Asset Returns and State-Dependent Risk Preferences

We propose a consumption-based capital asset pricing model in which the representative agent's preferences display state-dependent risk aversion. We obtain a valuation equation in which the vector of excess on equity includes both consumption risk as well as the risk associated with variations in preferences. We develop a simple model that can be estimated without specifying the functional form linking risk aversion with state variables. Our estimates are based on Markov chain Monte Carlo estimation of exact discrete-time parameterizations for linear diffusion processes. Since consumption risk is not forced to account for the entire risk premium, our results contrast sharply with estimates from models in which risk aversion is state-independent. We find that relaxing fixed risk preferences yields estimates for relative risk aversion that are (i) reasonable by usual standards, (ii) correlated with both consumption and returns and (iii) indicative of an additional preference risk of holding the asests.Asset pricing models, Bayesian analysis, continuous-time econometric models, data augmentation, equity premium puzzle, Markov chain Monte Carlo, risk aversion, state-dependent preferences, wealth

A purely kinetic description of the evaporation of water droplets

The process of water evaporation, although deeply studied, does not enjoy a kinetic description that captures known physics and can be integrated with other detailed processes such as drying of catalytic membranes embedded in vapor-fed devices and chemical reactions in aerosol whose volumes are changing dynamically. In this work, we present a simple, three-step kinetic model for water evaporation that is based on theory and validated by using well-established thermodynamic models of droplet size as a function of time, temperature, and relative humidity as well as data from time-resolved measurements of evaporating droplet size. The kinetic mechanism for evaporation is a combination of two limiting processes occurring in the highly dynamic liquid-vapor interfacial region: direct first order desorption of a single water molecule and desorption resulting from a local fluctuation, described using third order kinetics. The model reproduces data over a range of relative humidities and temperatures only if the interface that separates bulk water from gas phase water has a finite width, consistent with previous experimental and theoretical studies. The influence of droplet cooling during rapid evaporation on the kinetics is discussed; discrepancies between the various models point to the need for additional experimental data to identify their origin

The determinants of agricultural production : a cross-country analysis

In this analysis of capital's role in agricultural production, a new construction of data on capital allowed the authors to advance the cross-country study of production functions. The model reveals the relative importance of capital, a finding quite robust to modifications of the model and the disaggregation of capital to its two components. The model is also consistent with the view that lack of physical capital serves as a constraint on agricultural growth. The shift to more productive techniques is associated with a decline in labor, reflecting labor-saving technical changes. This is not news, but it is emphasized here because it comes out an integral view of the process which distinguishes between the core technology and the changes that took place over time and between countries. Not only is capital important to agricultural production, and agricultural development dependent on the economic environment, but agriculture is more cost-capital-intensive than nonagriculture. Capital is all the more important as a factor of production in that land (also important) varies little over time. The availability of agricultural capital determines whether the gap between available and applied technologies can be closed. Prices have little direct, immediate impact on agricultural growth, beyond their impact through inputs and choice of technology. The legacy of past policies that distorted the relative returns to economic activity is enshrined in current stocks, which may respond slowly to policy reform. The analysis assumes that the production technology is heterogeneous and the implemented technology is endogenous and determined jointly with the level of unconstrained inputs. Thus, a change in the state variables affects both the technology and the inputs, so the production function is not identified. To overcome that problem, changes in productivity are decomposed to three orthogonal components caused by the fundamentally different processes underlying panel data. The statistical framework explains the unstable results observed in production functions derived from panel data. Statistically, the results depend on how the data are projected. Comparisons between units over time or of deviations from unit-means or time-means all describe different processes. This is based on theory but has an intuitive appeal as well. In this case, the spread in productivity among countries is different from the spread in productivity for a country through time. The factors explaining the spread will differ. The modeling approach should explicitly recognize the fact that panel data measure a combination of economic phenomena.Labor Policies,Environmental Economics&Policies,Economic Theory&Research,Agricultural Knowledge&Information Systems,General Technology,Economic Theory&Research,Environmental Economics&Policies,Agricultural Knowledge&Information Systems,Economic Growth,Scientific Research&Science Parks

