Asymmetric information: the multiplier
effect of financial instability
Erasmus University Rotterdam
Financial markets and financial intermediation are
essential to well-functioning economy. They perform the
role of channeling funds to parties that have value creating
investment opportunities. However, asymmetric
information can seriously impair the process when parties
to the financial contract are not fully aware of the risks
involved and, as a result, can limit their exposure to
financial agreements to prevent themselves from possible
losses. Increasing asymmetric information as we explain in
the article has a tendency to bring a ripple effect in the
financial system. This negative money multiplier then sets
the stage until it severely hampers money supply,
productive investment opportunities and finally aggregate
economic activity. The article introduces the reader with
the framework of asymmetric information developed by
several authors in the last few decades and builds on the
recent financial developments that pose new challenges.
The theory of asymmetric information is one of the most powerful framework theories that can explain
data patterns in the different factors during the periods of economic crises.
The academics have analyzed the asymmetric information and its consequences that arise due to
dissimilarities of information that is available to parties that enter financial agreements. Often the main
problem is that borrowers are more alert of pitfalls of financial contract since they are better aware of
the risks involved in a project for which financing is requested. These informational differences are the
very underlying cause of adverse selection or what is already known as the lemons problem which was
introduced by Akerlof in 1970. A lemons problem occurs in debt markets because lenders have trouble
determining whether borrower’s investment opportunities are attractive enough compared to the level
of risk involved (i.e. he is a “good risk” or “bad risk”). When that happens, lenders provide loans at an
average interest rate that balances off expected return for a loan portfolio that constitutes both high
quality and low quality credits. Presumably, one can see this as a fact that risks and the associated
required return for high quality borrowers is overstated, whereas that of low quality borrowers is
understated. Lenders tend to average out these differences; as a result, high quality borrowers end up
paying more, whereas low quality borrowers less than they should. If that happens, high quality
borrowers will not seek financing and forego profitable investment opportunities.
Furthermore, as demonstrated by Stiglitz and Weiss (1981), borrowers with the riskiest investment
projects will now be the ones most likely to take out the loans at high interest rates, since they will reap
the benefits and leave the loses for lenders should they occur. These risky undertakings on behalf of
borrowers will result in lenders cutting down on the number of loans that they make, this way causing
the supply of loans decrease with higher interest rates more than it would at equilibrium. Mankiw
(1986) has shown that a marginal increase in the risk-free rate can significantly decrease or even cause a
collapse in lending through the ripple effect described above.
The mechanism suggests that a major sign of financial crisis would be a significant increase in interest
rate of loans available for those borrowers whose risk characteristics are hard to identify. Higher and
lower grade bond yields essentially reflect the perception about the risk related to the undertakings of
higher and lower quality borrowers. This perception might arise either because the lenders are well
aware of the risks related to both high and low quality borrowers, or more likely, because information
about the low quality borrowers is not available. As a result, the large spread between high and low
grade bonds should signal when the adverse selection problem in the debt markets is far stretching.
To reduce the adverse selection problem in debt markets lenders secure their loans with collaterals or
with the borrowers’ net worth. However, value of collateral or net worth can decrease because of lower
future income streams (ex. market crash, see Greenwald and Stiglitz, 1988, Bernanke and Gertler, 1989)
or increased interest rates at which one discounts these income streams. As a result, should a borrower
default in any of these cases, the lender will bear higher losses not covered by the value of collateral.
Just as before, we expect that the adverse selection problem stemming from the situation will again
widen the spread of interest rates on loans between low-quality and high-quality borrowers due to
differences in information available on the two groups of borrowers.
Asymmetric information also leads to moral hazard problem between the parties to the contract that
again impairs financial efficiency. Moral hazard refers to borrower’s behavior that occurs after the
financing has been obtained. Because lenders are not fully able to ascertain the quality of investment or
monitor the use of the funds, the borrower has incentive to engage in personally beneficial activities (ex.
excessive risk taking, misallocation of funds) that increases the probability of default and deteriorates
the quality of loan. The borrower will reap the benefits should it turn for the best, while lender will bear
the losses if borrower defaults.
This agency problem between the contract
parties will result in suboptimal levels of
financing as lenders cut down on number of
loans trying to limit themselves from the
The agency problem will further amplify the
ripple effect on the aggregate economy
should there occur an unanticipated
deflation. Under deflation, real value of
debt grows while the real value of assets
does not and wealth is redistributed to
lenders at the expense of borrowers.
Shrinking net worth of borrowers would
prevent them from new undertakings which
would eventually lead to decline in
investment and economic activity.
The presence of information asymmetries
in debt markets explains the vital role that
banks play in reducing adverse selection and moral hazard in credit markets through financial
The expertise that they have in screening and distinguishing bad borrowers from good ones allows them
to reduce information asymmetries at low cost (Stiglitz and Weiss, 1983).
