Does additional shareholder liability reduce bank failure? We compare the performance of around 4,400 state-regulated banks of similar size in neighboring U.S. states with different liability regimes during the Great Depression. We find that additional shareholder liability reduced bank failure by 30%. Results are robust to a diff-in-diff analysis incorporating National banks (which faced the same regulations in every state), and are not driven by other differences in state regulation, FED membership, or differential selection into state and nationally regulated banks. Our results suggest that exposing shareholders to more downside risk reduces bank risk taking.

We develop a model of financial crises with both a financial amplification mechanism, via frictional intermediation, and a role for sentiment, via time-varying beliefs about an illiquidity state. We confront the model with data on credit spreads, equity prices, credit, and output across the financial crisis cycle. In particular, we ask the model to match data on the frothy pre-crisis behavior of asset markets and credit, the sharp transition to a crisis where asset values fall, disintermediation occurs and output falls, and the post-crisis period characterized by a slow recovery in output. We find that a pure amplification mechanism quantitatively matches the crisis and aftermath period but fails to match the pre-crisis evidence. Mixing sentiment and amplification allows the model to additionally match the pre-crisis evidence. We consider two versions of sentiment, a Bayesian belief updating process and one that overweighs recent observations. We find that both models match the crisis patterns qualitatively, generating froth pre-crisis, non-linear behavior in the crisis, and slow recovery. The non-Bayesian model improves quantitatively on the Bayesian model in matching the extent of the pre-crisis froth.

Conjoint experiments enjoy increasing popularity in political and social science, but there is a paucity of research on respondents' underlying decision-making processes. We leverage eye-tracking methodology and a conjoint experiment, administered to a subject pool consisting of university students and local community members, to examine how respondents process information when completing conjoint surveys. Our study has two main findings. First, we find a positive correlation between attribute importance measures inferred from the stated choice data and attribute importance measures based on eye movement. This validation test supports the interpretation of common conjoint metrics, such as Average Marginal Component Effects and marginal R^2 values, as valid measures of attribute importance. Second, when we experimentally increase the number of attributes and profiles in the conjoint table, respondents on average view a larger absolute number of cells but a smaller fraction of the total cells displayed, and the patterns in which they search between cells change conditionally. At the same time, however, their stated choices remain remarkably stable. This overall pattern speaks to the robustness of conjoint experiments and is consistent with a bounded rationality mechanism. Respondents can adapt to complexity by selectively incorporating relevant new information to focus on the important attributes, while ignoring less relevant information to reduce the cognitive processing costs. Together, our results have implications for both the design and interpretation of conjoint experiments.

Standard mortgage contracts include periodic debt repayment plans (amortization schedules) designed to build-up illiquid savings in the form of home equity, which can be substantial even from a macroeconomic standpoint. For example, U.S. households invest hundreds of ($) billions each year in mortgage amortization plans – comparable in size to pension program contributions. We provide the first empirical evidence on the causal effects of mortgage amortization on wealth accumulation. Ex-ante, effects are unclear. If increased debt repayments crowd-out households’ non-mortgage savings, rather than alter their consumption/labor supply, there would be no effect on wealth. We use individual administrative data and plausibly exogenous variation in the timing of home purchases surrounding an interest-only mortgage reform in the Netherlands. We find little-to-no change in the accumulation of non-mortgage savings, even four years later, despite a significant increase in debt repayment. This lack of crowding-out implies a surprising near 1-for-1 rise in net worth and little savings-debt fungibility, financed via increased labor supply and reduced expenditures. Results hold using life-events (ex. birth of a child) as an instrument for the timing of home purchase, and appear unaffected by potential selection or confounded treatment concerns. Effects also hold focusing on buyers with substantial liquid savings and across the spectrum of ages, suggesting general applicability beyond just non-savers and the young. Our findings suggest that homeownership, when coupled with amortizing mortgages, is a key driver of household wealth building and inequality, and that the amortization-wealth elasticity is a crucial consideration for macroprudential policies.

