Characterizations of logarithmic series distrimtrans

The distributions of X, Y and (X. Y ), where X and Y are random variables with probability functions of a logarithmic series law, are characterized by the regression function of X on Y and the conditional distribution of Y given X. Moreover, characterizations are given for binomial or Pascal conditional distributions in terms of the regression function of X on Y and the marginal distribution of X.     

MAXIMUM ENTROPY REVISITED

Maximum entropy or minumum information distributions have their flexibilities severely curtailed if R or R₊ is the domain and α is imposed as a Lebesgue measure. Tremendous flexibility is gained by removing these restrictions.     

Uncertainty and Amenity Values in Renewable Resource Economics

In this paper, we study the effects of amenities and uncertainty on the optimal exploitation of a renewable resource. First, if society displays a protection motive (in the presence of amenities), its optimal harvesting strategy will be more conservative. Second, we show that ecological uncertainty leads society to develop the opposite behavior, thus reducing its exposition towards risk. A stationary analysis is undertaken to analytically quantify and compare these two effects. With a Gompertz natural regeneration function and a proportional risk, the amenity effect is proved to prevail if and only if stochastic fluctuations on the resource stock are not too large.     

Absenteeism in the workplace: results from Danish sample survey data

Absentee data is analyzed using a worker environmental survey carried out in 1995. In a model which distinguishes between discretionary and involuntary absences individuals are assumed to maximize expected utility. This generates a probability distribution of days absent per year which is a mixture of two negative binomial distributions representing the behaviour of two unknown types of agent. This distribution is estimated separately for men and women. For each gender the number of days absent is quite small relative to what researchers have found in other countries. In the empirical model we identify different effects of the explanatory variables for workers with low rates of absenteeism and workers with high rates of absenteeism.     

旅游目的地合作关系发展刍议

在旅游市场经济条件下，加强旅游目的地合作关系是实现旅游资源优化整合，提高旅游市场竞争力，实现旅游可持续发展的重要途径和必然选择。分析了旅游目的地合作关系发展的现状，并探讨了旅游目的地合作关系的特点以及发展趋势。     

Industry R&D intensity distributions: regularities and underlying determinants

This paper aims to examine the nature of the distributions of firm R&D intensities within industries and explore the factors that underlie the industry R&D intensity distributions. In particular, following the seminal study by Cohen and Klepper (1992) and using some new and rich data on firm R&D intensities for seven industries across six countries, this study examines the regularities in the industry R&D intensity distributions and demonstrates, based on a simple model of firm R&D, that the industry R&D intensity distributions are governed by the distributions of technological competence, a measure of firm R&D productivity, which corresponds to the notion of the “unobserved R&D-related capabilities” suggested by Cohen and Klepper (1992). This study found that firm R&D intensities within industries are lognormally distributed, displaying a strikingly regular pattern across industries, that the industry distributions of the levels of technological competence are also lognormal, and that, based on the formal model of firm R&D and the notion of the unobserved R&D-related capabilities, the distribution of firm technological competence within an industry underlies the industry's firm R&D intensity distribution.     

Computational Methods for Measuring the Difference of Empirical Distributions

This paper presents a simple computational method for measuring the difference of independent empirical distributions estimated by bootstrapping or other resampling approaches. Using data from a field test of external scope in contingent valuation, this complete combinatorial method is compared with other methods (empirical convolutions, repeated sampling, normality, nonoverlapping confidence intervals) that have been suggested in the literature. Tradeoffs between methods are discussed in terms of programming complexity, time and computer resources required, bias, and the precision of the estimate.     

Mixed Poisson Distributions

Mixed Poisson distributions have been used in a wide range of scientific fields for modeling nonhomogeneous populations. This paper aims at reviewing the existing literature on Poisson mixtures by bringing together a great number of properties, while, at the same time, providing tangential information on general mixtures. A selective presentation of some of the most prominent members of the family of Poisson mixtures is made.     

Dual Class IPOs ARE Underpriced Less Severely

We analyze a sample of dual and single class initial public offerings (IPOs) to investigate whether empirical estimates of underpricing determinants are consistent across alternative measures of firm size and alternative techniques intended to account for underwriter price stabilization efforts. We find that results from long‐standing methods for estimating underpricing relations are generally robust to one's choice of size proxy and are consistent with estimates obtained from censored regressions of first‐day returns and from least squares regressions of longer horizon initial returns. We also confirm an existing finding in the literature that dual class IPOs endure less underpricing than do single class firms.     

Minimax estimation of constrained parametric functions for discrete families of distributions

For a vast class of discrete model families where the natural parameter is constrained to an interval, we give conditions for which the Bayes estimator with respect to a boundary supported prior is minimax under squared error loss type functions. Building on a general development of éric Marchand and Ahmad Parsian, applicable to squared error loss, we obtain extensions to various parametric functions and squared error loss type functions. We provide illustrations for various distributions and parametric functions, and these include examples for many common discrete distributions, as well as when the parametric function is a zero-count probability, an odds-ratio, a Binomial variance, and a Negative Binomial variance, among others. The Research of M. Jafari Jozani is supported by a grant of the Institute for Research and Planning in Higher Education, Ministry of Science, Research and Technology, Iran. The Research of é. Marchand is supported by NSERC of Canada.