Solving Leontief Input-Output Model with Trapezoidal Fuzzy Numbers and Gauss-Seidel Algorithm

In this work a fuzzy linear system is used to solve Leontief input-output model with fuzzy entries. For solving this model, we assume that the consumption matrix from di erent sectors of the economy and demand are known. These assumptions heavily depend on the information obtained from the industries. Hence uncertainties are involved in this information. The aim of this work is to model these uncertainties and to address them by fuzzy entries such as fuzzy numbers and LR-type fuzzy numbers (triangular and trapezoidal). Fuzzy linear system has been developed using fuzzy data and it is solved using Gauss-Seidel algorithm. Numerical examples show the e ciency of this algorithm. The famous example from Prof. Leontief, where he solved the production levels for U.S. economy in 1958, is also further analyzed.

The salvo combat model with area fire

This paper analyzes versions of the salvo model of missile combat where area fire is used by one or both sides in a battle. While these models share some properties with the area fire Lanchester model and the aimed fire salvo model, they also display some interesting differences, especially over the course of several salvos. Whereas the relative size of each force is important with aimed fire, with area fire it is the absolute size that matters. Similarly, while aimed fire exhibits square law behavior, area fire shows approximately linear behavior. When one side uses area and the other uses aimed fire, the model displays a mix of square and linear law behavior.

Empirical Assessment of an Intertemporal Option Pricing Model with Latent variables

This paper assesses the empirical performance of an intertemporal option pricing model with latent variables which generalizes the Hull-White stochastic volatility formula. Using this generalized formula in an ad-hoc fashion to extract two implicit parameters and forecast next day S&P 500 option prices, we obtain similar pricing errors than with implied volatility alone as in the Hull-White case. When we specialize this model to an equilibrium recursive utility model, we show through simulations that option prices are more informative than stock prices about the structural parameters of the model. We also show that a simple method of moments with a panel of option prices provides good estimates of the parameters of the model. This lays the ground for an empirical assessment of this equilibrium model with S&P 500 option prices in terms of pricing errors.

Estimating the Tobit Model with Serial Correlation: an Operational Approach

Several Authors Have Discussed Recently the Limited Dependent Variable Regression Model with Serial Correlation Between Residuals. the Pseudo-Maximum Likelihood Estimators Obtained by Ignoring Serial Correlation Altogether, Have Been Shown to Be Consistent. We Present Alternative Pseudo-Maximum Likelihood Estimators Which Are Obtained by Ignoring Serial Correlation Only Selectively. Monte Carlo Experiments on a Model with First Order Serial Correlation Suggest That Our Alternative Estimators Have Substantially Lower Mean-Squared Errors in Medium Size and Small Samples, Especially When the Serial Correlation Coefficient Is High. the Same Experiments Also Suggest That the True Level of the Confidence Intervals Established with Our Estimators by Assuming Asymptotic Normality, Is Somewhat Lower Than the Intended Level. Although the Paper Focuses on Models with Only First Order Serial Correlation, the Generalization of the Proposed Approach to Serial Correlation of Higher Order Is Also Discussed Briefly.

Asymptotic Approximations in the Near-Integrated Model with a Non-Zero Initial Condition

This paper considers various asymptotic approximations in the near-integrated firstorder autoregressive model with a non-zero initial condition. We first extend the work of Knight and Satchell (1993), who considered the random walk case with a zero initial condition, to derive the expansion of the relevant joint moment generating function in this more general framework. We also consider, as alternative approximations, the stochastic expansion of Phillips (1987c) and the continuous time approximation of Perron (1991). We assess how these alternative methods provide or not an adequate approximation to the finite-sample distribution of the least-squares estimator in a first-order autoregressive model. The results show that, when the initial condition is non-zero, Perron's (1991) continuous time approximation performs very well while the others only offer improvements when the initial condition is zero.

The Exchange Rate in a Dynamic-Optimizing Current Account Model with Nominal Rigidities: a Quantitative Investigation.

This paper studies a dynamic-optimizing model of a semi-small open economy with sticky nominal prices and wages. the model exhibits exchange rate overshooting in response to money supply shocks. the predicted variability of nominal and real exchange rates is roughly consistent with that of G7 effective exchange rates during the post-Bretton Woods era.

