Papers increasingly attempt to model financial uncertainty

There used to be time when a belief in the eternally optimal market outcomes was the article of truth. Paper after economic paper was littered with stylized models depicting these desirable outcomes, jingoisitically referred to as “Pareto efficient” or “Pareto-optimal equilibria”.

Few lone voices, like Hyman Minsky, argued that no such “equilibria” existed and that markets are, after a bout with exuberance, prone to self crashing.

Minsky gained in notoriety after the great 2008 crash, but behind his financial instability hypothesis was left a “modeling” void – an absence of a stylized set of circumstances onto which economists can apply equations, do some calculus on them, and “show” that, indeed, markets are crazy.

“Although individuals in our model are rational; markets are not,” says the latest paper by Roger E.A. Farmer, Carine Nourry, Alain Venditti.

This triplet of economists says that markets are not rational because had it been rational no trader would be able to profit. The fact that some, in the financial world, make money by trading on the account of informational discrepancy, is indicator enough that there is no such thing as rational markets.

As a result, financial markets do no produce “Pareto efficient outcomes, except by chance,” say the authors.

They are critical of the existing literature which starts from the premise that all is logical in the financial markets and the screw-ups are caused by various types of “frictions” – sort of road blocks that srew up the intrinsic bliss of the free-flow of financial information and trading skills.

“We do not rely on frictions, market incompleteness or transactions costs of any kind. Instead, we modify a simple stochastic representative agent model by allowing for birth and death and by allowing for heterogeneity in agents’ discount factors,” say the author cryptically.

The “birth and death” problem assumes that a financial contract made in the past is incongruent with the financial realities that predominate right now. As a result, some traders are  “unable to participate in markets that open before they are born” therefore they have inadequate means to hedge against that.

“The first welfare theorem fails because participation in financial markets is necessarily incomplete as a consequence of the fact that agents cannot trade risk in financial markets that open before they are born. For this reason, financial markets do not work well in the real world,” conclude authors.

We see such outcomes in the wage and wealth numbers of cohorts.

“When agents have realistic death probabilities and discount factors ranging from 2% to 10%, we find that the human wealth of new-born agents can differ by a factor of 25% depending on whether they are born into a boom or into a recession,” note the authors.

With full intricacies of their stylized model and pages of equations dabble, the paper is available here.

Critical of IMF, economist calls for fiscal spending

Known for his advocacy of the so-called balance sheet recession, Richard Koo says that IMF is sketchy on the solution for the EU malaise, that it is succumbing to German economists who are betting their careers on austerity and is critical that governments are not unleashing a fiscal stimulus.

“The IMF said the negative multiplier effect from fiscal consolidation was greater than initially anticipated, but did not provide a convincing explanation as to why that was the case,” writes Koo in his latest research note.

“If the IMF had been watching private savings trends in these countries via flow-of-funds data, it would have understood from the outset that no amount of fiscal consolidation would boost private investment. But it did not,” says Koo.

Koo says that money that fled the EU would return if a fiscal stimulus is announced but taking such position is unlikely because of the “heavy resistance from the economists and German politicians who have bet their careers on fiscal consolidation.”

Fiscal policy is, however, most effective precisely now when people are saving despite zero interest rates.

“Fiscal policy is most effective precisely when monetary policy is most impotent—i.e. when zero interest rates are unable to stimulate the economy. That is the situation we face today. When a recession has been triggered by a private-sector decision to save more and work off debt, there is no risk of crowding out, distortions in resource allocation, or other potential downsides to fiscal policy,” says Koo.

As a result, Koo is critical of the Republican candidates and says that the whole party has “zero understanding of balance sheet recessions”.

“Businesses and households would not be saving a net 8% of GDP at a time of zero interest rates if the US private sector were as strong as Mr. [Paul] Ryan claims,” says Koo.

“The private sector’s decision to save 8% of GDP a year when interest rates are at zero means the government must step in and borrow and spend an equal amount.”

