Worker Turnover,Capital Dispersion,and Matching

Abstract. A model acknowledging technology and wage dispersion, search frictions, and costly worker turnover is used for testing the notion of random matching. Using a linked employer–employee data set on roughly 9,000 Norwegian establishments and 200,000 jobs during the period 1989–95, I show that establishments investing more in capital, pay more, and experience lower worker turnover rate. Strictly convex turnover costs are identified. High‐wage establishments post on average less intensively than low‐wage establishments. Positive relationships between wages and posting are observed for high‐tech industries and in the capital and surroundings. Thus, the notion of random matching is generally rejected.     

A Terror Management Perspective on Ageism

In the present article, we present a theoretical perspective on ageism that is derived from terror management theory. According to the theory, human beings manage deeply-rooted fears about their vulnerability to death through symbolic constructions of meaning and corresponding standards of value. We extend this perspective to suggest that elderly individuals present an existential threat for the non-elderly because they remind us all that: (a) death is inescapable, (b) the body is fallible, and (c) the bases by which we may secure self-esteem (and manage death anxiety) are transitory. We review some recent empirical evidence in support of these ideas and then discuss possible avenues for combating ageism.     

Profit implications of estimation methods for the allocation of marketing resources

We deal with the question whether estimating heterogeneous multiplicative sales response models without carry over effects by either ordinary least squares or Gibbs sampling makes a difference if resources (like advertising budgets, sales budgets, sales force sizes, sales calls) have to be allocated to sales units (like sales districts, customer groups, individual costumers or prospects) in a profit maximizing way and only short time series are available. To this end we generate artificial series on sales and allocations by stochastic simulation. These series are used to estimate multiplicative models whose coefficients are either specific to individual sales units or follow a hierarchical Bayesian framework. Ordinary least squares and Gibbs sampling serve as appropriate estimation methods. Performance of the two estimation methods is measured by recovery of optimal profits which are computed on the basis of the known true parameter values. We start to determine optimal allocations based on the plug-in method which uses average coefficients to determine expected profits. Gibbs sampling always leads to profits nearer to the true optima. This advantage of Gibbs sampling is especially pronounced for combinations with high average elasticity, high variation of elasticity and high number of sales units. On the other hand, differences between Gibbs sampling and OLS become smaller the more observations are available. Optimization with expected profits taking parameter uncertainty (i.e., the distribution of parameters) into account leads to higher profits than the plug-in method, but relative increases turn out to be rather small.     

DEALER INTERMEDIATION BETWEEN MARKETS

We develop a dynamic model of dealer intermediation between a monopolistic customer–dealer market and a competitive interdealer limit order market. Dealers face inventory constraints and adverse selection. We characterize the optimal quote setting and inventory management behavior for both markets in closed form and reveal how price setting in one market segment influences quote behavior in the other. The framework is used to explore market stability issues of the two‐tier market structure and delivers testable predictions about how the dispersion of retail prices is related to the state of the interdealer limit order book. Data from the European sovereign bond market is used to test for inventory related retail price dispersion.     

Sickness Absence,Sick Leave Pay,and Pay Schemes

Utilizing Norwegian linked register and survey data, while exploiting a discontinuity in public sick pay legislation, I show that the public sick pay compensation level causally affects male performance pay workers' sick leave days. Both male and female performance pay workers experience longer sick leaves when provided private supplementary sick pay compared with those being eligible for public sick pay only. This differential impact of the replacement rate on workers' sick leave rates reveals heterogeneous behavioural changes following public sick pay cuts, and this heterogeneity will be reinforced by the provision of employer‐provided sick pay to attractive worker groups.     

Robust-efficient fitting of mixed linear models: Methodology and theory

In many areas of application mixed linear models serve as a popular tool for analyzing highly complex data sets. For inference about fixed effects and variance components, likelihood-based methods such as (restricted) maximum likelihood estimators, (RE)ML, are commonly pursued. However, it is well-known that these fully efficient estimators are extremely sensitive to small deviations from hypothesized normality of random components as well as to other violations of distributional assumptions. In this article, we propose a new class of robust-efficient estimators for inference in mixed linear models. The new three-step estimation procedure provides truncated generalized least squares and variance components' estimators with hard-rejection weights adaptively computed from the data. More specifically, our data re-weighting mechanism first detects and removes within-subject outliers, then identifies and discards between-subject outliers, and finally it employs maximum likelihood procedures on the “clean” data. Theoretical efficiency and robustness properties of this approach are established.