Knowledge that Transforms

With a focus on two sorts of regulation—renewable electricity and clean energy standards, and automobile fuel-economy standards—we analyze problematic interactions that arise when state policies are nested within the domain of Federal policy. Here state efforts may fail to reduce greenhouse gas emissions nationally, and may compromise cost-effectiveness. Difficulties from overlapping regulations are avoidable through price- (as opposed to quantity-) based Federal policy. We identify some potentially positive interactions between state and Federal policies, and identify rationales for state action when Federal and state policies do not overlap.

The quantity of human-generated light visible from outer space reflects variation in both population density and income per capita. In this paper we explore the usefulness of the change in visible light as a measure of GDP growth. We discuss the data, and then present a statistical framework that uses lights growth to augment existing income growth measures, assuming that measurement errors in the two series are uncorrelated. For some countries with very poor income measurement, we significantly revise estimates of growth. Our technique also produces growth estimates for cities or regions where no other data are available.

When does a common group identity improve efficiency in coordination games? To answer this question, we propose a group-contingent social preference model and derive conditions under which social identity changes equilibrium selection. We test our predictions in the minimum-effort game in the laboratory under parameter configurations which lead to an inefficient low-effort equilibrium for subjects with no group identity. For those with a salient group identity, consistent with our theory, we find that learning leads to ingroup coordination to the efficient high-effort equilibrium. Additionally, our theoretical framework reconciles findings from a number of coordination game experiments. (JEL C71, C91, D71)

Multiproduct firms can set separate prices for all possible bundled combinations of its products (“mixed bundling”). However, this is impractical for firms with more than a few products, because the number of prices increases exponentially with the number of products. We find that simple pricing strategies are often nearly optimal. Specifically, we show that bundle-size pricing—setting prices that depend only on the size of bundle purchased—tends to be more profitable than offering the individual products priced separately and tends to closely approximate the profits from mixed bundling. (JEL D24, D42, L11, L13, L25).

We show how changes in the volatility of the real interest rate at which small open emerging economies borrow have an important effect on variables like output, consumption, investment, and hours. We start by documenting the strong evidence of time-varying volatility in the real interest rates faced by four emerging economies: Argentina, Brazil, Ecuador, and Venezuela. We estimate a stochastic volatility process for real interest rates. Then, we feed this process in a standard small open economy business cycle model. We find that an increase in real interest rate volatility triggers a fall in output, consumption, investment, hours, and debt. (JEL E13, E20, E32, E43, F32, F43, 011)

A central difficulty in economics is to create a model with both good business cycle properties and asset pricing properties. I show how to solve this difficulty by a simple portable modeling device: the “disasterization” of models. Take an economy with good business cycle properties and create a new, “disasterized” economy, which is essentially identical to the original one except that disasters can destroy part of the capital stock and productivity. In such a disasterized economy, asset prices exhibit high and volatile risk premia, but macro variables remain unchanged. Perturbations of this benchmark allow for feedback from finance to macro.

We test for residential sorting and changes in neighborhood characteristics in response to the cleanup of hazardous waste sites using restricted access fine-geographical-resolution block data. We examine changes between 1990 and 2000 in blocks within 5km of sites that are proposed to the National Priority List that fall in a narrow interval of Hazardous Ranking Scores, comparing blocks near sites that were cleaned with those near sites that were not. Cleanup leads to increases in population density and housing unit density; increases in mean household income and shares of college-educated; but also to increases in the shares of minorities.

The burden of proof is a central feature of adjudication, and analogues exist in many other settings. It constitutes an important but largely unappreciated policy instrument that interacts with the level of enforcement effort and magnitude of sanctions in controlling harmful activity. Models are examined in which the prospect of sanctions affects not only harmful acts but also benign ones, on account of the prospect of mistaken application of sanctions. Accordingly, determination of the optimal strength of the burden of proof, as well as optimal enforcement effort and sanctions, involves trading off deterrence and the chilling of desirable behavior, the latter being absent in previous work. The character of the optimum differs markedly from prior results and from conventional understandings of proof burdens, which can be understood as involving Bayesian posterior probabilities. Additionally, there are important divergences across models in which enforcement involves monitoring (posting officials to be on the lookout for harmful acts), investigation (inquiry triggered by the costless observation of particular harmful acts), and auditing (scrutiny of a random selection of acts). A number of extensions are analyzed, in one instance nullifying key results in prior work.

I study how limited abilities to process information affect choice behavior. I model the decision-making process by an automaton, and measure the complexity of a specific choice rule by the minimal number of states an automaton implementing the rule uses to process information. I establish that any choice rule that is less complicated than utility maximization displays framing effects. I then prove that choice rules that result from an optimal trade-off between maximizing utility and minimizing complexity are history-dependent satisficing procedures that display primacy and recency effects. (JEL D01, D03, D11, D83)

ABSTRACT Motivating innovation is important in many incentive problems. This paper shows that the optimal innovation‐motivating incentive scheme exhibits substantial tolerance (or even reward) for early failure and reward for long‐term success. Moreover, commitment to a long‐term compensation plan, job security, and timely feedback on performance are essential to motivate innovation. In the context of managerial compensation, the optimal innovation‐motivating incentive scheme can be implemented via a combination of stock options with long vesting periods, option repricing, golden parachutes, and managerial entrenchment.