Knowledge that Transforms

The Combinatorial Clock Auction (CCA) is an important recent innovation in auction design which has been adopted for many spectrum auctions worldwide. Since its inception, the CCA has been in almost continual evolution. We begin by reviewing some important changes which have already occurred. Despite these enhancements, we observe that the performance of the CCA is still limited by weak activity rules, suboptimal price feedback, and a missing-bid problem. We then describe further evolutionary changes, including new activity rules, new approaches to pricing, and an integration of non-mutually-exclusive bids, which will help to address these issues.

Value-added models (VAMs) are increasingly used to measure school effectiveness. Yet, random variation in school attendance is necessary to test the validity of VAMs and to guide the selection of models for measuring causal effects of schools. In this paper, I use random assignment from a public school choice lottery to test the predictive power of VAM specifications. In VAMs with minimal controls and two or more years of prior data, I fail to reject the hypothesis that school effects are unbiased. Overall, many commonly used VAMs are accurate predictors of student achievement gains.

Current forecasts suggest that the vast majority of growth in energy demand will come from the developing world, and that China will play a major part in that growth. This paper presents evidence suggesting that the shape of the income distribution, which is typically omitted from forecasting models, plays a major role in driving household acquisition of energy-using durable goods in rural China. We use province-level data for rural households to show that the share of the population living above the poverty line is an important determinant of household appliance holdings even controlling for average household income.

Quantitatively, we investigate the allocative and welfare effects of secondary markets for cars. An important source of gains from trade in these markets is the heterogeneity in the willingness to pay for higher-quality (newer) goods, but transaction costs are an impediment to instantaneous trade. Calibration of the model successfully matches several aggregate features of the US and French used-car markets. Counterfactual analyses show that transaction costs have a large effect on volume of trade, allocations, and the primary market. Aggregate effects on consumer surplus and welfare are relatively small, but the effect on lower-valuation households can be large.

Nonlinear pricing and taxation complicate economic decisions by creating multiple marginal prices for the same good. This paper provides a framework to uncover consumers’ perceived price of nonlinear price schedules. I exploit price variation at spatial discontinuities in electricity service areas, where households in the same city experience substantially different nonlinear pricing. Using household-level panel data from administrative records, I find strong evidence that consumers respond to average price rather than marginal or expected marginal price. This suboptimizing behavior makes nonlinear pricing unsuccessful in achieving its policy goal of energy conservation and critically changes the welfare implications of nonlinear pricing.

We provide conditions under which contingent claim and asset demands are consistent with state independent Expected Utility maximization. The paper focuses on the case of a single commodity and demands are allowed to be functions of probabilities and not just prices and income. We extend prior analyses by deriving three distinct tests for demands to be rationalized by Expected Utility: (i) a contingent claim analogue to the certainty strong axiom of revealed preference, (ii) a characterization of the functional form for demand, and (iii) necessary and sufficient conditions based on the Slutsky matrix.

Food purchases differ substantially across countries. We use detailed household-level data from the United States, France, and the United Kingdom to (i) document these differences; (ii) estimate a demand system for food and nutrients; and (iii) simulate counterfactual choices if households faced prices and nutritional characteristics from other countries. We find that differences in prices and characteristics are important and can explain some difference (e.g., United States–France difference in caloric intake) but generally cannot explain many of the compositional patterns by themselves. Instead, it seems an interaction between the economic environment and differences in preferences is needed to explain cross-country differences.

Using data recently collected by the Panel Study of Income Dynamics, we find that the intergenerational correlation in expenditures is no larger than that in income, suggesting limited intra-family risk-sharing. On the other hand, even after controlling for the intergenerational correlation in income, the expenditures correlation remains significant. This suggests that other factors such as preferences, access to credit, and non-pecuniary inter vivos transfers potentially played a role in consumption smoothing across generations within a family. We also find that the correlation coefficients estimated using food and imputed total expenditures are smaller than that estimated using the measured total expenditures.

Massive Online Open Courses (MOOCs) present the potential to deliver high quality education to a large number of students. But they suffer from low completion rates. This paper identifies disorganization as a factor behind failure to complete a MOOC. Students who enroll one day late are 17 percentage points less likely to earn a certificate than students who enroll exactly on time. This reflects selection, but it does seem to be related to demographic characteristics, motivation to complete the course, or ability. This suggests that building in even more structure in the MOOC could be a factor in improving performance.

We use rich historical data on military procurement to estimate the effects of government spending. We exploit regional variation in military buildups to estimate an “open economy relative multiplier” of approximately 1.5. We develop a framework for interpreting this estimate and relating it to estimates of the standard closed economy aggregate multiplier. The latter is highly sensitive to how strongly aggregate monetary and tax policy “leans against the wind.” Our open economy relative multiplier “differences out” these effects because monetary and tax policies are uniform across the nation. Our evidence indicates that demand shocks can have large effects on output.