Thursday, August 04, 2011

Identifying Asset Bubbles Before They Get Dangerously Big

Several years ago, I considered trying to obtain funding for a project aimed at providing policymakers with tools to identify bubbles before they grow to dangerous proportions. For a variety of reasons I did not pursue the project but I have mentioned the basic ideas several times and they have taken on a cyber life of their own. I therefore post below my notions on the subject as I wrote them back in 2008-9. 

Ex Ante Identification of Asset Bubbles

By Robert E. Wright, Nef Family Chair of Political Economy, Augustana College SD

Perhaps some readers will turn their attention to developing empirical tests that can reliably distinguish between bubbles and other phenomena that affect asset prices, of which there is now a shortage (LeRoy 2004).

Crises, major and minor, litter financial history. Most crises, including the most recent one, occurred when rapidly declining asset values caused the failure of highly leveraged investors, leading to credit constraints that negatively impacted the financial system and aggregate output (Kindleberger 2000). The frequency and severity of financial crises would be diminished if asset bubbles could be identified ex ante, to wit before they become large enough to pose a major threat to macroeconomic stability. U.S. policymakers admit that bubbles (“rational” or otherwise) are possible and potentially destabilizing but believe that they cannot be identified ex ante (Raines et al 2007). Even if they were detectable, the proper policy response would remain far from clear (Barlevy 2007). Academic economists debate whether bubbles can be identified econometrically even ex post (Gurkaynak 2008; Bhattacharya and Yu 2008)!

Contrary to O’Hara’s (2008) claim that no clear “operational way to establish empirically the existence of a bubble” exists, this paper hypothesizes that the likelihood of bubble formation in specific markets can be estimated ex ante and that regulators can implement inexpensive policies to minimize them. Building on Allen et al (1993), bubbles are more likely to form in markets for assets that:
a)      can be shorted or otherwise arbitraged only at great expense (Abreu and Brunnermeier 2003; Brunnermeier 2007);
b)      can be purchased with cheap borrowed money;
c)      are subject to high agency costs, including poor corporate governance (Benmelech et al 2008);
d)     have recently attracted numerous (Tirole 1982)[1] inexperienced participants (Porter and Smith 2003; Greenwood and Nagel 2008);
e)      are subject to higher levels of risk-taking due to the moral hazard created by repeated recent bailouts (Hetzel 2009).

The paper will formalize the model then test it empirically using evidence from a wide range of markets spanning the globe and several centuries. Shorting costs will be proxied by a new index, borrowing costs with appropriate interest rates (using Homer and Sylla 2005 for historical markets) compared to the Taylor Rule (McKinnon 2008), corporate governance with an index such as Nicolo 2008, new market participants by market entry costs, and moral hazard by the number and nature of government bailouts in the period prior to bubble formation (Reinhart and Rogoff 2008a, b). Bubbles are assumed to have caused all financial crises without obvious non-bubble causes, such as military defeats (e.g. the sack of Washington, D.C. in August 1814, which triggered the suspension of payments in banks south and west of the Hudson river) and natural disasters (e.g. the Kanto earthquake of 1923, which caused a Japanese banking crisis).

An initial literature survey suggests that the model will receive ample empirical support. From alpacas to sugar beets to thoroughbred racehorses, agricultural markets are particularly prone to asset bubble formation because shorting is impossible (except in the limited sense of selling the asset) and investor entry barriers low (Saitone and Sexton 2007). As an example of agency costs, hedge funds and mutual funds knowingly invested in overvalued stocks in the late 1990s when investors compensated them to achieve short-term returns similar to other funds in the same class. When rewarded for longer term or above average returns, by contrast, funds invested much less in overvalued stocks (Dass et al 2008). Historically, many bubbles have involved real estate, which suffers from short sale constraints and entry barriers low enough that a significant number of traders may suffer from basic fallacies such as money illusion (Brunnermeier and Julliard 2008).

If bubbles can be identified ex ante, the appropriate regulators should monitor markets at high risk for bubble formation, ensure that participants are aware of that fact, and credibly warn them that government bailouts will not be available (Hetzel 2009) or that access to the safety net will be appropriately priced (Acharya and Richardson 2009). Government intervention in this manner is Pareto improving because short-circuiting the price-to-price feedback loop at the heart of most bubbles is inexpensive relative to blunter monetary policy options (e.g., increasing the Fed funds rate), limits the moral hazard and redistribution associated with bailouts (Wright 2009), and provides an information and analysis service that market participants are unable to provide or reliably obtain themselves. Agency ratings have again proven themselves impotent due to the conflict of interest at the heart of their current business model (namely, receiving the bulk of their revenue from issuers) and other problems (Partnoy 1999). Moreover, market participants apparently have difficulty incorporating highly relevant historical precedents into their market forecasting. For example, apparently no major investment bank executive knew that six earlier U.S. mortgage securitization schemes had failed due to incentive misalignments between originators and ultimate investors, a misalignment identically replicated in the 21st century (Snowden 1995). Similarly, many home buyers apparently did not realize that the long-term upward trend in house prices did not mean that prices were monotonic. In fact, the trend has been repeatedly punctuated with reversals (White 2008).

