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A power law is the form taken by a large number of surprising empirical regularities in economics and finance. This article surveys well-documented empirical power laws concerning income and wealth, the size of cities and firms, stock market returns, trading volume, international trade, and executive pay. It reviews detail-independent theoretical motivations that make sharp predictions concerning the existence and coefficients of power laws, without requiring delicate tuning of model parameters. These theoretical mechanisms include random growth, optimization, and the economics of superstars coupled with extreme value theory. Some of the empirical regularities currently lack an appropriate explanation. This article highlights these open areas for future research.

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This paper defines and analyzes a "sparse max" operator, which is a less than fully attentive and rational version of the traditional max operator. The agent builds (as economists do) a simplified model of the world which is sparse, considering only the variables of first-order importance. His stylized model and his resulting choices both derive from constrained optimization. Still, the sparse max remains tractable to compute. Moreover, the induced outcomes reflect basic psychological forces governing limited attention. The sparse max yields a behavioral version of two basic chapters of the microeconomics textbook: consumer demand and competitive equilibrium. We obtain a behavioral version of Marshallian and Hicksian demand, the Slutsky matrix, the Edgeworth box, Roy's identity etc. The Slutsky matrix is no longer symmetric: non-salient prices are associated with anomalously small demand elasticities. Because the consumer exhibits nominal illusion, in the Edgeworth box, the offer curve is a two-dimensional surface rather than a one-dimensional curve. As a result, different aggregate price levels correspond to materially distinct competitive equilibria, in a similar spirit to a Phillips curve. This framework provides a way to assess which parts of basic microeconomics are robust, and which are not, to the assumption of perfect maximization.

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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 "cognitive discounting" parameter, which quantifies how poorly agents understand future economic disturbances. 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 reduces 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 brings a natural solution to 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 extant empirical evidence.

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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 a great deal of progress has been achieved, although much more work needs to be 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 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.

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This paper proposes that idiosyncratic firm-level fluctuations can explain an important part of aggregate shocks, and provide a microfoundation for aggregate productivity shocks. Existing research has focused on using aggregate shocks to explain business cycles, arguing that individual firm shocks average out in aggregate. I show that this argument breaks down if the distribution of firm sizes is fat-tailed, as documented empirically. The idiosyncratic movements of the largest 100 firms in the US appear to explain about one third of variations in output and the Solow residual. This "granular" hypothesis suggests new directions for macroeconomic research, in particular that macroeconomic questions can be clarified by looking at the behavior of large firms. This paper's ideas and analytical results may also be useful to think about the fluctuations of other economic aggregates, such as exports or the trade balance.