods, say, for 1994, 1995, 1996, etc. The correlation measure will be likely to ex­hibit severe instability; it will depend on the period for which it was com­puted. Yet people talk about correlation as if it were something real, making it tangible, investing it with a physical property, reifying it. The same illusion of concreteness affects what we call "standard" deviations. Take any series of historical prices or values. Break it up into subsegments and measure its "standard" deviation. Surprised? Every sample will yield a different "standard" deviation. Then why do people talk about standard deviations? Go figure. 

Note here that, as with the narrative fallacy, when you look at past data and compute one single correlation or standard deviation, you do not notice such instability (Taleb, The Black Swan, my emphasis).

So, in this post, I want to look at the time series data and see how the correlation evolves over time.  This is important for both the Philip's curve and the efficient policy frontier, as one can see if either of those relationships actually holds across all time periods.

Monthly CPI and unemployment data are obtained from the St. Louis Federal Reserve website, and variabilities for each variable are measured by the standard deviation of the past year's worth of observations.  Correlations were then calculated in five year windows, such that a correlation coefficient on month t is the correlation between the variables of interest in months t-59 to t.  As the concept of a standard deviation is a bit abstract and not well understood, I took the logarithms of the standard deviations, to allow an explanation in terms of percentage increases in one variable leading to percent increases in another.

Below is a tool to gain a qualitative understanding of the evolution of the correlations.  Red denotes high numbers (strong positive correlation), while green denotes low numbers (strong negative correlation).  The black lines mark every 10 years to give a sense of scale in the colorful "time series".

As expected, the correlation coefficients fluctuated throughout history. For the Philips curve, old Keynesian theory would predict a negative correlation.  However, if there's a supply shock, both inflation and unemployment move in the same direction.  This makes sense as the two major supply shocks in recent history were the negative aggregate supply oil shock in the mid 1980's, as well as the positive aggregate supply shock in the 1990's.

With this in mind, we see that the Philip's curve relationship was actually quite stable up until the 1990's.  Although the oil price shock did force the correlation positive for a short period, it quickly reverted to a negative value.  However, from about 1990 on, the correlation between unemployment and inflation became consistently, if only weakly, positive.  Since both inflation and unemployment rose in that time period, this is another piece of evidence that suggests much of the aggregate supply gains in the 1990's were steadily reversed in the 2000's.

However, the relationship between the two volatilities was not as clear cut.  A log-log regression of the unemployment volatility versus the inflation volatility over the entire 60 years yields a slope of 0.44, with a 95% confidence interval between 0.346 and 0.540, suggesting that 1% increase in inflation volatility resulted in about a 0.44% increase in unemployment volatility.  Yet this general correlation masks the variance.  Around the 1980's and 2010, the correlation was incredibly positive, while in the 1970's and 2000's the correlation is very negative.

From this, general conclusions can be made.  First, policy is not efficient.  Even if there were an efficient policy frontier, we're not on it.  The many zones of positive correlation indicate that there's much more monetary policy can do to limit volatility in the two variables.  Second, that there are interesting things going on with transmission mechanisms that would cause uncertain inflation to translate to uncertain output.  Third, if there are severe risks to inflation volatility, it may be in our interest to lower unemployment volatility as well.  Moderating the relationship between these two variables may become one of the biggest benefits of NGDP targeting, as uncertainty along the Philips curve may cause movement towards higher levels of volatility.

The "Efficient-as-you-get" Market Hypothesis - Limits to Knowledge

Quantum Entanglement in markets: A new look at the EMH

The concept of tail risk in Chinese housing markets made me think more about the efficient market hypothesis.  If there truly are events that lie beyond the public's ability to predict, how can markets be truly efficient?

No doubt, the strong form of the EMH, which states that anything that is possibly known about an asset is incorporated into its price, seems unreasonable.  Given cognitive limits, it's doubtful that market participants could fully incorporate every shred of information into complex models that, in many instances, are necessarily non-linear and unpredictable.  Even the Weak and Semi-Strong versions have been called into question in light of persistent instances of momentum.  Market bubbles have also sometimes been used as reason to reject the EMH, saying that the fundamental decoupling of prices and fundamental value showing how markets can never be truly efficient.  And then there are the legions of behavioral economists argue that biases such as overconfidence and hyperbolic discounting prove that there are gaps in individual decision making.

