TAX POLICY AND INCOME INEQUALITY IN THE UNITED STATES, 1979–2007

This paper assesses the effects of U.S. tax policy reforms on inequality over around three decades, from 1979 to 2007. It applies a new method for decomposing changes in government redistribution into (1) a direct policy effect resulting from policy changes and (2) the effects of changing market incomes. Over the period as a whole, the tax policy changes increased income inequality by pushing up the income share of high‐income earners (the top 20%). (JEL H23, H31, H53, P16)     

Joint Income-Wealth Inequality: Evidence from Lucerne Tax Data

Social Indicators Research - Using tax data from the Swiss canton of Lucerne, we study how measures of economic inequality change if they account for income and wealth rather than income alone....     

The Role of Statistical Models in the Prediction of Tropical Cyclone Motion

Tropical cyclones (tropical storms, hurricanes, typhoons, etc.) occur over many of the earth's tropical marine areas. Responsibility for tracking and predicting the future course of these storms is assigned to one or more domestic or foreign meteorological services. These services routinely activate a number of statistical and dynamical prediction models as objective guidance preparatory to issuing official forecasts on these storms. In this article, the role of the statistical models in this process is examined.     

Computational and statistical efficiency of semiparametric gls estimators

In this note, we report a dramatic improvement in the computational efficiency of semiparametric generalized least squares(SGLS) estimation. Computation of SGLS estimates no longer presents serious problems with data sets of moderate size. We also correct a numerical error in the standard errors of the SGLS estimates reported in our recent paper in this journal (Horowitz and Neumann, 1987). The corrected standard errors of SGLS are comparable to those we reported for quantile estimates.     

A tutorial on rank-based coefficient estimation for censored data in small- and large-scale problems

The analysis of survival endpoints subject to right-censoring is an important research area in statistics, particularly among econometricians and biostatisticians. The two most popular semiparametric models are the proportional hazards model and the accelerated failure time (AFT) model. Rank-based estimation in the AFT model is computationally challenging due to optimization of a non-smooth loss function. Previous work has shown that rank-based estimators may be written as solutions to linear programming (LP) problems. However, the size of the LP problem is O(n ²+p) subject to n ² linear constraints, where n denotes sample size and p denotes the dimension of parameters. As n and/or p increases, the feasibility of such solution in practice becomes questionable. Among data mining and statistical learning enthusiasts, there is interest in extending ordinary regression coefficient estimators for low-dimensions into high-dimensional data mining tools through regularization. Applying this recipe to rank-based coefficient estimators leads to formidable optimization problems which may be avoided through smooth approximations to non-smooth functions. We review smooth approximations and quasi-Newton methods for rank-based estimation in AFT models. The computational cost of our method is substantially smaller than the corresponding LP problem and can be applied to small- or large-scale problems similarly. The algorithm described here allows one to couple rank-based estimation for censored data with virtually any regularization and is exemplified through four case studies.     

Uncertainty, Contrariness and the Double-bind: Middle Managers' Reactions to Changing Contracts

This article describes the emerging changes in psychological contracts being experienced by British middle managers in relation to their employing organizations, the middle managers' negative reactions to these changes and organizational responses to such negativity. By analysing case studies of 16 organizations, a classification of changes to five elements of the psychological contract are identified: knowledge, motivation, goals and means, role behaviour and ethics. By analysing the semi-structured interviews of 37 middle managers, selected from a much larger database for their obvious negative reactions, a continuum of such reactions is considered: uncertainty, contrariness and double-bind. This consideration leads, then, to suggestions for further research.     

Ideal Values and Counter‐ideal Values as Two Distinct Forces: Exploring a Gap in Organizational Value Research

Motives and values at work have long been key topics of business and management studies. In a focused review of the literature on the nature of human values, this paper identifies a disconnect with the literature on human motivation, despite the otherwise inherent relatedness of the two fields. Specifically, extant theory and research have conceptualized values generally in terms of ideals, namely desired end‐states that individuals strive to approach. Although values, by this definition, express motivational concerns, theories of human motivation suggest that there are two forces to consider, i.e. approach and avoidance motivation. By applying this ‘two forces’ perspective to value research, this paper identifies a gap in the literature on values: namely, the idea that individuals are also influenced by counter‐ideal values, i.e. end‐states that they deliberately seek to avoid. The identification of this gap opens up new opportunities for value research in general and organizational value research in particular. To pave the way for future research, this paper critically discusses the few studies that have taken first steps in that direction and outlines research questions that may follow for issues such as employer branding and person–organization fit. This paper closes by providing suggestions on how to tackle the issue in organizational practice.