There has recently been an increased interest in studying the language development of non-western languages. This is not new - it began in 1960’s and continued into the 1980’s and 1990’s. The current renewed interest is much welcomed, and will benefit from many of the experimental methods and theoretical insights developed over the past decades.

In a series of recent experiments (Davis, Millner and Reilly, 2005, Eckel and Grossman, 2003, 2005a-c, 2006), matching subsidies generate significantly higher charity receipts than do theoretically equivalent rebate subsidies. This paper reports a laboratory experiment conducted to examine whether the higher receipts are attributable to a relative preference for matching subsidies or to an “isolation effect” (McCaffery and Baron, 2003, 2006). Some potential policy implications of isolation effects on charitable contributions are also considered.

Previous literature and conventional wisdom have led researchers to believe that boredom increases economic risk taking, but the evidence in support of this conclusion is limited and has important shortcomings. In four experiments (including more than 1,300 subjects), we systematically studied the effects of boredom on economic risk preferences. Across different risk elicitation tasks, boredom inductions, incentive schemes, subject pools, and using both reduced form and structural analyses, we consistently failed to find an effect of boredom on risky decisions. Our results disprove that boredom leads to even small increments in risk taking in one-shot elicitation tasks, and small to medium increases in multiple-choice elicitations. These findings question an important established belief, contribute to better understand the consequences of boredom, and have substantive implications for experiments on economic decision making.

In this paper, we document a violation of normative and descriptive models of decision making under risk. In contrast to uncertainty effects found by Gneezy, List and Wu (2006), some subjects in our experiments valued lotteries more than the best possible outcome. We show that the overbidding effect is more strongly related to individuals’ competitiveness traits than comprehension of the lottery’s payoff mechanism.

Subjects performed a decision task (Grether, 1980) in both a well-rested and experimentally sleep-deprived state. We found two main results: 1) final choice accuracy was unaffected by sleep deprivation, and yet 2) the estimated decision model differed significantly following sleep-deprivation. Following sleep deprivation, subjects placed significantly less weight on new information in forming their beliefs. Because the altered decision process still maintains decision accuracy, it may suggest that increased accident and error rates attributed to reduced sleep in modern society stem from reduced auxiliary function performance (e.g., slowed reaction time, reduced motor skills) or other components of decision making, rather than the inability to integrate multiple pieces of information.

We designed an experiment to test the robustness of Dana, Weber, and Kuang’s (DWK), 2007 results. DWK observed that, when participants were given a “costless” way — the click of a button — to ignore the consequences of their actions on others’ payoffs, they chose to remain ignorant and fair behavior diminished. By implementing a double-blind experiment together with a design that controls for alternative explanations for the observed behavior, we confirmed DWK’s findings.

This paper experimentally investigates a well-known anomaly in portfolio management, i.e., the fact that paper losses are realized less than paper gains (disposition effect). I confirm the existence of the disposition effect in a simple risky task in which choices are taken sequentially. However, when choices are planned ahead and a contingent plan is defined, a reversal in the disposition effect is observed.

The dominant paradigm of experiments in the social and behavioral sciences views an experiment as a test of a theory, where the theory is assumed to generalize beyond the experiment's specific conditions. According to this view, which Alan Newell once characterized as “playing twenty questions with nature,” theory is advanced one experiment at a time, and the integration of disparate findings is assumed to happen via the scientific publishing process. In this article, we argue that the process of integration is at best inefficient, and at worst it does not, in fact, occur. We further show that the challenge of integration cannot be adequately addressed by recently proposed reforms that focus on the reliability and replicability of individual findings, nor simply by conducting more or larger experiments. Rather, the problem arises from the imprecise nature of social and behavioral theories and, consequently, a lack of commensurability across experiments conducted under different conditions. Therefore, researchers must fundamentally rethink how they design experiments and how the experiments relate to theory. We specifically describe an alternative framework, integrative experiment design, which intrinsically promotes commensurability and continuous integration of knowledge. In this paradigm, researchers explicitly map the design space of possible experiments associated with a given research question, embracing many potentially relevant theories rather than focusing on just one. The researchers then iteratively generate theories and test them with experiments explicitly sampled from the design space, allowing results to be integrated across experiments. Given recent methodological and technological developments, we conclude that this approach is feasible and would generate more-reliable, more-cumulative empirical and theoretical knowledge than the current paradigm—and with far greater efficiency.

We consider the simultaneous propagation of two contagions over a social network. We assume a threshold model for the propagation of the two contagions and use the formal framework of discrete dynamical systems. In particular, we study an optimization problem where the goal is to minimize the total number of new infections subject to a budget constraint on the total number of available vaccinations for the contagions. While this problem has been considered in the literature for a single contagion, our work considers the simultaneous propagation of two contagions. This optimization problem is NP-hard. We present two main solution approaches for the problem, namely an integer linear programming (ILP) formulation to obtain optimal solutions and a heuristic based on a generalization of the set cover problem. We carry out a comprehensive experimental evaluation of our solution approaches using many real-world networks. The experimental results show that our heuristic algorithm produces solutions that are close to the optimal solution and runs several orders of magnitude faster than the ILP-based approach for obtaining optimal solutions. We also carry out sensitivity studies of our heuristic algorithm.