- Econometrician, specialized in time series analysis.edit
Los examenes y pruebas de evaluacion tienen un papel destacado dentro de los materiales docentes. Ello es asi debido al doble papel que juegan: por una parte, son cruciales para evaluar el nivel de conocimientos adquiridos por los... more
Los examenes y pruebas de evaluacion tienen un papel destacado dentro de los materiales docentes. Ello es asi debido al doble papel que juegan: por una parte, son cruciales para evaluar el nivel de conocimientos adquiridos por los estudiantes; pero tambien orientan al estudiante sobre como preparar las asignaturas. Por tanto los examenes son una herramienta fundamental en la docencia. Teniendo en mente esta consideracion, el objetivo de este proyecto era doble: (a) obtener un analisis objetivo y cualificado de los examenes y metodos de evaluacion utilizados, asi como (b) recoger sugerencias que permitan mejorar los procesos de evaluacion de las asignaturas consideradas.
Research Interests:
Research Interests:
Durante el período de entreguerras, en el que la inestabilidad económica constituyó una de las principales preocupaciones de las sociedades occidentales, se llevaron a cabo importantes investigaciones sobre la historia de los precios.... more
Durante el período de entreguerras, en el que la inestabilidad económica constituyó una de las principales preocupaciones de las sociedades occidentales, se llevaron a cabo importantes investigaciones sobre la historia de los precios. Gracias a los trabajos de Hamilton (1934 y 1947), el caso español no quedó al margen de ese impulso historiográfico. Posteriormente, los precios serían objeto de una atención preferente en Las crisis agrarias en la España moderna de Gonzalo Anes (1970). Este libro tuvo una gran influencia en las numerosas investigaciones de los setenta y ochenta sobre el sector agrario en la España del Antiguo Régimen. Sin embargo, en casi todos estos trabajos primó el interés por desvelar la evolución económica en el largo plazo, lo que indujo a fijarse primordialmente en la población, la producción agraria y la renta de la tierra, relegando a los precios a un papel secundario.
Research Interests:
En este trabajo se describe un proyecto piloto para desarrollar e implantar sistemas de evaluacion y auto-evaluacion a distancia. Para ello se han desarrollado prototipos basados en tres conceptos distintos: campus virtual (Moodle),... more
En este trabajo se describe un proyecto piloto para desarrollar e implantar sistemas de evaluacion y auto-evaluacion a distancia. Para ello se han desarrollado prototipos basados en tres conceptos distintos: campus virtual (Moodle), sistemas de encuesta online (Lime Survey) y documentos inteligentes (AcroTex). Estos prototipos se probaron mediante actividades de evaluacion (examenes) y auto-evaluacion (trabajo practico en un aula de informatica o en el domicilio) con alumnos reales. A partir de esta experiencia, hemos llegado a un conjunto de conclusiones y recomendaciones para su implantacion.
Research Interests:
The likelihood of multivariate GARCH models is ill-conditioned because of two faets. First, financial time series afien display high correlations, implying that an eigenvalue afthe conditional covariances fluctuates near the zero... more
The likelihood of multivariate GARCH models is ill-conditioned because of two faets. First, financial time series afien display high correlations, implying that an eigenvalue afthe conditional covariances fluctuates near the zero boundary. Secand, GARCH models explain conditional covariances in tenns of a linear combination of delayed squared errors and theu conditional expectation; this functional fonu implies that the likelihood function is almost flat in the neighborhood of the optimal estimates. Building on this analysis we propase a linear transformation of data which, not only stabilizes the likelihood computation, but also provides insight about the statistical properties of data. The use of this transfonnation is illustrated by modeling the short-nm conditional correlations of four nominal exchange rates, RESUMEN La verosimilitud de procesos GARCH multivariantes está mal condicionada por dos causas. En primer lugar, las series fmancieras a menudo están fuertemente correJadas...
