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

Epidemic models with an infected-infectious period

The introduction of an infective-infectious period on the geographic spread of epidemics is considered in two different models. The classical evolution equations arising in the literature are generalized and the existence of epidemic wave fronts is revised. The asymptotic speed is obtained and improves previous results for the Black Death plague

Probabilistic maximal covering location-allocation models with constrained waiting time or queue length for congested systems

When dealing with the design of service networks, such as healthand EMS services, banking or distributed ticket selling services, thelocation of service centers has a strong influence on the congestion ateach of them, and consequently, on the quality of service. In this paper,several models are presented to consider service congestion. The firstmodel addresses the issue of the location of the least number of single--servercenters such that all the population is served within a standard distance,and nobody stands in line for a time longer than a given time--limit, or withmore than a predetermined number of other clients. We then formulateseveral maximal coverage models, with one or more servers per service center.A new heuristic is developed to solve the models and tested in a 30--nodesnetwork.

On the short-time behavior of the implied volatility for jump-diffusion models with stochastic volatility

In this paper we use Malliavin calculus techniques to obtain an expression for the short-time behavior of the at-the-money implied volatility skew for a generalization of the Bates model, where the volatility does not need to be neither a difussion, nor a Markov process as the examples in section 7 show. This expression depends on the derivative of the volatility in the sense of Malliavin calculus.

Dynamic compact thermal models with multiple power sources: application to an ultrathin chip stacking technology

Whereas numerical modeling using finite-element methods (FEM) can provide transient temperature distribution in the component with enough accuracy, it is of the most importance the development of compact dynamic thermal models that can be used for electrothermal simulation. While in most cases single power sources are considered, here we focus on the simultaneous presence of multiple sources. The thermal model will be in the form of a thermal impedance matrix containing the thermal impedance transfer functions between two arbitrary ports. Eachindividual transfer function element ( ) is obtained from the analysis of the thermal temperature transient at node ¿ ¿ after a power step at node ¿ .¿ Different options for multiexponential transient analysis are detailed and compared. Among the options explored, small thermal models can be obtained by constrained nonlinear least squares (NLSQ) methods if the order is selected properly using validation signals. The methods are applied to the extraction of dynamic compact thermal models for a new ultrathin chip stack technology (UTCS).

Slow Dynamics of Ising Models with Energy Barriers

Using Monte Carlo simulations we study the dynamics of three-dimensional Ising models with nearest-, next-nearest-, and four-spin (plaquette) interactions. During coarsening, such models develop growing energy barriers, which leads to very slow dynamics at low temperature. As already reported, the model with only the plaquette interaction exhibits some of the features characteristic of ordinary glasses: strong metastability of the supercooled liquid, a weak increase of the characteristic length under cooling, stretched-exponential relaxation, and aging. The addition of two-spin interactions, in general, destroys such behavior: the liquid phase loses metastability and the slow-dynamics regime terminates well below the melting transition, which is presumably related with a certain corner-rounding transition. However, for a particular choice of interaction constants, when the ground state is strongly degenerate, our simulations suggest that the slow-dynamics regime extends up to the melting transition. The analysis of these models leads us to the conjecture that in the four-spin Ising model domain walls lose their tension at the glassy transition and that they are basically tensionless in the glassy phase.

Exactly solvable phase oscillator models with syncrhonization dynamics

Populations of phase oscillators interacting globally through a general coupling function f(x) have been considered. We analyze the conditions required to ensure the existence of a Lyapunov functional giving close expressions for it in terms of a generating function. We have also proposed a family of exactly solvable models with singular couplings showing that it is possible to map the synchronization phenomenon into other physical problems. In particular, the stationary solutions of the least singular coupling considered, f(x) = sgn(x), have been found analytically in terms of elliptic functions. This last case is one of the few nontrivial models for synchronization dynamics which can be analytically solved.

Growth Models with Exogenous Saving Rates, Unemployment and Wage Inertia

[cat] El propòsit d'aquest article és introduir una mercat de treball no competitiu i atur en el model de creixement amb taxes d'estalvi exògenes que es pot trobar en els llibres de text de creixement (Sala‐i‐Martín, 2000; Barro and Sala‐i‐Martín, 2003; Romer, 2006). Primer, derivem un marc general amb una funció de producció neoclàssica per analitzar la relació entre creixement i ocupació. Utilitzem aquest marc per estudiar les dinàmiques conjuntes del creixement i l'ocupació sota diferents regles de fixació salarial.

