Countervailing incentives in adverse selection models. A synthesis

In this paper we propose a simple method of characterizing countervailing incentives in adverse selection problems. The key element in our characterization consists of analyzing properties of the full information problem. This allows solving the principal problem without using optimal control theory. Our methodology can also be applied to different economic settings: health economics, monopoly regulation, labour contracts, limited liabilities and environmental regulation.

Scale-Dependent Habitat Selection of Nesting Great Egrets and Snowy Egrets

Foraging habitat selection of nesting Great Egrets ( Ardea alba ) and Snowy Egrets ( Egretta thula ) was investigated within an estuary with extensive impounded salt marsh habitat. Using a geographic information system, available habitat was partitioned into concentric bands at five, ten, and 15 km radius from nesting colonies to assess the relative effects of habitat composition and distance on habitat selection. Snowy Egrets were more likely than Great Egrets to depart colonies and travel to foraging sites in groups, but both species usually arrived at sites that were occupied by other wading birds. Mean flight distances were 6.2 km (SE = 0.4, N = 28, range 1.8-10.7 km) for Great Egrets and 4.7 km (SE = 0.48, N = 31, range 0.7-12.5 km) for Snowy Egrets. At the broadest spatial scale both species used impounded (mostly salt marsh) and estuarine edge habitat more than expected based on availability while avoiding unimpounded (mostly fresh water wetland) habitat. At more local scales habitat use matched availability. Interpretation of habitat preference differed with the types of habitat that were included and the maximum distance that habitat was considered available. These results illustrate that caution is needed when interpreting the results of habitat preference studies when individuals are constrained in their choice of habitats, such as for central place foragers.

Is there a subgroup of long-term evolution among patients with advanced lung cancer?: Hints from the analysis of survival curves from cancer registry data

Background: Recently, with the access of low toxicity biological and targeted therapies, evidence of the existence of a long-term survival subpopulation of cancer patients is appearing. We have studied an unselected population with advanced lung cancer to look for evidence of multimodality in survival distribution, and estimate the proportion of long-term survivors. Methods: We used survival data of 4944 patients with non-small-cell lung cancer (NSCLC) stages IIIb-IV at diagnostic, registered in the National Cancer Registry of Cuba (NCRC) between January 1998 and December 2006. We fitted one-component survival model and two-component mixture models to identify short-and long-term survivors. Bayesian information criterion was used for model selection. Results: For all of the selected parametric distributions the two components model presented the best fit. The population with short-term survival (almost 4 months median survival) represented 64% of patients. The population of long-term survival included 35% of patients, and showed a median survival around 12 months. None of the patients of short-term survival was still alive at month 24, while 10% of the patients of long-term survival died afterwards. Conclusions: There is a subgroup showing long-term evolution among patients with advanced lung cancer. As survival rates continue to improve with the new generation of therapies, prognostic models considering short-and long-term survival subpopulations should be considered in clinical research.