These inefficiencies have been thoroughly discussed, but I think they miss another dimension: the fundamental unknowability of future events.  Prediction markets, in theory, incorporate all possible information into their judgments, but they are still contingent on what public information is available.  Also, just because prediction markets are more accurate than other forecasts, it doesn't mean they're sufficiently accurate to support highly leveraged and fragile investments.  The Black Swan events that shake the foundations of markets are, by definition, unknown unknowns.  These Black Swans can be even more pernicious because the information that could predict them may be out there.  However, the market may not be able to piece the information together, whether due to bounded rationality or the fact that certain information is not always public.  In the end, it may be these rogue investments that weren't obvious that makes much of the other information observed irrelevant.  Thus, this new formulation of the EMH differs from the other formulations by rejecting the idea that all information is incorporated.  Not all of it is, and if it is it might not be truly understood.

But what impact does this have on the practical application of the EMH?  Are there any meaningful practical implications that can be drawn from the fallibility of information inefficient markets?  On this issue, I like to view it like attempts to use quantum entanglement to transfer messages over long distances.  The theory of quantum entanglement offers a way to transfer a signal faster than the speed of light, but the information transferred is random.  As a result, no net, low entropy information can be communicated at faster than the speed of light .  As applied to markets, the EMH would say that even if prices deviate from their fundamental value, the deviation does not convey any information because there's no apriori way to know what the fundamental value is. Even if there's information that's not incorporated into the price, there's no way for you to know what the new information is, or how that new information should interact with the accumulated knowledge of all the other investors.  You don't know what the price is telling you.  The errors are unknowable ex-ante, and only obvious ex-post.

This model incorporates several aspects of the EMH and criticisms thereof very nicely.  First, it still maintains that there's no point in playing the market.  Even if prices don't reflect all information, it's impossible for you to consistently pluck reality out, save with enough time and invisible hands.  It's pointless to get good at trading, because the excess returns will always be gobbled up by firms who are smarter and computers that are faster.  When companies trade on the basis of milliseconds, do you really think your human thinking will get you anywhere?  This makes advertisements for the Online Trading Academy particularly laughable.  Pity in all those finance mini-lessons they don't teach the foundation of financial theory.

Second, crises don't disprove this formulation of the EMH.  "Seismic" price adjustments don't occur in any predictable manner, which means mispricings are random.  The price adjustment may not have even been the result of a new discovery of information, it could have just arisen from a new conceptualization of the already available information.  Again, there's no way to predict from the past.  This would then lead to Scott Sumner's disdain for tighter subprime regulation as a possible solution to 2006 housing bubble (my emphasis):

One can look at the sub-prime fiasco from a theoretical perspective, or a empirical perspective, but what one cannot do is compare an ideal regulatory scheme to actual banking practices.  No one doubts that we would be better off if we could go back in time and install a regulation banning sub-prime mortgages in 2004.  But if we had that ability, the bankers would have also known what was coming, and would never had made the loans in the first place.

Hindsight is 20/20; the efficiency of markets is a ex-ante postulate, not an ex-post proof.

Third, informational criticisms based on computer science seem to be particularly non-sensical.  This random information argument is not "perfect markets everywhere", but rather "ok markets everywhere".  Additionally, this new interpretation of the EMH actually focuses on limited rationality that is the result of algorithms that can only run in polynomial time.  But even if markets aren't efficient, there's no way for you to exploit it.  If there are more efficient allocations, your central planning algorithms can't target them on a case-by-case basis.

