Establishment Wage Differentials

Economists have long known that individual wages depend on a combination of employee and employer characteristics, as well as the interaction of the two. Although it is important to understand how employee and employer characteristics are related to wages, little is known about the magnitude and relation of these wage effects. This is primarily due to the lack of microdata which links individuals to the establishments where they work, but also due to technical difficulties associated with separating out employee and employer effects. This paper uses data from the Occupational Employment Statistics program at the Bureau of Labor Statistics that permit both of these issues to be addressed. Our results show that employer effects contribute substantially to earnings differences across individuals. We also find that establishments that pay well for one occupation also pay well for others. This paper contributes to the growing literature that analyzes firms’ compensation policies, and specifically the topic of employer effects on wages.Establishment Wage Differentials; Occupational Employment Statistics

Business Employment Dynamics: Tabulations by Employer Size

The gross job gains and gross job loss statistics from the BLS Business Employment Dynamics (BED) program measure the large gross job flows that underlie the quarterly net change in employment. In the fourth quarter of 2004, employment grew by 869,000 jobs. This growth is the sum of 8.1 million gross job gains from opening and expanding establishments, and 7.2 million gross job losses from contracting and closing establishments. The new BED data have captured the attention of economists and policymakers across the country, and these data are becoming a major contributor to our understanding of employment growth and business cycles in the U.S. economy. Following the initial release of the BED data in September 2003, the BED data series expanded in May 2004 with the release of industry statistics. The BLS then began work on tabulations by size class. The production of size-class statistics is a complex task involving several economic and statistical issues. Although it is trivial to classify a business into a size class in any given quarter, it is difficult to classify a business into a size class for a longitudinal analysis of employment growth. Several different classifications exist, and many of these possible classifications have appealing theoretical and statistical properties. Furthermore, these alternative classification methodologies result in sharply different portraits of employment growth by size class. In this article, we discuss the alternative statistical methodologies that the BLS considered for creating size class tabulations from the Business Employment Dynamics data. Our primary focus is on four methodologies: quarterly base-sizing, annual base-sizing, mean-sizing, and dynamic-sizing. We discuss the evaluation criteria that BLS considered for choosing its official size class methodology.gross job gains; gross job losses; business employment dynamics; size-class statistics; dynamic-sizing

A Framework and Architecture for Multi-Robot Coordination

In this paper, we present a framework and the software architecture for the deployment of multiple autonomous robots in an unstructured and unknown environment with applications ranging from scouting and reconnaissance, to search and rescue and manipulation tasks. Our software framework provides the methodology and the tools that enable robots to exhibit deliberative and reactive behaviors in autonomous operation, to be reprogrammed by a human operator at run-time, and to learn and adapt to unstructured, dynamic environments and new tasks, while providing performance guarantees. We demonstrate the algorithms and software on an experimental testbed that involves a team of car-like robots using a single omnidirectional camera as a sensor without explicit use of odometry