Knowledge that Transforms

Beginning in 2018, U.S. public firms were required to report the ratio of the chief executive officer's (CEO) compensation to their median employee's compensation in the annual proxy statement. Exploiting the staggered reporting of pay ratios, we find little evidence that total CEO compensation changes in response to pay ratio disclosure reform. However, we do find that boards significantly adjust the mix of compensation awarded by reducing the sensitivity of CEO pay to equity price changes, particularly when the CEO is likely to garner media scrutiny, and by reducing reliance on stock‐based and other compensation components that are most susceptible to media coverage surrounding the pay ratio disclosure. Firms ultimately disclosing higher pay ratios garner more media coverage around the filing of their proxy statement, and more negative‐toned coverage in the subsequent month. Finally, we find evidence that greater pay disparity is associated with greater selling activity by retail investors and more negative say‐on‐pay votes following pay ratio reform, consistent with a broad set of investors responding to public scrutiny resulting from pay ratio disclosures.

Most U.S. government spending on highways and bridges is done through “scaling” procurement auctions, in which private construction firms submit unit price bids for each piece of material required to complete a project. Using data on bridge maintenance projects undertaken by the Massachusetts Department of Transportation (MassDOT), we present evidence that firm bidding behavior in this context is consistent with optimal skewing under risk aversion: firms limit their risk exposure by placing lower unit bids on items with greater uncertainty. We estimate the amount of uncertainty in each auction, and the distribution of bidders' private costs and risk aversion. Simulating equilibrium item‐level bids under counterfactual settings, we estimate the fraction of project spending that is due to risk and evaluate auction mechanisms under consideration by policymakers. We find that scaling auctions provide substantial savings relative to lump sum auctions and show how our framework can be used to evaluate alternative auction designs.

Using an endogenous growth model, Liu, Mian, and Sufi (2022) (LMS) show that a decline in the interest rate can lead to a fall in productivity growth and a rise in leader‐laggard productivity gaps and firm profits. We identify two issues in their quantitative analysis of transition dynamics: a time‐scale error and the omission of composition terms in calculating productivity growth along the transition to a new balanced growth path. Correcting the time‐scale error and including the composition terms, the decline in the interest rate that LMS study leads to a large and protracted productivity boom lasting about 20 years. In addition, the average leader‐laggard gap grows much more slowly than reported in their paper. We also point out an issue in their quantitative analysis of steady‐state profit shares. These issues are related to the quantitative exercises, and do not affect the key theoretical contributions of LMS.

This paper assesses when the validity of difference‐in‐differences depends on functional form. We provide a novel characterization: the parallel trends assumption holds under all strictly monotonic transformations of the outcome if and only if a stronger “parallel trends”‐type condition holds for the cumulative distribution function of untreated potential outcomes. This condition for parallel trends to be insensitive to functional form is satisfied if and essentially only if the population can be partitioned into a subgroup for which treatment is effectively randomly assigned and a remaining subgroup for which the distribution of untreated potential outcomes is stable over time. These conditions have testable implications, and we introduce falsification tests for the null that parallel trends is insensitive to functional form.

We study how discounting and monitoring jointly determine whether cooperation is possible in repeated games with imperfect (public or private) monitoring. Our main result provides a simple bound on the strength of players' incentives as a function of discounting, monitoring precision, and on‐path payoff variance. We show that the bound is tight in the low‐discounting/low‐monitoring double limit, by establishing a public‐monitoring folk theorem where the discount factor and the monitoring structure can vary simultaneously.

The U.S. spends significant amounts on non-medical transfers for its working-age population in a wide range of programs that support low and middle-income households. How valuable are these programs for U.S. households? Are there simpler, welfare improving ways to transfer resources that are supported by a majority? What are the macroeconomic effects of such alternatives? We answer these questions in an equilibrium, life-cycle model with single and married households who face idiosyncratic productivity risk, in the presence of costly children and potential skill losses of females associated with non-participation. Our findings show that a potential revenue-neutral elimination of the welfare state generates large welfare losses in the aggregate, although most households support the move as losses are concentrated among a small group. We fond that a Universal Basic Income program does not improve upon the current system. If instead per-person transfers are implemented alongside a proportional tax, a Negative Income Tax experiment, it becomes feasible to improve upon the current system. Providing per-person transfers to all households is costly, and reducing tax distortions helps to provide for resources to expand redistribution.

Since network data commonly consists of observations from a single large network, researchers often partition the network into clusters in order to apply cluster‐robust inference methods. Existing such methods require clusters to be asymptotically independent. Under mild conditions, we prove that, for this requirement to hold for network‐dependent data, it is necessary and sufficient that clusters have low conductance, the ratio of edge boundary size to volume. This yields a simple measure of cluster quality. We find in simulations that when clusters have low conductance, cluster‐robust methods control size better than HAC estimators. However, for important classes of networks lacking low‐conductance clusters, the former can exhibit substantial size distortion. To determine the number of low‐conductance clusters and construct them, we draw on results in spectral graph theory that connect conductance to the spectrum of the graph Laplacian. Based on these results, we propose to use the spectrum to determine the number of low‐conductance clusters and spectral clustering to construct them.