Housing market capitalization of environmental risk: evidence from the Tianjin explosion.

Do environmental risks affect housing prices in the vicinity of industrial plants? Prior studies concentrated on the capitalization effect of infrequent natural disasters instead of industry-related environmental risks caused by production accidents in our everyday lives. In this paper, we first use the 2015 Tianjin explosion in China as an exogenous shock, which led to serious casualties and property damage with nationwide concern, to estimate the effects of environmental risk on housing prices far away from the explosion site. Based on the housing transaction units and chemical plant datasets in Beijing with the difference-in-differences hedonic model, the results indicate that first, housing prices near chemical plants decreased significantly after the explosion and lasted for at least 2 years. Second, the mitigation effects of production and consumption amenities and regional demographic features were examined. The conclusions of this paper provide a policy basis for constantly implementing public sentiment management and safety supervision, balancing industrial and residential land layouts, and improving local amenities and demographics to ensure the stability of the land market.

Response to modeling and notation of DEA with strong and weak disposable outputs.

In this brief communiction we respond to comments on our earlier publication, which contained some notational errors.

The impact of CON regulation on hospital efficiency.

In this paper we propose an empirically implementable measure of aggregate-level efficiency along the lines of Debreu's (1951) coefficient of resource utilization but restricted to the production side. The efficiency measure is based on directional distance functions, which allows the overall measure of efficiency to be decomposed into measures of technical and "structural" efficiency. The latter measure, which captures inefficiencies associated with the organization of production within an industry, is further decomposed into measures of scale and mix efficiency. The measures developed in the paper are illustrated using U.S. hospital data. The illustration sheds light on the efficacy of certificate of need (CON) regulations.

Analysis of uncompensated hospital care using a DEA model of output congestion.

Uncompensated care can create financial difficulties for hospitals. The problem is likely to worsen as the number of individuals lacking health insurance continues to grow. The objective of this study is to measure how uncompensated care affects hospitals' ability to provide the services for which they do receive compensation. Applying output-based data envelopment analysis (DEA) under various assumptions on the disposability of outputs to a sample of Pennsylvania hospitals, we find that, on average, hospitals could have produced 7% more output if they had all operated on the best-practice frontier and that uncompensated care reduced the production of other hospital outputs by 2%. Thus, even if hospitals were to operate efficiently, they might still face financial distress as a result of providing uncompensated care. The findings in our study suggest that policy makers should continue looking at ways to increase funding to hospitals providing uncompensated care while not distorting economic incentives to reduce excessive costs.