Available here.

HSBC makes contrarian call on equities

Current low in the global risk appetite is a bullish sign for the equities, says HSBC Global Research, and notes that going long European telecoms and utilities is the way to profit from the underweight position of the international funds in this area.

“Last month we saw international funds tentatively return to emerging markets but this has not been sustained. Holdings are now relatively low for China, Brazil, India and Russia. In Europe, telecoms and utilities look interesting. International funds have been underweight for much of the past three years but are now beginning to close-out their underweight positions,” writes HSBC in its July 26 note.

Since then, Dow has moved from well over 550 points and the 10-year bond yield has gone from the historic lows of under 1.5% to the current 1.82%.

“One of the most reliable ways a European fund manager has been able to outperform since 2009 has been to be underweight telecoms and utilities. However, we detect signs that being underweight these two sectors has become a cosy consensus and it is beginning to unravel. We have seen buying of both sectors from a low base,” says HSBC.

HSBC says that these two sectors will outperform because a “cosy consensus” and “herd-like behaviour” has formed so that by “tracking holdings in high-beta or cyclical equities, we can also shed light on what these investors are expecting. Groups with low holdings tend to outperform.”

Dangers of outsize banking & other stories

History suggests, says University of Virginia economist Alan M. Taylor in his latest paper, that outsized banking and banking crisis in a globalized world occurred just prior to the financial trouble while, for the last 60 years, “until 2008, we had all but forgotten about financial crises” and that, says the author, “amounted to nothing so much as an opportunity, albeit a self-created one, for advanced countries to lull themselves into a false sense of security.”

Titled The Great Leveraging, the paper is a highly readable essay that should be on a recommended list because it examines 10 points of current financial interest that need not only the short-term policy resolution but also a long-term theoretical framework.

The historical fact that financial crises are much more painful then ordinary recessions and that since 2008 we had to relearn this occurs in an (un)opportune time when banks hold an unprecedented economic sway in the developed world.

By tracing bank loans, assets and M2 in 14 advanced countries, the author notes that since circa 1970 banks have exploded in their size (chart below).

“We can refer to this first period from 1870 to the 1970s as the ‘Age of Money’ and apart from the Great Depression, and subsequent years of financial repression in the 1940s and 1950s, the ratio of loans to money was more or less stable,” notes the author.

After the 1970s, however, things just got out of hand in finance.

Writes Taylor:

From the 1970s this picture changed dramatically, and we entered what might be called the ‘Age of Credit.’ Although broad money relative to GDP remained almost flat at around 0.7 (rising a little only in the 2000s), the asset side of banks’ balance sheets exploded. Loans to GDP doubled from 0.5 to 1.0 and assets to GDP tripled from about 0.7 to roughly 2. The decoupling of loans from broad money reflected the rise of nonmonetary liabilities on bank balance sheets, such as wholesale funding. The even faster expansion of bank assets reflected this too, plus the rise in more interbank lending. Along the way risk also increased, as the banks’ asset mix put an ever diminishing weight on safe assets (government securities), a fraction which was down to virtually zero in the 2000s, after starting at 60%–70% in 1950.

Taylor suggests 3 different reasons for this development which can be read in the paper, but intriguing is the shift in asset holdings by banks from “safe” public paper to presumably “unsafe” or “less safe” private debt, and problems this may cause in executing monetary policy.

The scale of the increase in the balance sheets in the banking sector has effectively flipped the main credit risk nexus, measured by debt magnitude, from the sovereign side to the banking side. After the war, banks were cautious and had few loans to the private sector on their books, but the sovereigns had very large debts. But by the 1990s and 2000s — and even after substantial postcrisis increases in average public debt in advanced countries — this observation still holds true, as seen in Figure 4 [chart above]. It is private debts on bank balance sheets that far outweigh public debts on sovereign balance sheets.