Twin-Peaks - What the Knowledge-Based Approach Can Say about the Dynamics of the World Income Distribution

One of the most recently observed stylised facts in the field of economic growth is the persistent bimodal shape of the world income distribution.. Of course, some theoretical explanations for this new stylised fact already have been provided by neoclassical growth theory within a maximising framework. Although innovation and technology are recognised as being the driving forces behind growth processes, these models maintain the restrictive assumption of a rational acting representative agent. In this paper we draw on a synergetic approach of evolutionary economics. In the model, the countries' productivity development is depicted as a sequence of relative technological levels and the movement from one level to the next higher one is governed by stochastic transition rates. The motivation for these transition rates is based on the knowledge-based approach of evolutionary economics, thereby taking into account depleting technological opportunities, the effects of technological infrastructure and permanent technological obsolescence due to an ubiquitous scientific progress. With this model we are able to show how a persistent bimodal distribution - the twin peaks - endogenously emerges via self-organisation. This simulated distribution matches well with the kernel density plot, calculated for GDP per worker data relative to the GDP per worker in the USA over the period 1960-90 for a sample of 104 countries. Both the empirical and theoretical results show an evolution of the density function toward bimodality with a decreasing number of countries with low relative productivity levels and an increasing number of countries with high relative productivity levels, indicating a prevalent catching-up during the period of investigation. However, the separation of both groups of countries is getting more significant over time and therefore further catching-up is expected to become increasingly difficult in the future.

Dwell time symmetry in random walks and molecular motors

The statistics of steps and dwell times in reversible molecular motors differ from those of cycle completion in enzyme kinetics. The reason is that a step is only one of several transitions in the mechanochemical cycle. As a result, theoretical results for cycle completion in enzyme kinetics do not apply to stepping data. To allow correct parameter estimation, and to guide data analysis and experiment design, a theoretical treatment is needed that takes this observation into account. In this paper, we model the distribution of dwell times and number of forward and backward steps using first passage processes, based on the assumption that forward and backward steps correspond to different directions of the same transition. We extend recent results for systems with a single cycle and consider the full dwell time distributions as well as models with multiple pathways, detectable substeps, and detachments. Our main results are a symmetry relation for the dwell time distributions in reversible motors, and a relation between certain relative step frequencies and the free energy per cycle. We demonstrate our results by analyzing recent stepping data for a bacterial flagellar motor, and discuss the implications for the efficiency and reversibility of the force-generating subunits. Key words: motor proteins; single molecule kinetics; enzyme kinetics; flagellar motor; Markov process; non-equilibrium fluctuations.Comment: revtex, 15 pages, 8 figures, 2 tables. v2: Minor revision, corrected typos, added references, and moved mathematical parts to new appendice

Concerning Technology Adoption and Inequality

Empirical evidence suggests that there has been a divergence over time in income distributions across countries and within countries. Furthermore, developing economies show a great deal of diversity in their growth patterns during the process of economic development. For example, some of these countries converge rapidly on the leaders, while others stagnate, or even experience reversals and declines in their growth processes. In this paper we study a simple dynamic general equilibrium model with household specific costs of technology adoption which is consistent with these stylized facts. In our model, growth is endogenous, and there are two-period lived overlapping generations of agents, assumed to be heterogeneous in their initial holdings of wealth and capital. We find that in a special case of our model, with costs associated with the adoption of more productive technologies fixed across households, inequalities in wealth and income may increase over time, tending to delay the convergence in international income differences. The model is also capable of explaining some of the observed diversity in the growth pattern of transitional economies. According to the model, this diversity may be the result of variability in adoption costs over time, or the relative position of a transitional economy in the world income distribution. In the more general case of the model with household specific adoption costs, negative growth rates during the transitional process are also possible. The model’s prediction that inequality has negative impact on technology adoption is supported by empirical evidence based on a cross country data set.inequality, technology adoption, international income differences, altruism, negative growth rates.

