Job search and asset accumulation under borrowing constraints

In this paper I show how borrowing constraints and job search interact.I fit a dynamic model to data from the National Longitudinal Survey(1979-cohort) and show that borrowing constraints are significant. Agentswith more initial assets and more access to credit attain higher wagesfor several periods after high school graduation. The unemployed maintaintheir consumption by running down their assets, while the employed saveto buffer against future unemployment spells. I also show that, unlikein models with exogenous income streams, unemployment transfers, byallowing agents to attain higher wages do not 'crowd out' but increasesaving.

Testing for multicointegration in panel data with common factors

The paper addresses the concept of multicointegration in panel data frame- work. The proposal builds upon the panel data cointegration procedures developed in Pedroni (2004), for which we compute the moments of the parametric statistics. When individuals are either cross-section independent or cross-section dependence can be re- moved by cross-section demeaning, our approach can be applied to the wider framework of mixed I(2) and I(1) stochastic processes analysis. The paper also deals with the issue of cross-section dependence using approximate common factor models. Finite sample performance is investigated through Monte Carlo simulations. Finally, we illustrate the use of the procedure investigating inventories, sales and production relationship for a panel of US industries.

Testing for multicointegration in panel data with common factors

The paper addresses the concept of multicointegration in panel data frame- work. The proposal builds upon the panel data cointegration procedures developed in Pedroni (2004), for which we compute the moments of the parametric statistics. When individuals are either cross-section independent or cross-section dependence can be re- moved by cross-section demeaning, our approach can be applied to the wider framework of mixed I(2) and I(1) stochastic processes analysis. The paper also deals with the issue of cross-section dependence using approximate common factor models. Finite sample performance is investigated through Monte Carlo simulations. Finally, we illustrate the use of the procedure investigating inventories, sales and production relationship for a panel of US industries.

Financial convergence in transition economies: EU enlargement

This paper analyses the financial impact of the enlargement of the European Union (EU) to include 10 new Central and Eastern European Nations (CEEN) on firms’ business and financial structures. To this end, we employ quantitative analytic techniques and financial ratios. In this context, we hope to discover whether firms in the new EU member States tend to converge with business in the Europe of the 15 in terms of the structure of firms’ financial statements. We examine the extent to which the increasing integration of the former may foster the convergence of productive structures. The methodology followed consists of an analysis of the evolution of 12 financial ratios in a sample of firms obtained from the AMADEUS data base. To that end, we perform a Dynamic Factor Analysis that identifies the determining factors of the joint evolution of deviations in the financial ratios with respect to the average value of firms in the EU-15. This analysis allows us to analyse the convergence in each of the CEEN nations with respect to the EU-15.

Self-dynamic structure factor of dense liquids: Theory and simulation

The self-intermediate dynamic structure factor Fs(k,t) of liquid lithium near the melting temperature is calculated by molecular dynamics. The results are compared with the predictions of several theoretical approaches, paying special attention to the Lovesey model and the Wahnstrm and Sjgren mode-coupling theory. To this end the results for the Fs(k,t) second memory function predicted by both models are compared with the ones calculated from the simulations.

Are one factor logarithmic volatility models useful to fit the features of financial data? An application to microsoft data.

This paper provides empirical evidence that continuous time models with one factor of volatility, in some conditions, are able to fit the main characteristics of financial data. It also reports the importance of the feedback factor in capturing the strong volatility clustering of data, caused by a possible change in the pattern of volatility in the last part of the sample. We use the Efficient Method of Moments (EMM) by Gallant and Tauchen (1996) to estimate logarithmic models with one and two stochastic volatility factors (with and without feedback) and to select among them.

Estimation of dynamic latent variable models using simulated nonparametric moments

Given a model that can be simulated, conditional moments at a trial parameter value can be calculated with high accuracy by applying kernel smoothing methods to a long simulation. With such conditional moments in hand, standard method of moments techniques can be used to estimate the parameter. Since conditional moments are calculated using kernel smoothing rather than simple averaging, it is not necessary that the model be simulable subject to the conditioning information that is used to define the moment conditions. For this reason, the proposed estimator is applicable to general dynamic latent variable models. Monte Carlo results show that the estimator performs well in comparison to other estimators that have been proposed for estimation of general DLV models.

Estimation of dynamic latent variable models using simulated nonparametric moments

Abstract. Given a model that can be simulated, conditional moments at a trial parameter value can be calculated with high accuracy by applying kernel smoothing methods to a long simulation. With such conditional moments in hand, standard method of moments techniques can be used to estimate the parameter. Because conditional moments are calculated using kernel smoothing rather than simple averaging, it is not necessary that the model be simulable subject to the conditioning information that is used to define the moment conditions. For this reason, the proposed estimator is applicable to general dynamic latent variable models. It is shown that as the number of simulations diverges, the estimator is consistent and a higher-order expansion reveals the stochastic difference between the infeasible GMM estimator based on the same moment conditions and the simulated version. In particular, we show how to adjust standard errors to account for the simulations. Monte Carlo results show how the estimator may be applied to a range of dynamic latent variable (DLV) models, and that it performs well in comparison to several other estimators that have been proposed for DLV models.

