Forward Looking and Myopic Regional Computable General Equilibrium Models. How Significant is the Distinction?

We present a stylized intertemporal forward-looking model able that accommodates key regional economic features, an area where the literature is not well developed. The main difference, from the standard applications, is the role of saving and its implication for the balance of payments. Though maintaining dynamic forward-looking behaviour for agents, the rate of private saving is exogenously determined and so no neoclassical financial adjustment is needed. Also, we focus on the similarities and the differences between myopic and forward-looking models, highlighting the divergences among the main adjustment equations and the resulting simulation outcomes.

Shallow-level migmatization of gabbros in a metamorphic contact aureole, Fuerteventura Basal Complex, Canary Islands

Migmatization of gabbroic rocks at 2-3 kbar has occurred in the metamorphic contact aureole of a mafic pluton in the Fuerteventura Basal Complex (Canary Island;). Migmatites are characterized by a dense network: of closely spaced millimetre-wide leucocratic veins with perfectly preserved igneous textures. They are all relatively enriched in Al, Na I: Sr Ba, Nb, Y and the rare earth elements compared with the unaffected country rock beyond the aureole. Migmatization under such low-pressure conditions war possible because of the unusual tectonic and magmatic contact in which ii occurred. Multiple basic intrusions associated with extrusive volcanic activity created high heat flow in a small area. Alkaline and metasomatized rocks present in the country rock of the intruding pluton were leached by high-temperature fluids during contact metamorphism. These enriched fluids then favoured partial melting of the host gabbroic rocks, and contaminated both the leucosomes and melanosomes. A transpressive tectonic setting at the time of intrusion created shearing along the contact between the intrusion and its host rock. This shearing enhanced circulation of the fluids and allowed segregation of the nea-formed melts from their restite by opening tension veins into which the melts migrated. Depending on the relative timing of melt segregation and recrystallization leucosomes range in composition from a 40-60% mixture of clinopyroxene (+/- amphibole) and plagioclase to almost pure feldspathic veins. Comparable occurrences of gabbros migmatized at low pressure are expected only at a snail scale in localized areas of high heat flow in the presence of fluids, such as in. mid-ocean ridges or ocean-islands.

Surfactant protein-D and exposure to bioaerosols in wastewater and garbage workers.

PURPOSE: Bioaerosols and their constituents, such as endotoxins, are capable of causing an inflammatory reaction at the level of the lung-blood barrier, which becomes more permeable. Thus, it was hypothesized that occupational exposure to bioaerosols can increase leakage of surfactant protein-D (SP-D), a lung-specific protein, into the bloodstream. METHODS: SP-D was determined by ELISA in 316 wastewater workers, 67 garbage collectors, and 395 control subjects. Exposure was assessed with four interview-based indicators and by preliminary endotoxin measurements using the Limulus amoebocyte lysate assay. Influence of exposure on serum SP-D was assessed by multiple linear regression considering smoking, glomerular function, lung diseases, obesity, and other confounders. RESULTS: Overall, mean exposure levels to endotoxins were below 100 EU/m(3). However, special tasks of wastewater workers caused higher endotoxin exposure. SP-D concentration was slightly increased in this occupational group and associated with the occurrence of splashes and contact to raw sewage. No effect was found in garbage collectors. Smoking increased serum SP-D. No clinically relevant correlation between spirometry results and SP-D concentrations appeared. CONCLUSIONS: These results support the hypothesis that inhalation of bioaerosols, even at low concentrations, has a subclinical effect on the lung-blood barrier, the permeability of which increases without associated spirometric changes.

No Good Deals - No Bad Models

Faced with the problem of pricing complex contingent claims, an investor seeks to make his valuations robust to model uncertainty. We construct a notion of a model- uncertainty-induced utility function and show that model uncertainty increases the investor's eff ective risk aversion. Using the model-uncertainty-induced utility function, we extend the \No Good Deals" methodology of Cochrane and Sa a-Requejo [2000] to compute lower and upper good deal bounds in the presence of model uncertainty. We illustrate the methodology using some numerical examples.

Identification of particular groups of microRNAs that positively or negatively impact on beta cell function in obese models of type 2 diabetes.

