Question

Asymmetric information is the phenomenon where one person (seller or buyer) in a market transaction acts on information the other does not have. How did no-doc mortgages, ARMs, and CDOs give evidence of asymmetric information?  How did the regulators fail to act to prevent the crisis?

Answer 1

The mortgage market was the starting point for several of the post-Lehman crises: the subprime crisis, the Irish crisis, the Spanish crisis, and many more. It is a market typified by massive information asymmetries, and it has been argued that a market based on highly asymmetric information contributed to the buildup of bad mortgage debt during the first half of the last decade.

In tracking down the links between asymmetry of information and bad mortgage debt, most research has focused on asymmetric information concerning repayment characteristics of borrowers (Elul 2009, Keys et al. 2010). Similarly, much of the recent policy discussion that has aimed to address the issue of asymmetric information in mortgage lending has focused on proposals that alleviate information asymmetries about borrower characteristics, for instance the debate on the removal of low-documentation mortgages.

A different perspective, collateral value of property

But there is another key source of information asymmetry: the collateral value of properties. Due to the illiquid and heterogeneous nature of housing, knowing a property’s true worth is difficult. In recent research (Stroebel 2012) I empirically analyse the sources and magnitude of asymmetric information between lenders, and find these lenders to differ significantly in their information about true underlying housing collateral values. From a policy perspective, the identification of collateral values as a key source of asymmetric information in mortgage lending helps to develop proposals to improve the functioning of the market. For example, it suggests that better credit scoring technology and the more extensive sharing of borrower information will not address all forms of asymmetric information and that policies to address asymmetric information about collateral quality are also important.

The focus on lenders that compete to originate mortgages used to purchase newly constructed properties. This market is characterised by property developers regularly providing home buyers with mortgage financing offers through vertically integrated mortgage lenders. These integrated lenders might have better information than non-integrated lenders about aspects of construction quality that are difficult for non-integrated lenders to observe. Such information might include, for example, the skills of the individual subcontractors constructing neighboring homes within a development. I find that such asymmetric information about collateral quality is a significant source of adverse selection in this market. In addition to testing for the presence of asymmetric information and uncovering its sources, also quantify the impact of this asymmetric information on the cost of mortgages, which I find to be significant.

• A model of integrated lenders and non-integrated lenders

A simple theoretical model is used to guide the analysis of the competition between the better informed integrated lender and other non-integrated lenders. In the model, an integrated lender obtains an informative signal about the quality of the housing collateral, while competing lenders only know the average collateral quality. The better informed integrated lender conditions its financing offer on its superior information (offering lower interest rates for mortgages secured by higher-quality collateral) and thereby subjects non-integrated lenders to adverse selection, similar to a ‘winner’s curse’, where the winner tends to overpay. As true house quality is revealed over time, those homes initially financed by an integrated lender should thus experience larger price increases relative to ex-ante similar homes financed by non-integrated lenders. This effect is bigger when the integrated lender's signal about collateral quality is more precise. To compensate for the adverse selection, non-integrated lenders charge higher interest rates to break even than if they were competing only against equally informed lenders. Interest rates rise by more for borrowers whose repayment is more sensitive to changes in collateral values, for example because they make a smaller downpayment.

It shows empirically that such asymmetric information between competing lenders is in fact an important feature in the financing of newly developed homes. I construct a dataset of all housing transactions and associated mortgages in Arizona between 2000 and 2011 to track the return of properties following their initial sale. About 85% of new homes are in developments with an active integrated lender, and, when present, the average market share of these integrated lenders is about 73%. I find that in developments with an integrated lender, those houses financed by the integrated lender outperform ex-ante similar houses in the same development financed by non-integrated lenders by an average of 40 basis points annually. When I consider the distribution of returns, I find that the 40 basis point mean return difference is usually driven by a lower probability of the integrated lender financing houses that experience very significant capital losses (i.e. a thinner left-tail in the distribution of returns conditional on observable characteristics). This is suggests that the information of the integrated lender is related to the relative likelihood of low-probability, high-cost events, such as the cracking of foundations. I also find that mortgages financed by an integrated lender are over 40% less likely to enter into foreclosure than ex-ante observationally similar mortgages financed by other lenders.

An important result is that the annual outperformance of the integrated lender's collateral portfolio is larger (about 100 basis points) amongst houses built on ‘expansive soil’, a high-clay content soil that makes housing returns more sensitive to unobservable aspects of construction quality such as the care with which the foundation was poured. This result provides additional evidence that the construction quality of the housing collateral is a significant source of asymmetric information.

• Foreclosures

I also compare the return and foreclosure probability for the ownership duration of the second owner of the house. The relative outperformance of those houses initially financed by the integrated lender remains the same. This result confirms that the outperformance is to a large extent explained by asymmetric information about the housing collateral, not the borrower, since the identity of a possible second owner of the house was not known to any lender at the time the mortgage was granted to the initial owner.

