Knowledge that Transforms

Lower prices produce higher demand… or do they? A bank's direct marketing to holders of “free” checking accounts shows that a large discount on 60% APR overdrafts reduces overdraft usage, especially when bundled with a discount on debit card or autodebit transactions. In contrast, messages mentioning overdraft availability without mentioning price increase usage. Neither change persists long after the messages stop. These results do not square easily with classical models of consumer choice and firm competition. Instead, they support behavioral models where consumers underestimate and are inattentive to overdraft costs, and firms respond by shrouding overdraft prices in equilibrium.

We argue that tests of reduced‐form factor models and horse races between “characteristics” and “covariances” cannot discriminate between alternative models of investor beliefs. Since asset returns have substantial commonality, absence of near‐arbitrage opportunities implies that the stochastic discount factor can be represented as a function of a few dominant sources of return variation. As long as some arbitrageurs are present, this conclusion applies even in an economy in which all cross‐sectional variation in expected returns is caused by sentiment. Sentiment‐investor demand results in substantial mispricing only if arbitrageurs are exposed to factor risk when taking the other side of these trades.

We uncover a negative relation between herding behavior and skill in the mutual fund industry. Our new, dynamic measure of fund‐level herding captures the tendency of fund managers to follow the trades of the institutional crowd. We find that herding funds underperform their antiherding peers by over 2% per year. Differences in skill drive this performance gap: Antiherding funds make superior investment decisions even on stocks not heavily traded by institutions, and can anticipate the trades of the crowd; furthermore, the herding‐antiherding performance gap is persistent, wider when skill is more valuable, and larger among managers with stronger career concerns.

Using proprietary data from the China Development Bank (CDB), this paper examines the effects of government credit on firm activities. Tracing the effects of government credit across different levels of the supply chain, I find that CDB industrial loans to state‐owned enterprises (SOEs) crowd out private firms in the same industry but crowd in private firms in downstream industries. On average, a $1 increase in CDB SOE loans leads to a $0.20 decrease in private firms' assets. Moreover, CDB infrastructure loans crowd in private firms. I use exogenous timing of municipal politicians' turnover as an instrument for CDB credit flows.

We argue and demonstrate empirically that a firm's institutional and legal context has first‐order effects in tests that use state antitakeover laws for identification. A priori, the size and direction of a law's effect on a firm's takeover protection depends on (i) other state antitakeover laws, (ii) preexisting firm‐level takeover defenses, and (iii) the legal regime as reflected by important court decisions. In addition, (iv) state antitakeover laws are not exogenous for many easily identifiable firms. We show that the inferences from nine prior studies related to nine different outcome variables change substantially when we include controls for these considerations.

Many natural competitors are jointly held by a small set of large institutional investors. In the U.S. airline industry, taking common ownership into account implies increases in market concentration that are 10 times larger than what is “presumed likely to enhance market power” by antitrust authorities. Within‐route changes in common ownership concentration robustly correlate with route‐level changes in ticket prices, even when we only use variation in ownership due to the combination of two large asset managers. We conclude that a hidden social cost—reduced product market competition—accompanies the private benefits of diversification and good governance.

We empirically explore the fragility of wholesale funding of banks, using transaction‐level data on short‐term, unsecured certificates of deposit in the European market. We do not observe a market‐wide freeze during the 2008 to 2014 period. Yet, many banks suddenly experience funding dry‐ups. Dry‐ups predict, but do not cause, future deterioration in bank performance. Furthermore, during periods of market stress, banks with high future performance tend to increase reliance on wholesale funding. We therefore fail to find evidence consistent with adverse selection models of funding market freezes. Our evidence is in line with theories highlighting heterogeneity between informed and uninformed lenders.

We present a model of credit cycles arising from diagnostic expectations—a belief formation mechanism based on Kahneman and Tversky's representativeness heuristic. Diagnostic expectations overweight future outcomes that become more likely in light of incoming data. The expectations formation rule is forward looking and depends on the underlying stochastic process, and thus is immune to the Lucas critique. Diagnostic expectations reconcile extrapolation and neglect of risk in a unified framework. In our model, credit spreads are excessively volatile, overreact to news, and are subject to predictable reversals. These dynamics can account for several features of credit cycles and macroeconomic volatility.

We study the conflict of interest that arises when a universal bank conducts proprietary trading alongside its retail banking services. Our data set contains the stock holdings of every German bank and those of their corresponding retail clients. We investigate (i) whether banks sell stocks from their proprietary portfolios to their retail customers, (ii) whether those stocks subsequently underperform, and (iii) whether retail customers of banks engaging in proprietary trading earn lower portfolio returns than their peers. We present affirmative evidence for all three questions and conclude that proprietary trading can, in fact, be detrimental to retail investors.

We test the asset pricing implications of collateralized borrowing (that is, of using assets as collateral to borrow money) in the laboratory. To this purpose, we develop a general equilibrium model with collateral constraints amenable to laboratory implementation and gather experimental data. In the laboratory, assets that can be leveraged fetch higher prices than assets that cannot, even though assets' payoffs are identical in all states of the world. Collateral value, therefore, creates deviations from the Law of One Price. The spread between collateralizeable and noncollateralizeable assets is significant and quantitatively close to theoretical predictions.