AIMS/HYPOTHESIS: MicroRNAs are key regulators of gene expression involved in health and disease. The goal of our study was to investigate the global changes in beta cell microRNA expression occurring in two models of obesity-associated type 2 diabetes and to assess their potential contribution to the development of the disease. METHODS: MicroRNA profiling of pancreatic islets isolated from prediabetic and diabetic db/db mice and from mice fed a high-fat diet was performed by microarray. The functional impact of the changes in microRNA expression was assessed by reproducing them in vitro in primary rat and human beta cells. RESULTS: MicroRNAs differentially expressed in both models of obesity-associated type 2 diabetes fall into two distinct categories. A group including miR-132, miR-184 and miR-338-3p displays expression changes occurring long before the onset of diabetes. Functional studies indicate that these expression changes have positive effects on beta cell activities and mass. In contrast, modifications in the levels of miR-34a, miR-146a, miR-199a-3p, miR-203, miR-210 and miR-383 primarily occur in diabetic mice and result in increased beta cell apoptosis. These results indicate that obesity and insulin resistance trigger adaptations in the levels of particular microRNAs to allow sustained beta cell function, and that additional microRNA deregulation negatively impacting on insulin-secreting cells may cause beta cell demise and diabetes manifestation. CONCLUSIONS/INTERPRETATION: We propose that maintenance of blood glucose homeostasis or progression toward glucose intolerance and type 2 diabetes may be determined by the balance between expression changes of particular microRNAs.

Model Switching and Model Averaging in Time- Varying Parameter Regression Models

This paper investigates the usefulness of switching Gaussian state space models as a tool for implementing dynamic model selecting (DMS) or averaging (DMA) in time-varying parameter regression models. DMS methods allow for model switching, where a different model can be chosen at each point in time. Thus, they allow for the explanatory variables in the time-varying parameter regression model to change over time. DMA will carry out model averaging in a time-varying manner. We compare our exact approach to DMA/DMS to a popular existing procedure which relies on the use of forgetting factor approximations. In an application, we use DMS to select different predictors in an in ation forecasting application. We also compare different ways of implementing DMA/DMS and investigate whether they lead to similar results.

A toxicokinetic model to assess exposure to folpet fungicide from urinary biomarkers

Folpet is one of the most widely employed fungicides in agriculture. It is typically used in the culture of vegetables, fruits and ornamental plants. Once absorbed in the human body, it has been found to be very reactive, especially in acid conditions. According to various in vitro and in vivo experiments in animals, Folpet is first fractioned at the N-S link when in contact with aqueous solutions and thiol groups. From this non-enzymatic process a phthalimide (PI) molecule is formed, which may be used as a biomarker of exposure, along with the short-lived thiophosgene. We have built a human toxicokinetic model to account for the biotransformation of Folpet into PI and its subsequent excretion while accounting for other non-monitored metabolites. The mathematical parameters of the model were determined accordingly from best-fits to the time courses of PI in blood and urine of five volunteers administered orally 1 mg/kg and dermally 10 mg/kg of Folpet. In both cases, the mean elimination half-life of PI from the body (either through faeces, urine or metabolism) was found to be 31.6 h. The average final fractions of administered dose recovered in urine as PI were 0.025% and 0.002%, for oral and dermal administration, respectively after 96 h. According to the model, when orally administered, PI rapidly hydrolyzes to phthalamic and phthalic acids such that only 0.04% of the PI found in the gastrointestinal tract is absorbed into the blood stream. Likewise, after dermal application, model predicts that only 7.4% of the applied Folpet dose crosses the epidermis. In the model, the PI initial metabolite of Folpet is formed in the dermis and further metabolized prior to reaching systemic circulation, such that only 0.125% of PI formed at the site-of-entry reaches systemic blood. Our mathematical model is in accordance with both measures of blood (R2=0.57 for dermal and R2=0.66 for oral) and urine (R2 =0.98 for dermal and R2=0.99 for oral).

Model Uncertainty in Panel Vector Autoregressive Models.

We develop methods for Bayesian model averaging (BMA) or selection (BMS) in Panel Vector Autoregressions (PVARs). Our approach allows us to select between or average over all possible combinations of restricted PVARs where the restrictions involve interdependencies between and heterogeneities across cross-sectional units. The resulting BMA framework can find a parsimonious PVAR specification, thus dealing with overparameterization concerns. We use these methods in an application involving the euro area sovereign debt crisis and show that our methods perform better than alternatives. Our findings contradict a simple view of the sovereign debt crisis which divides the euro zone into groups of core and peripheral countries and worries about financial contagion within the latter group.

Model Uncertainty in Panel Vector Autoregressive Models.

