Homelessness in Europe and the United States: A Comparison of Prevalence and Public Opinion

Random samples of 250–435 adults were interviewed by telephone in five different nations ( N = 1,546): Belgium, Germany, Italy, the UK, and the United States. The interview included questions on respondent attitudes, knowledge, and opinions regarding homelessness; respondents' own personal experiences with homelessness and homeless people; and demographic characteristics of the respondents. The highest rates for lifetime literal homelessness were found in the UK (7.7%) and United States (6.2%), with the lowest rate in Germany (2.4%), and intermediate rates in Italy (4.0%) and Belgium (3.4%). Less compassionate attitudes toward the homeless were also found on many dimensions in the United States and the UK. Possible explanations of these findings, drawn from various theoretical perspectives, and policy implications are provided .     

A Dynamic Model of Welfare Reform

A dynamic structural model of labor supply, welfare participation, and food stamp participation is estimated using the 1992, 1993, and 1996 panels of the Survey of Income and Program Participation. Details of various policies including welfare time limits, work requirements, and Earned Income Tax Credit (EITC) are incorporated formally in the budget constraint. Policy simulations reveal that the economy accounts for half of the increase in the labor supply of female heads of family between 1992 and 1999. A time limit results in a larger efficiency gain than a work requirement or a direct reduction in welfare benefits. A reform package can lead to both a reduction in the government expenditure and an improvement in utility. The EITC expansion results in a substantial efficiency gain among individuals with the lowest expected wage. These individuals are almost unaffected by the economic expansion, but their income and utility increase significantly under the reform package.     

VOLATILITY,LABOR MARKET FLEXIBILITY,AND THE PATTERN OF COMPARATIVE ADVANTAGE

This paper studies the link between volatility, labor market flexibility, and international trade. International differences in labor market regulations affect how firms can adjust to idiosyncratic shocks. These institutional differences interact with sector specific differences in volatility (the variance of the firm‐specific shocks in a sector) to generate a new source of comparative advantage. Other things equal, countries with more flexible labor markets specialize in sectors with higher volatility. Empirical evidence for a large sample of countries strongly supports this theory: the exports of countries with more flexible labor markets are biased towards high‐volatility sectors. We show how differences in labor market institutions can be parsimoniously integrated into the workhorse model of Ricardian comparative advantage of Dornbusch, Fischer, and Samuelson (1977, American Economic Review, 67, 823–839). We also show how our model can be extended to multiple factors of production.     

Is the German system of corporate governance converging towards the Anglo-American model?

This paper analyses whether the German corporate governance is converging towards Anglo-American practices. We summarise the extant empirical evidence on the various governance mechanisms that economic theory suggests ensure efficiency and describe recent legal developments. We find no clear signs of convergence in form, i.e. the main distinctive features of the German system have remained largely unaltered. However, changes occurred over the last decade (specially in the legal framework) suggest a certain convergence in function, i.e. some governance mechanisms have effectively incorporated aims and/or goals generally associated with the Anglo-American model.

Complete ranking procedures with appropriate loss functions

This paper treats the problem of comparing different evaluations of procedures which rank the variances of k normal populations. Procedures are evaluated on the basis of appropriate loss functions for a particular goal. The goal considered involves ranking the variances of k independent normal populations when the corresponding population means are unknown. The variances are ranked by selecting samples of size n from each population and using the sample variances to obtain the ranking. Our results extend those of various authors who looked at the narrower problem of evaluating the standard proceduv 3 associated with selecting the smallest of the population variances (see e.g.,P. Somerville (1975)).

Different loss functions (both parametric and non-parametric) appropriate to the particular goal under consideration are proposed. Procedures are evaluated by the performance of their risk over a particular preference zone. The sample size n, the least favorable parametric configuration, and the maximum value of the risk are three quantities studied for each procedure. When k is small these quantities, calculated by numerical simulation, show which loss functions respond better and which respond worse to increases in sample size. Loss functions are compared with one another according to the extent of this response. Theoretical results are given for the case of asymptotically large k. It is shown that for certain cases the error incurred by using these asymptotic results is small when k is only moderately large.

This work is an outgrowth of and extends that of J. Reeves and M.J. Sobel (1987) by comparing procedures on the basis of the sample size (perpopulation) required to obtain various bounds on the associated risk functions. New methodologies are developed to evaluate complete ranking procedures in different settings.     

A note on the rubustness of the lilliefors test for univariate normality with respect to equicorrelated data

The Lilliefors test, which was developed by Lilliefors (1967), is a well-known test for univariate normality when population parameters are unknown. The main assumption for implementing the test is the independent-data assumption. This paper demonstrates the robustness of the Lilliefors test against equicorrelated observations. More specifically, we show that the null distribution of the Lilliefors test statistic is invariant under the alternate assumption that the observations are equicorrelated.     

A New Approach to the Estimation of Inter-Variable Correlation

The use of different measures of similarity between observed vectors for the purposes of classifying or clustering them has been expanding dramatically in recent years. One result of this expansion has been the use of many new similarity measures, designed for the purpose of satisfying various criteria. A noteworthy application involves estimating the relationships between genes using microarray experimental data. We consider the class of ‘correlation-type’ similarity measures. The use of these new measures of similarity suggest that the whole problem needs to be formulated in statistical terms to clarify their relative benefits. Pursuant to this need, we define, for each given observed vector, a baseline representing the ‘true’ value common to each of the component observations. These ‘true’ values are taken to be parameters. We define the ‘true correlation’ between each two observed vectors as the average (over the distribution of the observations for given baseline parameters) of Pearson's correlation with sample means replaced by the corresponding baseline parameters. Estimators of this true correlation are assessed using their mean squared error (MSE). Proper Bayes estimators of this true correlation, being based on the predictive posterior distribution of the data, are both difficult to calculate/analyze and highly non robust. By constrast, empirical Bayes estimators are: (i) close to their Bayesian counterparts; (ii) easy to analyze; and (iii) strongly robust. For these reasons, we employ empirical Bayes estimators of correlation in place of their Bayesian counterparts. We show how to construct two different kinds of simultaneous Bayes correlation estimators: the first assumes no apriori correlation between baseline parameters; the second assumes a common unknown correlation between them. Estimators of the latter type frequently have significantly smaller MSE than those of the former type which, in turn, frequently have significantly smaller MSE than their Pearson estimator counterparts. For purposes of illustrating our results, we examine the problem of inferring the relationships between gene expression level vectors, in the context of observing microarray experimental data.     

On the Dynamics of Unemployment and Wage Distributions

Postel‐Vinay and Robin's (2002) sequential auction model is extended to allow for aggregate productivity shocks. Workers exhibit permanent differences in ability while firms are identical. Negative aggregate productivity shocks induce job destruction by driving the surplus of matches with low ability workers to negative values. Endogenous job destruction coupled with worker heterogeneity thus provides a mechanism for amplifying productivity shocks that offers an original solution to the unemployment volatility puzzle (Shimer (2005)). Moreover, positive or negative shocks may lead employers and employees to renegotiate low wages up and high wages down when agents' individual surpluses become negative. The model delivers rich business cycle dynamics of wage distributions and explains why both low wages and high wages are more procyclical than wages in the middle of the distribution.