Central banks, to be sure, deal with public debt in order to manipulate interest rates and adjust monetary policy but – and here is the lemma of a quandary -  to the extent that the ratio of public to private debt is skewed in favor of the private and given diminished potency of the monetary policy during this recession does this mean that there is or needs to be some optimal public/private ratio so that the monetary policy remains unimpeded? Yet still, if there is a permanent shift in public/private ratio, do we need to rethink the very basis of how a monetary policy is conducted?

Tasking questions indeed but this brings us to to claims that additional QE, to the extent that it is based on purchases of government hence “safe” paper, will have less effect then the previous one even if any of an effect.

The point here is that any subsequent QE makes US debt paper less liquid because there is less of them to be traded and if those yields are a standard according to which risk is to be set then the risk may look way underpriced for banks to enter into… and this makes the private, those “less safe” loans, more important to the monetary policy but the Fed does not trade with them.

We could, to be sure, go on and on discussing the easy-money-no-investment quandary we are in but Taylor, in this paper, gives an optimistic look at this.

“Demographic shifts will start to put a drag on savings, and the world’s investment drought, intensified by the near disappearance of DM net capital formation in 2008–09, will leave a large overhang of unmet investment requirements,” opines Taylor.

Should the “overhang of unmet” investment increase, pressure on the yields is sure to be felt and such pressure, Taylor notes, is to occur sooner rather then later.

“The DM world now faces a demographic tailwind as the boomers retire, and in the EM world aging populations are set to grow as the demographic transition winds down. Substantial heterogeneity lies behind these averages of course, but these patterns presage major changes in the saving-investment balance going forward,” says Taylor.

Paper, highly recommended, available here.

Obesity next investment frontier says BofA

Obesity is set to become the  major investment theme over next 25-50 years as amount of overweight people has tripled global over last 30 years says latest research note by Bank of America Merrill Lynch.

“By 2008, c.500mn people over the age of 20 were obese. The prevalence of overweight and obese individuals was highest in the Americas (62% overweight in both sexes, and 26% obese) and lowest in South-East Asia (14% overweight in both sexes and 3% obese). In Europe, the Eastern Mediterranean and Americas, over 50% of women were overweight. In all three regions, approximately half of these overweight women were obese (23%, 24% and 29%, respectively),” writes BofA that was penned by Sarbjit Nahal, Valery Lucas-Leclin and John King.

They say that overweight people, which includes the obese ones, carry 15 million tons of extra weight which amounts to 242 million of normally weighted folks. Of this number, the obese carry 3.5 million tons, equivalent to 56 million people.

All of this extra global fat “would pose significant cost challenges to the longterm financial viability of public and private health insurance programmes, as spending growth outstrips revenue growth.” In fact, BofA says that these costs are underestimated not just in health care but costs associated with servicing so many fat people.

For example, BofA says that fat folks push up food and fuel costs offsetting gains in food production and airline and car efficiencies; they produce more excretion which adversely impacts environment and cause increased safety issues.

“With over 80% of US citizens having health insurance coverage, there is a clear incentive for insurers to promote obesity diagnosis, screening, treatment and prevention to reduce medical claims and costs. That said, insurers do not consistently pay for obesity prevention and treatment unless there are comorbidities. Given the nature of the problem, obesity prevention should arguably be considered a core service similar to cancer prevention and counseling,” write authors.

As a result, BofA recommends drug firms, athletics, health and medical stacks (see table).

Momentum trading produces outsized losses, paper

Piling in on the hot stock can be all too exciting not just because of the exuberance from outsized gains but also because of the pain of outsized losses such trading strategy can bring and which one of these possibilities happens depends on when such trading strategy is employed, says the latest paper from a triplet of professors.

It has been well documented that price momentum strategy – long position in past winners and an equal short position in past loser – produces outsized gains but based on data from July 1927 to December 2010, authors Kent Daniel, Ravi Jagannathan and Soohun Kim, find that such strategy inflicts staggering losses suggesting that the strategy has a hidden bias in it.