Fourth, while we can't prepare for any individual crisis, we can still take stock of certain warning signs.  With regard to these warning signs, I'm talking about payoffs, and not probabilities.  There are certain limits to our conception of small probabilities, but it's not infeasible to consider the issue of impact.  On this issue, I think specifically about the impact of debt.  Debt financed cycles seem to be particularly problematic, as they magnify the impact of the crisis.  I have no idea what's the fundamental stable value for debt, but I can definitely be scared of the deleveraging effects of debt.  The fragility of the financial system becomes really apparent when small shocks can propagate themselves through chains of defaults.

As a result, policy should be geared towards moderating these aggregates, such as debt, that give rise to fragility.  These may not allow policy makers to avoid crises, but the reduction in fragility should have substantial benefit in reducing the severity of crises.  NGDP targeting can even have a powerful role in this regard, as given enough crises, the high leverage strategy would become dominated by the more conservative strategy as the government could allow the fragile banks to fall apart.

This policy recommendation might seem a bit peculiar; if markets are truly efficient, how can the government have any recommendations for it?  As the argument for market efficiency is fundamentally an informational one, it's possible that information about systemic issues may be substantially less obvious than the fundamentals underlying each asset price.  But more importantly, the concern about the market aggregates arises less from an understanding of whether the crisis will unfold, but rather if the crisis unfolds.  I don't really know what a safe level of debt is and my estimates may be randomly wrong, but I don't want to be caught on the wrong side of the skew left distribution.  Nobody knows, but the individual investor is at freedom to guess wrong; he or she can take the chance.  However, policy makers are tasked with averting these large scale systemic crises, and therefore have to be much more aware of the fragility inducing effects of debt.

So while markets may not incorporate all information into prices, it's a fool's errand to try to figure out what the excluded information is.  Yet while markets may be efficient for investors, regulators may want to be aware of factors that lead to large scale systemic crises outside the domain of traditional models.  It's this focus on payoff, and not probabilities, that forms the basis of activist policy in an "efficient" market.

Edit: More analysis on the issue of timing

Momentum Trading

I recently read an interesting article on momentum trading, and I was wondering how it jives with the EMH.  It left me wondering whether there was some degree of survivorship bias when it comes to momentum trading, as the people who trade going up can make some returns, while the people who get burned by guessing the turning point wrong eventually leave the market.

This kind of asymmetry would also create an environment where there's an incentive to bid-up increases in prices.  If the general belief is that upward prices will keep on going upward, one can make money through buying stocks that are rising in price.  However, when the music ends, the people who bought on the way up still have their money; the people who got burned on the way down are no longer in the market to be evaluated.  In a sense, there's a coordination problem for momentum trading.  While all companies would prefer to not bid up the price of a stock, they are almost "forced" to by the asymmetric arbitrage opportunities.  These seem to be interesting game theory dynamics in a possibly efficient market.

Chinese Housing Market: More than "Tail Risk"

The story of the Chinese housing market has been a nerve wracking one.  Property prices have been soaring, and with all property price growth, there is fear that it could pop in a bubble.  This problem is especially prominent in the public consciousness in light of the U.S. real estate bubble, which seemed to show that no matter what governments may say about soft landings, housing bubbles can usually accumulate into larger macroeconomic crises.  While, yes, I am aware that housing crashed two years before the sharp drop in NGDP, the lack of Chuck Norris-esque monetary declaration in China to maintain steady NGDP growth seems to suggest that a banking crisis, which is essentially an aggregate supply issue, can accelerate into broader macroeconomic troubles.

Some recent news out of the housing market has been simultaneously comforting as well as concerning.  Housing prices have fallen five days in a row, yet the stock market is still rallying behind the bonds of several major Chinese property companies.  This has been interpreted as a prediction for a soft landing, as firms are still willing to invest in housing.  The CNBC article also outlines some other reasons for optimism:

In a report issued last month, Standard Chartered also pointed out that there were signs of hope after the drumbeat of negative news last year. "Apartment sales have improved since the Lunar New Year break," Lan Shen and Stephen Green wrote. "Developers are a little more confident about apartment sales, and price cuts of 10-20 percent are apparently helping to nurture demand."

