Trade in intermediate goods and total factor productivity

We develop and calibrate a model where differences in factor endowments lead countries to trade intermediate goods, and gains from trade reflect in total factor productivity. We perform several output and growth decompositions, to assess the impact that barriers to trade, as well as changes in terms of trade, have on measured TFP. We find that for very poor economies gains from trade are large, in some cases representing a doubling of GDP. Also, that an improvement in the terms of trade - by allowing the use of a better mix of intermediate inputs in the production process - translates into productivity growth.

Gains from trade and measured total factor productivity

We develop and calibrate a model where diferences in factor en-dowments lead countries to trade di¤erent goods, so that the existence of international trade changes the sectorial composition of output from one country to another. Gains from trade re ect in total factor productivity. We perform a development decomposition, to assess the impact of trade and barriers to trade on measured TFP. In our sample, the median size of that e¤ect is about 6.5% of output, with a median of 17% and a maximum of 89%. Also, the model predicts that changes in the terms of trade cause a change of productivity, and that efect has an average elasticity of 0.71.

Constructing common-factor portfolios

In this paper we construct common-factor portfolios using a novel linear transformation of standard factor models extracted from large data sets of asset returns. The simple transformation proposed here keeps the basic properties of the usual factor transformations, although some new interesting properties are further attached to them. Some theoretical advantages are shown to be present. Also, their practical importance is confirmed in two applications: the performance of common-factor portfolios are shown to be superior to that of asset returns and factors commonly employed in the finance literature.

Simulation-based smoothing and filtering in factor stochastic volatility models : two econometric applications

In this article we use factor models to describe a certain class of covariance structure for financiaI time series models. More specifical1y, we concentrate on situations where the factor variances are modeled by a multivariate stochastic volatility structure. We build on previous work by allowing the factor loadings, in the factor mo deI structure, to have a time-varying structure and to capture changes in asset weights over time motivated by applications with multi pIe time series of daily exchange rates. We explore and discuss potential extensions to the models exposed here in the prediction area. This discussion leads to open issues on real time implementation and natural model comparisons.

Simulation -based smoothing and filtering in factor stochastic volatility models : two econometric applications (July-2001)

The past decade has wítenessed a series of (well accepted and defined) financial crises periods in the world economy. Most of these events aI,"e country specific and eventually spreaded out across neighbor countries, with the concept of vicinity extrapolating the geographic maps and entering the contagion maps. Unfortunately, what contagion represents and how to measure it are still unanswered questions. In this article we measure the transmission of shocks by cross-market correlation\ coefficients following Forbes and Rigobon's (2000) notion of shift-contagion,. Our main contribution relies upon the use of traditional factor model techniques combined with stochastic volatility mo deIs to study the dependence among Latin American stock price indexes and the North American indexo More specifically, we concentrate on situations where the factor variances are modeled by a multivariate stochastic volatility structure. From a theoretical perspective, we improve currently available methodology by allowing the factor loadings, in the factor model structure, to have a time-varying structure and to capture changes in the series' weights over time. By doing this, we believe that changes and interventions experienced by those five countries are well accommodated by our models which learns and adapts reasonably fast to those economic and idiosyncratic shocks. We empirically show that the time varying covariance structure can be modeled by one or two common factors and that some sort of contagion is present in most of the series' covariances during periods of economical instability, or crisis. Open issues on real time implementation and natural model comparisons are thoroughly discussed.

Using irregularly spaced returns to estimate multi-factor models : application to Brazilian equity data

Multi-factor models constitute a use fui tool to explain cross-sectional covariance in equities retums. We propose in this paper the use of irregularly spaced returns in the multi-factor model estimation and provide an empirical example with the 389 most liquid equities in the Brazilian Market. The market index shows itself significant to explain equity returns while the US$/Brazilian Real exchange rate and the Brazilian standard interest rate does not. This example shows the usefulness of the estimation method in further using the model to fill in missing values and to provide intervaI forecasts.

