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We designed a commitment savings product for a Philippine bank and implemented it using a randomized control methodology. The savings product was intended for individuals who want to commit now to restrict access to their savings, and who were sophisticated enough to engage in such a mechanism. We conducted a baseline survey on 1777 existing or former clients of a bank. One month later, we offered the commitment product to a randomly chosen subset of 710 clients; 202 (28.4 percent) accepted the offer and opened the account. In the baseline survey, we asked hypothetical time discounting questions. Women who exhibited a lower discount rate for future relative to current trade-offs, and hence potentially have a preference for commitment, were indeed significantly more likely to open the commitment savings account. After twelve months, average savings balances increased by 81 percentage points for those clients assigned to the treatment group relative to those assigned to the control group. We conclude that the savings response represents a lasting change in savings, and not merely a short-term response to a new product. I.

This study develops theory and uses a door-to-door fund-raising field experiment to explore the economics of charity. We approached nearly 5000 households, randomly divided into four experimental treatments, to shed light on key issues on the demand side of charitable fund-raising. Empirical results are in line with our theory: in gross terms, the lotteries raised more money than the voluntary contributions treatments. Interestingly, in terms of both maximizing current contributions and inducing participation, we find that a one-standard deviation increase in female solicitor physical attractiveness is similar to that of the lottery incentive. I.

In many field settings, participants sort among environments based on their preferences, beliefs, and skills. Experiments, however, often ignore the potential impact of such sorting. We demonstrate the importance of sorting for experiments, in the domain of social preferences. When individuals are constrained to play a dictator game, 61 % of the subjects share. But when subjects are allowed to avoid the situation altogether, only 23 % share. This reversal of proportions illustrates the importance of sorting for drawing inferences from experimental findings to the field. In a second experiment, we subsidize participation in the dictator game with higher payoffs relative to opting out. We find that the subjects whom the increased payoffs attract back into the sorting environment are primarily those who share the least. Thus, even with subsidization, the portion shared by participants remains much lower than without sorting. A second consequence of sorting, then, is that incentives aimed at enticing pro-social behavior can induce adverse selection. Both experiments also shed light on the motives for sharing. While much sharing is consistent with other-regarding preferences, the majority of sharers prefer to avoid the sharing environment.

Online labor markets have great potential as platforms for conducting experiments. They provide immediate access to a large and diverse subject pool, and allow researchers to control the experimental context. Online experiments, we show, can be just as valid—both internally and externally—as laboratory and field experiments, while often requiring far less money and time to design and conduct. To demonstrate their value, we use an online labor market to replicate three classic experiments. The first finds quantitative agreement between levels of cooperation in a prisoner’s dilemma played online and in the physical laboratory. The second shows – consistent with behavior in the traditional laboratory – that online subjects respond to priming by altering their choices. The third demonstrates that when an identical decision is framed differently, individuals reverse their choice, thus replicating a famed Tversky-Kahneman result. Then we conduct a field experiment showing that workers have upwardsloping labor supply curves. Finally, we analyze the challenges to online experiments, proposing methods to cope with the unique threats to validity in an online setting, and examining the conceptual issues surrounding the external validity of online results. We conclude by presenting our views on the potential role that online experiments can play within the social sciences, and then recommend software development priorities and best practices. ∗Thanks to Alex Breinin and Xiaoqi Zhu for excellent research assistance. Thanks to

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In this paper we propose an approach to knowledge intensive CBR, where explanations are generated from a domain model consisting partly of a semantic network and partly of a Bayesian network (BN). The BN enables learning within this domain model based on the observed data. The domain model is used to focus the retrieval and reuse of past cases, as well as the indexing when learning a new case. Essentially, the BN-powered submodel works in parallel with the semantic network model to generate a statistically sound contribution to case indexing, retrieval and explanation. 1. Introduction and

An important question facing experimental economists is whether behavior inside the laboratory is a good indicator of behavior outside the laboratory. We begin with a model that assumes the choices that individuals make depend not just on financial implications, but also on the nature and extent of scrutiny by others, the particular context in which a decision is embedded, and the manner in which participants are selected. To the extent that lab and naturally-occurring environments systematically differ on any of these dimensions, the results obtained inside and outside the lab need not correspond. Based on theory and empirical evidence, we argue that lab experiments are a useful tool for generating qualitative insights, but are not well-suited for obtaining deep structural parameter estimates. We conclude that the sharp dichotomy sometimes drawn between lab experiments and data generated in natural settings is a false one. Each approach has strengths and weaknesses, and a combination of the two is likely to provide deeper insights than either in isolation.

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We design a field experiment to explore the use of social comparison to increase contributions to an online community. We find that, after receiving behavioral information about the median user’s total number of movie ratings, users below the median demonstrate a 530-percent increase in the number of monthly movie ratings, while those above the median decrease their ratings by 62-percent. When given outcome information about the average user’s net benefit score, aboveaverage users mainly engage in activities that help others. Our findings suggest that effective personalized social information can increase the level of public goods provision. (JEL C93, H41) With the increasing popularity of the Internet, information technology is changing the way we interact, entertain, communicate and consume. In online communities, groups of people meet to share information, discuss mutual interests, play games and carry out business. Users of communities such as SourceForge