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    Greenwood, Robin, Andrei Shleifer, and Yang You. 2019. “Bubbles for Fama.” Journal of Financial Economics 131 (1): 20-43. Abstract
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    We evaluate Eugene Fama’s claim that stock prices do not exhibit price bubbles. Based on US industry returns 1926-2014 and international sector returns 1985-2014, we present four findings: (1) Fama is correct in that a sharp price increase of an industry portfolio does not, on average, predict unusually low returns going forward; (2) such sharp price increases predict a substantially heightened probability of a crash; (3) attributes of the price run-up, including volatility, turnover, issuance, and the price path of the run-up can all help forecast an eventual crash and future returns; and (4) some of these characteristics can help investors earn superior returns by timing the bubble. Results hold similarly in US and international samples.

    Barberis, Nicholas, Robin Greenwood, Lawrence Jin, and Andrei Shleifer. 2018. “Extrapolation and Bubbles.” Journal of Financial Economics 129 (2): 203-227.
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    Bordalo, Pedro, Nicola Gennaioli, and Andrei Shleifer. 2018. “Diagnostic Expectations and Credit Cycles.” Journal of Finance. Abstract
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    We present a model of credit cycles arising from diagnostic expectations – a belief formation mechanism based on Kahneman and Tversky’s (1972) representativeness heuristic. In this formulation, when forming their beliefs agents overweight future outcomes that have become more likely in light of incoming data. The model reconciles extrapolation and neglect of risk in a unified framework. Diagnostic expectations are forward looking, and as such are immune to the Lucas critique and nest rational expectations as a special case. In our model of credit cycles, credit spreads are excessively volatile, over-react to news, and are subject to predictable reversals. These dynamics can account for several features of credit cycles and macroeconomic volatility

    Rognlie, Matthew, Andrei Shleifer, and Alp Simsek. 2018. “Investment Hangover and the Great Recession.” American Economic Journal: Macroeconomics 10 (2): 113-53. Abstract
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    We present a model of investment hangover motivated by the Great Recession. Overbuilding of durable capital such as housing requires a reallocation of productive resources to other sectors, which is facilitated by a reduction in the interest rate. When monetary policy is constrained, overbuilding induces a demand-driven recession with limited reallocation and low output. Investment in other capital initially declines due to low demand, but it later booms and induces an asymmetric recovery in which the overbuilt sector is left behind. Welfare can be improved by expost policies that stimulate investment (including in overbuilt capital), and ex-ante policies that restrict investment.

    Glaeser, Edward, Wei Huang, Yueran Ma, and Andrei Shleifer. 2017. “A Real Estate Boom with Chinese Characteristics” 31 (1): 93-116. Abstract
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    Chinese housing prices rose by over 10 percent per year in real terms between 2003 and 2014, and are now between two and ten times higher than the construction cost of apartments. At the same time, Chinese developers built 100 billion square feet of residential real estate. This boom has been accompanied by a large increase in the number of vacant homes, held by both developers and households. This boom may turn out to be a housing bubble followed by a crash, yet that future is far from certain. The demand for real estate in China is so strong that current prices might be sustainable, especially given the sparse alternative investments for Chinese households, so long as the level of new supply is radically curtailed. Whether that happens depends on the policies of the Chinese government, which must weigh the benefits of price stability against the costs of restricting urban growth.

    Bordalo, Pedro, Katherine Coffman, Nicola Gennaioli, and Andrei Shleifer. 2016. “Stereotypes.” Quarterly Journal of Economics 131 (4): 1753-1794. Publisher's Version Abstract
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    We present a model of stereotypes based on Kahneman and Tversky’s representativeness heuristic. A decision maker assesses a target group by overweighting its representative types, defined as the types that occur more frequently in that group than in a baseline reference group. Stereotypes formed this way contain a ‘‘kernel of truth’’: they are rooted in true differences between groups. Because stereotypes focus on differences, they cause belief distortions, particularly when groups are similar. Stereotypes are also context dependent: beliefs about a group depend on the characteristics of the reference group. In line with our predictions, beliefs in the lab about abstract groups and beliefs in the field about political groups are context dependent and distorted in the direction of representative types. JEL Codes: D03, D83, D84, C91.

    Bordalo, Pedro, Nicola Gennaioli, and Andrei Shleifer. 2016. “Competition for Attention.” Review of Economic Studies 83 (2): 481-513. Abstract
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    We present a model of market competition in which consumers' attention is drawn to the products' most salient attributes. Firms compete for consumer attention via their choices of quality and price. Strategic positioning of a product affects how all other products are perceived. With this attention externality, depending on the cost of producing quality some markets exhibit “commoditized” price salient equilibria, while others exhibit “de-commoditized” quality salient equilibria. When the costs of quality change, innovation can lead to radical shifts in markets, as in the case of decommoditization of the coffee market by Starbucks. In the context of financial innovation, the model generates the phenomenon of “reaching for yield”.

    Gennaioli, Nicola, Yueran Ma, and Andrei Shleifer. 2016. “Expectations and Investment.” NBER Macroeconomics Annual, Vol. 30 (2015): 379-442. Abstract
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    Using micro data from Duke University quarterly survey of Chief Financial Officers, we show that corporate investment plans as well as actual investment are well explained by CFOs’ expectations of earnings growth. The information in expectations data is not subsumed by traditional variables, such as Tobin’s Q or discount rates. We also show that errors in CFO expectations of earnings growth are predictable from past earnings and other data, pointing to extrapolative structure of expectations and suggesting that expectations may not be rational. This evidence, like earlier findings in finance, points to the usefulness of data on actual expectations for understanding economic behavior.   

    Hanson, Samuel, Andrei Shleifer, Jeremy C Stein, and Robert W Vishny. 2015. “Banks as patient fixed-income investors.” Journal of Financial Economics 117 (3): 449-469. Abstract
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    We examine the business model of traditional commercial banks when they compete with shadow banks. While both types of intermediaries create safe “money-like” claims, they go about this in different ways. Traditional banks create money-like claims by holding illiquid fixed-income assets to maturity, and they rely on deposit insurance and costly equity capital to support this strategy. This strategy allows bank depositors to remain “sleepy”: they do not have to pay attention to transient fluctuations in the market value of bank assets. In contrast, shadow banks create money-like claims by giving their investors an early exit option requiring the rapid liquidation of assets. Thus, traditional banks have a stable source of funding, while shadow banks are subject to runs and fire-sale losses. In equilibrium, traditional banks have a comparative advantage at holding fixed-income assets that have only modest fundamental risk but are illiquid and have substantial transitory price volatility, whereas shadow banks tend to hold relatively liquid assets.

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