An Average Derivative Estimation of Stochastic Frontiers

This paper utilizes the average derivative estimation of Stoker (1986) and the pesudo-likelihood estimation of Fan, Li, and Weersink (1996) to estimate a semiparametric stochastic frontier regression, y = g(x) + , where the function g(.)is unknown and is a composite error in a standard setting. The proposed semiparametric method of estimation is applied to data on farmers' credit unions in Taiwan. Empirical results show that the banking services of the farmers' credit unions is subject to economies of scale, but high degree of cost inefficiency in operation.     

Hölder continuity of the policy function approximation in the value function approximation

We show that given a value function approximation V of a strongly concave stochastic dynamic programming problem (SDDP), the associated policy function approximation is Hölder continuous in V.     

Flexibility at different stages in the life cycle of projects: An empirical illustration of the “freedom to maneuver”

Many textbooks on project management present illustrations concerning the relative size of project attributes during different project phases. The derived models all have attributes in common, such as uncertainty, significance of decisions, and degree of freedom to maneuver, that are typically high in the beginning of the project and low in the end. At the same time, variables such as the accumulated cost and available information begin at low levels and end up at a high level at the end of the project. Based on empirical data from projects, this paper illustrates and quantifies one of these attributes, the freedom to maneuver, in different project phases.     

The topography of metropolitan employment: Identifying centers of employment in a polycentric urban area

While it is well recognized that US metropolitan areas are polycentric, there is little consensus as to the appropriate method for identifying concentrations of employment within them. Existing methods suffer from strong assumptions about parametric form, misspecification, or reliance on local knowledge to calibrate model parameters. This paper introduces a new nonparametric method for identifying subcenters. Results indicate that this, more flexible, nonparametric approach yields greater accuracy with regard to both urban and suburban centers compared with other approaches. This approach should provide better data for the numerous topics that depend on the spatial accounting of employment within metropolitan areas.     

Drug testing and the law

This article examines judicial and administrative rulings and legislation involving or related to the issue of drug testing in the workplace. It discusses the rights of employees in the public and private sector: constitutional rights; federal, state, and local statutory rights; rights of unionized employees; and common law rights. It analyzes both the current state of the law and future directions the law may take, as courts and administrative agencies decide more cases and governmental bodies continue to pass drug testing legislation.     

Remarks on sequential estimation of a linear function of two means: The normal case

Asymptotic normality of the stopping time ofMukhopadhyay [1976] relating to the point estimation problem is proved. Also moderate sample size behaviour of this stopping time has been studied by Monte-Carlo methods.     

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.     

Productivity and Welfare

Technical change is generally characterized by a rate and biases, both evaluated for given producer prices. This paper examines the potential discrepancy between this rate and the corresponding rate of consumer welfare change as measured by Allais distributable surplus. We postulate a general equilibrium context with various market failures (taxes, quotas, imperfect competition, and “poorly priced” commodities), and use comparative statics to express the rate of welfare change in terms of the rate and biases of the technical change. An elementary simulation model of a taxed economy suggests that the rate of welfare change may differ from the rate of technical change by as much as 50% under plausible circumstances.