A Sea Change at the World Bank?

In a world of heated debates over policy responses to the global crisis, it seems that old institutions are changing.  No longer does the IMF stand for "it's mostly fiscal", it might now slant towards impressive macroeconomic flexibility.  And with the possibility of Jim Yong Kim, an expert in health and not finance, leading the World Bank, what can we expect?  Recently, there's been criticism of Kim for a volume of articles he co-authored with  Joyce V. Millen, Alec Irwin, and John Gershman.  And some of this criticism shouldn't be surprising; some of the passages from the book aren't things one would expect a World Bank president would say.

“The studies in this book present evidence that the quest for growth in GDP and corporate profits has in fact worsened the lives of millions of women and men.” (p.7)

 “Through a series of specific cases, we have demonstrated how growth – the market-led economic growth sought by governments, the growth in profits celebrated by businesses, and the growth in power and influence of transnational financial and corporate interests – often comes at the expense of the disenfranchised and vulnerable…  As the imperatives of growth at any cost increasingly determine economic and social policy and the behavior of global corporations, more people join the ranks of the poor and greater numbers suffer and die.” (p. 363)

This seems in line with the theme of a TED talk by Hans Rosling on global health and poverty.  While technological progress is an incredible tool to raise people out of poverty, it is not enough.  Often, the distribution of progress can rend societies as many of the previously poor stay poor, without any access to the new advanced capital.  As a corollary, public investments in education are incredibly important to democratize economic growth and to allow everybody to have the chance at the brighter future.

However, the World Bank mission statement does not seem to take this into account.  According to Article 1 from the Articles of agreement:

The purposes of the Bank are: 

(i) To assist in the reconstruction and development of territories of members by facilitating the investment of capital for productive purposes, including the restoration of economies destroyed or disrupted by war, the reconversion of productive facilities to peacetime needs and the encouragement of the development of productive facilities and resources in less developed countries. 

(ii) To promote private foreign investment by means of guarantees or participations in loans and other investments made by private investors; and when private capital is not available on reasonable terms, to supplement private investment by providing, on suitable conditions, finance for productive purposes out of its own capital, funds raised by it and its other resources. 

(iii) To promote the long-range balanced growth of international trade and the maintenance of equilibrium in balances of payments by encouraging international investment for the development of the productive resources of members, thereby assisting in raising productivity, the standard of living and conditions of labor in their territories. 

(iv) To arrange the loans made or guaranteed by it in relation to international loans through other channels so that the more useful and urgent projects, large and small alike, will be dealt with first. 

(v) To conduct its operations with due regard to the effect of international investment on business conditions in the territories of members and, in the immediate postwar years, to assist in bringing about a smooth transition from a wartime to a peacetime economy.

Interestingly, there does not seem to be any clause recognizing the possibility that neoliberal reforms can actually harm development.  Clause ii has a strong focus on private capital, and although clause iii talks about "balanced growth", it focuses on international investment as a way to access more sustainable growth, and thereby ignores the possibility that international investment can impede sustainable growth.

This kind of debate goes to the core of Dani Rodrik's book on the Globalization Paradox.  Often times, free trade can buffet small economies with waves that can cripple their human capital and cultural institutions.  Most of the East Asian miracles, such as China, South Korea, and Japan, began with very protectionist policies, with high tariffs and state sponsored monopolies.  However, with more development, they were able to move towards freer trade.  In effect, free trade was not a cause of their prosperity, but rather an effect.  In the context of development, it means that allowing massive amounts of foreign investment isn't always the answer.  Rather, proper development policies can be initiated with directives from within the country, not from the corporations from distant shores.

Thus, I hope that if Kim does become a president, he can use his development expertise to recognize that neoliberalism does not always mean equitable development, that development is a means to an end, and not an end in itself, that any growth in development requires recognition for its distribution in a society.  That, perhaps, the World Bank will no longer be seen as a front for neoliberalism, but rather as an institution that can transcend developing/developed nation binaries and foster truly equitable development.