“Given the low unconditional volatility of the momentum strategy, if returns were normal the probability of observing a month with a loss exceeding 42% in a sample of 1002 months would be one in 29,000, and the probability of seeing five or more months with losses exceeding 42% would be almost zero. Yet the lowest five monthly returns in the sample are: -79%, -60%, -46%, -44%, and -42%, a rare black swan like occurrence from the perspective of someone who believes that the time series of monthly momentum returns are generated from an i.i.d. normal distribution,” calculate the authors.

The authors then spend some time looking for a mathematical model that would capture these two states of events, and after some discussion they settle on the “two state hidden Markov model” – a jingo for breaking up the market into two characters: turbulent or calm.

Based on the 1002 months of data, the authors calculate that the “average duration of 16 months and turbulent months have an average duration of 4 months” and it is within these 4 months that these staggering losses occur.

“All the 13 months with losses exceeding 20%/month occur during turbulent months, i.e., months when the predicted probability of the hidden state being turbulent exceeds 0.5 [50%],” write the authors.

“We find that it is possible to predict which of the two hidden states the economy is in with some degree of confidence,” say the authors but even when “such turbulent states are avoided, the monthly Sharpe Ratio of momentum strategy returns increases to 0.32 and price momentum poses still more of a challenge to standard asset pricing models.”

Authors leave this “challenge” perhaps for another paper, but as far as this one is concerned, there are some additional informative data points.

For example, not every turbulent month produced negative returns but rather a subset within that time period. Out of 1002 trading months in the sample, 206 months are classified as turbulent and within this time only 124 months or 60% of the turbulent time produced negative returns on the momentum portfolio. Otherwise, on the whole of 1002, 303 months produced negative returns.

In other words, less then 12.5% of the trading time [124/1002] is responsible for the outsized negativity but being able to predict this small sliver of negativity can be nearly impossible: if in the standard normal distribution probability of a 79% loss is 3 x 10-24 [basically zero] then this is a good approximation of the probability of being able to guess when such a loss would occur in a non-normally distributed momentum strategy.

Ergo the confirmation of traditional trading dictums: can’t predict the direction of the market all the times; avoid momentum plays during turbulent times like these.

Paper is available here.

High uncertainty & growth correlated, paper

Bouts of increased uncertainty are associated with lower growth rates across western countries and therefore play a pivotal role in formation of an “observed equity premium and risk-free rate” in those countries, says the latest paper by three Columbia professors.

“Uncertainty shocks play an important role in generating movements in asset prices in our model. Shocks that raise expected future uncertainty lead stock prices to fall. And expected returns are predictably high following stock market declines provoked by such uncertainty shocks,” say authors Emi Nakamura, Dmitriy Sergeyev, Jon Steinsson in Growth-Rate and Uncertainty Shocks in Consumption: Cross-Country Evidence published in May.

For traders using volatility hedges like VIX, these presumptions maybe nothing new but, in the world of economics, where stylized models often clash with data, a model presented in this paper presents significant improvements in the research world while giving a glimpse as to where we may be in the longer set of financial trends.

For the research world, where uncertainty is sometimes an appendage to the end of an equation (stochastic variable) in order to make the model work, these authors link economic growth with uncertainty and convincingly show that there is a significant and negative correlation between the two.

“For the same utility function parameters, the model without growth-rate and uncertainty shocks generates an equity premium that is more than an order of magnitude smaller,” say the authors, meaning that absence of uncertainty in asset pricing models improperly prices those assets.

By using consumption-based asset pricing, the model authors develop pretty much corresponds to the bullish periods in the stock market: just replace (paragraph below) higher stock prices for every period where volatility has been calculated to have fallen.

“We estimate that world volatility was high in the early post-WWII period and has been on an uneven downward trend since then. World volatility fell a great deal in the 1960′s, but was high again in the 1970′s and early 1980′s. It fell sharply in the mid-to-late 1980′s but was relatively high in the early 1990′s | likely due to the ERM crisis in Europe. From 1995 to 2007 the world experienced a long period of relative tranquility with volatility falling sharply towards the end of this period to record lows. At the end of our sample period, world volatility rose sharply once again,” write the authors (graph above).

