Productive Efficiency of the Swine Industry in Hawaii: Stochastic Frontier vs. Data Envelopment Analysis

Improving productive efficiency is an increasingly important determinant of the future of the swine industry in Hawaii. This paper examines the productive efficiency of a sample of swine producers in Hawaii by estimating a stochastic frontier production function and the constant returns to scale (CRS) and variable returns to scale (VRS) output-oriented DEA models. The technical efficiency estimates obtained from the two frontier techniques are compared. The scale properties are also examined under the two approaches. The industry's potential for increasing production through improved efficiency is also discussed.     

Assessment of Interjudge Reliability in the Open-Ended Questions Coding Process

In the process of coding open-ended questions, the evaluation of interjudge reliability is a critical issue. In this paper, using real data, the behavior of three coefficients of reliability among coders, Cohen’s K, Krippendorff’s α and Perreault and Leigh’s I _r are patterned, in terms of the number of judges involved and the categories of answer defined. The outcome underlines the importance of both variables in the valuations of interjudge reliability, as well as the higher adequacy of Perreault and Leigh’s I _r and Krippendorff’s α for marketing and opinion research.     

RECEIPT OF INFORMATION AND INFLUENCE OVER DECISIONS IN HOSPITALS BY THE BOARD, CHIEF EXECUTIVE OFFICER AND MEDICAL STAFF

This article examines relationships between receipt of internal administrative information in hospitals, influence over general management decisions, and the extent to which certain organizational characteristics predict the receipt of information by each of the three major groups in hospitals: the board, the CEO, and the medical staff. Using a US national sample of 287 non-profit community hospitals, CEOs were found to receive the greatest amount of information and had highest influence while medical staffs were lowest on both measures. of five major organizational characteristics, hospital size emerged as the single strongest predictor of receipt of information for both boards (beta =?0.28, p 0.001) and medical staffs (beta =?0.42, p 0.001). Overall, the five dependent variables explained 18 per cent of the variance in receipt of information by boards and 28 percent of the variance for medical staffs.     

DEVIL'S ADVOCACY IN MANAGERIAL DECISION-MAKING

There is some debate about the potential value of using devil's advocates in top-level organizational decision-making. In this paper, the contrasting views on this question are summarized briefly and the field and laboratory research on the devil's advocate and related techniques is discussed. This research is then used as the basis for detailed suggestions on the effective use of devil's advocates in improving managerial decisions.     

Simpler Probabilistic Population Forecasts: Making Scenarios Work

The traditional high-low-medium scenario approach to quantifying uncertainty in population forecasts has been criticized as lacking probabilistic meaning and consistency. This paper shows, under certain assumptions, how appropriately calibrated scenarios can be used to approximate the uncertainty intervals on future population size and age structure obtained with fully stochastic forecasts. As many forecasting organizations already produce scenarios and because dealing with them is familiar territory, the methods presented here offer an attractive intermediate position between probabilistically inconsistent scenario analysis and fully stochastic forecasts.     

Inter-market competition for exchange traded funds

We examine how the different mix of informed and liquidity trading in the market for ETFs affects the nature of inter-market competition. We find that both the characteristics of the securities and the structures of the competing markets jointly determine the nature of inter-market competition. Given the superior execution quality on the ECNs and the low adverse selection costs in the ETF market, anonymous market such as the ECNs, attract both liquidity and informed traders. We also find that markets compete in a subset of ETFs. In addition, we find that quotebased competition is prevalent in the market for ETFs.     

On minimum distance estimators for unimodal densities

It is shown that minimum distance estimators for families of unimodal densities are always consistent; the rate of convergence is indicated. An algorithm is proposed for computing the minimum distance estimator for the family of all unimodal densities. References are given to the maximum likelihood method and the kernel method.     

Preventing HIV in injection drug users: exploring the tradeoffs between interventions

Injection drug users (IDUs) transmit the human immunodeficiency virus (HIV) via both needle sharing and sex. Available interventions for this population have varying costs and effectiveness and focus on different risk behaviors. In this analysis, we look at two interventions. One is inexpensive, broad-based and provides modest risk reductions (street outreach (SO)); the other is narrowly focused, expensive and relatively effective (methadone maintenance). This analysis explores the effects of population risk behavior, intervention effectiveness, intervention costs, and decision constraints when allocating funds between these two interventions to maximize effectiveness. We develop a model of the spread of HIV, dividing IDUs into susceptibles (uninfected) and infectives, and separately portraying sex and injection risk. We simulate the epidemic in New York City for time periods from the mid-1980s to the early 1990s, and incorporate the behavioral effects of two interventions performed singly or in combination to find the allocation that maximizes the number of infections averted in the IDUs and their noninjecting sex partners, assuming interventions have increasing marginal costs. We find that the optimal allocation nearly always involves spending the maximum allowable amount on SO. This result is largely insensitive to variations in risk parameters, intervention efficacy, or cost. The model's structure, however, makes clear that many factors contribute to this insensitivity, namely the scope of the interventions, the dual drug/sex nature of HIV risk in the population, the asymmetry of sexual risk for men and women, and the potential benefits to nonIDUs.     

The Impact of Transaction Costs and the Expected Length of Stay on Homeownership

Economic theory suggests that an increase in the expected length of stay in a dwelling increases the probability of a household choosing to own a house rather than rent. This hypothesis is derived from recognition that there are substantial transaction costs associated with homeownership and increased expected time in the home reduces the annualized transaction cost. Using a military data set, we confirm that expected length of stay in a dwelling and the transaction costs of selling are very important to the ownership decision. Our best estimate of the transaction costs of selling a home are the sum of 3% of house value and 4% of household earnings.     

Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models

Nine macroeconomic variables are forecast in a real-time scenario using a variety of flexible specification, fixed specification, linear, and nonlinear econometric models. All models are allowed to evolve through time, and our analysis focuses on model selection and performance. In the context of real-time forecasts, flexible specification models (including linear autoregressive models with exogenous variables and nonlinear artificial neural networks) appear to offer a useful and viable alternative to less flexible fixed specification linear models for a subset of the economic variables which we examine, particularly at forecast horizons greater than 1-step ahead. We speculate that one reason for this result is that the economy is evolving (rather slowly) over time. This feature cannot easily be captured by fixed specification linear models, however, and manifests itself in the form of evolving coefficient estimates. We also provide additional evidence supporting the claim that models which ‘win’ based on one model selection criterion (say a squared error measure) do not necessarily win when an alternative selection criterion is used (say a confusion rate measure), thus highlighting the importance of the particular cost function which is used by forecasters and ‘end-users’ to evaluate their models. A wide variety of different model selection criteria and statistical tests are used to illustrate our findings.