Growth Models with Exogenous Saving Rates, Unemployment and Wage Inertia

[cat] El propòsit d'aquest article és introduir una mercat de treball no competitiu i atur en el model de creixement amb taxes d'estalvi exògenes que es pot trobar en els llibres de text de creixement (Sala‐i‐Martín, 2000; Barro and Sala‐i‐Martín, 2003; Romer, 2006). Primer, derivem un marc general amb una funció de producció neoclàssica per analitzar la relació entre creixement i ocupació. Utilitzem aquest marc per estudiar les dinàmiques conjuntes del creixement i l'ocupació sota diferents regles de fixació salarial.

Quantum chaos in SU(3) models with trapped ions

A scheme to generate long-range spin-spin interactions between three-level ions in a chain is presented, providing a feasible experimental route to the rich physics of well-known SU(3) models. In particular, we demonstrate different signatures of quantum chaos which can be controlled and observed in experiments with trapped ions.

Stock market volatility and learning

Introducing bounded rationality in a standard consumption-based asset pricing model with time separable preferences strongly improves empirical performance. Learning causes momentum and mean reversion of returns and thereby excess volatility, persistence of price-dividend ratios, long-horizon return predictability and a risk premium, as in the habit model of Campbell and Cochrane (1999), but for lower risk aversion. This is obtained, even though our learning scheme introduces just one free parameter and we only consider learning schemes that imply small deviations from full rationality. The findings are robust to the learning rule used and other model features. What is key is that agents forecast future stock prices using past information on prices.

Una comparación de la selección de los ratios contables en los modelos contable-financieros de predicción de la insolvencia empresarial : la literatura previa frente al analisis factorial

En los últimos 30 años la proliferación de modelos cuantitativos de predicción de la insolvencia empresarial en la literatura contable y financiera ha despertado un gran interés entre los especialistas e investigadores de lamateria. Lo que en un principio fueron unos modelos elaborados con un único objetivo, han derivado en una fuente de investigación constante.En este documento se formula un modelo de predicción de la insolvencia a través de la combinación de diferentes variables cuantitativas extraídas de los estados contables de una muestra de empresas para los años 1994-1997. A través de un procedimiento por etapas se selecciona e interpreta cuáles son las más relevantes en cuanto a aportación de información.Una vez formulado este primer tipo de modelos se busca una alternativa a las variables anteriores a través de la técnica factorial del análisis de componentes principales. Con ella se hace una selección de variables y se aplica, junto conlos ratios anteriores, el análisis univariante. Por último, se comparan los modelos obtenidos y se concluye que aunque la literatura previa ofrece mejores porcentajes de clasificación, los modelos obtenidos a través del análisis decomponentes principales no deben ser rechazados por la claridad en la explicación de las causas que conducen a una empresa a la insolvencia.

Una comparación de la selección de los ratios contables en los modelos contable-financieros de predicción de la insolvencia empresarial : la literatura previa frente al analisis factorial

En los últimos 30 años la proliferación de modelos cuantitativos de predicción de la insolvencia empresarial en la literatura contable y financiera ha despertado un gran interés entre los especialistas e investigadores de lamateria. Lo que en un principio fueron unos modelos elaborados con un único objetivo, han derivado en una fuente de investigación constante.En este documento se formula un modelo de predicción de la insolvencia a través de la combinación de diferentes variables cuantitativas extraídas de los estados contables de una muestra de empresas para los años 1994-1997. A través de un procedimiento por etapas se selecciona e interpreta cuáles son las más relevantes en cuanto a aportación de información.Una vez formulado este primer tipo de modelos se busca una alternativa a las variables anteriores a través de la técnica factorial del análisis de componentes principales. Con ella se hace una selección de variables y se aplica, junto conlos ratios anteriores, el análisis univariante. Por último, se comparan los modelos obtenidos y se concluye que aunque la literatura previa ofrece mejores porcentajes de clasificación, los modelos obtenidos a través del análisis decomponentes principales no deben ser rechazados por la claridad en la explicación de las causas que conducen a una empresa a la insolvencia.