On Friday, China's largest property developer Vanke seemed to confirm a rebound, reporting a 24 percent increase in sales in March over the previous year. It was the second consecutive month Vanke had reported a year-on-year sales increase.

Scott Sumner is also very optimistic, framing recent concerns as just another false alarm from a long row of pundits.

The price system works surprisingly well in China, despite the half-communist nature of their economy.  Chinese buyers actually use their own money to buy homes, so in a sense the US housing market circa 2005 was much more “communist” than the Chinese market.

China boosters like Robert Fogel claim that China will soon grow to be twice as rich as France the EU.  Others pundits claim it will get stuck in the middle income trap.  Both the boosters and pessimists are wrong.  Like Japan, like Britain, like France, indeed like almost all developed countries, it will grow to be about 75% as rich as the US, and then level off.  It won’t get there unless it does lots more reforms.  But the Chinese are extremely pragmatic, so they will do lots more reforms.

China is currently a very poor country, so the Chinese model has nothing to teach the West.  If we want to learn from the Chinese culture, learn from Singapore(or Hong Kong), which is how idealistic Chinese technocrats would prefer to manage an economy; indeed it’s how China itself would be managed if selfish rent-seeking special interest groups didn’t get in the way.  But they do get in the way—hence China won’t ever be as rich as Singapore; it will join the ranks of Japan, Korea, Taiwan, and the other moderately successful East Asian countries.

This isn’t any sort of “miracle.”  Go visit China and look at the airports, roads, subways, office buildings, shopping malls, etc, that they are building.   Look at educational levels in the cities (to which they are rapidly moving.)  It would be a miracle if a country that could do those things got stuck at the middle income level.  I’ve visited both Mexico and China quite often.  Mexico is a middle income country that is currently richer than China.  But any tourist who visits both places (with eyes wide open) can quickly see who will be much richer in 30 years.  There’s no stable equilibrium where the coastal Han Chinese get fully developed and the interior Han Chinese stay middle income.  And the coastal Chinese are closing in on developed status very rapidly.

While the long run predictions seem accurate (convergence seems quite reasonable for China), the concern is in the short run when the storm is still here. Interestingly enough, the first CNBC article trumpeting the resiliency of stock markets seems to be internally contradictory.  I don't buy the "price cuts of 10-20 percent are apparently helping to nurture demand" argument.  If there is so much demand, why should there be a need to lower the prices to "nurture demand"?  Even the argument about equities rallying because of confidence in the housing market is also specious.  Why should the relationship between the housing market and the housing companies' bonds be linear? Markets are opaque: how do we know the rallying is from perceptions of a short term price spike with a medium term collapse, or will the forecasts just not match reality?  Fundamentally, we just don't know why the movements in prices are happening.  Quoting Taleb in The Black Swan:

History is opaque. You see what comes out, not the script that produces events, the generator of history. There is a fundamental incompleteness in your grasp of such events, since you do not see what's inside the box, how the mechanisms work. What I call the generator of historical events is different from the events themselves, much as the minds of the gods cannot be read just by witnessing their deeds. You are very likely to be fooled about their intentions (8). 

If we really don't know the causes, optimism is unfounded.  Scott's confidence that the housing market will keep on going up also ignores the dual nature of the price movement.  The continual upward climb can both be evidence of stable growth, or the indicator that a crash is coming.  Past performance does not guarantee future results.  Taleb, again:

Let us go one step further and consider induction's most worrisome aspect: learning backward. Consider that the turkey's experience may have, rather than no value, a negative value. It learned from observation, as we are all advised to do (hey, after all, this is what is believed to be the scientific method). Its confidence increased as the number of friendly feedings grew, and it felt increasingly safe even though the slaughter was more and more imminent. Consider that the feeling of safety reached its maximum when the risk was at the highest! But the problem is even more general than that; it strikes at the nature of empirical knowledge itself. Something has worked in the past, until—well, it unexpectedly no longer does, and what we have learned from the past turns out to be at best irrelevant or false, at worst viciously misleading (41). 

