Collective Voluntary Agreements and the Production of Less Polluting Products

Recently, some industries have collectively agreed not to produce models that do not meet an energy efficiency (and hence an environmental) standard. This paper presents a simple model that can be used to examine a voluntary collective agreement to limit or completely eliminate the low efficiency model of a given product (e.g., a low efficiency washing machine). We show that, when there is competition between firms, a collective agreement to limit or even eliminate production of the polluting model can actually increase profits for all firms in the industry. This suggests that a collective agreement of this type might actually be beneficial to firms, while at the same time improving environmental quality. However, the implicit enforcement that comes from the public nature of the commitment is necessary to ensure this outcome. This suggests that, by promoting such agreements, policymakers may be able to achieve substantial environmental gains with relatively little inducement. The impact on social welfare will then depend on whether these gains are sufficiently large to offset consumer losses from reductions in product variety and the associated price increases.

Creating Useful Products From Connecticut's 2000 LIDAR Data Set JHR 08-314 Project 07-2

The State of Connecticut owns a LIght Detection and Ranging (LIDAR) data set that was collected in 2000 as part of the State’s periodic aerial reconnaissance missions. Although collected eight years ago, these data are just now becoming ready to be made available to the public. These data constitute a massive “point cloud”, being a long list of east-north-up triplets in the State Plane Coordinate System Zone 0600 (SPCS83 0600), orthometric heights (NAVD 88) in US Survey feet. Unfortunately, point clouds have no structure or organization, and consequently they are not as useful as Triangulated Irregular Networks (TINs), digital elevation models (DEMs), contour maps, slope and aspect layers, curvature layers, among others. The goal of this project was to provide the computational infrastructure to create a first cut of these products and to serve them to the public via the World Wide Web. The products are available at http://clear.uconn.edu/data/ct_lidar/index.htm.