Knowledge that Transforms

The recent unravelling of the Eurozone’s financial integration raised concerns about feedback loops between sovereign and banking insolvency. This article provides a theory of the feedback loop that allows for both domestic bailouts of the banking system and sovereign debt forgiveness by international creditors or solidarity by other countries. Our theory has important implications for the re-nationalization of sovereign debt, macroprudential regulation, and the rationale for banking unions.

We study asset prices and portfolio choice with overlapping generations, where the young disregard history to learn from own experience. Disregarding history implies less precise estimates of output growth, which in equilibrium leads the young to increase their investment in risky assets after positive returns, that is, they act as trend chasers. In equilibrium, the risk premium decreases after a positive shock and, therefore, trend chasing young agents lose wealth relative to old agents who behave as contrarians. Consistent with findings from survey data, the average belief about the risk premium in the economy relates negatively to future excess returns and is smoother than the true risk premium.

This article studies the transmission of financial shocks in a model where corporate credit is intermediated via both banks and bond markets. In choosing between bank and bond financing, firms trade-off the greater flexibility of banks in case of financial distress against the lower marginal costs of large bond issuances. I find that, in response to a contraction in bank credit supply, aggregate bond issuance in the corporate sector increases, but not enough to avoid a decline in aggregate borrowing and investment. Keeping leverage constant while retiring bank debt would expose firms to a higher risk of financial distress; they offset this by reducing total borrowing. A calibration of the model to the Great Recession indicates that this precautionary mechanism can account for one-third of the total decline in investment by firms with access to bond markets.

We propose a dynamic non-cooperative framework for long-term-care (LTC) decisions of families and use it to evaluate LTC policy options for the U.S. We first document the importance of informal caregiving and economic determinants of care arrangements. We then build a heterogeneous-agents model with imperfectly-altruistic overlapping generations to account for the patterns we find. A key innovation is the availability of informal care (IC), which is determined through intra-family bargaining. This opens up a new margin in response to policy and allows for informal insurance through home-production of care. Our calibrated model captures the observed care arrangements well. We study the implications of non-means-tested IC and formal care (FC) subsidies as well as changes to means-tested Medicaid. We find that IC responds strongly to these policies. An IC subsidy substantially reduces reliance on Medicaid, while the reduction of tax revenues due to lower labour supply by caregivers is modest. There are large welfare gains from a combination of IC and FC subsidies, even when combined with a reduction of the Medicaid program.

We provide new empirical evidence for the way in which financial markets process information. Our results rely critically on high-frequency intraday price and volume data for the S&P 500 equity portfolio and U.S. Treasury bonds, along with new econometric techniques, for making inference on the relationship between trading intensity and spot volatility around public news announcements. Consistent with the predictions derived from a theoretical model in which investors agree to disagree, our estimates for the intraday volume-volatility elasticity around important news announcements are systematically below unity. Our elasticity estimates also decrease significantly with measures of disagreements in beliefs, economic uncertainty, and textual-based sentiment, further highlighting the key role played by differences-of-opinion.

We find that daily air pollution levels have a significant effect on the decision to purchase or cancel health insurance in a manner inconsistent with rational choice theory. A one standard deviation increase in daily air pollution leads to a 7.2% increase in the number of insurance contracts sold that day. Conditional on purchase, a one standard deviation decrease in air pollution during the cooling-off (i.e. cost-free cancellation) period relative to the order-date level increases the return probability by 4.0%. We explore a range of potential mechanism and find the most support for projection bias and salience.

We propose a criterion of approximate incentive compatibility, strategy-proofness in the large (SP-L), and argue that it is a useful second-best to exact strategy-proofness (SP) for market design. Conceptually, SP-L requires that an agent who regards a mechanism’s “prices” as exogenous to her report—be they traditional prices as in an auction mechanism, or price-like statistics in an assignment or matching mechanism—has a dominant strategy to report truthfully. Mathematically, SP-L weakens SP in two ways: (1) truth-telling is required to be approximately optimal (within epsilon in a large enough market) rather than exactly optimal, and (2) incentive compatibility is evaluated ex interim, with respect to all full-support i.i.d. probability distributions of play, rather than ex post with respect to all possible realizations of play. This places SP-L in between the traditional notion of approximate SP, which evaluates incentives to manipulate ex post and as a result is too strong to obtain our main results in support of SP-L, and the traditional notion of approximate Bayes-Nash incentive compatibility, which, like SP-L, evaluates incentives to manipulate ex interim, but which imposes common knowledge and strategic sophistication assumptions that are often viewed as unrealistic.

This article studies non-parametric panel data models with multidimensional, unobserved individual effects when the number of time periods is fixed. I focus on models where the unobservables have a factor structure and enter an unknown structural function non-additively. The setup allows the individual effects to impact outcomes differently in different time periods and it allows for heterogeneous marginal effects. I provide sufficient conditions for point identification of all parameters of the model. Furthermore, I present a non-parametric sieve maximum likelihood estimator as well as flexible semiparametric and parametric estimators. Monte Carlo experiments demonstrate that the estimators perform well in finite samples. Finally, in an empirical application, I use these estimators to investigate the relationship between teaching practice and student achievement. The results differ considerably from those obtained with commonly used panel data methods.

We explore costly deliberation by two differentially informed and possibly biased jurors: A hawk Lones and a dove Moritz alternately insist on a verdict until one concedes. Debate assumes one of two genres, depending on bias: A juror, say Lones, is intransigent if he wishes to prevail and reach a conviction for any type of Moritz next to concede. In contrast, Lones is ambivalent if he wants the strongest conceding types of Moritz to push for acquittal. Both jurors are ambivalent with small bias or high delay costs. As Lones grows more hawkish, he argues more forcefully for convictions, mitigating wrongful acquittals. If dovish Moritz is intransigent, then he softens (strategic substitutes), leading to more wrongful convictions. Ambivalent debate is new, and yields a novel dynamic benefit of increased polarization. For if Moritz is ambivalent, then he toughens (strategic complements), and so, surprisingly, a more hawkish Lones leads to fewer wrongful acquittals and convictions. So more polarized but balanced debate can improve communication, unlike in static cheap talk. We also show that patient and not too biased jurors vote against their posteriors near the end of the debate, optimally playing devil’s advocate. We shed light on the adversarial legal system, peremptory challenges, and cloture rules.

We introduce learning into an otherwise standard two-sided search-and-bargaining market. There is uncertainty about the price distribution due to uncertainty about an underlying exogenous state of relative demand: in the high state, buyers are on the long side; otherwise, they are on the short side. In equilibrium, prices are on average higher in the high state. Individual agents learn about the distribution while searching. Agents typically start out by experimenting with a tough bargaining position—buyers may initially insist on a low price and sellers on a high price. After successive failures to trade, agents become increasingly pessimistic about the market conditions and soften their bargaining stance. When frictions are small, equilibrium transaction prices are approximately market clearing, despite aggregate demand being unknown. Thus, the search-and-bargaining procedure enables price discovery in a decentralized market.