Back to the CNBC article, it continues with analyses of severe risks among the housing companies:

Some credit analysts are also warning that the sector faces judgement day as builders struggle to pay back debt. On Thursday, Standard and Poor's cut the credit rating on Hopson Development and Glorious Property. 

"We have to remember, ratings agencies are not the leading indicators, ratings agencies follow the market," says SJ Seymour's Yadav. 

According to her, the best thing for investors to do is to choose the bigger names, which have exposure to mass-market housing and projects outside the large tier-1 cities. She recommends the corporate bonds of Evergrande. 

"We reckon the bigger players, simply because of the bigger number of projects, the diversification, will assist them. The smaller players can come under pressure very quickly," says Yadav. 

Meanwhile, analysts expect further consolidation among the smaller developers. Donald Han, Senior Advisor, HSR Property Group said his firm was advising some of these smaller companies. 

"A lot of these companies by in large have a fairly strong asset bases in terms of balance sheet but the difficulty is trying to move sales and converting that into stronger liquidity," Han told CNBC. "Some of the smaller companies may go through consolidation. The result of the consolidation exercise would turn some of the new entities into a bigger more stable companies."

I see multiple red flags here.  The fact that rating agencies are no longer comfortable with the levels of debt seems to hint at problems bubbling up from underneath.  The fact that they follow the market is not very comforting; it merely suggests that the economy is already moving towards that negative direction.  Additionally, while the analyst recommends investing in large firms to get stability, one has to be aware of how this consolidation of firms, in reality, merely masks tail risk with stability.  Quoting Taleb:

Just as there is a fallacy of aggregation, I believe in the fallacy of scale (because of concavities). Properties change with scale.

It is as if the firms are locking arms to face the wind.  While for small winds they are more stable, a large gust can pull them all away.

The last line about "fairly strong asset bases" but lack of "stronger liquidity" is especially concerning.  It suggests that the market is very prone to panics and shocks; there's no buffer of liquidity to assuage the fears of depositors.  This is all assuming that the asset bases are priced correctly and are actually strong.  Yet even a few minor errors here can propagate systemic risk through the markets incredibly quickly.

Some anecdotal evidence that I saw during my last trip to China also gave me shivers.  We were looking at houses near Shanghai, and found houses relatively far from the city center that were in the 5m RMB range, or about 830,000 USD.  And these relatively "new" houses were not very well constructed either: the walls often had relatively large cracks and the windows were not properly sealed.  Given the apparent high depreciation rate of housing capital: what could justify the high cost?

Of course, that can only pull on my gut feelings; perhaps there is some benefit of having a home at distances that make the city center at least accessible.  But when we were in the cab after looking in houses, I remember the driver talking about how housing prices would never fall, and that there was nothing to worry about.  Worst case scenario, there's a soft landing, but there should be no large scale concerns about housing prices.  This terrified me.  When one can buy 2 RMB newspapers about the housing market from street vendors, and then hear people saying housing price collapses are impossible, it's time to consider the "impossible": a hard landing for housing prices.

Now some may critique this argument, saying that the same arguments about opacity apply to my narrative as well.  The whole problem with low probability high impact events is that the events are fundamentally unpredictable.  We've never observed the probability before: how would we know?  The fact that it's anecdotal evidence is even more specious; I could just be telling a story and not listing the facts.  But the argument I here is not that the housing market will crash by 30% in 6 months and 16 days, but rather that we can't just wave our hands and hide the risks in China.  The problem is more than tail risk.  It's asymmetric tail risk.

If China continues on its current path, it's not going to magically get substantially higher growth.  Even if all the loans go off without a hitch, and all the banks stay liquid and solvent, the Chinese economy cannot grow much faster than 12%.  But if, for some reason, a systemic crisis befalls China, the negative payoff has a very fat tail.  Borrowing and collateral chains would collapse worldwide, and longtime trade partners would suffer through great turbulence to adapt to the new international trade.  Especially with the crisis in Europe, even a small credit shock in China could have massive global effects.  History does not crawl; it leaps.  My fears now are that while we crawl forward with housing construction, we may find ourselves in a "Great Leap Backwards", destroying many of the gains of the past decade.

