Agency Problems between Managers and Employees in Nonprofit Organizations: A Discrete Choice Experiment

Most principal–agent literature of nonprofit organizations has focused on the relationship between board members and managers. However, in addition to the role as an agent of the board, the manager also performs a role as principal with respect to the nonprofit employees. By using a discrete choice experiment, we identify the objectives of managers and employees in nonprofit organizations and assess the presence of agency problems in this relationship. Our sample consists of 76 headmasters, 161 teachers, and 39 administrative employees in 74 secondary nonprofit schools in Belgium. We find that the six objectives set out in the experiment play an important role for both headmasters and subordinate staff. However, the results also indicate that some of these objectives are significantly more important for the headmasters. In sum, our results suggest that agency theory and stewardship theory are not necessarily in conflict with each other but can be combined into a more general governance framework for nonprofit organizations. Consequently, we argue that incentive structures that incorporate different types of objectives can facilitate the recruitment and retention of employees in nonprofit organizations.     

Genes, longevity, and technology: meeting report from the 2nd conference on functional genomics of aging in Crete

Whole-genome sequences are now available, and methods have evolved for targeting, in parallel, each gene in a genome, offering for the first time the opportunity to study the entire dynamic network of genes involved in aging. At a recent conference in Hersonissos, Crete, around 200 internationally renowned experts gathered to discuss techniques and emerging results as the science of aging undergoes a shift toward systems biology.     

Optimal Dynamic Order Scheduling under Capacity Constraints Given Demand‐Forecast Evolution

We consider a manufacturer without any frozen periods in production schedules so that it can dynamically update the schedules as the demand forecast evolves over time until the realization of actual demand. The manufacturer has a fixed production capacity in each production period, which impacts the time to start production as well as the production schedules. We develop a dynamic optimization model to analyze the optimal production schedules under capacity constraint and demand‐forecast updating. To model the evolution of demand forecasts, we use both additive and multiplicative versions of the martingale model of forecast evolution. We first derive expressions for the optimal base stock levels for a single‐product model. We find that manufacturers located near their market bases can realize most of their potential profits (i.e., profit made when the capacity is unlimited) by building a very limited amount of capacity. For moderate demand uncertainty, we also show that it is almost impossible for manufacturers to compensate for the increase in supply–demand mismatches resulting from long delivery lead times by increasing capacity, making lead‐time reduction a better alternative than capacity expansion. We then extend the model to a multi‐product case and derive expressions for the optimal production quantities for each product given a shared capacity constraint. Using a two‐product model, we show that the manufacturer should utilize its capacity more in earlier periods when the demand for both products is more positively correlated.     

Locally most powerful two-sample rank tests for Lévy distributions

For two independent samples of independent random variables which follow a Lévy distribution, the scores for the locally most powerful rank tests for the location and scale problem are obtained. To carry the asymptotic normality of the rank statistics into practice the null means and variances are calculated. Research supported by Deutsche Forschungsgemeinschaft (DFG).     

An application of cartographic area interpolation to German administrative data

In many situations the applied researcher wishes to combine different data sources without knowing the exact link and merging rule. This paper considers different cartographic interpolation methods for interpolating attributes from German employment office districts to German counties and vice versa. In particular, we apply dasymetric weighting as an alternative to simple area weighting, both of which are based on estimated intersection areas. We also present conditions under which the choice of interpolation method does not matter and confirm the theoretical results with a simulation study. Our application to German administrative data suggests robustness of estimation results of interpolated attributes with respect to the choice of interpolation method. We provide weighting matrices for regional data sources of the two largest German data producers.     

Authors’ response: on the role of data,statistics and decisions in a pandemic

AStA Advances in Statistical Analysis -