Distinguishing Probability Weighting from Risk Misperceptions in Field Data

The paper outlines a strategy for distinguishing rank-dependent probability weighting from systematic risk misperceptions in field data. Our strategy relies on singling out a field environment with two key properties: (i) the objects of choice are money lotteries with more than two outcomes and (ii) the ranking of outcomes differs across lotteries. We first present an abstract model of risky choice that elucidates the identification problem and our strategy. The model has numerous applications, including insurance choices and gambling. We then consider the application of insurance deductible choices and illustrate our strategy using simulated data

Estimating Risk Preferences in the Field

We survey the literature on estimating risk preferences using field data. We concentrate our attention on studies in which risk preferences are the focal object and estimating their structure is the core enterprise. We review a number of models of risk preferences—including both expected utility (EU) theory and non-EU models—that have been estimated using field data, and we highlight issues related to identification and estimation of such models using field data. We then survey the literature, giving separate treatment to research that uses individual-level data (e.g., property insurance data) and research that uses aggregate data (e.g., betting market data). We conclude by discussing directions for future research

IRAS 23385+6053: a candidate protostellar massive object

We present the results of a multi-line and continuum study towards the source IRAS 23385+6053,performed with the IRAM-30m telescope, the Plateau de Bure Interferometer, the Very Large Array Interferometer and the James Clerk Maxwell Telescope. The new results confirm our earlier findings, namely that IRAS 23385+6053 is a good candidate high-mass protostellar object, precursor of an ultracompact H$_{II}$ region. The source is roughly composed of two regions: a molecular core $\sim0.03\div0.04$ pc in size, with a temperature of $\sim40$ K and an H$_{2}$ volume density of the order of 10$^{7}$ cm$^{-3}$, and an extended halo of diameter $\leq$0.4 pc, with an average kinetic temperature of $\sim 15$ K and H$_{2}$ volume density of the order of 10$^{5}$ cm$^{-3}$. The core temperature is much smaller than what is typically found in molecular cores of the same diameter surrounding massive ZAMS stars. We deduce that the core luminosity is between 150 and $1.6\times10^{4}L_{\odot}$, and we believe that the upper limit is near the ``true'' source luminosity. Moreover, by comparing the H$_{2}$ volume density obtained at different radii from the IRAS source, we find that the halo has a density profile of the type $n_{\rm H_{2}}\propto r^{-2.3}$. This suggests that the source is gravitationally unstable. Finally, we demonstrate that the temperature at the core surface is consistent with a core luminosity of $10^3 L_{\odot}$ and conclude that we might be observing a protostar still accreting material from its parental cloud, whose mass at present is $\sim 6 M_{\odot}$.Comment: 18 pages, 20 figure

The Cost of Legal Restrictions on Experience Rating

We investigate the cost of legal restrictions on experience rating in auto and home insurance. The cost is an opportunity cost as experience rating can mitigate the problems associated with unobserved heterogeneity in claim risk, including mispriced coverage and resulting demand distortions. We assess this cost through a counterfactual analysis in which we explore how risk predictions, premiums, and demand in home insurance and two lines of auto insurance would respond to unrestricted multiline experience rating. Using claims data from a large sample of households, we first estimate the variance-covariance matrix of unobserved heterogeneity in claim risk. We then show that conditioning on claims experience leads to material refinements of predicted claim rates. Lastly, we assess how the households’ demand for coverage would respond to multiline experience rating. We find that the demand response would be large

The Nature of Risk Preferences: Evidence from Insurance Choices

We use data on households' deductible choices in auto and home insurance to estimate a structural model of risky choice that incorporates "standard" risk aversion (concave utility over final wealth), loss aversion, and nonlinear probability weighting. Our estimates indicate that nonlinear probability weighting plays the most important role in explaining the data. More specifically, we find that standard risk aversion is small, loss aversion is nonexistent, and nonlinear probability weighting is large. When we estimate restricted models, we find that nonlinear probability weighting alone can better explain the data than standard risk aversion alone, loss aversion alone, and standard risk aversion and loss aversion combined. Our main findings are robust to a variety of modeling assumptions.

Mesonic correlation functions at finite temperature and density in the Nambu-Jona-Lasinio model with a Polyakov loop

We investigate the properties of scalar and pseudo-scalar mesons at finite temperature and quark chemical potential in the framework of the Nambu-Jona-Lasinio (NJL) model coupled to the Polyakov loop (PNJL model) with the aim of taking into account features of both chiral symmetry breaking and deconfinement. The mesonic correlators are obtained by solving the Schwinger-Dyson equation in the RPA approximation with the Hartree (mean field) quark propagator at finite temperature and density. In the phase of broken chiral symmetry a narrower width for the sigma meson is obtained with respect to the NJL case; on the other hand, the pion still behaves as a Goldstone boson. When chiral symmetry is restored, the pion and sigma spectral functions tend to merge. The Mott temperature for the pion is also computed.Comment: 24 pages, 9 figures, version to appear in Phys. Rev.

Surface nano-patterning through styrene adsorption on Si(100)

We present an ab initio study of the structural and electronic properties of styrene molecules adsorbed on the dimerized Si(100) surface at different coverages, ranging from the single-molecule to the full monolayer. The adsorption mechanism primarily involves the vinyl group via a [2+2] cycloaddition process that leads to the formation of covalent Si-C bonds and a local surface derelaxation, while it leaves the phenyl group almost unperturbed. The investigation of the functionalized surface as a function of the coverage (e.g. 0.5 -- 1 ML) and of the substrate reconstruction reveals two major effects. The first results from Si dimer-vinyl interaction and concerns the controlled variation of the energy bandgap of the interface. The second is associated to phenyl-phenyl interactions, which gives rise to a regular pattern of electronic wires at surface, stemming from the pi-pi coupling. These findings suggest a rationale for tailoring the surface nano-patterning of the surface, in a controlled way.Comment: 19 pages (preprint), 4 figures, supplementary materia