What is with inflation expectations? Analysis from Cleveland Fed Data

After working with TIPS data in a previous post, I became more interested in the relationship between inflation expectations and actual inflation over time.  Generally, as per a paper by Mankiw, Reis, and Wolfers, inflation expectations can be highly contentious, with uncertainty among Economists especially high in times of crisis.  However, even though the data suggests that inflation expectation are well correlated with past inflation, the hypothesis of rational expectations and inflation predictions is a bit more uncertain.  In the Mankiw et al. study, the short term predictions of the Michigan, Livingston, and Survey of Professional Forecasters seemed reasonably accurate; how does this accuracy carry over to longer term measures of inflation expectation?

However, since the TIPS data does not go back very far, I used the Cleveland Fed's inflation expectation data instead.  And as per some comparative analysis between the two measures, the Cleveland Fed data can be more descriptive in times of major change, which is when the stability of expectations is the most important.  From the CPI data, I calculated the actual inflation over the future timeframe of the expectation, and then associated this inflation rate with each month's inflation expectation data starting from January 1982.  Thus, for the 5-Year inflation expectation data for January 1982, the actual inflation was the average annual inflation from January 1982 to December 1986.  These two numbers formed a point.  I then took 60 of these points (five years), and used them to calculate a Pearson's r-value, a measure of the correlation between the two values.  For example, the set of data beginning with a point in January 1982 includes the inflation data from December 1992 to make the last calculation for actual inflation.  The movements of the different correlations are plotted below:

What is immediately apparent is that the stability of the relationship changes with time.  During the second half of the 80's, expectations matched reality quite well, with an r-value of over 0.9 for the 5 year expectation data.  This seems to match the rational expectations proposition that the expectation should be the reality.  However, beginning with the 90's, the correlation between inflation expectations and actual inflation became more negative.  What is striking is that the correlation kept on going down, reaching almost -0.8 with the 5 year expectation.  The correlation is consistent with the r value of about -0.73 with the TIPS data, lending credibility to the fact that Cleveland Fed predictions are theoretically robust.

What is more interesting than the correlations are the slopes; an increase in expected inflation predicts how much of an increase in actual inflation over the future period?  The data is graphed below.  A value of 1 means that for every percentage point increase in inflation expectations in a period, the actual inflation in the corresponding term is 1 percentage point higher.

Before looking at the actual numbers, what should we expect the slope to be?  In a world of perfect rational expectations, in which , the slope should be one.  Although there may be error, the expectation should, on average, match reality.  In the world of an inflation targeting central bank (with or without rational expectations), the slope should be 0, as actual inflation should always gravitate towards a constant.  This analysis of central banks is supported by comparisons between US (non-inflation targeting) and UK and Swedish (inflation targeting) central banks.  Below are both the time series of the slopes, as well as box and whisker plots showing the distributions of the slopes.

As can be seen from the time series, the slopes don't stay constant.  Rather, they jump around, with the 1-Year slope value substantially more volatile than the 5 or 10 year slopes.  In spite of this, the median of the slopes do lie around zero.  However, their distributions are skewed right, with the outliers mostly coming from the mid 1980's to the early 1990's time period, which was the time after the brunt of the Volcker disinflation.  The amazing convergence of measures at that time suggest it has something to do with people adjusting to a new monetary regime.  It is as if, in the transition to the fight against inflation, people were able to accurately predict the new stable regime, creating the high correlation as people lowered their expectations of inflation.  Later, as the regime became stable, the correlation became weaker as noise gained a proportionally larger effect.

But then what explains the negative slopes in more recent times?  One interpretation is that they're statistical anomalies: the 1 year data goes much farther and, while it does have a few blips into negative slope, they revert back to mildly positive relatively quickly.  Given this volatility, we will have to wait for more data to try to evaluate the impact of the regime on inflation and their expectations.

Weird Econometrics (TIPS)

The TIPS spread is the interest rate spread between a regular treasury and the corresponding inflation protected treasury.  It functions as a measure of expected inflation, and I was curious about its specific mechanisms. Especially since the theory forms the basis of a cornerstone of the NGDP targeting utopia, it seemed important to look into the effectiveness of TIPS at estimating inflation.