Stochastic discount factor bounds and rare events: a review

We aim to provide a review of the stochastic discount factor bounds usually applied to diagnose asset pricing models. In particular, we mainly discuss the bounds used to analyze the disaster model of Barro (2006). Our attention is focused in this disaster model since the stochastic discount factor bounds that are applied to study the performance of disaster models usually consider the approach of Barro (2006). We first present the entropy bounds that provide a diagnosis of the analyzed disaster model which are the methods of Almeida and Garcia (2012, 2016); Ghosh et al. (2016). Then, we discuss how their results according to the disaster model are related to each other and also present the findings of other methodologies that are similar to these bounds but provide different evidence about the performance of the framework developed by Barro (2006).

Association of an insulin-like growth factor 1 gene microsatellite with phenotypic variation and estimated breeding values of growth traits in Canchim cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Short-term temporal changes of soil carbon losses after tillage described by a first-order decay model

Tillage stimulates soil carbon (C) losses by increasing aeration, changing temperature and moisture conditions, and thus favoring microbial decomposition. In addition, soil aggregate disruption by tillage exposes once protected organic matter to decomposition. We propose a model to explain carbon dioxide (CO2) emission after tillage as a function of the no-till emission plus a correction due to the tillage disturbance. The model assumes that C in the readily decomposable organic matter follows a first-order reaction kinetics equation as: dC(sail)(t)/dt = -kC(soil)(t) and that soil C-CO2 emission is proportional to the C decay rate in soil, where C-soil(t) is the available labile soil C (g m(-2)) at any time (t). Emissions are modeled in terms soil C available to decomposition in the tilled and non-tilled plots, and a relationship is derived between no-till (F-NT) and tilled (F-Gamma) fluxes, which is: F-T = a1F(NT)e(-a2t), where t is time after tillage. Predicted and observed fluxes showed good agreement based on determination coefficient (R-2), index of agreement and model efficiency, with R-2 as high as 0.97. The two parameters included in the model are related to the difference between the decay constant (k factor) of tilled and no-till plots (a(2)) and also to the amount of labile carbon added to the readily decomposable soil organic matter due to tillage (a,). These two parameters were estimated in the model ranging from 1.27 and 2.60 (a(1)) and - 1.52 x 10(-2) and 2.2 x 10(-2) day(-1) (a(2)). The advantage is that temporal variability of tillage-induced emissions can be described by only one analytical function that includes the no-till emission plus an exponential term modulated by tillage and environmentally dependent parameters. (C) 2008 Elsevier B.V. All rights reserved.

Structural modeling and mutational analysis of yeast eukaryotic translation initiation factor 5A reveal new critical residues and reinforce its involvement in protein synthesis

Eukaryotic translation initiation factor 5A (eIF5A) is a protein that is highly conserved and essential for cell viability. This factor is the only protein known to contain the unique and essential amino acid residue hypusine. This work focused on the structural and functional characterization of Saccharomyces cerevisiae eIF5A. The tertiary structure of yeast eIF5A was modeled based on the structure of its Leishmania mexicana homologue and this model was used to predict the structural localization of new site-directed and randomly generated mutations. Most of the 40 new mutants exhibited phenotypes that resulted from eIF-5A protein-folding defects. Our data provided evidence that the C-terminal alpha-helix present in yeast eIF5A is an essential structural element, whereas the eIF5A N-terminal 10 amino acid extension not present in archaeal eIF5A homologs, is not. Moreover, the mutants containing substitutions at or in the vicinity of the hypusine modification site displayed nonviable or temperature-sensitive phenotypes and were defective in hypusine modification. Interestingly, two of the temperature-sensitive strains produced stable mutant eIF5A proteins - eIF5A(K56A) and eIF5A(Q22H,L93F)- and showed defects in protein synthesis at the restrictive temperature. Our data revealed important structural features of eIF5A that are required for its vital role in cell viability and underscored an essential function of eIF5A in the translation step of gene expression.