Fiscal Policy in a Monetary Union

Recently, I read a post about the desirability of the various UK austerity programs within the UK monetary union.  What is special about the countries in the UK monetary union is that they are, to a certain extent, a fiscal union as well.  Scotland, Northern Ireland, Wales all have voting power within the English parliament at Westminster.  However, England does not have voting power in the parliaments of the other states, and therefore they still have some degrees of freedom to pursue their own fiscal policy, including the power to finance the policy through bond markets.  What this means is that fiscal policy, in a sense, can be devolved from the “federal” government to the individual countries.  Such a possibility is discussed by Brian Ashcroft when he calls upon the Scottish government to pursue policy to counteract the effects of fiscal austerity.

Well, first, it suggests that an independent Scotland as an accepted part of the UK sterling monetary union should be able to adopt a different fiscal policy stance to stabilise GDP than rUK. However, it also suggests that providing the degree of fiscal devolution is sufficient to allow changes in tax and spend that can influence aggregate demand then this option is also available within the UK political union. Further academic research is required on the appropriate form and degree of fiscal devolution for effective stabilisation but there is little doubt that stabilisation at the level of nations and regions within the UK is feasible. 

Moreover, if an independent Scotland is part of the sterling monetary union the Bank of England and rUK government will almost certainly require that the Scottish government abide by a set of fiscal rules - see this earlier post. The fiscal framework could be little different under devolution from that under independence. Under devolution, Scotland could have a separate stabilisation policy as well as the benefits from the risk pooling arrangements e.g. social security, bank bailouts etc. that are available as part of the UK. It is true that the high levels of trade with the UK would make it difficult for fiscal policy to chart a radically different stabilisation path from rUK but that would apply to an independent Scotland too.

Based on this concept, what if fiscal policy were devolved in the United States?  This concept of devolution would allow each state to design a fiscal policy appropriate for the macroeconomic conditions in each state.  Such a policy would be somewhat consistent with the concept of Market Preserving Federalism (MPF).  MPF was originally used by Weingast in the context of public choice; how do subnational units efficiently provide public goods to their citizens?  Samuelson argued that it was impossible, and that due to cross-border externalities, the central government had to intervene.  However, Weingast, building on Tiebout, argued that the subfederal units could be thought of as firms, and that they could compete against each other to reach optimal public good bundles.  For this to occur, five conditions must be met:

1. 1.    There exists a hierarchy of governments with a delineated scope of authority (for example, between the national and subnational governments) so that each government is autonomous in its own sphere of authority.
2. 2.    The subnational governments have primary authority over the economy within their jurisdictions.
3. 3.    The national government has the authority to police the common market and to ensure the mobility of goods and factors across subgovernment jurisdictions.
4. 4.    Revenue sharing among governments is limited and borrowing by governments is constrained so that all governments face hard budget constraints.
5. 5.    The allocation of authority and responsibility has an institutionalized degree of durability so that it cannot be altered by the national government either unilaterally or under the pressures from subnational governments.

Each of these five conditions are important to supporting MPF.  Without a hierarchy of governments (1), there is no federalism; the unitary state cannot be differentiated from the federal unit.  If subnational governments don’t have primary control (2), then they can’t properly compete against each other.  Without factor mobility (3), there is no competition.  As MPF was originally formulated in the context of public choice, the factors of production must have choice in where they are located.  Subnational control over factor mobility in the common market would prevent this.  Without (4), transfer payments can be used to smooth over competitive differences, limiting efficiency.  Finally, without (5), there is too much policy uncertainty, and the MPF regime may fall apart.

In devolved fiscal policy, the public good is no longer something concrete like transportation infrastructure or police protection; it’s aggregate demand management.  AD policy truly is a public good, as when the macroeconomy is doing well in an area, nobody can opt out of it (nonrival), and the government cannot effectively exclude, outside of arbitrary jailing, any citizen from the benefits.  Yet in the provision of this public good, the fourth condition, the hard budget constraint, becomes very problematic.  A hard budget constraint substantially limits the ability of the sub-federal units to pursue counter-cyclical fiscal policy such that, in recessions, the sub-federal units are forced to cut spending.  As a result, the economy suffers due to the shortfall in aggregate demand.  This is confirmed by data from the 2008 recession: over the course of the downturn, state and local spending collapsed, effectively counteracting the effect of the federal stimulus.