I downloaded the monthly TIPS spread data, as well as the monthly percent change CPI data from FRED.  From the monthly percent change CPI, I calculated the average annual inflation from each month to the month 5 years in the future.  The data is plotted on the xy-scatter below.



The x-axis is the 5-year TIPS spread for a given month, and the y-axis is the actual average inflation over the course of the next five years.  The FRED data on the TIPS spread only starts in January 2003, and since I wanted inflation over the next five years after each month, the CPI data could only give five year future average inflation up to March 2007.  Excel calculates the trendline to be y=-0.8105x + 4.4188, with the 95% confidence interval on the slope as (-1.03553, -0.5854) and a 95% confidence interval on the intercept as (3.894, 4.944).  Thus, a one percent increase in the TIPS spread in a month predicts a -0.81 percentage point drop in the actual average inflation over the future five year period.  This is a very peculiar given the TIPS spread is used as such a common tool to describe inflation expectations, especially by a certain market monetarist who uses them to tell his stories.

At first glance, this seems to reject rational expectations.  Rational expectations predicts a regression equation with a slope of approximately 1 and a small intercept, as future inflation should always be fully predicted in the TIPS spread.  Yet, in the data, one sees a negative slope, with an intercept that's actually relatively large.


However, the expectations hypothesis can still be salvaged from the Sumnerian perspective of having to take the policy regime into account.  One could interpret the negative relationship as expectations in an inflation targeting regime: when expected inflation is low, future actual inflation is higher; when expected inflation is high, future actual inflation is lower, all because the Fed takes the forecast into account and adjusts accordingly.

With this analysis, we could approximate the inflation target.  Wherever the Fed target is, it should lie on the line y=x, where the expectation is the actual inflation.  At that point, the Fed is "satisfied" with what inflation is forecasted to be, and therefore sees no reason to change it with policy.   For the mean parameter values for the regression, this intersection is at about 2.44% inflation.  With the various values in the confidence interval, the target can also range from 1.91% to 3.11%.  These values seem reasonable for the Federal Reserve's legacy of flexible inflation targeting.

Even after this analysis, a wrinkle persists; why do markets consistently predict lower inflation rates that in actuality?  Based on this graph, there seems to be an arbitrage opportunity.  As soon as the TIPS spread goes above the critical value of 2.44, actual inflation will likely be lower.   As soon as the TIPS spread goes below 2.44, actual inflation will likely be higher.  Perhaps this anomaly will be washed out with more data.  The time period analyzed was less than 5 years, which may not have been enough for the market to learn, especially given that the 5-Year bonds bought at the beginning of the period had not matured yet by the end.

Regime Shifts and Expectations - A Move Towards Fragility?

One of the foundations of Market Monetarism is the role of expectations in influencing policy.  The whole goal of a 5% nominal GDP target is so that the economy can expect the same level of nominal growth, thereby allowing the highest efficiency in an economy, as agents can plan for a stable future.  Such a view was recently summed up by Scott Summers in a post calling for a better Monetary REGIME instead better Monetary POLICY:

... If there is some sort of policy that you think needs fixing via monetary policy, then you have the wrong monetary policy regime. You are targeting the wrong variable. Thus you might (wrongly) decide it’s a good idea to target headline inflation at 2%, and then suddenly notice that that target conflicts with your gut instinct that unemployment is too high because of inadequate AD. In that case the right decision is not to pull out the monetary policy tool, but rather to entirely abandon your inflation targeting regime. If you have the right regime, then YOU SHOULD NEVER, EVER, ADJUST MONETARY POLICY.

This concept of a regime makes me think along the lines of the possible impact of large shocks to the macroeconomic system; what if the regime shifts?  While a previous regime shift, such as FDR's decision to depreciate the dollar in the middle of the Great Depression, may have worked to restore the economy, the question is whether a new NGDP targeting regime would be stable.  From a differential equations standpoint, would it be a sink or a source?  The centrality of expectations to the theory seems to suggest that if the expectations were to become unanchored at some point, chaos would ensue.

