Computing factors for exact two-sided tolerance limits for a normal distribution

A self-contained FORTRAN subroutine is provided which computes factors for Wald-Wolfowitz type tolerance limits allowing arbitrary combinations of sample size n and degrees of freedom ν. The exact calculations from our program reveal inadequacies of two existing approximations, especially when ν ? n. Numerous applications where ν ≠ n ? 1 are cited; two of these are discussed and illustrated.     

MATCHED PAIRS DISCRIMINATION: METHODOLOGY AND AN INVESTIGATION OF CORPORATE ACCOUNTING POLICIES

The matched-pairs methodology is becoming increasingly popular as a means of controlling extraneous factors in business research. This paper develops discriminant procedures for matched data and examines the properties of these methods. Data from a recent study by Hunt [14] on the determinants of inventory method choice are used to contrast the performance of the different methods. While all of the methods yield the same set of discriminating variables, those procedures that allow for the dependence among observations within a pair provide greater classificatory power than traditional multivariate techniques.     

Insurance Policies for Monetary Policy in the Euro Area

In this paper, we aim to design a monetary policy for the euro area that is robust to the high degree of model uncertainty at the start of monetary union and allows for learning about model probabilities. To this end, we compare and ultimately combine Bayesian and worst‐case analysis using four reference models estimated with pre–European Monetary Union (EMU) synthetic data. We start by computing the cost of insurance against model uncertainty, that is, the relative performance of worst‐case or minimax policy versus Bayesian policy. While maximum insurance comes at moderate costs, we highlight three shortcomings of this worst‐case insurance policy: (i) prior beliefs that would rationalize it from a Bayesian perspective indicate that such insurance is strongly oriented towards the model with highest baseline losses; (ii) the minimax policy is not as tolerant towards small perturbations of policy parameters as the Bayesian policy; and (iii) the minimax policy offers no avenue for incorporating posterior model probabilities derived from data available since monetary union. Thus, we propose preferences for robust policy design that reflect a mixture of the Bayesian and minimax approaches. We show how the incoming EMU data may then be used to update model probabilities, and investigate the implications for policy. (JEL: E52, E58, E61)     

Knowledge Accession and Knowledge Acquisition in Strategic Alliances: The Impact of Supplementary and Complementary Dimensions

This paper advances the concepts of knowledge accession and knowledge acquisition in strategic alliances by identifying supplementary and complementary dimensions to these knowledge transfer modes. Complementary knowledge transfer reflects the similarity of knowledge that the partners have and is conducted in pursuit of higher efficiency and productivity to enhance partner firms' existing competitiveness. Supplementary knowledge transfer occurs when partners each possess distinctive core competences and the information that is acquired or accessed increases the business scope of partners. As knowledge accession entails knowledge amalgamation that does not involve organizational learning, costs associated with the transfer process are lower and trust is easier to establish than in the case of knowledge acquisition. The paper reviews the implications of these transfer modes on trust building in alliances and their costs implications and presents a number of propositions for further exploration.     

State estimation for nonlinear state-space transmission models of tuberculosis

Given the high prevalence of tuberculosis (TB) and the mortality rate associated with the disease, numerous models, such as the Gammaitoni and Nucci (GN) model, were developed to model the risk of transmission. These models typically rely on a quanta generation rate as a measurement of infectivity. Since the quanta generation rate cannot be measured directly, the unique contribution of this work is to develop state estimators to estimate the quanta generation rate from available measurements. To estimate the quanta generation rate, the GN model is adapted into an augmented single-room GN model and a simplified two-room GN model. Both models are shown to be observable, i.e., it is theoretically possible to estimate the quanta generation rate given available measurements. Kalman filters are used to estimate the quanta generation rate. First, a continuous-time extended Kalman filter is used for both adapted models using a simulation and measurement sampling rate of 60 s. Accurate quanta generate rate estimates are achieved in both cases. A more realistic scenario is also considered with a measurement sampling rate of one day. For these estimates, a hybrid extended Kalman filter (HEKF) is used. Accurate quanta generation rate estimates are achieved for the more realistic scenario. Future work could potentially use the HEKFs, the adapted models, and real-time measurements in a control system feedback loop to reduce the transmission of TB in confined spaces such as hospitals.     

Quasiextinction Probabilities as a Measure of Impact on Population Growth

A probabilistic language based on stochastic models of population growth is proposed for a standard language to be used in environmental assessment. Environmental impact on a population is measured by the probability of quasiextinction. Density-dependent and independent models are discussed. A review of one-dimensional stochastic population growth models, the implications of environmental autocorrelation, finite versus "infinite" time results, age-structured models, and Monte Carlo simulations are included. The finite time probability of quasiextinction is presented for the logistic model. The sensitivity of the result with respect to the mean growth rate and the amplitude of environmental fluctuations are examined. Stochastic models of population growth form a basis for formulating reasonable criteria for environmental impact estimates.     

Analysis of the National Gambling Impact Study Commission Act

The following article by Keith Whyte represents the first of occasionally reprinted publications that are relevant to important historical events in the field of gambling studies. This article describes the act that led to the formation of the National Gambling Impact Study Commission. This Commission released its findings to the President and Congress of the United States during June of 1999.     

The Impact of Imperfect Processes on Production Run Times

This paper investigates the interaction between the economics of production and imperfections in the production process. Specifically, this paper is the first to devise a model in an attempt to provide managers with guidelines to choose the appropriate production run times to buffer against both the production of defective items and stoppages occurring due to machine breakdowns. In addition to providing several structural properties of the model, we show that a manager will always incur a cost penalty when (s)he uses the results of two oft‐cited models‐the EMQ (Economic Order/Manufacturing Quantity) and the NR‐E (No‐Resumption, Exponential machine breakdown)‐to determine production run times.