Model’s high conformity to reality has an additional interesting feature – the “sensitivity to the world growth-rate process”.

For example, by setting the sensitivity index of the US to 1, the current culprits of global financial troubles – Spain, Italy, Portugal and Belgium – have a visible high mean sensitivity index along with higher swings (standard deviation) in it (Table A.1).

If a person was to pick out the trouble spots just by looking at those numbers, absent any knowledge of the news, the countries listed in the table on the left clearly stand out. Of particular interest, at least in this exercise, would be Finland and The Netherlands, both considered to be part of the EU “core” and largely immune to the ongoing financial crisis… but are they?

Paper available here.

Federal spending on roads has huge GDP effect, paper

Federal government spending on highways has a huge positive effect on local economy and that such effects are much larger than any previous estimates, find the latest paper on this subject by the San Francisco Fed researchers.

“[W]e found that highway spending shocks positively affect GDP at two specific horizons. There is a significant impact in the first couple of years and then a larger second-round effect after six to eight years. Yet, we find no permanent effect, as GDP is back to pre-shock levels after ten years,” write authors Sylvain Leduc and Daniel Wilson.

The fall in GDO one year after spending starts is “not statistically significantly” meaning that it may not be attributable to the spending. Moreover, absence of a permanent effect of the spending on the GDP does not imply that there is no permanent effect on the broadening of the economic base. In fact, authors find that the GDP base as measured by the population expansion does have a permanent effect.

“Interestingly, population is the only variable that appears to be permanently affected by the highway shock. A natural interpretation of this result is that highway/road improvements enable population growth as, for example, new housing developments are built around new or improved roads and as new commuting options are made possible. Such a response is consistent with Duranton and Turner’s (2011) recent finding that increases in a state’s road lane-miles cause proportionate increases in vehicle miles traveled,” note the authors.

And how does all this happen?

“Combining these results with the macroeconomic responses in Figure 6, particularly the increase in GDP per worker 6-8 years after the shock, the results point to a possible productivity effect of improved highway infrastructure. Under this interpretation of our results, an initial shock to federal grants leads to highway construction activity over the following 3 to 5 years and results in new (or improved) highway capital put in place around 6-8 years out. In turn, the new highway capital triggers higher productivity in transportation-intensive sectors, reducing goods prices and boosting demand. Ultimately, the increase in economic activity raises state tax revenues and increases state government spending as a result,” note authors.

These broad range effects can be measured via multipliers – the amount of subsequent effect of the initial spending level where anything over 1 means that spending has much greater impact then its original value.

Although all of the multipliers are well over 1, there is some difference as to the funding scenario.

For example, highway spending via federal grants has “the multiplier on impact is about 3.4, the peak multiplier (at 6 years out) is 7.8, and the mean multiplier is 1.7.”

This means that each dollar federal government spends on local highway has a $3.40 immediate impact, peaks at $6 and has an average life effects of $1.70.

This scenario, however, does not consider the “flypaper effect” or the extent to which federal spending forces local governments to spend on maintenance.

Multiplier effect is much smaller if highway spending is done by the state with the “impact multiplier would be 2.7, the peak multiplier 5.9, and the mean multiplier 1.3.”

“The bottom line is that based on the most sensible measures of government highway infrastructure investment, the GDP multiplier implied by our estimated impulse responses appear to be considerably larger than those based on defense or overall government spending as estimated in previous studies,” say the authors.

Authors also find that highway spending during a recession has a much larger impact then during an expansion.

“Interestingly, the initial impact of highway spending shocks are much larger when they occur in state-years experiencing a recession. The impact elasticity in recessions is 0.028 (s.e. = 0.015), which is statistically significant at the 10% level and about twice as large as the average impact response,” calculate the authors.