We develop methods for Bayesian model averaging (BMA) or selection (BMS) in Panel Vector Autoregressions (PVARs). Our approach allows us to select between or average over all possible combinations of restricted PVARs where the restrictions involve interdependencies between and heterogeneities across cross-sectional units. The resulting BMA framework can find a parsimonious PVAR specification, thus dealing with overparameterization concerns. We use these methods in an application involving the euro area sovereign debt crisis and show that our methods perform better than alternatives. Our findings contradict a simple view of the sovereign debt crisis which divides the euro zone into groups of core and peripheral countries and worries about financial contagion within the latter group.

The convenient calculation of some test statistics in models of discrete choice

The paper considers the use of artificial regression in calculating different types of score test when the log

Secondary contact zones and hybridizations: the case of the lesser white-toothed shrew (Crocidura suaveolens group, Soricidae)

In the present study, we analyzed 58 samples of the lesser white-toothed shrew group (Crocidura suaveolens) from eastern Europe and Turkey, where, according to previous publications, three different mitochondrial and nuclear lineages are present. We sequenced 799 bp of the nuclear BRCA1 gene and 400 bp of the mitochondrial cytochrome b gene to: (1) determine a potential contact zone between the lineages; (2) detect hybridizations and introgressions between them; and (3) comment on the level of reproductive isolation of the different lineages. We revealed two zones of hybridization in Turkey, of which the first occurred west of the Bosphorus Straits (three hybrids) and the second in Anatolia (twelve hybrids). In the latter, the nuclear markers revealed a large zone of hybridization, of approximately 600 km. It also revealed that hybrids of first, second, and later generations are present within the populations, and therefore that the reproductive isolation between the different lineages is weak.

Time Varying Dimension Models

Time varying parameter (TVP) models have enjoyed an increasing popularity in empirical macroeconomics. However, TVP models are parameter-rich and risk over-fitting unless the dimension of the model is small. Motivated by this worry, this paper proposes several Time Varying dimension (TVD) models where the dimension of the model can change over time, allowing for the model to automatically choose a more parsimonious TVP representation, or to switch between different parsimonious representations. Our TVD models all fall in the category of dynamic mixture models. We discuss the properties of these models and present methods for Bayesian inference. An application involving US inflation forecasting illustrates and compares the different TVD models. We find our TVD approaches exhibit better forecasting performance than several standard benchmarks and shrink towards parsimonious specifications.

Hierarchical Shrinkage in Time-Varying Parameter Models

In this paper, we forecast EU-area inflation with many predictors using time-varying parameter models. The facts that time-varying parameter models are parameter-rich and the time span of our data is relatively short motivate a desire for shrinkage. In constant coefficient regression models, the Bayesian Lasso is gaining increasing popularity as an effective tool for achieving such shrinkage. In this paper, we develop econometric methods for using the Bayesian Lasso with time-varying parameter models. Our approach allows for the coefficient on each predictor to be: i) time varying, ii) constant over time or iii) shrunk to zero. The econometric methodology decides automatically which category each coefficient belongs in. Our empirical results indicate the benefits of such an approach.

Computing Markov-Perfect Optimal Policies in Business-Cycle Models

Time-inconsistency is an essential feature of many policy problems (Kydland and Prescott, 1977). This paper presents and compares three methods for computing Markov-perfect optimal policies in stochastic nonlinear business cycle models. The methods considered include value function iteration, generalized Euler-equations, and parameterized shadow prices. In the context of a business cycle model in which a scal authority chooses government spending and income taxation optimally, while lacking the ability to commit, we show that the solutions obtained using value function iteration and generalized Euler equations are somewhat more accurate than that obtained using parameterized shadow prices. Among these three methods, we show that value function iteration can be applied easily, even to environments that include a risk-sensitive scal authority and/or inequality constraints on government spending. We show that the risk-sensitive scal authority lowers government spending and income-taxation, reducing the disincentive households face to accumulate wealth.

Structured and unstructured continuous models for Wolbachia infections

We introduce and investigate a series of models for an infection of a diplodiploid host species by the bacterial endosymbiont Wolbachia. The continuous models are characterized by partial vertical transmission, cytoplasmic incompatibility and fitness costs associated with the infection. A particular aspect of interest is competitions between mutually incompatible strains. We further introduce an age-structured model that takes into account different fertility and mortality rates at different stages of the life cycle of the individuals. With only a few parameters, the ordinary differential equation models exhibit already interesting dynamics and can be used to predict criteria under which a strain of bacteria is able to invade a population. Interestingly, but not surprisingly, the age-structured model shows significant differences concerning the existence and stability of equilibrium solutions compared to the unstructured model.