1.1 2008 Financial Turmoil and the “Lemon Brothers”
The failure of financial intermediation and the resulting
increase in asymmetric information is a probably the simplest
best way to explain the recent financial turmoil that has led to
Slowing economy coupled with insolvency of mortgage
borrowers and the housing market crash caused the value of
collaterals to drop sharply. Huge losses related to mortgage
related debt instruments pushed a major financial institution –
Lehman Brothers - into bankruptcy and caused increased risk-
aversion in the markets. Because many financial and non-
financial institutions had exposure to these collateralized debt
obligations, banks stopped the lending since they could not
distinguish between those who had loss bearing positions in
CDOs and could default and those who were not. This has lead
to an immediate spike in interest rates and dry-up of liquidity
in debt markets. As a result, even largest and most prominent
US bluechips could not access debt markets to fund their
operations and investment activities. This caused a severe
drop in production output and a contraction in aggregate
They are more efficient than individuals in monitoring the contracts and enforcing restrictive covenants
that reduce moral hazard problem that is likely to arise (Diamond, 1984).
The existence of asymmetric information in debt markets gives us an important underlying rationale
about the significance of banks in channeling funds from savers to borrowers who have the most
attractive investment opportunities. Bernanke (1983) also argued that turmoil in financial markets often
harms intermediation performed by banks and brings down financing of valuable investment
opportunities which in the end leads to economic downturn.
Bank panics are one major example of the failure of banks to fully perform their intermediation role. In
a panic, depositors, fearing the safety of their deposits, withdraw them from the banking system and
cause a major wipe out of funds and significant reduction in lending activities of banks. Undoubtedly the
asymmetric information is one of the main ingredients of financial panic. As depositors are not able to
distinguish between solvent and insolvent banks they rush to withdraw funds from all of the banks that
could possibly fail to meet their obligations or return the deposits in time. The resulting capital deposit
outflow bank capital to level where they either cannot meet their obligations, provide new loans or
both. Cost of financial intermediation rises, new profitable investment opportunities are not financed
and as there is no value created in the economy, it slips into recession.
Given the absence of intervention of policy makers, bank panic decreases liquidity which leads to higher
interest rates. The ripple effect continues since higher interest rates as mentioned previously (adverse
selection) decreases firm value. Therefore, bank run is another channel through which asymmetric
information both enters the financial markets as well as is further reinforced. Again, as a result, there
should be a pattern of widening spreads between lower and higher grade investments in the dawn of
All in all, asymmetric information is a very powerful framework that presents the dynamics and resulting
downturn that happen once there is a decrease in money supply. However, decline in money supply is
not the only area of financial discrepancies that asymmetric information can explain. Instead, one
should take a much broader picture to see informational asymmetries that exist in financial markets (see
box 1.2) that can induce a financial meltdown.
1.2 Asymmetric Information and Financial Derivatives
It appears that with the evolution of financial system and financial products, there not only has been a significant improvement in the
reduction of information asymmetries in the financial markets through major advances in technology and regulation, but also hand in
hand increase in information asymmetries through off-balance sheet trading activities in highly complex structured derivative
products and OTC (over-the-counter) market development. Not to mention that, even simple derivative products such as forwards
that exhibit steeper pay-off schemes than that of the underlying asset already amplify the consequences of asymmetric information
through implicit leverage if a party to the contract fails to follow agreement. This can make even simple and sound linear derivative
contracts very risky. Meanwhile, OTC markets allow for less transparency on such agreements. To continue with the example, OTC
forward agreements unlike their peer contracts traded on an exchange, i.e. futures, allow parties to engage into contract and settle it
only on the maturity; this way party losing money in the contract avoids daily margin calls to cover marginal losses should the market
turn out unfavorable. Again asymmetric information and specifically moral hazard is at its height since party to the contract is not
aware if the counterparty will be able to meet the obligations on maturity. The loses by the end of the contract might be so huge that
the party losing money might not be able to follow the agreement. Finally, even more complex derivative contracts such as CDOs
enable debt to be repackaged and resold to multiple buyers while staying off the bank’s balance sheets; the debt loses its origins –
risk characteristics are modified and information related to the original debtor is lost. Instead, risk characteristics are assigned by
parties that are intermediating the contract (i.e. investment banks) as well as those that are trusted to monitor them (i.e. rating
agencies). Such structure of funneling funds through essentially multiple stages increases significantly asymmetric information
between the initial borrower and the final lender, whereas the responsibility of reducing these asymmetries is then concentrated in
the hands of several institutions which - as recent events show – happen to fail in their roles.
