Knowledge that Transforms

This paper proposes a model of cab drivers' labor supply, building on Henry S. Farber's (2005, 2008) empirical analyses and Botond Kőszegi and Matthew Rabin's (2006; henceforth “KR”) theory of reference-dependent preferences. Following KR, our model has targets for hours as well as income, determined by proxied rational expectations. Our model, estimated with Farber's data, reconciles his finding that stopping probabilities are significantly related to hours but not income with Colin Camerer et al.'s (1997) negative “wage” elasticity of hours; and avoids Farber's criticism that estimates of drivers' income targets are too unstable to yield a useful model of labor supply.

This paper analyzes the predictive power of a new data set of consumer gasoline price forecasts taken from the Michigan Survey of Consumers (MSC). MSC data generally perform as well as a no-change forecast in predicting future gasoline prices, and they substantially out-perform the no-change forecast during the recent economic crisis, during which time they track futures market prices. Finally, the cross-respondent dispersion of the MSC forecasts increases substantially during the economic crisis, paralleling the large increase in price volatility at this time.

This paper characterizes the optimal contract for a principal who repeatedly chooses among N potential agents under the threat of holdup. Over time, the principal would like to trade with different agents; however, the possibility of ex-post opportunism allows agents to collect rents and creates a fixed cost of initiating new relationships. In the optimal contract, the principal divides agents into “insiders” with whom she trades efficiently, and “outsiders” whom she is biased against. The optimal contract is self-enforcing if the principal is sufficiently patient and can be implemented by an “employment contract” that is robust to asymmetric information. JEL: C73, D82, D83, D86

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.

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.

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.

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.