A prototypical seasonal adjustment model

Se presenta un analisis detallado del problema de modelizar y estimar los componentes no-observables en el modelo ARIMA mas simple que presenta tendencia, estacionalidad y variaciones irregulares. En el analisis se ilustra la relacion entre los metodos de descomposicion basados en la forma reducida y los basados en la forma estructural, se examinan las propiedades de los estimadores de los componentes con error cuadratico medio minimo y, finalmente, se derivan los errores implicitos en la estimacion preliminar y final

Numerical simulation of a binary communication channel: Comparison between a replica calculation and an exact solution

The mutual information of a single-layer perceptron with $N$ Gaussian inputs and $P$ deterministic binary outputs is studied by numerical simulations. The relevant parameters of the problem are the ratio between the number of output and input units, $\alpha = P/N$, and those describing the two-point correlations between inputs. The main motivation of this work refers to the comparison between the replica computation of the mutual information and an analytical solution valid up to $\alpha \sim O(1)$. The most relevant results are: (1) the simulation supports the validity of the analytical prediction, and (2) it also verifies a previously proposed conjecture that the replica solution interpolates well between large and small values of $\alpha$.Comment: 6 pages, 8 figures, LaTeX fil

The transmission of data noise into policy noise in monetary control

Se analiza el efecto de los errores en las series de oferta monetaria sobre la politica monetaria (estos errores estan dominados por las revisiones en los factores estacionales). Se demuestra como la extraccion de ruido en la serie preliminar, mas una politica de compensacion de los shocks inesperados de oferta y de acomodacion de los shocks inesperados de demanda, implica que los errores en los datos, aunque importantes, tengan un efecto muy reducido sobre la politica a corto plazo. Se presenta algunos resultados teoricos sobre modelos econometricos con errores en las variables

Constructing seasonally adjusted data with time-varying confidence intervals

Seasonal adjustment methods transform observed time series data into estimated data, where these estimated data are constructed such that they show no or almost no seasonal variation. An advantage of model-based methods is that these can provide confidence intervals around the seasonally adjusted data. One particularly useful time series model for seasonal adjustment is the basic structural time series [BSM] model. The usual premise of the BSM is that the variance of each of the components is constant. In this paper we address the possibility that the variance of the trend component in a macro-economic time series in some way depends on the business cycle. One reason for doing so is that one can expect that there is more uncertainty in recession periods. We extend the BSM by allowing for a business-cycle dependent variance in the level equation. Next we show how this affects the confidence intervals of seasonally adjusted data. We apply our extended BSM to monthly US unemployment and we show that the estimated confidence intervals for seasonally adjusted unemployment change with past changes in the oil price

Neural Decision Boundaries for Maximal Information Transmission

We consider here how to separate multidimensional signals into two categories, such that the binary decision transmits the maximum possible information transmitted about those signals. Our motivation comes from the nervous system, where neurons process multidimensional signals into a binary sequence of responses (spikes). In a small noise limit, we derive a general equation for the decision boundary that locally relates its curvature to the probability distribution of inputs. We show that for Gaussian inputs the optimal boundaries are planar, but for non-Gaussian inputs the curvature is nonzero. As an example, we consider exponentially distributed inputs, which are known to approximate a variety of signals from natural environment.Comment: 5 pages, 3 figure

Recensiones [Revista de Historia Económica Año III Invierno 1985 n. 1 pp. 157-191]

Antonio Domínguez Ortiz. Política fiscal y cambio social en la España del siglo (Por Juan Zafra Oteyza). -- Guillermo Céspedes del Castillo. América Hispánica (1492-1898) (Por Zacarías Moutoukias). -- Carmelo Mesa Lago. La economía en Cuba socialista. Una evaluación de dos décadas (Por Juan Carlos Jiménez). -- Louis Henry. Manual de demografía histórica (Por David-Sven Reher). -- Ezequiel Gallo. La Pampa Gringa (Por Carlos Rodríguez Braun). -- Javier García Fernández. El origen del Municipio Constitucional: Autonomía y Centralización en Francia y España (Por Concepción de Castro). -- David E. Vassberg. La venta de tierras baldías. El comunitarismo agrario y la Corona de Castilla durante el siglo XVI (Por Bartolomé Yun Casalilla). -- José Manuel Mutiloa. Guipúzcoa en el siglo XIX (Por Luis Castells). -- Diego Azqueta Oyarzun. Teoría económica de la acumulación socialista (Por Alfons Barceló). -- T. H. Hollingsworth. Demografía histórica (Por Francisco Bustelo). -- Ricardo Calle Sáiz. La Hacienda en la II República española (Por Juan Hernández Andréu). -- Jordi Nadal ; Carles Sudriá. Historia de la Caja de Pensiones (La «Caixa» dentro del sistema financiero catalán) (Por Rafael Castejón). -- Daniel Peña ; Nicolás Sánchez-Albornoz. Dependencia dinámica entre precios agrícolas: El trigo en España, 1857-1890. Un estudio empírico (Por Agustín Maravall).Publicad

A Dynamic Model of Interactions of Ca^(2+), Calmodulin, and Catalytic Subunits of Ca^(2+)/Calmodulin-Dependent Protein Kinase II

During the acquisition of memories, influx of Ca^(2+) into the postsynaptic spine through the pores of activated N-methyl-D-aspartate-type glutamate receptors triggers processes that change the strength of excitatory synapses. The pattern of Ca^(2+) influx during the first few seconds of activity is interpreted within the Ca^(2+)-dependent signaling network such that synaptic strength is eventually either potentiated or depressed. Many of the critical signaling enzymes that control synaptic plasticity, including Ca^(2+)/calmodulin-dependent protein kinase II (CaMKII), are regulated by calmodulin, a small protein that can bind up to 4 Ca^(2+) ions. As a first step toward clarifying how the Ca^(2+)-signaling network decides between potentiation or depression, we have created a kinetic model of the interactions of Ca^(2+), calmodulin, and CaMKII that represents our best understanding of the dynamics of these interactions under conditions that resemble those in a postsynaptic spine. We constrained parameters of the model from data in the literature, or from our own measurements, and then predicted time courses of activation and autophosphorylation of CaMKII under a variety of conditions. Simulations showed that species of calmodulin with fewer than four bound Ca^(2+) play a significant role in activation of CaMKII in the physiological regime, supporting the notion that processing ofCa^(2+) signals in a spine involves competition among target enzymes for binding to unsaturated species of CaM in an environment in which the concentration of Ca^(2+) is fluctuating rapidly. Indeed, we showed that dependence of activation on the frequency of Ca^(2+) transients arises from the kinetics of interaction of fluctuating Ca^(2+) with calmodulin/CaMKII complexes. We used parameter sensitivity analysis to identify which parameters will be most beneficial to measure more carefully to improve the accuracy of predictions. This model provides a quantitative base from which to build more complex dynamic models of postsynaptic signal transduction during learning