So what happens if the fourth condition is loosened; what if state and local governments were allowed to borrow?  In effect, there then would be fifty states with sovereign fiscal policies in a common monetary union; a situation quite similar to that in Europe.  During the construction of the European monetary union, the United States was often used as a model in the literature to help describe how Europe would work.  In this case, Europe can be used to help evaluate a hypothetical United States, in which sub-federal, and not the federal, units have borrowing power.

In Europe, the concern was that, in the absence of borrowing rules, the fiscal policies of the individual European states would err towards fiscal irresponsibility.  Since prices for most goods would not be affected by an individual country’s fiscal policy, aggregate supply would be much more elastic, heightening the effect of expansionary fiscal policy.  As a result, each state would have an incentive to boost its output through government spending and push the debt to the future.  However, once every state decides to pursue fiscal expansion, the aggregate supply relation puts the brakes on output growth, resulting in higher inflation instead.

Would the same thing happen for devolved fiscal policy in the United States?  According to analysis by McKinnon, the answer is “not necessarily.”  Because of Ricardian equivalence, a state’s decision to take up higher levels of debt can be interpreted as an obligation to raise taxes or cut spending on other programs in the future.  Assuming sufficient factor mobility to cause horizontal competition between states, the taxes to finance the debt spur firms to move away from indebted states to move towards lower debt states.  Consequently, debt financed expansions would be limited to public goods that have a positive return in the state, as those would be the only programs for which firms would be willing to pay taxes.  Note that these public goods can include education and health care systems as well.  If workers are drawn to the state by the productive investments in human capital, firms will have more opportunities to find talented workers in that state.  These local public goods would also be the answer to the spillover effect of fiscal stimulus.  As per open economy models of fiscal stimulus, simple increases in consumption have a high probability of being spent in other states.  On the other hand, local investments contain more of the stimulatory effect within the state.  As a result of competition between states, there is more likely to be efficiency within states.

What is particularly attractive about this arrangement is that it forces aggregate demand management in recessions to function as quasi-aggregate supply management.  As “easy” stimulus would diffuse across borders, so the more onerous task of improving the capital stock, both human and traditional, becomes the key mechanism through which to achieve macroeconomic stability.  This also creates exciting possibilities with regards to the interaction between each subnational unit’s fiscal policy and national monetary policy.  If the price level is pushed down as a result of an increase in aggregate supply, it may force the hand of an inflation targeting central bank that is otherwise unwilling to fill the output gap.

Some may point to Europe as an example of why this system would not work; devolved fiscal policy under a monetary union has only led to severe debt crises there.  However, one key difference is the extent of factor mobility in Europe as compared to the United States.  Much of the empirical literature on the Eurozone has pointed out the limited mobility of labor within the Eurozone.  Although many of the de jure barriers to immigration have been removed, the de jure barriers are still very problematic.  Moving from Germany to Portugal is not quite as simple as moving from Maine to California.  One has to learn a new language, use it effectively in a job, and then be aware of new cultural mores to truly fit in.  Consequently, labor mobility in the Eurozone has been estimated at about one third of that in the United States.  After adding high levels of transfer payments between countries, there is very little competition between the European countries for labor; there is no “factor-price equalization.”  As a result, firms cannot easily relocate, giving individual countries more space to pursue inefficient levels of government spending.  The threat of future taxes embodied by present debt is not strong enough to spur firms to move.

With Scott Sumner proudly proclaiming a market monetarist end to macro, it is time to turn our attention to what we can do afterwards.  In a world in which knowledge is increasingly dispersed, and centralization is unequipped to deal with the complex nature of economic policy, devolving policy domains, such as fiscal policy, may be the answer.