Optimal Contracts, Adverse Selection, and Social Preferences: An Experiment

It has long been standard in agency theory to search for incentive-compatible mechanisms on the assumption that people care only about their own material wealth. However, this assumption is clearly refuted by numerous experiments, and we feel that it may be useful to consider nonpecuniary utility in mechanism design and contract theory. Accordingly, we devise an experiment to explore optimal contracts in an adverse-selection context. A principal proposes one of three contract menus, each of which offers a choice of two incentive-compatible contracts, to two agents whose types are unknown to the principal. The agents know the set of possible menus, and choose to either accept one of the two contracts offered in the proposed menu or to reject the menu altogether; a rejection by either agent leads to lower (and equal) reservation payoffs for all parties. While all three possible menus favor the principal, they do so to varying degrees. We observe numerous rejections of the more lopsided menus, and approach an equilibrium where one of the more equitable contract menus (which one depends on the reservation payoffs) is proposed and agents accept a contract, selecting actions according to their types. Behavior is largely consistent with all recent models of social preferences, strongly suggesting there is value in considering nonpecuniary utility in agency theory.

Monoclonal antibodies to carcinoembryonic antigen: ionic strength as a factor in the selection of antibodies for immunoscintigraphy.

As part of an ongoing effort to improve the technique of immunoscintigraphy for the detection of human carcinomas with radiolabeled monoclonal antibodies (MABs) to carcinoembryonic antigen (CEA), we have developed a series of MABs to CEA and have studied the effects of low- and physiological molarity buffers on their CEA binding and affinity, as well as their cross-reactivity with granulocyte glycoprotein(s). These in vitro results in different buffer systems were then correlated with the use of these MABs to CEA in the detection of human colon carcinoma grafts in nude mice. Our results show that the binding of CEA by some MABs is influenced by ionic strength and that this may be an important factor in their successful use for the immunolocalization of carcinomas in vivo.

A Model of Collateral, Investment, and Adverse Selection

This paper characterizes the relationship between entrepreneurial wealth and aggregate investment under adverse selection. Its main finding is that such a relationship need not be monotonic. In particular, three results emerge from the analysis: (i) pooling equilibria, in which investment is independent of entrepreneurial wealth, are more likely to arise when entrepreneurial wealth is relatively low; (ii) separating equilibria, in which investment is increasing in entrepreneurial wealth, are most likely to arise when entrepreneurial wealth is relatively high and; (iii) for a given interest rate, an increase in entrepreneurial wealth may generate a discontinuous fall in investment.

Time Series Input Selection using Multiple Kernel Learning

In this paper we study the relevance of multiple kernel learning (MKL) for the automatic selection of time series inputs. Recently, MKL has gained great attention in the machine learning community due to its flexibility in modelling complex patterns and performing feature selection. In general, MKL constructs the kernel as a weighted linear combination of basis kernels, exploiting different sources of information. An efficient algorithm wrapping a Support Vector Regression model for optimizing the MKL weights, named SimpleMKL, is used for the analysis. In this sense, MKL performs feature selection by discarding inputs/kernels with low or null weights. The approach proposed is tested with simulated linear and nonlinear time series (AutoRegressive, Henon and Lorenz series).

Mouse alarm pheromone shares structural similarity with predator scents.

Sensing the chemical warnings present in the environment is essential for species survival. In mammals, this form of danger communication occurs via the release of natural predator scents that can involuntarily warn the prey or by the production of alarm pheromones by the stressed prey alerting its conspecifics. Although we previously identified the olfactory Grueneberg ganglion as the sensory organ through which mammalian alarm pheromones signal a threatening situation, the chemical nature of these cues remains elusive. We here identify, through chemical analysis in combination with a series of physiological and behavioral tests, the chemical structure of a mouse alarm pheromone. To successfully recognize the volatile cues that signal danger, we based our selection on their activation of the mouse olfactory Grueneberg ganglion and the concomitant display of innate fear reactions. Interestingly, we found that the chemical structure of the identified mouse alarm pheromone has similar features as the sulfur-containing volatiles that are released by predating carnivores. Our findings thus not only reveal a chemical Leitmotiv that underlies signaling of fear, but also point to a double role for the olfactory Grueneberg ganglion in intraspecies as well as interspecies communication of danger.

Prevalence of alcohol-impaired drivers based on random breath tests in a roadside survey

Sobriety checkpoints are not usually randomly located by traffic authorities. As such, information provided by non-random alcohol tests cannot be used to infer the characteristics of the general driving population. In this paper a case study is presented in which the prevalence of alcohol-impaired driving is estimated for the general population of drivers. A stratified probabilistic sample was designed to represent vehicles circulating in non-urban areas of Catalonia (Spain), a region characterized by its complex transportation network and dense traffic around the metropolis of Barcelona. Random breath alcohol concentration tests were performed during spring 2012 on 7,596 drivers. The estimated prevalence of alcohol-impaired drivers was 1.29%, which is roughly a third of the rate obtained in non-random tests. Higher rates were found on weekends (1.90% on Saturdays, 4.29% on Sundays) and especially at night. The rate is higher for men (1.45%) than for women (0.64%) and the percentage of positive outcomes shows an increasing pattern with age. In vehicles with two occupants, the proportion of alcohol-impaired drivers is estimated at 2.62%, but when the driver was alone the rate drops to 0.84%, which might reflect the socialization of drinking habits. The results are compared with outcomes in previous surveys, showing a decreasing trend in the prevalence of alcohol-impaired drivers over time.

