Monetary Discounting of Delayed Consequences Predict Employment Nudity: Exotic Dancers Versus Waitresses

The present study examined temporal monetary discounting rates among exotic dancers, waitresses who are required to wear revealing uniforms, and waitresses at a local restaurant where revealing clothes are not part of work attire. Current findings indicate that exotic dancers and waitresses who are required to wear revealing clothing discounted significantly more than waitresses at restaurants where provocative dress is not required. These results suggest that the type of job held may predict impulsivity, with nude or risqué occupations indicating steeper patterns of overall discounting.     

Planning and analysis of measurement reliability studies

In the traditional plan for assessing the reliability of a measurement system, a number of raters each measure the same group of subjects. If the system has a large number of raters, we recommend a new set of plans that has two advantages over the traditional plan. First, the proposed plans provide greater precision for estimating the intraclass correlation coefficient with the same total number of measurements. Second, the plans are flexible and can be adapted to constraints on the number of times any subject can be assessed or the number of times any rater can make an assessment. We provide a simple tool for planning a reliability study, access to the software for the planning in the case where there are constraints and an example to demonstrate the analysis of data from the proposed plans. The Canadian Journal of Statistics 39: 344–355; 2011 © 2011 Statistical Society of Canada     

Local and omnibus goodness-of-fit tests in classical measurement error models

We consider functional measurement error models, i.e. models where covariates are measured with error and yet no distributional assumptions are made about the mismeasured variable. We propose and study a score-type local test and an orthogonal series-based, omnibus goodness-of-fit test in this context, where no likelihood function is available or calculated-i.e. all the tests are proposed in the semiparametric model framework. We demonstrate that our tests have optimality properties and computational advantages that are similar to those of the classical score tests in the parametric model framework. The test procedures are applicable to several semiparametric extensions of measurement error models, including when the measurement error distribution is estimated non-parametrically as well as for generalized partially linear models. The performance of the local score-type and omnibus goodness-of-fit tests is demonstrated through simulation studies and analysis of a nutrition data set.     

Identification and Estimation of a Discrete Game of Complete Information

We discuss the identification and estimation of discrete games of complete information. Following Bresnahan and Reiss (1990, 1991), a discrete game is a generalization of a standard discrete choice model where utility depends on the actions of other players. Using recent algorithms to compute all of the Nash equilibria to a game, we propose simulation‐based estimators for static, discrete games. We demonstrate that the model is identified under weak functional form assumptions using exclusion restrictions and an identification at infinity approach. Monte Carlo evidence demonstrates that the estimator can perform well in moderately sized samples. As an application, we study entry decisions by construction contractors to bid on highway projects in California. We find that an equilibrium is more likely to be observed if it maximizes joint profits, has a higher Nash product, uses mixed strategies, and is not Pareto dominated by another equilibrium.