Motivating innovation is important in many incentive problems. This paper shows that the optimal innovation‐motivating incentive scheme exhibits substantial tolerance (or even reward) for early failure and reward for long‐term success. Moreover, commitment to a long‐term compensation plan, job security, and timely feedback on performance are essential to motivate innovation. In the context of managerial compensation, the optimal innovation‐motivating incentive scheme can be implemented via a combination of stock options with long vesting periods, option repricing, golden parachutes, and managerial entrenchment

Revisions in successive Greenbook forecasts of quarterly real GDP growth proxy for news of current and expected future economic growth. In the sample 1975 through 2015, news of future growth is slightly negatively related to contemporaneous changes in Treasury bond yields, while news of current growth is strongly positively related to changes in these yields. Both results are difficult to reconcile with a representative agent's bondholding first‐order condition. A continuous‐time dynamic model of output attributes almost all of the covariation with yields to martingale innovations in log output and a minimal amount to innovations in the conditional drift of log output

This paper models components of the return distribution, which are assumed to be directed by a latent news process. The conditional variance of returns is a combination of jumps and smoothly changing components. A heterogeneous Poisson process with a time‐varying conditional intensity parameter governs the likelihood of jumps. Unlike typical jump models with stochastic volatility, previous realizations of both jump and normal innovations can feed back asymmetrically into expected volatility. This model improves forecasts of volatility, particularly after large changes in stock returns. We provide empirical evidence of the impact and feedback effects of jump versus normal return innovations, leverage effects, and the time‐series dynamics of jump clustering

In one of the greatest extensions of property rights in human history, common law countries began giving rights to married women in the 1850s. Before this “women's liberation,” the doctrine of coverture strongly incentivized parents of daughters to hold real estate, rather than financial assets such as money, stocks, or bonds. We exploit the staggered nature of coverture's demise across U.S. states to show that women's rights led to shifts in household portfolios, a positive shock to the supply of credit, and a reallocation of labor toward nonagriculture and capital‐intensive industries. Investor protection thus deepened financial markets, aiding industrialization.

We show that over the past half‐century, innovative disruptions were central to understanding corporate defaults. In a given year, industries experiencing abnormally high venture capital or initial public offering activity subsequently see higher default rates, higher segment exits by conglomerates, and higher yields on bonds issued by the firms in these industries. Overall, we find that disruption is a broad phenomenon, negatively affecting incumbent firms across the spectrum of age, valuation, and levers, with the exception of very large and low‐leverage firms, in line with our central hypothesis

Financial economists have long debated whether monetary policy is neutral. This article addresses this question by examining how stock return data respond to monetary policy shocks. Monetary policy is measured by innovations in the federal funds rate and nonborrowed reserves, by narrative indicators, and by an event study of Federal Reserve policy changes. In every case the evidence indicates that expansionary policy increases ex‐post stock returns. Results from estimating a multi‐factor model also indicate that exposure to monetary policy increases an asset's ex‐ante return

Using information in returns, we identify the stochastic process of consumption. We find that aggregate consumption reacts over multiple quarters to innovations spanned by financial markets. This persistent component accounts for over a quarter of consumption variation. These shocks command a large and significant risk premium, driving a large share of stocks' and a small yet significant fraction of bonds' time‐series variation. Nevertheless, we find no support for stochastic volatility of consumption driving time‐varying risk premia. Finally, an otherwise standard recursive utility model based on our estimated process explains equity premium and risk‐free rate puzzles with low‐risk aversion

Innovations in statistical technology in functions including credit‐screening have raised concerns about distributional impacts across categories such as race. Theoretically, distributional effects of better statistical technology can come from greater flexibility to uncover structural relationships or from triangulation of otherwise excluded characteristics. Using data on U.S. mortgages, we predict default using traditional and machine learning models. We find that Black and Hispanic borrowers are disproportionately less likely to gain from the introduction of machine learning. In a simple equilibrium credit market model, machine learning increases disparity in rates between and within groups, with these changes attributable primarily to greater flexibility

Severe flight to quality episodes involve uncertainty about the environment, not only risk about asset payoffs. The uncertainty is triggered by unusual events and untested financial innovations that lead agents to question their worldview. We present a model of crises and central bank policy that incorporates Knightian uncertainty. The model explains crisis regularities such as market‐wide capital immobility, agents' disengagement from risk, and liquidity hoarding. We identify a social cost of these behaviors, and a benefit of a lender of last resort facility. The benefit is particularly high because public and private insurance are complements during uncertainty‐driven crises

The study of household finance is challenging because household behavior is difficult to measure, and households face constraints not captured by textbook models. Evidence on participation, diversification, and mortgage refinancing suggests that many households invest effectively, but a minority make significant mistakes. This minority appears to be poorer and less well educated than the majority of more successful investors. There is some evidence that households understand their own limitations and avoid financial strategies for which they feel unqualified. Some financial products involve a cross‐subsidy from naive to sophisticated households, and this can inhibit welfare‐improving financial innovation