Having said that, it seems that with the development of financial world, asymmetric information, at least in certain markets, has been
only increasing. No wonder that one of the world’s most renowned investors Warren Buffett has called derivatives the financial
weapons of mass destruction.
Historically, financial crises have begun with stock market crash, rise in interest rates and resulting credit
spread rather than with a failure of a financial institution, with the latter more likely being a
consequence than a cause. The failure of a major financial intermediary however significantly increases
the uncertainty in the market (see the box 1.1). Ceteris paribus, asymmetric information introduces a
multiplier effect through which rise in interest rates raises lemons problem in the credit markets, agency
problem and value destruction in stock markets. Failing banking institutions make the interest rates
rocket, cause the final stock market crash both of which are reflected in the widening credit spreads
between high grade and lower grade bonds. The events amplify asymmetric information to the degree
where economic growth is halted.
There would be sorting of solvent from insolvent banks through public authorities and clearing-house
associations (Mishkin, 1990). Furthermore, government as we have seen recently might induce money
supply by providing liquidity. Uncertainty would slowly fade out, markets might recover, interest rates
fall back and if deflationary processes would not pertain, one might see credit spreads shrinking and
economy recovering as seen through 2009.
This course of events might be hampered if a substantial deflation sets in, leading to a debt-deflation
process that transfers wealth from debtors to creditors as described by Fisher Irving (1933) and
deteriorates the value of the companies. Should that happen, given already lower demand for products
balance sheets of companies would worsen leaving them with excessive liabilities, liquidity problems
and potential bankruptcy as seen in major corporations in Japan in 1990’s. Investment spending and
aggregate economy would then remain depressed for a longer period of time.
As you can see from the figure 1.1, theory is rather consistent with the empirical data. Credit spreads
seem to balloon in the dawn of a crisis and during recessions. In addition, an interesting finding is that of
the recent crisis. Apparently seeing signs of slowing economy on August 2007 Federal Reserve of the
United States cut interest rates to induce monetary supply. Despite that, later next month the yield
US Credit Spreads and Business Cycle
Baa-10 Year Treasuries
Source:Authors calculations based on NBER, Federal Reserve & Moody's data
spread between Baa graded bonds and 10-Year treasuries had already been at 20 year historical heights
well above 2 percentage points. FED continued cutting interest rates in the following months, however,
that did not stimulate economy sufficiently and on December 2007 the United States had slipped into
recession which turned out to be comparable in scale to the Great Depression.
More than that, it is surprising to see how Mishkin (2000) has presented the vicious cycle to the Central
Bank of Iceland in his later work just to see the meltdown of the county’s financial system ten years
To test the predictive power of credit spreads and stock market we ran multiple least squares
regressions between credits spreads, stock market and US industrial output using different time lags.
Sample period dating back to 1920’s has been used. We have found that over the period from 1920’s
until 2010 stock market has had the most explanatory power in predicting negative industrial output 4
months before it has occurred, whereas wide credit spreads 1 month before the crisis. A sample
regression in figure 1.2 below shows that despite the fact that the credit spreads between high and low
quality borrowers have marginal explanatory power for fully predicting economic activity, i.e. low R^2, it
shows that it is significant to the variation of US industrial output, i.e. high t-value. This is however
consistent with the fact that timely and well measured monetary easing and liquidity injections from
central bank not accounted for in the regression often induce lending activities by banks, reduce high
risk-aversion and information asymmetries in the market that are then reflected in the back drop of
credit spreads, the result of all which is a prevention financial and economic paralysis.
All in all, although there has been empirical evidence that the degree of asymmetric information has
diminished over the course of financial development1, new century and financial derivates for which
asymmetric information seems to be second nature pose new challenges that we should take very
Dependent Variable: IND (US Industrial output)
Method: Least Squares
Sample (adjusted): 2 637
Included observations: 636 after adjustments
Newey-West HAC Standard Errors & Covariance (lag truncation=6)
Coefficient Std. Error t-Statistic Prob.
S.E. of regression
Sum squared resid
0.046140 Mean dependent var
0.044636 S.D. dependent var
0.854592 Akaike info criterion
463.0272 Schwarz criterion
-801.5076 Durbin-Watson stat
1 See Antzoulatos, Tsoumas, Kyriazis (2008), Financial Development and Asymmetric Information
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Journal of Economics, 84: 488-500.
Antzoulatos, A., Tsoumas, C., Kyriazis , D.(2008), “Financial Development and Asymmetric Information”
Bernanke, B.S. and M. Gertler (1989). "Agency Costs, Collateral, and Business Fluctuations", American
Economic Review, 79: 14-31.
Bernanke, Ben S. 1983. “Non-Monetary Effects of the Financial Crisis in the Propagation of the Great
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Mishkin, F.S. (1991). "Asymmetric Information and Financial Crises: A Historical Perspective", in R.G.
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