Regulators could also reduce the likelihood of bubbles by encouraging the development of inexpensive shorting mechanisms, enacting policies to improve corporate governance and investment fund contracts, and to limit access to markets by inexperienced participants more efficiently than is currently done. (For example, accredited investor status might best be subject to examination as well as asset and income limitations.) The paper will not address any of these complex areas in detail but will offer them as potential policy options requiring additional research.


Abreu, Dilip and Markus Brunnermeier. (2003) “Bubbles and Crashes.” Econometrica 71:173-204.
Acharya, Viral and Matthew Richardson, ed. (2009) Restoring Financial Stability: How to Repair a Failed System. Hoboken: Wiley.
Allen, Franklin, Stephen Morris, and Andrew Postlewaite. (1993) “Finite Bubbles with Short Sale Constraints and Asymmetric Information.” Journal of Economic Theory 61:206-29.
Barlevy, Gadi. (2007) “Economic Theory and Asset Bubbles.” Economic Perspectives: Federal Reserve Bank of Chicago 3Q:44-59.
Benmelech, Efraim, Eugene Kandel, and Pietro Veronesi. (2008) “Stock-Based Compensation and CEO (Dis)incentives.” NBER Working Paper 13732.
Bhattacharya, Utpal and Xiaoyun Yu. (2008) “The Causes and Consequences of Recent Financial Market Bubbles: An Introduction.” Review of Financial Studies 21:3-10.
Brunnermeier, Markus. (2007) “Bubbles.” In The New Palgrave Dictionary of Economics. New York: Oxford University Press.
Brunnermeier, Markus and Christian Julliard. (2008) “Money Illusion and Housing Frenzies.” Review of Financial Studies 21:135-180.
Dass, Nishant, Massimo Massa, and Rajdeep Patgiri (2008). “Mutual Funds and Bubbles: The Surprising Role of Contractual Incentives.” Review of Financial Studies 21:51-99.
Greenwood, Robin and Stefan Nagel (2008) “Inexperience Investors and Bubbles.” NBER Working Paper #14111.
Gurkaynak, Refet. (2008) “Econometric Tests of Asset Price Bubbles: Taking Stock.” Journal of Economic Surveys 22:166-86.
Hetzel, Robert. (2009) “Government Intervention in Financial Markets: Stabilizing or Destabilizing?” Federal Reserve Bank of Richmond. Working Paper.
Homer, Sidney and Richard Sylla. (2005) A History of Interest Rates. 4th ed. Hoboken: Wiley.
Kindleberger, Charles. (2000) Manias, Panics, and Crashes: A History of Financial Crises. 4th ed. Hoboken: Wiley.
LeRoy, Stephen. (2004) “Rational Exuberance.” Journal of Economic Literature 42:783-804.
McKinnon, Ronald. (2008) “Bagehot’s Lessons for the Fed.” Wall Street Journal 25 April.
Nicolo, Gianni, Luc Laeven, and Kenichi Ueda. (2008) “Corporate Governance Quality: Trends and Real Effects.” Journal of Financial Intermediation 17:198-228.
O’Hara, Maureen (2008) “Bubbles: Some Perspectives (and Loose Talk) from History.” Review of Financial Studies 21:11-17.
Partnoy, Frank. (1999) “The Siskel and Ebert of Financial Markets?: Two Thumbs Down for the Credit Rating Agencies.” Washington University Law Quarterly 77:619-714.
Porter, David and Vernon Smith (2003) “Stock Market Bubbles in the Laboratory.” Journal of Behavioral Finance 4:7-20.
Raines, J. Patrick, J. Ashley McLeod, and Charles Leathers. (2007) “Theories of Stock Prices and the Greenspan-Bernanke Doctrine on Stock Market Bubbles.” Journal of Post Keynesian Economics 29:393-408.
Reinhart, Carmen and Kenneth Rogoff. (2008a) “Banking Crises: An Equal Opportunity Menace.” NBER Working Paper 14587.
Reinhart, Carmen and Kenneth Rogoff. (2008b) “This Time Is Different: A Panoramic View of Eight Centuries of Financial Crises.” Working Paper, April.
Saitone, Tina and Richard Sexton. “Alpaca Lies? Speculative Bubbles in Agriculture: Whey They Happen and How to Recognize Them.” Review of Agricultural Economics 29:286-305.
Shiller, Robert J. (2003) New Financial Order: Risk in the 21st Century. Princeton: Princeton University Press.
Tirole, Jean. (1982) “On the Possibility of Speculation Under Rational Expectations.” Econometrica 50:1,163-81
White, Eugene. (2008) “The Great American Real Estate Bubble of the 1920s: Causes and Consequences.” Rutgers University Working Paper. October.
Wright, Robert E., ed. (2009) Bailouts: Public Money, Private Risk. New York: Columbia University Press.

[1] The number of investors need not be infinite, as some have argued, because that assumption is empirically fragile (Abel et al 1989). Rather, I’ll argue that the expected stream of new investors needs to grow fast enough to support expectations of rising prices. Bubbles burst when that condition is violated.

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