We study the impact of marital property legislation passed in the US South in the 1840s on households’ investment in risky, entrepreneurial projects. These laws protected the assets of newly married women from creditors in a world of virtually unlimited liability. We compare couples married after the passage of a marital property law with couples from the same state who were married before. Consistent with a simple model of household borrowing that trades off agency costs against risk sharing, the effect on investment was heterogeneous. It increased if most household property came from the husband and decreased if most came from the wife.

Time is the backdrop of historical inquiry, yet it is much more than a featureless setting for events. Different temporalities interact dynamically; sometimes they coexist tensely, sometimes they clash violently. In this innovative volume, editors Dan Edelstein, Stefanos Geroulanos, and Natasha Wheatley challenge how we interpret history by focusing on the nexus of two concepts—“power” and “time”—as they manifest in a wide variety of case studies. Analyzing history, culture, politics, technology, law, art, and science, this engaging book shows how power is constituted through the shaping of temporal regimes in historically specific ways. Power and Time includes seventeen essays on human rights; sovereignty; Islamic, European, Chinese, and Indian history; slavery; capitalism; revolution; the Supreme Court; the Anthropocene; and even the Manson Family. Power and Time will be an agenda-setting volume, highlighting the work of some of the world’s most respected and original contemporary historians and posing fundamental questions for the craft of history.

The recent digitization of complete count census data is an extraordinary opportunity for social scientists to create large longitudinal datasets by linking individuals from one census to another or from other sources to the census. We evaluate different automated methods for record linkage, performing a series of comparisons across methods and against hand linking. We have three main findings that lead us to conclude that automated methods perform well. First, a number of automated methods generate very low (less than 5%) false positive rates. The automated methods trace out a frontier illustrating the tradeoff between the false positive rate and the (true) match rate. Relative to more conservative automated algorithms, humans tend to link more observations but at a cost of higher rates of false positives. Second, when human linkers and algorithms use the same linking variables, there is relatively little disagreement between them. Third, across a number of plausible analyses, coefficient estimates and parameters of interest are very similar when using linked samples based on each of the different automated methods. We provide code and Stata commands to implement the various automated methods.

BACKGROUND

Research has consistently identified firearm availability as a risk factor for suicide. However, existing studies are relatively small in scale, estimates vary widely, and no study appears to have tracked risks from commencement of firearm ownership.

METHODS

We identified handgun acquisitions and deaths in a cohort of 26.3 million male and female residents of California, 21 years old or older, who had not previously acquired handguns. Cohort members were followed for up to 12 years 2 months (from October 18, 2004, to December 31, 2016). We used survival analysis to estimate the relationship between handgun ownership and both all-cause mortality and suicide (by firearm and by other methods) among men and women. The analysis allowed the baseline hazard to vary according to neighborhood and was adjusted for age, race and ethnic group, and ownership of long guns (i.e., rifles or shotguns).

RESULTS

A total of 676,425 cohort members acquired one or more handguns, and 1,457,981 died; 17,894 died by suicide, of which 6691 were suicides by firearm. Rates of suicide by any method were higher among handgun owners, with an adjusted hazard ratio of 3.34 for all male owners as compared with male nonowners (95% confidence interval [CI], 3.13 to 3.56) and 7.16 for female owners as compared with female nonowners (95% CI, 6.22 to 8.24). These rates were driven by much higher rates of suicide by firearm among both male and female handgun owners, with a hazard ratio of 7.82 for men (95% CI, 7.26 to 8.43) and 35.15 for women (95% CI, 29.56 to 41.79). Handgun owners did not have higher rates of suicide by other methods or higher all-cause mortality. The risk of suicide by firearm among handgun owners peaked immediately after the first acquisition, but 52% of all suicides by firearm among handgun owners occurred more than 1 year after acquisition.

CONCLUSIONS

Handgun ownership is associated with a greatly elevated and enduring risk of suicide by firearm. (Funded by the Fund for a Safer Future and others.)