However, what mechanisms could explain the shift to a more fragile system?  Besides artful comparisons to forest fires or animals' need for exercise, are there actual theoretically justified reasons for an increase in fragility?

Searching and the Role of the Efficient Market Hypothesis
Overall, the EMH is pretty effective at explaining financial markets; it's unlikely that there's some systematic error that causes financial mangers to consistently miss profit making opportunities.  However, some assumptions of the EMH have to be relaxed to make a NGDP monetary regime make sense.  Primarily, information flows are not instantaneous, which means markets do have to go through an adjustment process while economic agents search for the information to form their expectations.

However, what's the sense in searching in a world of stable NGDP growth?  An alternative to the EMH, the Adaptive Market Hypothesis, posits that survival of firms, instead of pure profit maximization, is a stronger driver of moves in the market.  In an aggregate market in which movements are generally stable, survival is not as severe of an issue.  While NGDP stability in theory should have no effect on intra-industry competition and churn, common sense experience seems to suggest that when times are tough, people look for more ways to become competitive to survive.  However, when times are stable, people choose not to use that psychic energy to optimize; they settle with just satisficing.  Admittedly, this requires a more behavioral approach, but considering the vast literature on cognitive biases that reject homo econimus, it seems reasonable.

Impact on Debt
The issue of debt seems to be problematic in a world of constant nominal GDP growth as well.  Such stable expectations allow greater and greater tolerance for debt, as people become more comfortable with the concept of constant growth and start to neglect the possibility of nominal shocks.  This would lead to vastly longer debt chains, which can, in effect, make the economy more fragile and vulnerable to systemic shocks.  While the hot potato effect does not necessarily depend on a function banking system, the flow of money and the repaying of debts can have a significant effect on short term NGDP expectations.  Even if there's a short term lag on repayments, the danger of debt chains breaking down seems like a major issue.  While financial problems really are more supply side issues, how would the government deal with them once the crisis hit?

Conclusions
In the end, my fears, however irrational, are predicated off of a very true, yet also startling quote from one of Nicolas Nassim Taleb's journal articles:

...Because a probability cannot be lower than 0, your expected probability should be higher, at least higher than the expected error rate in the computation of such probability.  Model error increases small probabilities in a disproportionate way...

How does NGDP targeting prepare for this?  If it can not adequately prepare, is there a middle compromise that allows sustainable growth with robustness to error?

The Efficient (Adaptative?) Market (Policy?) Hypothesis

I have been reading a bit about cognitive biases, which of course has led to a nice discussion about whether financial markets truly are as "random" as is commonly believed.  After wandering through some rather interesting articles, I stumbled upon an alternative paradigm described by Andrew Lo as the Adaptive Market Hypothesis.  Lo introduces the EMH with the classic joke:

...an economist [is] strolling down the street with a companion. They come upon a $100 bill lying on the ground, and as the companion reaches down to pick it up, the economist says, “Don’t bother—if it were a genuine $100 bill, someone would have already picked it up”.

Lo then goes on to describe the various "real world" critiques of the EMH, spanning the range of cognitive biases including loss aversion, miscalibration of probabilities, and regret.  Lo does admit that, in spite of these biases, the EMH can still be robust; arbitrage should take advantage of these irrational biases and price them out of the market.  However, Lo finds that this static conception of markets, as a collection of entities constantly reaching for a predetermined equilibrium, unsatisfactory for the highly dynamic world of finance.  Lo summarizes his new approach, termed the Adaptive Market Hypothesis, as an evolutionary approach to market efficiency.  In his words:

Prices reflect as much information as dictated by the combination of environmental conditions and the number and nature of "species" in the economy

This is a very interesting approach, as it takes into account the environment  in the formulation of market efficiency.  Lo's definition also leads room for evolving financial strategies, asymmetric information, and changing market size.  It posits that while the EMH can be true, it is only true in certain situations, and that, ala Grossman and Stiglitz, markets necessarily have some degree of inefficiency to justify their existence.  In a sense, the AMH is the general case of the EMH; the EMH is the asymptotic case of the AMH.  In markets of infinite agents with infinite cognitive capacity, the EMH holds.  In anything less, the AMH is more satisfactory.  Some Federal Reserve research on foreign exchange markets has also provided evidence that the AMH can function as a better explanatory framework.

