This paper presents a framework for analyzing how bounded rationality affects monetary and fiscal policy. The model is a tractable and parsimonious enrichment of the widely-used New Keynesian model – with one main new parameter, which quantifies how poorly agents understand future policy and its impact. That myopia parameter, in turn, affects the power of monetary and fiscal policy in a microfounded general equilibrium.
A number of consequences emerge. (i) Fiscal stimulus or “helicopter drops of money” are powerful and, indeed, pull the economy out of the zero lower bound. More generally, the model allows for the joint analysis of optimal monetary and fiscal policy. (ii) The Taylor principle is strongly modified: even with passive monetary policy, equilibrium is determinate, whereas the traditional rational model yields multiple equilibria, which reduce its predictive power, and generates indeterminate economies at the zero lower bound (ZLB). (iii) The ZLB is much less costly than in the traditional model. (iv) The model helps solve the “forward guidance puzzle”: the fact that in the rational model, shocks to very distant rates have a very powerful impact on today’s consumption and inflation: because agents are partially myopic, this effect is muted. (v) Optimal policy changes qualitatively: the optimal commitment policy with rational agents demands “nominal GDP targeting”; this is not the case with behavioral firms, as the benefits
of commitment are less strong with myopic firms. (vi) The model is “neo-Fisherian” in the long run, but Keynesian in the short run: a permanent rise in the interest rate decreases inflation in the short run but increases it in the long run. The non-standard behavioral features of the model seem warranted by the extant empirical evidence.
Survey paper on executive compensation, containing (1) Data on CEO and other top executive pay over time and across firms, including private firms and non-US firms. (2) Critical analysis of three explanations for the drivers of pay: shareholder value maximization (including a simple unifying model), rent extraction, institutional influences. (3) The “effects” of executive pay and challenges in causal identification. (4) Directions for future research.
Inattention is a central, unifying theme for much of behavioral economics. It permeates such disparate fields as microeconomics, macroeconomics, finance, public economics, and industrial organization. It enables us to think in a rather consistent way about behavioral biases, speculate about their origins, and trace out their implications for market outcomes.
This survey first discusses the most basic models of attention, using a fairly unified framework. Then, it discusses the methods used to measure attention, which present a number of challenges on which much progress has been done. It then examines the various theories of attention, both behavioral and more Bayesian. It finally discusses some applications. For instance, inattention offers a way to write a behavioral version of basic microeconomics, as in consumer theory, producer theory, and Arrow-Debreu. A last section is devoted to open questions in the attention literature.
This chapter is a pedagogical guide to the literature on attention. Derivations are self-contained.
This paper develops a theory of optimal taxation with behavioral agents. We use a general behavioral framework that encompasses a wide range of behavioral biases such as misperceptions, internalities and mental accounting. We revisit the three pillars of optimal taxation: Ramsey (linear commodity taxation to raise revenues and redistribute), Pigou (linear commodity taxation to correct externalities) and Mirrlees (nonlinear income taxation). We show how the canonical optimal tax formulas are modified and lead to a rich set of novel economic insights. We also show how to incorporate nudges in the optimal taxation frameworks, and jointly characterize optimal taxes and nudges. We explore the Diamond-Mirrlees productive efficiency result and the Atkinson-Stiglitz uniform commodity taxation proposition, and find that they are more likely to fail with behavioral agents. (JEL: D03, H21).
I propose a tractable behavioral "max" operator, the sparse max. It yields a behavioral version of basic consumer theory (e.g., Marshallian demand, Slutsky matrix, nominal illusion) and equilibrium theory (e.g., Arrow-Debreu, Edgeworth boxes.)