The hotelling model with multiple demands

The purpose of this chapter is to provide an elementary introduction to the non-renewable resource model with multiple demand curves. The theoretical literature following Hotelling (1931) assumed that all energy needs are satisfied by one type of resource (e.g. ‘oil’), extractible at different per-unit costs. This formulation implicitly assumes that all users are the same distance from each resource pool, that all users are subject to the same regulations, and that motorist users can switch as easily from liquid fossil fuels to coal as electric utilities can. These assumptions imply, as Herfindahl (1967) showed, that in competitive equilibrium all users will exhaust a lower cost resource completely before beginning to extract a higher cost resource: simultaneous extraction of different grades of oil or of oil and coal should never occur. In trying to apply the single-demand curve model during the last twenty years, several teams of authors have independently found a need to generalize it to account for users differing in their (1) location, (2) regulatory environment, or (3) resource needs. Each research team found that Herfindahl's strong, unrealistic conclusion disappears in the generalized model; in its place, a weaker Herfindahl result emerges. Since each research team focussed on a different application, however, it has not always been clear that everyone has been describing the same generalized model. Our goal is to integrate the findings of these teams and to exposit the generalized model in a form which is easily accessible.

Abdominal aortic aneurysm follow-up after endovascular repair in a canine model with non-invasive vascular elastography

Le traitement chirurgical des anévrismes de l'aorte abdominale est de plus en plus remplacé par la réparation endovasculaire de l’anévrisme (« endovascular aneurysm repair », EVAR) en utilisant des endoprothèses (« stent-grafts », SGs). Cependant, l'efficacité de cette approche moins invasive est compromise par l'incidence de l'écoulement persistant dans l'anévrisme, appelé endofuites menant à une rupture d'anévrisme si elle n'est pas détectée. Par conséquent, une surveillance de longue durée par tomodensitométrie sur une base annuelle est nécessaire ce qui augmente le coût de la procédure EVAR, exposant le patient à un rayonnement ionisants et un agent de contraste néphrotoxique. Le mécanisme de rupture d'anévrisme secondaire à l'endofuite est lié à une pression du sac de l'anévrisme proche de la pression systémique. Il existe une relation entre la contraction ou l'expansion du sac et la pressurisation du sac. La pressurisation résiduelle de l'anévrisme aortique abdominale va induire une pulsation et une circulation sanguine à l'intérieur du sac empêchant ainsi la thrombose du sac et la guérison de l'anévrisme. L'élastographie vasculaire non-invasive (« non-invasive vascular elastography », NIVE) utilisant le « Lagrangian Speckle Model Estimator » (LSME) peut devenir une technique d'imagerie complémentaire pour le suivi des anévrismes après réparation endovasculaire. NIVE a la capacité de fournir des informations importantes sur l'organisation d'un thrombus dans le sac de l'anévrisme et sur la détection des endofuites. La caractérisation de l'organisation d'un thrombus n'a pas été possible dans une étude NIVE précédente. Une limitation de cette étude était l'absence d'examen tomodensitométrique comme étalon-or pour le diagnostic d'endofuites. Nous avons cherché à appliquer et optimiser la technique NIVE pour le suivi des anévrismes de l'aorte abdominale (AAA) après EVAR avec endoprothèse dans un modèle canin dans le but de détecter et caractériser les endofuites et l'organisation du thrombus. Des SGs ont été implantés dans un groupe de 18 chiens avec un anévrisme créé dans l'aorte abdominale. Des endofuites de type I ont été créés dans 4 anévrismes, de type II dans 13 anévrismes tandis qu’un anévrisme n’avait aucune endofuite. L'échographie Doppler (« Doppler ultrasound », DUS) et les examens NIVE ont été réalisés avant puis à 1 semaine, 1 mois, 3 mois et 6 mois après l’EVAR. Une angiographie, une tomodensitométrie et des coupes macroscopiques ont été réalisées au moment du sacrifice. Les valeurs de contrainte ont été calculées en utilisant l`algorithme LSME. Les régions d'endofuite, de thrombus frais (non organisé) et de thrombus solide (organisé) ont été identifiées et segmentées en comparant les résultats de la tomodensitométrie et de l’étude macroscopique. Les valeurs de contrainte dans les zones avec endofuite, thrombus frais et organisé ont été comparées. Les valeurs de contrainte étaient significativement différentes entre les zones d'endofuites, les zones de thrombus frais ou organisé et entre les zones de thrombus frais et organisé. Toutes les endofuites ont été clairement caractérisées par les examens d'élastographie. Aucune corrélation n'a été trouvée entre les valeurs de contrainte et le type d'endofuite, la pression de sac, la taille des endofuites et la taille de l'anévrisme.