However, as Scott Sumner reminds us in his post on the EMH, any criticism needs to have practical implications.  And Lo does have a long list of qualitative insights, , spanning many paradigm differences between the AMH and the EMH.  Fundamentally, these implications boil down to the need to think of markets as organic, evolving systems with changing preferences and strategies.

When I was thinking about these two paradigms, I found that a clarifying question in the context of these two theories is "Why is there no analogous 'Efficient Policy Hypothesis'?"  A certain webcomic humorously illustrates one reason why the hypothesis can't hold:


In the framework of asymptotic cases, the Efficient Policy Hypothesis lies at the other extreme of the AMH, opposite to the EMH.  Whereas efficient markets have a large number of agents with relatively little individual power over the market, policy is comprised of one agent, the government with very large power over the market.  Additionally, while markets can adaptive quickly to new situations, policy, especially if it requires democratic deliberation, has no such capacity.  This kind of thinking then creates a new mechanism through which the failure of policies (and nations) occurs.  It occurs not as simply a malevolence on the part of regulators, but as the natural result of unnatural selection.  And perhaps this does have "practical implications" on the design of policies; for societies to be robust, regulators must adapt.

An Exercise in Production Possibilities Frontiers

A persistent question that comes up in playful debates with my economics teacher is about the curvature of production possibilities frontiers.  In class, only two "realistic" examples are taught: constant opportunity cost and increasing opportunity cost.

Although intuition may suggest that a concave curve and a linear curve imply a convex curve, one is never presented.  It is a "mystery"!  Yet after looking through some journal articles, there seems to be a vast literature on the conditions specifying the shape of the frontier.  Wikipedia even has a picture of what a convex production possibilities frontier would look like:

In this post I try to sketch out a simple model of a production possibilities frontier, and then try to explain some of the insights that can emerge from the more mathematical analysis.

I start out with a two industry economy, M and N, that uses only one input: labor.  Both industries follow Cobb-Douglas production functions with a and b > 0. 

As with most production possibilities frontiers, full employment is assumed, so:



Where P is the total population. With this substitution, both of the production equations can be solved for LM, which can be rewritten as L, resulting in:




Setting these equal to each other allows one to solve for M as a function of N:


Differentiating once with respect to N yields:


What is interesting to note is that the first derivative must be less than zero, regardless of the values of a or b.

As


And since, according to the original production functions:



We find that:



This analysis, along with the properties of the equations in the form of , allows one to quickly deduce that the derivative must be negative. Here lies the classic concept of trade-offs; as the production of one product increases, the production of the other necessarily decreases. What is interesting is that this is true for all production possibilities frontiers, even "constant opportunity cost" or "decreasing opportunity cost". The constant or decreasing does not refer to the total amount of M one has given up to get a certain amount of N, but rather the marginal loss in M from the marginal gain of N. In other words, the adjective describing the production possibilities frontier isn't about the first derivative, but the second, which is calculated below:



Collecting terms and factoring yields:


The part in the square brackets is the punchline in our adventure.  With the previous analysis about positives and negatives in mind, the only terms in the equation for the second derivative that could affect the sign of the second derivative are (a-1) and (b-1).

This creates a few cases for the second derivative of the production possibilities frontier. If both a>1 and b>1, then both production functions correspond to increasing returns to scale, with a frontier that has a positive second derivative, making it convex. This corresponds to the "bowed in" shape that can be described as "decreasing opportunity costs". Note again that this does not say the total amount of good M given up is decreasing, but rather that the amount of the good given up for each marginal unit of N is decreasing.

If both a<1 and b<1, then the production functions correspond to decreasing returns to scale, and the second derivative of the frontier is negative, making it concave, much like the traditional "increasing opportunity costs" case. And if both a=b=1, the production functions are constant returns to scale, the second derivative of the frontier is zero, making it linear, corresponding with the "constant opportunity costs" frontier.

