Using data on essentially every US Supreme Court decision since 1946, we estimate a model of peer effects on the Court. We consider both the impact of justice ideology and justice votes on the votes of their peers. To identify these peer effects we use two instruments that generate plausibly exogenous variation in the peer group itself, or in the votes of peers. The ﬁrst instrument utilizes the fact that the composition of the Court varies from case to case due to recusals or absences for health reasons. The second utilizes the fact that many justices previously sat on Federal Circuit Courts. Those who served on the Circuit Courts for short (long) periods of time are empirically much more (less) likely to afﬁrm decisions from their “home” court. We ﬁnd large peer effects. Replacing a single justice with one who votes in a conservative direction 10 percentage points more frequently increases the probability that each other justice votes conservative by 1.6 percentage points. Further, a 10% increase in the probability that a given justice votes conservative leads to a 1.1 percentage point increase in the probability that each other justice votes conservative. This indirect effect increases the share of cases with a conservative outcome by 3.6 percentage points (excluding the direct effect of the new justice). In general, we ﬁnd indirect effects are large relative to the direct mechanical effect of a justice’s own vote.
In recent decades, states with Right-To-Work (RTW) laws have experienced higher employment and population growth than states without such laws. We investigate the extent to which these patterns, and other related labor market phenomena, are causally explained by these laws and closely related policies. Using border-pair differences, we find RTW laws are associated with a 3.2 percentage point increase in the manufacturing share of employment. This does not merely crowd out other economic activity; people who live in RTW regions have 1.6 percentage points higher employment, 1.4 percentage points higher labor force participation, and 0.34 percentage points lower disability receipt than residents of similar non-RTW areas. However, wages and labor compensation do not appear to be lower on average. In turn, these differences appear to influence both individual residence and workplace location choice. Since their passage, locations with RTW laws have seen higher population growth, and on net attract commuters from non-RTW locations. We investigate downstream effects on socioeconomic outcomes, and find lower childhood poverty rates and greater upward mobility. In particular, children at the 25th percentile of the parental income distribution during childhood have a 1.6 percentage point higher probability of reaching the top income quintile during adulthood if they grew up in a RTW location. These differences in outcomes were not present prior to the passage of RTW laws, persist after controlling for other major policy differences between states, and do not appear primarily attributable to local substitution.
The basic challenge in understanding the impact of credit on house prices is to separate supply and demand effects. We construct an instrument for mortgage credit supply by using county level changes in the conforming loan limit set by agencies. We estimate that an exogenous 1% increase in credit supply leads to a 0.38% increase in house prices. By focusing on transactions close to the border of differentially treated counties and since the conforming loan limits are only sporadically revised, we can plausibly rule out demand based explanations for our results.
Using data from 43 US cities, Correia, Luck, and Verner (2020) finds that the 1918 Flu pandemic decreased economic growth, but that Non Pharmaceutical Interventions (NPIs) mitigated its adverse economic effects. Their starting point is a striking positive correlation between 1914-1919 economic growth and the extent of NPIs adopted at the city level. We show that those results are driven by population growth between 1910 to 1917, before the pandemic. We also extend their difference in differences analysis to earlier periods, and find that once we account for pre-existing differential trends, the estimated effect of NPIs on economic growth are a noisy zero; we can neither rule out substantial positive nor negative effects of NPIs on employment growth.
High-profile disasters can cause large spikes in philanthropy and volunteerism. By providing temporary positive shocks to the altruism of donors, these natural experiments help identify heterogeneity in the distributions of the latent altruism which motivates donors. This study examines gender heterogeneity of volunteer response by blood donors following the most devastating Bushfires in Australia's history. Using difference in differences analyses, we observe a sharp increase in blood donations after the 2009 Victorian Bushfires. Several key features of this increase are consistent with the predictions of a model where the distribution of latent altruism has smaller variance among women than men. First, the highest increase in donations occurs among previous non-donors, lapsed donors and less frequent donors. Further, the increase in donations following the Bushfires, compared to non-disaster periods, is substantially greater for females than males; the proportional increase in the number of females donating for the first time after the disaster is approximately twice the proportional increase for men. Notably, this gender gap decreases with the frequency with which people have previously donated.
Behavioural theories of belief updating emphasize violations from Bayesian rationality, as people exhibit biases such as over-extrapolation from recent news and false inference of momentum. This implies forecasts are conditionally biased, and exhibit mean-reversion. To test this theory, I study a market where agents update past beliefs in a very measurable way - betting odds on tennis matches. From live odds at the end of each set, I show market prices change by more than would be expected under a simple heuristic where agents do not believe in momentum. This suggests news shocks cause markets to revise their beliefs about players' probability of winning subsequent sets. I test to see whether this updating is rational, and find that changes in beliefs have strong predictive power over outcomes, but also predict a modest amount of future belief reversion, suggesting modest over-extrapolation from news. Second, exploiting the extensive structure of markets for an individual match, I show that ex ante conditional beliefs are consistent with belief in momentum - future outcome probabilities depend on initial, yet unrealised, outcomes. These ex ante beliefs can be compared to updated beliefs once the initial outcomes are realized. I find that belief updating is almost consistent with the law of iterated expectations, exhibiting relatively little mean reversion, and furthermore that updated beliefs are well calibrated with final outcome probabilities.