Spending effects during an expansion produce negative results but are negligible.

“The impact elasticity in expansions, on the other hand, is slightly below zero and statistically insignificant,” say authors.

Authors also use their methodology to calculate effects of the 2009 government bail-out spending known as the 2009 American Recovery and Reinvestment Act.

“We find that both the contemporaneous and the year ahead effects on GDP were significantly higher from highway shocks in 2009 than the average effect over the 1993-2010 sample,” say the authors.

Paper is available here.

Easy credit part of the bubble fuel, paper

Easy credit and optimistic perception of fundamentals impacts price bubbles, notes recent NBER paper coauthored by a Fed economist.

In a study of the 1910s farm price bubble,  economists Raghuram Rajan and Rodney Ramcharan conclude that optimistic fundamentals in the commodities markets correlated with flood of credit to fuel farm price bubble which collapsed in 1920 when communists in Russia decided to starve their people by selling grain to the world in order to finance themselves.

“Thus both the perceived shock to fundamentals as well as the availability of credit seem to be correlated with higher land prices. What is particularly interesting is the interaction between the two. As the availability of credit increases from a low level, the shock to fundamentals is associated with a greater impact on land prices, suggesting that the availability of credit amplifies shocks,” say the authors.

To many, conclusions of this paper maybe nothing new but an affirmation of what goes on in the banking industry – loan officers flock to hot sectors in search of credit-worthy borrowers and, as a result, flood the sector with cash fueling prices.

Despite these affirmative qualities, this paper is significant for several additional reasons.

First, it contributes to an ongoing debate as to whether easy credit fuels bubbles in the first place. Glaeser, Gottleb and Gyourko, for example, argue convincingly that cheap credit explains very little of the housing bubble. They say that “lower real rates can explain only one-fifth of the rise in prices” and that they find “no convincing evidence that changes in approval rates or loan-to-value levels can explain the bulk of the changes in house prices”.

Other literature, obviously, disagrees with these conclusions and Rajan and Ramcharan conclusions belong in this camp.

Second, since the collapse in Lehman, the Fed has been increasingly looking at the issue of price bubbles seeking to get a theoretical handle on it with prospects of developing some measures to control them. The Fed is, of course, no longer dismissing bubbles as a phenomena that will correct itself and has hired its army of economists to look for a policy role for itself. This paper, of course, adds to this body of effort.

Third, and of contemporary  relevance, is that the the story of the 1920 farm price bubble collapse that one can read in this paper reminds all too much of the exuberance in today’s farm prices. Fueled by rise in corn prices, farm prices are sky high in places like Iowa.

For some parallel:

“The national average of farmland values was 68 percent higher in 1920 compared to 1914, and 22 percent higher compared to 1919,” say the authors.

“Iowa’s current statewide average price for farmland, $6,608 an acre, is a record in nominal dollars. But it’s also a record in inflation-adjusted dollars. Just before the crash in land values in the 1980s, Iowa land values had reached about $6,000 an acre in the 1970s,” writes Daniel Looker at agriculture.com.

The fundamental exuberance in today’s farm market has been corn price which has tripled on optimistic views for the corn demand used to make fuel with statistics showing that corn usage in making fuel has outstripped corn usage for food.

What’s different this time, investors argue, is the leverage.

“Mortgage debt per acre increased 135% from 1910 to 1920, approximately the same rate of increase as the per acre value of the ten leading crops,” write the authors.

“Investors discount worries of a price bubble, if only because the rapid appreciation in land doesn’t seem to be fueled by easy credit. In states such as Nebraska, roughly half the land purchases are for cash. The USDA estimates that farm real-estate debt fell 3% this year and remains 35% lower, on an inflation-adjusted basis, than 30 years ago,” says WSJ.

Of note is that the farmer income suffered for a long time when the bubble burst in 1920 even though those with high leverage got flushed out.