What is elegant about this conclusion is that the three types of production frontiers correspond very nicely to the three modes of production: increasing returns with decreasing opportunity costs, decreasing returns with increasing opportunity costs, and constant returns with constant opportunity costs.  Therefore, while the traditional example of guns and butter makes sense for the increasing opportunity costs case, the decreasing opportunity costs case would require an example with scale economies, such as those seen in technology fields or in infrastructure.  An example would be the production of plane flights or train rides.  In each of these industries, initial capital costs to build the airports or the railroads are very high.  But after some are built, subsequent investments are cheaper due to a network effect.  As a result, both industries are subject to increasing returns, and their combined production frontier can exhibit decreasing opportunity costs.  Of course, this can only hold true as long as scale economies persist.  If both industries revert back to diseconomies of scale at high production levels, the frontier in those regions will exhibit increasing opportunity cost.  However, what this analysis has gone to show is that there is good reason for why frontiers can have zones of convexity, exhibiting the "mysterious" property of decreasing opportunity costs.

Nominal GDP Targeting and Complexity

The Complexity View

I've recently started rereading passages of The Black Swan: The Impact of the Highly Improbable and I find it fascinating. The prose is fluid, and the arguments are powerful. Much of the book mocks economic theory, as models tend to minimize the role of large shocks that defy normal distributions.  In the book, Taleb inserts the following chart that shows how much these "outliers" influence the stock market.

Taleb places the blame for these large swings in the market on the shoulders of the Federal Reserve.  He argues that stabilization policy actually makes the economy more fragile, making it more likely to go down in a dramatic fashion once the "big one" hits.  He sums up this argument in the following quote from a section titled "Beware Manufactured Stability" in a supplementary essay.

...fear of volatility, leading to interference with nature to impose "regularity" makes us more fragile across so many domains.  Preventing small forest fires sets the grounds for more extreme ones; giving out antibiotics when it is not very necessary makes us more vulnerable to severe epidemics... 

Which brings me to another organism: economic life. Our aversion to variability and desire for order and our acting on it has helped precipitate severe crises... Another thing we saw in the 2008 debacle: the U.S. government (or, rather, the Federal Reserve) had been trying for years to iron out the business cycle, making us exposed to a severe disintegration. This is the sort of reasoning I have against "stabilization" policies and manufacturing a nonvolatile environment ...

In a sense, the reduction of volatility in the Great Moderation was only an illusion of stability.  We were, as Taleb would say, "sitting on a pile of dynamite," unaware of the risk that lay underneath.

Impact on NGDP Targeting Policy

This kind of critique seems rather damning against nominal GDP targeting.  The typical analysis of NGDP targeting hinges on the assertion that low volatility implies high stability.  But what if this isn't true?  What if these times of low volatility are just times of high fragility?  Some analysis of the arguments for NGDP targeting even suggest mechanisms by which this is the case.  Debt problems are waved away because NGDP is stable, financial opacity becomes a non-issue because monetary policy compartmentalizes it,  perceptions of "safe" assets  change because expectations of nominal growth are maintained.  Stable expectations permit these innovations because agents can plan ahead, allowing for higher growth.

However, this higher efficiency comes at the cost of redundancy.  Taleb jokes in an interview with Russ Roberts that:

An economist would never design a human being with two lungs and two kidneys. It's wasteful. Deadweight loss.  

He follows up with:

So, the opposite of spare parts would be debt. And nature doesn't like debt. Nature likes redundancies. This mechanism of overreaction is redundancy.

And this is what terrifies me about NGDP targeting.  The incredibly stable regime creates an environment in which redundancy is eschewed in favor of fragility.  Perhaps it would be better to have a more resilient economy that wouldn't be able to accumulate as much capital, but one that has lower levels of debt.  The cost of a mistake in an NGDP targeting world would be incredible.  Even if, theoretically, under a stable monetary regime, there are no demand-side recessions, would you be willing to bet the stability of the entire global financial system on it?  Even if it were true, can you guarantee the Fed will be able to maintain a "stable monetary regime" for perpetuity?