To further test the theory, I analyse textual descriptions of houses in ‘for sale’ property listings. I scan these property listings for evidence of significant depreciation and identify listings that signal damage to the property. I find that when they are listed for resale, those houses initially financed by integrated lenders are less likely to contain evidence of damage to the property than ex-ante similar homes financed by non-integrated lenders, suggesting that the integrated lender's outperformance can be best explained by differential depreciation rates of houses, not differential initial pricing.

also analyse the cost to borrowers in terms of higher interest rates that result from this asymmetric information. I find that non-integrated lenders charge an average interest rate premium of about ten basis points annually for otherwise similar mortgages when competing against an integrated lender. This higher interest rate compensates non-integrated lenders for the adverse selection in the presence of an integrated lender. As predicted by the model, the interest rate increase is larger for mortgages with a low downpayment, rising to almost 50 basis points annually for mortgages with a downpayment of less than 3%. For those mortgages the repayment probability is more sensitive to changes in collateral values. Non-integrated lenders thus need to charge higher interest rates to break even when facing adverse selection on collateral quality.

• Insights

In addition to help inform the debate about policies to limit the impact of information asymmetries in mortgage lending, this project also provides insights into the lending behaviour of financial institutions in the pre-crisis period 2000-2007. It has sometimes been argued that due to the lack of ‘skin in the game’ – where high-ranking individuals invest in the companies they run – generated by securitisation or agency problems within firms, many loan officers no longer had incentives to distinguish between borrowers and collateral of differential quality, which could help to explain the lower quality of mortgages originated. In contrast, the evidence uncovered in this project is highly consistent with lenders actually attempting to price cross-sectional differences in collateral quality in a highly sophisticated manner.

This project provides new evidence on the role of integrated lenders during the recent construction boom, and suggests that rather than making low-quality mortgages in order to sell more houses, integrated lenders were actually able to select an equilibrium portfolio of mortgages that was of higher quality than that of competing non-integrated lenders.

• Why is a Government Safety Net Needed?

A government safety net for the banking system is needed because of the existence of asymmetric information in the banking system: that is, banking institutions (defined here as including both commercial banks and thrift institutions) engage in activities such as making private loans that are not transparent to depositors. Thus asymmetric information exists because the banking institution knows more about the riskiness inherent in its activities than do its depositors.  

As a result, depositors_ lack of information about the quality of bank assets or the market risk exposure it is carrying can lead to bank panics which can have serious harmful consequences for the economy. This can be easily understood by considering the following situation. Suppose there is no deposit insurance, and an adverse shock hits the economy. As a result of the shock, 5% of the banks have such large losses on loans that they become insolvent (have a negative net worth and so are bankrupt). Because of asymmetric information, depositors are unable to tell whether their bank is a good bank or one of the 5% of banks that are insolvent. Depositors at bad and good banks recognize that they may not get back 100 cents on the dollar for their deposits and will want to withdraw them. Indeed, because banks operate on a sequential service constraint (a first-come, first-served basis), depositors have a very strong incentive to show up at the bank first because if they are last in line, the bank may run out of funds and they will get nothing. Uncertainty about the health of the banking system in general can lead to runs on banks both good and bad, and the failure of one bank can hasten the failure of others producing a contagion effect. If nothing is done to restore the public_s confidence, a bank panic can ensue.  

Indeed, bank panics were a fact of American life in the nineteenth and early twentieth centuries, with major ones occurring every 20 years or so in 1819, 1837, 1857, 1873, 1884, 1893, 1907, an9.1930_1933. Bank failures were a serious problem even during the boom years of the 1920s, when the number of bank failures averaged around 600 per year.  

A government safety net for depositors can short circuit runs on banks and bank panics, and by protecting the depositor can remove their reluctance to put their funds in the banking system.  

One form of the safety net is deposit insurance, a guarantee such as that provided by the Federal Deposit Insurance Corporation (FDIC) in the United States in which depositors are paid off in full on the first $100,000 they have deposited in the bank no matter what happens to the bank. With fully insured deposits, depositors don -t need to run to the bank to make withdrawals -even if they are worried about the bank_ s health_ because their deposits will be worth 100 cents on the dollar no matter what. From 1930 to 1933, the years immediately preceding the creation of the FDIC, the number of bank failures averaged over 2000 per year, producing a severe banking crisis that is now viewed as the source of the worst contraction in economic activity in U.S. history. After the establishment of the FDIC in 1934, the United States has been free of bank panics. Indeed, bank failures averaged less than 15 per year until 1981, but then rose to the 200 level in the late 1980s.  

It is important to recognize that deposit insurance is not the only way in which governments provide a safety net to depositors. In other countries, governments have often stood ready to provide support to domestic banks when they face runs even in the absence of explicit deposit insurance. This support is sometimes provided by lending from the central bank to troubled institutions, and is often referred to as the "lender-of-last-resort" role of the central bank. In other cases, funds are provided directly by the government to troubled institutions, or these institutions are taken over by the government and the government then guarantees that depositors will receive their money in full.