Evaluation of a generic agro-hydrological model for water and nitrogen dynamics (SMCR_N) in the soil–wheat system

Agro-hydrological models have widely been used for optimizing resources use in agriculture for maximum crop growth and minimum environmental consequences. The SMCR_N model is a recently developed, process-based, multi-crop and management-oriented agro-hydrological model for water and nitrogen dynamics in the soil–crop system, and has been validated against data from field experiments over a range of vegetable crops. In this study, the model is further tested against the comprehensive measured datasets from field experiments conducted under different circumstances on wheat. It has been found that given the proper parameterization of the simple growth equation, which worked well with vegetable crops, the model was able to simulate wheat growth accurately. The predicted relative root length density distributions at various development stages agreed with the measurements and those modeled by alternative approaches in the literature. The explicit hydrological algorithm for the basic equations governing water and nitrogen transport in soil performed well. Compared with other conventional numerical schemes, the algorithm used in the study was much simpler and easy to implement. The simulated spatial–temporal soil water content was in good agreement with the measurements, given the information of groundwater table was known. The model was also capable of reproducing the data of nitrogen uptake and soil mineral nitrogen concentration measured at depths and at time intervals. This indicates that the key equations for various processes governing water and nitrogen dynamics in the soil–wheat system were correctly formulated, and the model was properly parameterized. The results from this exercise, together with the model's previous validation over 16 vegetable crops, make the model a good candidate to be used for water and nitrogen management for growing diverse crops

Analysis of stratospheric ozone, temperature, and minor constituent data

The objective of this research is to use available satellite measurements of temperature and constituent concentrations to test the conceptual picture of stratospheric chemistry and transport. This was originally broken down into two sub-goals: first, to use the constituent data to search for critical tests of our understanding of stratospheric chemistry and second, to examine constituent transport processes emphasizing interactions with chemistry on various time scales. A third important goal which has evolved is to use the available solar backscattered ultraviolet (SBUV) and Total Ozone Mapping Spectrometer (TOMS) data from Nimbus 7 to describe the morphology of recent changes in Antarctic and global ozone with emphasis on searching for constraints to theories. The major effort now being pursued relative to the two original goals is our effort as a theoretical team for the Arctic Airborne Stratospheric Expedition (AASE). Our effort for the AASE is based on the 3D transport and chemistry model at Goddard. Our goal is to use this model to place the results from the mission data in a regional and global context. Specifically, we set out to make model runs starting in late December and running through March of 1989, both with and without heterogeneous chemistry. The transport is to be carried out using dynamical fields from a 4D data assimilation model being developed under separate funding from this task. We have successfully carried out a series of single constituent transport experiments. One of the things demonstrated by these runs was the difficulty in obtaining observed low N2O abundances in the vortex without simultaneously obtaining very high ozone values. Because the runs start in late December, this difficulty arises in the attempt to define consistent initial conditions for the 3D model. To accomplish a consistent set of initial conditions, we are using the 2D photochemistry-transport model of Jackman and Douglass and mapping in potential temperature, potential vorticity space as developed by Schoeberl and coworkers

Construction of Multi-Dimensional Functions for Optimization of Additive-Manufacturing Process Parameters

The authors present a generic framework for parameter optimization of additive manufacturing (AM) processes, one tailored to a high-throughput experimental methodology (HTEM). Given the large number of parameters, which impact the quality of AM-metallic components, the authors advocate for partitioning the AM parameter set into stages (tiers), based on their relative importance, modeling one tier at a time until successful, and then systematically expanding the framework. The authors demonstrate how the construction of multi-dimensional functions, based on neural networks (NN), can be applied to successfully model relative densities and Rockwell hardness obtained from HTEM testing of the Inconel 718 superalloy fabricated, using a powder-bed approach. The authors analyze the input data set, assess its suitability for predictions, and show how to optimize the framework for the multi-dimensional functional construction, such as to obtain the highest degree of fit with the input data. The novelty of the research work entails the versatile and scalable NN framework presented, suitable for use in conjunction with HTEM, for the AM parameter optimization of superalloys, and beyond.Comment: Submitted to the Journal of Additive Manufacturing on November 10, 202