Voluntary income sharing and the design of unemployment insurance

This paper uses a model of search unemployment to discuss the interaction between publicly provided insurance and informal insurance through voluntary income sharing, e.g., between spouses. Income sharing reduces the optimal level of public unemployment insurance. While it is always individually rational for partners to share income, the effect of voluntary income sharing on welfare will be negative unless partners can either observe each other's search behavior or are sufficiently altruistic towards each other. The model is also used to examine a family-based policy. The welfare gains from using such policy are argued to be small. Received: 14 December 2000/Accepted: 5 November 2001     

Family size and optimal income taxation

This paper studies the role of family size in the design of optimal income taxation. We consider a second best setting where the government observes the number of children and the income of the parents but not their productivity. With a linear tax schedule the marginal tax rate is shown to decrease with the number of children, while the relationship between the demogrant and family size appears to be ambiguous. With two ability levels, optimal non-linear income tax implies zero marginal tax rates for the higher ability parents; low ability parents have positive marginal tax rates that decrease with family size. Received: 4 September 2000/Accepted: 17 May 2001     

The protestant work ethic,human values and attitudes towards taxation

The literature on demographic determinants of attitudes towards taxation was briefly reviewed. Whereas most previous concerned the relationship between such things as income, vote etc. and tax attitudes, this study examined the relationship between Protestant Work Ethic beliefs, social value systems and attitudes toward taxation. It was demonstrated that subjects who strongly endorsed the Protestant Work Ethic were more opposed to taxation than those who did not strongly endorse these beliefs. Further many of the instrumental and terminal value systems of subjects who were pro-taxation were significantly different from those who were anti-taxation. The results are discussed in terms of the psychology of lay-economic beliefs and implications for social change were noted.     

Binary-image restoration

We consider the problem of binary-image restoration. The image being restored is not random, and we make no assumption about the nature of its contents. The estimate of the colour at each site is a fixed (the same for all sites) function of the data available in a neighbourhood of that site. Under this restriction, the estimate minimizing the overall mean squared error of prediction is the conditional expectation of the true colour given the observations in the neighbourhood of a site. The computation of this conditional expectation leads to the formal definition of the local characteristics of an image, namely, the frequency with which each pattern appears in the true unobserved image. When the “true” distribution of the patterns is unknown, it can be estimated from the records. The conditional expectation described above can then be evaluated using the estimated distribution of the patterns, and this procedure leads to a very natural estimate of the colour at each site. We propose two unbiased and consistent estimates for the distribution of patterns when the noise is a Gaussian white noise. Since the size of realistic images is very large, the estimated pattern distribution is usually close to the true one. This suggests that the estimated conditional expectation can be expected to be nearly optimal. An interesting feature of the proposed restoration methods is that they do not require prior knowledge of the local or global properties of the true underlying image. Several examples based on synthetic images show that the new methods perform fairly well for a variety of images with different degrees of colour continuity or textures.     

Estimation of parameters in survey sampling: Optimality

Some recent works on estimation in survey sampling are analyzed and extended from the perspective of the theory of optimal estimating functions.     

On nonparametric profile analysis of several multivariate samples

A unified development is offered for asymptotically distribution-free profile analysis of several multivariate samples. This includes as special cases procedures based on generalized U-statistics and also those based on linear rank statistics. Furthermore, it includes as special cases analysis of location profiles and also scalar profiles. Finally, asymptotic power and consistency properties are discussed for tests of hypotheses and subhypotheses of interest.     

Agricultural policies and development: A socioeconomic investigation applied to Sri Lanka

This paper explores the interrelationship between agricultural policies and development by means of a dynamically recursive, computable general equilibrium model applied to Sri Lanka. The agricultural policies investigated include elimination of the food subsidy, land reform, and technical change in agriculture. The goals considered are the levels and growth rates of GNP and employment, the distribution of income, and the real income level of the lowest income group. The study provides a quantitative assessment of the association between policies and goals and identifies the key economic mechanisms in this association.     

Robustness of the linear discriminant function to nonnormality: Johnson's system

The asymptotic distribution of the Errors of Misclassification in using the Linear Discriminant Function is investigated here. The purpose is to study the effects of nonnormality on these errors. The class of distributions considered is the Johnson's system. Each of the three random variables can be transformed to normality. In one particular case numerical evaluations are made, based on which it is possible to recommend whether or not it is necessary to make the transformation prior to classification. In a parallel study, we present similar results for the Edgeworth Series distribution, where the random variables cannot be transformed to normality.     

Geostochastic calculus

A stochastic calculus for a family of continuous measure-valued Markov processes is developed. Such processes arise naturally in the construction of stochastic models of spatially distributed populations. The stochastic calculus is a tool whereby a class of density-dependent models can be studied in terms of the multiplicative measure diffusion process. In this paper the stochastic integral is introduced in the space-time setting and a Cameron-Martin-Girsanov theorem is established.     

Multivariate Kendall's tau for change‐point detection in copulas

Statistical procedures for the detection of a change in the dependence structure of a series of multivariate observations are studied in this work. The test statistics that are proposed are $L_1$ , $L_2$ , and $L_{\infty }$ distances computed from vectors of differences of Kendall's tau; two multivariate extensions of Kendall's measure of association are used. Since the distributions of these statistics under the null hypothesis of no change depend on the unknown underlying copula of the vectors, a procedure based on the multiplier central limit theorem is used for the computation of p‐values; the method is shown to be valid both asymptotically and for moderate sample sizes. Alternative versions of the tests that take into account possible breakpoints in the marginal distributions are also investigated. Monte Carlo simulations show that the tests are powerful under many scenarios of change‐point. In addition, two estimators of the time of change are proposed and their efficiency is carefully studied. The methodologies are illustrated on simulated series from the Canadian Regional Climate Model. The Canadian Journal of Statistics 41: 65–82; 2013 © 2012 Statistical Society of Canada