We develop a new approach for the identification of Pareto‐improving tax reforms. This approach yields necessary and sufficient conditions for the existence of Pareto‐improving reform directions. A main insight is that “Two brackets are enough”: When the system cannot be improved by altering tax rates in one or two income brackets, then there is no continuous reform direction that is Pareto‐improving. We also show how to check whether a given tax reform is Pareto‐improving. We use these tools to study the introduction of the Earned Income Tax Credit (EITC) in the United States in 1975. A robust finding is that, prior to the EITC, the U.S. tax‐transfer system was not Pareto‐efficient. Under plausible assumptions about behavioral responses, the 1975 reform was not Pareto‐improving. Qualitatively, though, it had the right properties: A similar reform with earnings subsidies made available to a broader range of incomes would have been Pareto‐improving.

We propose improved standard errors and an asymptotic theory for two-way clustered panels. Our theory allow for arbitrary serial dependence in the common time effects, which is excluded by existing two-way methods. Our asymptotic distribution theory is the first which allows for this level of inter-dependence. Under weak conditions, we demonstrate that OLS is asymptotically normal, our proposed variance estimator is consistent, and t-ratios are asymptotically standard normal. The results extend to two-way fixed-effect models; we argue that two-way clustering is still necessary even if two-way fixed effects are included. Simulation and empirical illustration are provided.

Contracting between tax entities and tax professionals occurs millions of times every year, yet little is known about the nature of these economic interactions. This study examines the effect of commonly occurring contextual factors on tax professionals’ billing decisions for tax research. These contextual factors are unrelated to the tax research itself and the time it takes to conduct the tax research, but we find that billing decisions are strongly influenced by the three non‐time‐related contextual factors that we manipulate. Initial client volume impacts amounts billed for tax research, with lower initial client volume resulting in higher per client fees. Further, we find that initial billing decisions serve as value billing benchmarks for unanticipated subsequent clients who benefit from research conducted for initial clients. As a result, subsequent clients are billed higher fees when they follow a smaller number of initial clients. We also find that client referrals are billed higher fees than nonclient referrals because professionals attempt to avoid making initial clients feel as though they have been treated unfairly relative to subsequent clients who would otherwise be billed lower fees. The results of this study are relevant beyond the traditional confines of accounting research—they are relevant to the millions of tax entities that contract with tax professionals each year.

How does transparency, a key feature of central bank design, affect monetary policy makers’ deliberations? Theory predicts a positive discipline effect and negative conformity effect. We empirically explore these effects using a natural experiment in the Federal Open Market Committee in 1993 and computational linguistics algorithms. We first find large changes in communication patterns after transparency. We then propose a difference-in-differences approach inspired by the career concerns literature, and find evidence for both effects. Finally, we construct an influence measure that suggests the discipline effect dominates.

This paper describes links between the max-min expected utility theory of Gilboa and Schmeidler (1989) and the applications of robust control theory proposed by Anderson, Hansen and Sargent (2000) and Dupuis, James and Petersen (1998).

Instrumental variable (IV) methods are widely used to identify causal effects in models with endogenous explanatory variables. Often the instrument exclusion restriction that underlies the validity of the usual IV inference is suspect; that is, instruments are only plausibly exogenous. We present practical methods for performing inference while relaxing the exclusion restriction. We illustrate the approaches with empirical examples that examine the effect of 401(k) participation on asset accumulation, price elasticity of demand for margarine, and returns to schooling. We find that inference is informative even with a substantial relaxation of the exclusion restriction in two of the three cases.

We use decision theory to confront uncertainty that is sufficiently broad to incorporate “models as approximations.” We presume the existence of a featured collection of what we call “structured models” that have explicit substantive motivations. The decision-maker confronts uncertainty through the lens of these models, but also views these models as simplifications, and hence, as misspecified. We extend the max–min analysis under model ambiguity to incorporate the uncertainty induced by acknowledging that the models used in decision making are simplified approximations. Formally, we provide an axiomatic rationale for a decision criterion that incorporates model misspecification concerns. We then extend our analysis beyond the max-min case allowing for a more general criterion that encompasses a Bayesian formulation.

Tropical deforestation accounts for almost one-fifth of greenhouse gas emissions and threatens the world’s most diverse ecosystems. Much of this deforestation is driven by illegal logging. We use novel satellite data that tracks annual deforestation across eight years of Indonesian institutional change to examine how local officials’ incentives affect deforestation. Increases in the number of political jurisdictions lead to increased deforestation and lower timber prices, consistent with Cournot competition between jurisdictions. Illegal logging and local oil and gas rents are short-run substitutes, but this effect disappears over time with political turnover. The results illustrate how local officials’ incentives affect deforestation and show how standard economic theories can explain illegal behavior.