Paper is available here.

Rise of 1-percenters the cause to too much debt, paper

Financial market liberalization and the rise in income of the super-rich are a significant cause of too much government indebtedness says recent paper published by the Philadelphia Fed.

“In this paper we study a multicountry politico-economic model where the incentives of governments to borrow increase both when financial markets become internationally integrated and when inequality rises. We propose this mechanism as one of the possible explanations for the growing stocks of government debt observed in most of the advanced economies since the early 1980s. We have also conducted a cross-country empirical analysis using OECD data, and the results are consistent with the theoretical predictions,” write authors Marina Azzimonti, Eva de Francisco, and Vincenzo Quadrini.

How so?

Financial market liberalization induces lower elasticity of the interest rate meaning that as the market for debt enlarges the rise of new net debt is proportionally smaller to the overall market then it would be in a closed, autarkic situation. In other word, open and large financial markets cause interest rates to be less responsive to new government debt issuance.

“The difference is that in autarky the interest rate is determined only by domestic debt… With mobility, the interest rate is a function of average worldwide debt… Therefore, when the domestic government considers a change in B’ [new debt], the induced change in worldwide debt… is smaller than in the autarky regime… Effectively, the worldwide interest rate is perceived by each individual government as being less elastic to its own supply of bonds. This changes the (individual) incentive to issue debt because the marginal increase in the repayment costs R is lower,” explain the authors.

This approach also explains why so many small economies, particularly in the EU, found debt as a great substitute for consumption.

“Since small countries face a larger world market relative to their own economy, they perceive the world interest rate as less sensitive to their own per-capita debt. As a result, they issue more debt,” note the authors.

In both country sizes, explain the authors, the workers and the entrepreneurs both look positively on borrowing.

For workers, the financial liberalization lowers the rate at which they can borrow but over a longer period, workers’ “consumption stabilizes at a lower level than the consumption in the autarky steady state. This is because the higher debt implies higher payment of interests and, therefore, lower transfers to workers (which become negative in the long run).”

As a result, welfare gains from liberalization, in the long run, accrue to the entrepreneurs (graph below)

Now, many authors argue that that financial liberalization is the direct cause of the rise in the super-rich but in this paper, the authors treat the super-rich, euphemistically referred to as an income inequality event, as a separate variable apart from the financial liberalization.

Financial liberalization, explain the authors, increases idiosyncratic risk, an event detrimental to smoothing of the entrepreneurial income and wealth. As the idiosyncratic risk rises, entrepreneurs prefer more government debt so that they can park their wealth into and derive risk-free income from government debt paper.

For the super-rich, in essence, government debt is an insurance policy that preserves their huge wealth, income and status while shifting risk associated with such wealth onto a larger debt-fiduciary pool that provides such insurance.

The authors also provide some numbers of these effects.

“The increase in income inequality is generated by a higher volatility of the idiosyncratic risk, which changes from [delta] = 0.91 to [delta] = 0.984. As described above, [delta] = 0.91 was chosen to generate the 6% concentration of income at the top 1% in the autarky steady state. The new value is chosen to have a share of 9% for the top income earners in the steady state with capital mobility,” say the authors.

As a result see, “the increase in inequality (ignoring liberalization), increases long-term debt from 30% of income to about 55% of income. If we focus instead on capital liberalization alone (keeping inequality constant), long-term debt increases to 51% of income. When the two changes are considered together, long-term debt increases to 73%,” calculate the authors.

Nor is the private debt an equal substitute for the public one.

“If governments have higher credit capacity than workers, then the economy with public debt will not be equivalent to the economy with private debt since the latter will have zero or insufficient private debt,” say the authors.

Finally a note on sovereign debt crisis…

“If debt crises are more likely to arise when the stock of public debt is higher, then the growth in government borrowing induced by capital markets liberalization and increased income inequality may contribute to trigger a sovereign debt crisis,” say the authors but the extent of that is altogether another paper.

Available here.