Nonlinear inverse dynamic models of gas sensing systems based on chemical sensor arrays for quantitative measurements

Gas sensing systems based on low-cost chemical sensor arrays are gaining interest for the analysis of multicomponent gas mixtures. These sensors show different problems, e.g., nonlinearities and slow time-response, which can be partially solved by digital signal processing. Our approach is based on building a nonlinear inverse dynamic system. Results for different identification techniques, including artificial neural networks and Wiener series, are compared in terms of measurement accuracy.

Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models

Background: Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results: Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions: Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.

Dynamic matching and bargaining: the role of deadlines

We consider a dynamic model where traders in each period are matched randomly into pairs who then bargain about the division of a fixed surplus. When agreement is reached the traders leave the market. Traders who do not come to an agreement return next period in which they will be matched again, as long as their deadline has not expired yet. New traders enter exogenously in each period. We assume that traders within a pair know each other's deadline. We define and characterize the stationary equilibrium configurations. Traders with longer deadlines fare better than traders with short deadlines. It is shown that the heterogeneity of deadlines may cause delay. It is then shown that a centralized mechanism that controls the matching protocol, but does not interfere with the bargaining, eliminates all delay. Even though this efficient centralized mechanism is not as good for traders with long deadlines, it is shown that in a model where all traders can choose which mechanism to

An analysis of strategic paths through the decomposition of total factor productivity: the case of Spanish savings banks

The Spanish savings banks attracted quite a considerable amount of interest within the scientific arena, especially subsequent to the disappearance of the regulatory constraints during the second decade of the 1980s. Nonetheless, a lack of research identified with respect to mainstream paths given by strategic groups, and the analysis of the total factor productivity. Therefore, on the basis of the resource-based view of the firm and cluster analysis, we make use of changes in structure and performance ratios in order to identify the strategic groups extant in the sector. We attain a threeways division, which we link with different input-output specifications defining strategic paths. Consequently, on the basis of these three dissimilar approaches we compute and decompose a Hicks-Moorsteen total factor productivity index. Obtained results put forward an interesting interpretation under a multi-strategic approach, together with the setbacks of employing cluster analysis within a complex strategic environment. Moreover, we also propose an ex-post method of analysing the outcomes of the decomposed total factor productivity index that could be merged with non-traditional techniques of forming strategic groups, such as cognitive approaches.

Explaining High Economic Growth in Small Tourism Countries with a Dynamic General Equilibrium Model

This paper shows that tourism specialisation can help to explain the observed high growth rates of small countries. For this purpose, two models of growth and trade are constructed to represent the trade relations between two countries. One of the countries is large, rich, has an own source of sustained growth and produces a tradable capital good. The other is a small poor economy, which does not have an own engine of growth and produces tradable tourism services. The poor country exports tourism services to and imports capital goods from the rich economy. In one model tourism is a luxury good, while in the other the expenditure elasticity of tourism imports is unitary. Two main results are obtained. In the long run, the tourism country overcomes decreasing returns and permanently grows because its terms of trade continuously improve. Since the tourism sector is relatively less productive than the capital good sector, tourism services become relatively scarcer and hence more expensive than the capital good. Moreover, along the transition the growth rate of the tourism economy holds well above the one of the rich country for a long time. The growth rate differential between countries is particularly high when tourism is a luxury good. In this case, there is a faster increase in the tourism demand. As a result, investment of the small economy is boosted and its terms of trade highly improve.

¿Es el sexo femenino un factor de riesgo quirúrgico en la cirugía de valvular?

RESULTADOS: Se intervino un 60,7% de los pacientes de SV aórtica, un 25,7% de SV mitral , un 13,6% de doble SV. Además, en el 22,5% se realizó revascularización coronaria. Las mujeres presentaban más edad, SV mitral, reintervención, fibrilación auricular, anemia y peor clase funcional. Los varones presentaron más tabaquismo, SV aórtica, enfermedad coronaria, cirugía de revascularización coronaria, función sistólica deprimida y tiempo de clampaje aórtico. En el análisis bivariado relacionado con mortalidad hospitalaria (8,35%) fueron significativos la edad, el sexo, la clase funcional, la posición de la prótesis, la superficie corporal, la anemia, el número de concentrados de hematíes y el tiempo de clampaje aórtico. Se constató como factores de riesgo independientes el sexo (OR 2,92; 95% intervalo confianza 1,05-8,14) y la anemia (OR 4,23; 95% intervalo confianza 1,66-10,8) tras ajustarlos con los factores de riesgo, factores confusores y el año de intervención. CONCLUSIONES: El sexo femenino es un factor de riesgo independiente para la mortalidad hospitalaria en la cirugía de sustitución valvular.

Correcting Measurement Error Bias in Interaction Models with Small Samples

Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression