Returns to Education: Evidence from U.K. Twins by Dorothe Bonjour, Lynn F. Cherkas, Jonathan E. Haskel, Denise D. Hawkes and Tim D. Spector. Published in volume 93, issue 5, pages 1799-1812 of American Economic Review, December 2003

The thesis of this symposium, organized by James Bicksler, was that while finance theory will surely inform practitioners, it seems appropriate to pay some attention to the opposite flow: practitioners can inform theory. Contributors include a distinguished group of practitioners with extensive backgrounds in economics, and economists with extensive public policy experience: Martin Feldstein, Robert Glauber, David Mullins, and Steven Wallman. Their topics range from privatizing social security, to managing market crashes, to the regulatory agency cost problem, to regulatory constraints in a technologically advanced world.

The thesis of this symposium, organized by James Bicksler, was that while finance theory will surely inform practitioners, it seems appropriate to pay some attention to the opposite flow: practitioners can inform theory. Contributors include a distinguished group of practitioners with extensive backgrounds in economics, and economists with extensive public policy experience: Martin Feldstein, Robert Glauber, David Mullins, and Steven Wallman. Their topics range from privatizing social security, to managing market crashes, to the regulatory agency cost problem, to regulatory constraints in a technologically advanced world.

This paper provides a systematic analysis of identification in linear social interactions models. This is a theoretical and econometric exercise as the analysis is linked to a rigorously delineated model of interdependent decisions. We develop an incomplete information game for individual choice under social influences that nests standard models as special cases. We consider identification of both endogenous and contextual social effects under alternative assumptions regarding an analyst’s a priori knowledge of social structure or access to individual-level or aggregate data. Finally, we discuss potential ramifications for identification of endogenous formation of social structure.

Focuses on a project by the American Accounting Association's Committees on Professional Examinations which evaluated the professional examinations for accountants. Objectives of the project; Methodology of the projects; Comparison of examinations and accounting curricula; Recommendations.

This study examines why people initially give to charities, why they remain committed to the cause, and what factors attenuate these influences. Using an experimental design that links donations across distinct treatments separated in time, we present several results. For example, previous donors are more likely to give, and contribute more, than other donor types. Yet, how previous donors were acquired is critical: agents initially attracted by an economic mechanism are more likely to continue giving than agents attracted by a nonmechanism factor. From a methodological viewpoint, our study showcases the benefit of moving beyond an experimental design that focuses on short-run substitution effects.

We propose a new framework for optimal experimentation, which we term the “A/B testing problem.” Our model departs from the existing literature by allowing for fat tails. Our key insight is that the optimal strategy depends on whether most gains accrue from typical innovations or from rare, unpredictable large successes. If the tails of the unobserved distribution of innovation quality are not too fat, the standard approach of using a few high-powered “big” experiments is optimal. However, if the distribution is very fat tailed, a “lean” strategy of trying more ideas, each with possibly smaller sample sizes, is preferred. Our theoretical results, along with an empirical analysis of Microsoft Bing’s EXP platform, suggest that simple changes to business practices could increase innovation productivity.

We introduce a new method to measure the temporal discounting of money. Unlike preceding methods, our method requires neither knowledge nor measurement of utility. It is easier to implement, clearer to subjects, and requires fewer measurements than existing methods.