Describing fatigue crack growth and load ratio effects in Al 2524 T3 alloy with an enhanced exponential model

The fatigue crack behavior in metals and alloys under constant amplitude test conditions is usually described by relationships between the crack growth rate da/dN and the stress intensity factor range Delta K. In the present work, an enhanced two-parameter exponential equation of fatigue crack growth was introduced in order to describe sub-critical crack propagation behavior of Al 2524-T3 alloy, commonly used in aircraft engineering applications. It was demonstrated that besides adequately correlating the load ratio effects, the exponential model also accounts for the slight deviations from linearity shown by the experimental curves. A comparison with Elber, Kujawski and "Unified Approach" models allowed for verifying the better performance, when confronted to the other tested models, presented by the exponential model. (C) 2012 Elsevier Ltd. All rights reserved.

Corona Discharge Model for Transmission Lines by Lumped Elements

This paper shows the insertion of corona effect in a transmission line model based on lumped elements. The development is performed considering a frequency-dependent line representation by cascade of pi sections and state equations. Hence, the detailed profile of currents and voltages along the line, described from a non-homogeneous system of differential equations, can be obtained directly in time domain applying numerical or analytic solution integration methods. The corona discharge model is also based on lumped elements and is implemented from the well-know Skilling-Umoto Model.

Model for determining flow diameter and economic velocity in water elevating systems

The purpose of this paper was to develop a model for calculating the economical flow diameter and velocity, by obtaining the economical diameter, using Swamee's friction factor equation, by minimizing the total annual cost. The application of the model to a regular supply condition showed that the diameter of the actual condition, 250 mm, compared with the diameter calculated by the mode, at the same tariff as that applied to the property ( ground), 284.1 mm, involved the necessity to generate, transmit, and distribute extra electrical energy, due to the higher load loss caused by the original diameter, approximately 30800 kWh/year. This means that in one year, the consumer would spend R$2,804.00 more on pumping cost alone.

Chronic ethanol intake promotes double gluthatione S-transferase transforming growth factor-alpha-positive hepatocellular lesions in male Wistar rats

The chronic ethanol intake influence on the gluthatione S-transferase (GST-P) and transforming growth factor alpha (TGF-alpha) expression in remodeling/persistent preneoplastic lesions (PNLs) was evaluated in the resistant hepatocyte model. Male Wistar rats were allocated into five groups: G1, non-treated, fed water and chow ad libitum; G2, non-treated and pair-fed chow (restricted to match that of G3 group) and a maltodextrin (MD) solution in tap water (matched ethanol-derived calories); G3, fed 5% ethanol in drinking water and chow ad libitum; G4, diethylnitrosamine (DEN, 200 mg/kg, body weight) plus 200 parts per million of 2-acetylaminofluorene (2-AAF) for 3 weeks and pair-fed chow (restricted to match that of G5 group) and an MD solution in tap water (matched ethanol-derived calories); G5, DEN/2-AAF treatment, fed ethanol 5% and chow ad libitum. All animals were subjected to 70% partial hepatectomy at week 3 and sacrificed at weeks 12 or 22, respectively. Liver samples were collected for histological analysis or immunohistochemical expression of GST-P, TGF-alpha and proliferating cell nuclear antigen or zymography for matrix metalloproteinases-2 and -9. At the end of ethanol treatment, there was a significant increase in the percentage of liver area occupied by persistent GST-P-positive PNLs, the number of TGF-alpha-positive PNLs and the development of liver tumors in ethanol-fed and DEN/2-AAF-treated groups (G5 versus G4, P < 0.001). In addition, ethanol feeding led to a significant increase in cell proliferation mainly in remodeling and persistent PNLs with immunoreactivity for TGF-alpha at week 22 (P < 0.001). Gelatinase activities were not altered by ethanol treatment. The results demonstrated that ethanol enhances the selective growth of PNL with double expression of TGF-alpha and GST-P markers.

Amitriptyline aggravates the fibrosis process in a rat model of infravesical obstruction

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)