Myocardial flow reserve by Rb-82 cardiac PET improves the selection of patients eligible for invasive coronary angiography

Aim: We asked whether myocardial flow reserve (MFR) by Rb-82 cardiac PET improve the selection of patients eligible for invasive coronary angiography (ICA). Material and Methods: We enrolled 26 consecutive patients with suspected or known coronary artery disease who performed dynamic Rb-82 PET/CT and (ICA) within 60 days; 4 patients who underwent revascularization or had any cardiovascular events between PET and ICA were excluded. Myocardial blood flow at rest (rMBF), at stress with adenosine (sMBF) and myocardial flow reserve (MFR=sMBF/rMBF) were estimated using the 1-compartment Lortie model (FlowQuant) for each coronary arteries territories. Stenosis severity was assessed using computer-based automated edge detection (QCA). MFR was divided in 3 groups: G1:MFR<1.5, G2:1.5≤MFR<2 and G3:2≤MFR. Stenosis severity was graded as non-significant (<50% or FFR ≥0.8), intermediate (50%≤stenosis<70%) and severe (≥70%). Correlation between MFR and percentage of stenosis were assessed using a non-parametric Spearman test. Results: In G1 (44 vessels), 17 vessels (39%) had a severe stenosis, 11 (25%) an intermediate one, and 16 (36%) no significant stenosis. In G2 (13 vessels), 2 (15%) vessels presented a severe stenosis, 7 (54%) an intermediate one, and 4 (31%) no significant stenosis. In G3 (9 vessels), 0 vessel presented a severe stenosis, 1 (11%) an intermediate one, and 8 (89%) no significant stenosis. Of note, among 11 patients with 3-vessel low MFR<1.5 (G1), 9/11 (82%) had at least one severe stenosis and 2/11 (18%) had at least one intermediate stenosis. There was a significant inverse correlation between stenosis severity and MFR among all 66 territories analyzed (rho= -0.38, p=0.002). Conclusion: Patients with MFR>2 could avoid ICA. Low MFR (G1, G2) on a vessel-based analysis seems to be a poor predictor of severe stenosis severity. Patients with 3-vessel low MFR would benefit from ICA as they are likely to present a significant stenosis in at least one vessel.

Comparative resilience of clinical perimetric tests to induced levels of intraocular straylight.

PURPOSE: To investigate the effect of intraocular straylight (IOS) induced by white opacity filters (WOF) on threshold measurements for stimuli employed in three perimeters: standard automated perimetry (SAP), pulsar perimetry (PP) and the Moorfields motion displacement test (MDT).¦METHODS: Four healthy young (24-28 years old) observers were tested six times with each perimeter, each time with one of five different WOFs and once without, inducing various levels of IOS (from 10% to 200%). An increase in IOS was measured with a straylight meter. The change in sensitivity from baseline was normalized, allowing comparison of standardized (z) scores (change divided by the SD of normative values) for each instrument.¦RESULTS: SAP and PP thresholds were significantly affected (P < 0.001) by moderate to large increases in IOS (50%-200%). The drop in motion displacement (MD) from baseline with WOF 5, was approximately 5 dB, in both SAP and PP which represents a clinically significant loss; in contrast the change in MD with MDT was on average 1 minute of arc, which is not likely to indicate a clinically significant loss.¦CONCLUSIONS: The Moorfields MDT is more robust to the effects of additional straylight in comparison with SAP or PP.

Genetic team composition and level of selection in the evolution of cooperation

In cooperative multiagent systems, agents interac to solve tasks. Global dynamics of multiagent teams result from local agent interactions, and are complex and difficult to predict. Evolutionary computation has proven a promising approach to the design of such teams. The majority of current studies use teams composed of agents with identical control rules ("geneti- cally homogeneous teams") and select behavior at the team level ("team-level selection"). Here we extend current approaches to include four combinations of genetic team composition and level of selection. We compare the performance of genetically homo- geneous teams evolved with individual-level selection, genetically homogeneous teams evolved with team-level selection, genetically heterogeneous teams evolved with individual-level selection, and genetically heterogeneous teams evolved with team-level selection. We use a simulated foraging task to show that the optimal combination depends on the amount of cooperation required by the task. Accordingly, we distinguish between three types of cooperative tasks and suggest guidelines for the optimal choice of genetic team composition and level of selection

A new method for constructing exact tests without making any assumptions

We present a new method for constructing exact distribution-free tests (and confidence intervals) for variables that can generate more than two possible outcomes.This method separates the search for an exact test from the goal to create a non-randomized test. Randomization is used to extend any exact test relating to meansof variables with finitely many outcomes to variables with outcomes belonging to agiven bounded set. Tests in terms of variance and covariance are reduced to testsrelating to means. Randomness is then eliminated in a separate step.This method is used to create confidence intervals for the difference between twomeans (or variances) and tests of stochastic inequality and correlation.

Resolving inconsistencies in utility measurement under risk: Tests of generalizations of expected utility

This paper explores biases in the elicitation of utilities under risk and the contribution that generalizations of expected utility can make to the resolution of these biases. We used five methods to measure utilities under risk and found clear violations of expected utility. Of the theories studies, prospect theory was most consistent with our data. The main improvement of prospect theory over expected utility was in comparisons between a riskless and a risky prospect(riskless-risk methods). We observed no improvement over expected utility in comparisons between two risky prospects (risk-risk methods). An explanation why we found no improvement of prospect theory over expected utility in risk-risk methods may be that there was less overweighting of small probabilities in our study than has commonly been observed.