I'm not trying to say the current monetary system is ideal; the dismal employment numbers firmly reject that view.  But when we look onto NGDP targeting as the solution to the global economic malaise, we need to be careful that we don't put all of our eggs into one basket.  NGDP targeting is an incredible tool for monetary policy; but it can't be a panacea for all of these troubles.  

This critique of NGDP targeting brings up another key issue for the design of policy.  Optimal policy has to do more than maximize welfare, it must also be robust to errors.  While in the game playing, platonic world of models NGDP targeting should create incredible reductions in volatility and instability, what are the possible effects on global fragility?  Policy engineering needs to take into account Murphy's Law: "If anything can go wrong, it will."  The only question is how we prepare.

Mechanisms Behind NGDP Stability

I just wanted to jot this post down so I could remember the over 9000 reasons NGDP targeting is more effective than the alternatives:

Instantaneous - future expectations of nominal GDP determine today's NGDP
Focus on the policy variable - there is no intermediate proxy, ergo hell or high water, the target is hit
Lessens impact of financial crises - as long as expectations are anchored, the biggest failures don't spread throughout the macroeconomy
Resiliency to supply shocks - no overshooting or undershooting compared to an inflation targeting regime
Is "costless" - as compared to fiscal policy, NGDPLT doesn't require sovereign debt
Stable expectations - level targeting has a "memory", so past failures are corrected for
Politics - it's easier to advocate for higher nominal incomes than higher inflation
No impact of inflation on creditors - fundamentally, it's about NGDP.  If it's a real shock, everybody has to bite the bullet
Interest rates - higher NGDP expectations raise the interest rate, allowing more room for conventional monetary policy

NGDP Targeting: What if it fails?

Recently in the economics blogosphere, the monetary paradigm of nominal GDP level targeting (NGDPLT) has been gaining steam.  NGDP targeting takes a departure from the classic regime of inflation targeting by the growth rate in NGDP, allowing for balance between employment and inflation.  This then leads to a wide variety of benefits, as the new regime is robust to supply shocks, can craft stable expectations of overall future growth, and can reduce fears of any specific industry going through a crisis.  It's particularly attractive for financial crises, as if NGDP growth is stable, previously sustainable levels of debt are less likely to become unsustainable.  If the economy's productive capacity is constant, there's no reason for it to be less able to service its debt.

However, this view seems almost too simplistic.  Even though the US economy was incredibly stable during the over the 20 year Great Moderation, it all came down to a screeching halt with the 2008 financial crisis.  Similarly, even though Britain managed to stay out of a major recession for 16 years, NGDP fell by about 4.7% during the crisis.  Given that there had been such a long legacy of stability, how did expectations suddenly become unanchored?  Even if the US Federal Reserve made a bad policy decision at that point to focus on oil prices and other supply shocks to the detriment of nominal stability, why did the expectations of prudent policy in the future not "solve back" the concerns?  In the end, the crisis culminated into the worst disruption since the Great Depression: hardly a desired result for a responsible regime.

The unhappy ending in 2008 seems to suggest that responsible policy can break down into chaos given a large enough of an exogenous shock.  This problem is very close to what Nicolas Nassim Taleb discusses in The Black Swan: in exchange for low volatility, the economy goes along with high fragility, such that one large shock can cause non-linear, disproportionate harm.  So in the end, the question is about credibility.  How is it established?  How is it maintained?  If decades of prudent monetary policy were not enough to anchor expectations, why should we expect the Federal Reserve to be considered "credible" when the next large financial bubble appears?  If shadow banking markets start to grow shadows and systemic risk goes through the roof, why should we expect the Federal Reserve to be considered "credible"?  Especially if non-monetary factors as posited by Bernanke play a key role in recessions, why would nominal stability be enough?  And when everything crashes down, how will we deal with the mess of debt and contracts that were only sustainable under the old regime?  NGDP targeting seems to play on circular logic.  Boost aggregate demand to hold the expectation; with the expectation there's no need to boost aggregate demand.

So when a policy maker messes up, and lets a NGDP crisis unfold, the crisis emerges.  This is where the black swan hides, cloaked by the rhetoric of stable expectations and the "perfect" monetary policy.