Lower atmospheric temperature profile measurements using a Raman lidar

A Raman lidar system was used to measure the temperature profile of the upper troposphere and lower stratosphere. The system consists of a tripled Nd-YAG laser and a 1.5 meter diameter telescope. Two photomultipliers are used at the output of the telescope to allow for measurements at both the laser wavelength and at the Raman shifted wavelength due to atmospheric nitrogen. The signal from the photomultipliers is recorded as photon counts in 1 microsec bins. The results of a number of laser shots are summed together to provide atmospheric returns which have acceptable signal to noise characteristics. Measurements of the Raman nitrogen return were acquired up to an altitude in excess of 20 km. Temperature profiles were retrieved from the attenuation corrected Raman nitrogen return assuming the atmosphere to be in hydrostatic equilibrium and using the ideal gas law. Retrieved temperature profiles are shown compared with independent temperature measurements

Evaluating Asset-Pricing Models Using The Hansen-Jagannathan Bound: A Monte Carlo Investigation

We conduct Monte Carlo experiments to examine whether the bound proposed by Hansen and Jagannathan (1991) is a useful device for evaluating asset pricing models. Specifically, we use recently developed statistical tests, which are based on a 'distance' between the model and the Hansen-Jagannathan bound, to compute the rejection rates of true models. We provide finite-sample critical values for asset pricing models with time separable preferences, and show how they depend upon nuisance parameters—risk aversion and the rate of time preference. Further, we show that the finite-sample distribution of the test statistic associated with the risk-neutral case is extreme, in the sense that critical values based on this distribution will deliver type I errors no larger than intended—regardless of risk aversion or the rate of time preference. Extending the analysis to accommodate other preferences, we show that in the state non-separable case, the small-sample distributions of the test statistics are influenced significantly by the degree of intertemporal substitution, but not by attitudes toward risk. For habit formation preferences, the small-sample distributions are strongly influenced by the habit parameter. However, the maximal-size critical values for time-separable preferences are appropriate for habit formation as well as state non-separable preferences. We conclude that with these critical values the HJ bound is indeed a useful evaluation device. We then use the critical values to evaluate three asset pricing models using U.S. data. We find evidence against the time-separable model and mixed evidence on the remaining two models.

Asset Prices in a Time Series Model with Perpetually Disparately Informed, Competitive Traders

This paper develops a dynamic asset pricing model with persistent heterogeneous beliefs. The model features competitive traders who receive idiosyncratic signals about an underlying fundamentals process. We adapt Futia’s (1981) frequency domain methods to derive conditions on the fundamentals that guarantee noninvertibility of the mapping between observed market data and the underlying shocks to agents’ information sets. When these conditions are satisfied, agents must ‘forecast the forecasts of others’. The paper provides an explicit analytical characterization of the resulting higher-order belief dynamics. These additional dynamics can explain apparent violations of variance bounds and rejections of cross-equation restrictions.Asymmetric Information, Blaschke Factors

Forecasting using relative entropy

The paper describes a relative entropy procedure for imposing moment restrictions on simulated forecast distributions from a variety of models. Starting from an empirical forecast distribution for some variables of interest, the technique generates a new empirical distribution that satisfies a set of moment restrictions. The new distribution is chosen to be as close as possible to the original in the sense of minimizing the associated Kullback-Leibler Information Criterion, or relative entropy. The authors illustrate the technique by using several examples that show how restrictions from other forecasts and from economic theory may be introduced into a model's forecasts.Forecasting

Worldwide Persistence, Business Cycles, and Economic Growth

We study the time series properties of aggregate data drawn from the Penn World Tables using numerical Bayesian procedures which facilitate inference with small samples. We find substantial persistence in world aggregates, and some evidence for a world business cycle. Across economies, there is great dispersion in our measure of persistence of shocks to real gross domestic product. That we also find no evidence of a relationship between growth and persistence sheds light on which of two competing models of endogenous growth is likely to be able to explain the PWT data

Intraspecific Variation and Ecosystem Function: Implications for more effective Post-Restoration Monitoring

The effectiveness of stream restoration is often measured by the recolonization of certain focal species. However, important information regarding intraspecific variation (e.g. size structure) of these species is often ignored. Recent research suggests that intraspecific variation such as body size can have profound effects on food web dynamics and ecosystem functioning. Specifically, intraspecific predator size variation has been posited as a major determinant of a species’ ability to control lower trophic levels and even has the potential to alter trophic cascade intensity. The importance of predator feeding strategy (e.g. omnivory) and changes with body size may also be an important factor controlling the pervasiveness of top-down control. Therefore, considering factors such as size structure and how these factors interact with feeding strategy will enable better restoration planning and better predictions post restoration. We sought to identify the effects of size and size structure on top-down control by omnivorous Speckled Dace, Rhinichthys osculus, and how these effects scaled with density. Within our study system, R. osculus inhabit small isolated beaver ponds, the conditions of which we replicated in 1000L cattle tanks. Size, size structure, and density of R. osculus were then manipulated within these tanks and resulting changes in invertebrate and algal communities were monitored over 8 weeks. Benthic algal biomass was significantly lower in the fishless control and lowest fish density treatment, indicating that R. osculus may have caused a trophic cascade that varied in intensity by treatment. Invertebrate samples are currently being processed and should provide insight into the specific pathways of this potential trophic cascade. Once completed, this research will contribute to a growing body of knowledge regarding the role of intraspecific variation in maintaining the full suite of complex interactions that constitute healthy ecosystems. Additionally, this research highlights the importance of considering density and size structure in designing and assessing stream restorations

Asset Prices in a Time Series Model with Perpetually Disparately Informed, Competitive Traders

This paper develops a dynamic asset pricing model with persistent heterogeneous beliefs. The model features competitive traders who receive idiosyncratic signals about an underlying fundamentals process. We adapt Futia’s (1981) frequency domain methods to derive conditions on the fundamentals that guarantee noninvertibility of the mapping between observed market data and the underlying shocks to agents’ information sets. When these conditions are satisfied, agents must ‘forecast the forecasts of others’. The paper provides an explicit analytical characterization of the resulting higher-order belief dynamics. These additional dynamics can explain apparent violations of variance bounds and rejections of cross-equation restrictions

Relative size underlies alternative morph development in a salamander

Size thresholds commonly underlie the induction of alternative morphological states. However, the respective importance of absolute and relative size to such thresholds remains uncertain. If absolute size governs expression, morph frequency should differ among environments that influence absolute sizes (e.g. resources, competition), and individuals of the same morph should have similar average sizes across environments. If relative size determines expression, the frequency of each morph may not differ among environments, but morphs within each environment should differ in size relative to one another. We tested these predictions in a salamander (Ambystoma talpoideum) that develops into either a terrestrial metamorph or an aquatic paedomorph. To generate size variation within and among environments, we reared individuals in mesocosm ponds across three conspecific densities. We found that morph frequency did not differ among density treatments, and the morphs were not similarly sized within each density treatment. Instead, within each environment, relatively larger individuals became metamorphs and relatively smaller individuals became paedomorphs. Relative size therefore determined morph development, highlighting the importance of an individual’s social context to size-dependent morph induction