Earnings Management and Measurement Error

In this paper I consider the impact of a noisy indicator regarding a manager’s manipulative behavior on optimal effort incentives and the extent of earnings management. The analysis in this paper extends a twotask, single performance measure LEN model by including a binary random variable. I show that contracting on the noisy indicator variable is not always useful. More specifically, the principal uses the indicator variable to prevent earnings management only under conditions where manipulative behavior is not excessive. Thus, under conditions of excessive earnings management, accounting adjustments that yield a more congruent overall performance measure can be more effective than an appraisal of the existence of earnings management to mitigate the earnings management problem.

A Cooperative and Adaptive Variable Neighborhood Search for the Multi Depot Vehicle Routing Problem with Time Windows

In this paper we propose two cooperation schemes to compose new parallel variants of the Variable Neighborhood Search (VNS). On the one hand, a coarse-grained cooperation scheme is introduced which is well suited for being enhanced with a solution warehouse to store and manage the so far best found solutions and a self-adapting mechanism for the most important search parameters. This makes an a priori parameter tuning obsolete. On the other hand, a fine-grained scheme was designed to reproduce the successful properties of the sequential VNS. In combination with the use of parallel exploration threads all of the best solutions and 11 out of 20 new best solutions for the Multi Depot Vehicle Routing Problem with Time Windows were found.

Hating the neighbors: The role of hate crime in the perpetuation of black residential segregation

Grounded in group conflict theory and the defended neighborhoods thesis, this nationwide empirical study of cities and their residential segregation levels, examines the occurrence of hate crime using data on for all U.S. cities with populations over 95,000, and data compiled from the Uniform Crime Report for hate crime, in conjunction with 2000 census data. Hate crime is any illegal act motivated by pre-formed bias against, in this case, a person’s real or perceived race. This research asks: Do hate crime levels predict white/black segregation levels? How does hate crime predict different measures of white/black segregation? I use the dissimilarity index measure of segregation operationalized as a continuous, binary and ordinal variable, to explore whether hate crime predicts segregation of blacks from whites. In cities with higher rates of hate crime there was higher dissimilarity between whites and blacks, controlling for other factors. The segregation level was more likely to be “high” in a city where hate crime occurred. Blacks are continually multiply disadvantaged and distinctly affected by hate crime and residential segregation. Prior studies of residential segregation have focused almost exclusively on individual choice, residents’ lack of finances, or discriminatory actions that prevent racial minorities from moving, to explore the correlates of segregation. Notably absent from these studies are measures reflecting the level of hate crime occurring in cities. This study demonstrates the importance of considering hate crime and neighborhood conflict when contemplating the causes of residential segregation.