Partial Identification in Triangular Systems of Equations With Binary Dependent Variables

This paper studies the special case of the triangular system of equations in Vytlacil and Yildiz (2007), where both dependent variables are binary but without imposing the restrictive support condition required by Vytlacil and Yildiz (2007) for identification of the average structural function (ASF) and the average treatment effect (ATE). Under weak regularity conditions, we derive upper and lower bounds on the ASF and the ATE. We show further that the bounds on the ASF and ATE are sharp under some further regularity conditions and an additional restriction on the support of the covariates and the instrument.     

Reducing Boarding in a Post‐Anesthesia Care Unit

When operating room schedules in hospitals are produced, the constraints and preferences of surgeons and hospital workers are a primary consideration. The downstream impact on post‐operative bed availability is often ignored. This can lead to the boarding of patients overnight in the post‐anesthesia care unit (PACU) because intensive care unit beds are unavailable. In this paper, we apply integer programming and simulation to develop improved surgical scheduling assignments. We want to balance new surgeries with hospital discharges in order to reduce the variability of occupied beds from one day to the next and, as a result, to reduce boarding in the PACU.     

INFORMATION AND THE EQUITY PREMIUM

We determine how better information affects the average equity premium in a standard representative‐agent exchange economy. Perfect information obviously eliminates the equity premium, and a particular kind of information about the level of future consumption always lowers the average equity premium. Surprisingly, information sometimes raises the average equity premium, no matter what the preferences of the representative agent. Information purely about the volatility either of consumption or the marginal utility of consumption raises the equity premium for a wide class of preferences. Moreover, information can raise the average equity premium by an arbitrarily large percentage (while still matching important magnitudes, such as average growth and the risk‐free rate). We consider two different economies: a two‐period economy with arbitrary preferences for the representative agent; and an infinite horizon economy, in which we restrict both preferences and the endowment distribution.     

Integral Identities for Random Variables

Using a general method for deriving identities for random variables, we find a number of new results involving characteristic functions and generating functions. The method is simply to promote a parameter in an integral relation to the status of a random variable and then take expected values of both sides of the equation. Results include formulas for calculating the characteristic functions for x ², √x, 1/x, x ² + x, R ² = x ² + y ², and so forth in terms of integral transforms of the characteristic functions for x and (x, y), and so forth. Generalizations to higher dimensions can be obtained using the same method. Expressions for inverse/fractional moments, E{n!}, and so forth are also presented, demonstrating the method.     

An Empirical Nonlinear Data-Fitting Approach for Transforming Data to Normality

A general method is proposed by which nonnormally distributed data can be transformed to achieve approximate normality. The method uses an empirical nonlinear data-fitting approach and can be applied to a broad class of transformations including the Box-Cox, arcsine, generalized logit, and Weibull-type transformations. It is easy to implement using standard statistical software packages. Several examples are provided.     

Comparing tests judged asymptotically equally efficient

For comparing two competing testing procedures whose power functions cannot be calculated exactly, the Pitman asymptotic relative efficiency is commonly used. This measure offers the advantages of simplicity in computation and interpretation, but is asymptotic in nature. In particular, it cannot distinguish between certain pairs of tests, namely, those with an asymptotic relative efficiency of 1. In this paper, we offer an alternative basis for making finite sample comparisons between tests judged asymptotically equally efficient. The criteria for comparison is based on the ratio of efficacies. Using this new criterion, we consider a series of examples in which two tests with an ARE of 1 are compared for finite n. In each case, either exact or simulated power curves are used to evaluate the effectiveness of this criterion in properly discriminating between the competing test procedures. Lastly, conditions are specified where the proposed criterion should be most effective.     

Nonparametric versus Parametric Estimation of the Cure Fraction Using Interval Censored Data

This article discusses estimation of the cure rate by means of the bounded cumulative hazard (BCH) model using interval censored data. The parametric and nonparametric estimation methods within the framework of the EM algorithm were employed for cure rate estimation and their results compared. The Turnbull estimator was used in the nonparametric estimation while in parametric method both the exponential and Weibull distributions were considered. We show via simulation that the nonparametric method is a viable alternative to the parametric one when the censoring rate is rapidly increasing.     

Modified cramer-von mises and anderson-darling tests for weibull distributions with unknown location and scale parameters

The standard Cramer-von Mises and Anderson-Darling goodness-of-fit tests require continuous underlying distributions with known parameters. In this paper, tables of critical values are generated for both tests for Weibull distributions with unknown location and scale parameters and known shape parameters. The powers of the Cramer-von Mises, Anderson-Darling, Kolmogorov-Smirnov, and Chi-Square tests for this situation are investigated. The Cramer-von Mises test has most power when the shape is 1.0 and the Anderson-Darling test has most power when the shape is 3.5. Finally, a relation between critical value and inverse shape parameter is presented.