Oil price showed sharp fluctuations in recent years which revived the interest in its effect on inflation. In this paper, we discuss the relationship between oil price and inflation in Spain, at national and regional levels, and making... more
Oil price showed sharp fluctuations in recent years which revived the interest in its effect on inflation. In this paper, we discuss the relationship between oil price and inflation in Spain, at national and regional levels, and making the distinction between energy and non-energy inflation. To this end, we fit econometric models to measure the effect of oil price shocks on inflation and to predict them under different scenarios. Our results show that almost half of the volatility of changes in total inflation is explained by changes in oil price. As could be expected, the energy component of inflation drives this effect. We also find that, under the most likely scenarios, 1-year ahead total inflation will be moderate, with relevant differences across regions.
Research Interests:
Research Interests:
Research Interests:
In this paper we propose a new method to specify linear models for vectors of time series with some convenient properties: First, it provides a unique modeling approach for single and multiple time series, as the same decisions are... more
In this paper we propose a new method to specify linear models for vectors of time series with some convenient properties: First, it provides a unique modeling approach for single and multiple time series, as the same decisions are required in both cases. Second, it is scalable, meaning that it provides quickly a possibly crude but statistically adequate model, which can be refined in further modeling phases if required. Third, it is optionally automatic, meaning that the specification depends on a few key parameters that can be determined either automatically or by human decision. And last it is parsimonious, as it allows one to impose a canonical structure, which can be further simplified through exclusion constraints. Several examples with simulated and real data illustrate the practical application of this procedure and a MATLAB implementation is freely distributed through the Internet.
Research Interests:
Research Interests:
We compare the results obtained by applying the same signal-extraction procedures to two observationally equivalent state-space forms. The first model has different errors affecting the states and the observations, while the second has a... more
We compare the results obtained by applying the same signal-extraction procedures to two observationally equivalent state-space forms. The first model has different errors affecting the states and the observations, while the second has a single perturbation term which coincides with the one-step-ahead forecast error. The signals extracted from both forms are very similar but their variances are drastically different, because the states for the single-source error representation collapse to exact values while those coming from the multiple-error model remain uncertain. The implications of this result are discussed both with theoretical arguments and practical examples. We find that single error representations have advantages to compute the likelihood or to adjust for seasonality, while multiple error models are better suited to extract a trend indicator. Building on this analysis, it is natural to adopt a ‘best of both worlds’ approach, which applies each representation to the task in which it has comparative advantage.
Research Interests:
Research Interests:
We propose a fast and consistent procedure to detect unit roots based on subspace methods. It has three distinctive features. First, the same method can be applied to single or multiple time series. Second, it employs a flexible family of... more
We propose a fast and consistent procedure to detect unit roots based on subspace methods. It has three distinctive features. First, the same method can be applied to single or multiple time series. Second, it employs a flexible family of information criteria, which loss functions can be adapted to the statistical properties of the data. Last, it does not require specifying a model for the analyzed series. Besides, we provide a subspace-based consistent estimator for the cointegrating rank and the cointegrating matrix. Simulation exercises show that these procedures have good finite sample properties.
Research Interests:
Introduction Linear state-space models The multiple error model Single error models Model transformations Model decomposition Model combination Change of variables in the output Uses of these transformations Filtering and smoothing The... more
Introduction Linear state-space models The multiple error model Single error models Model transformations Model decomposition Model combination Change of variables in the output Uses of these transformations Filtering and smoothing The conditional moments of a state-space model The Kalman filter Decomposition of the smoothed moments Smoothing for a general state-space model Smoothing for fixed-coefficients and single-error models Uncertainty of the smoothed estimates in a fixed-coefficients SEM Examples Likelihood computation for fixed-coefficients models Maximum likelihood estimation The likelihood for a non-stationary model The likelihood for a model with inputs Examples The likelihood of models with varying parameters Regression with time-varying parameters Periodic models The likelihood of models with GARCH errors Examples Subspace methods Theoretical foundations System order estimation Constrained estimation Multiplicative seasonal models Examples Signal extraction Input and er...
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
This paper calculates indices of central bank autonomy (CBA) for 163 central banks as of end-2003, and comparable indices for a subgroup of 68 central banks as of the end of the 1980s. The results confirm strong improvements in both... more
This paper calculates indices of central bank autonomy (CBA) for 163 central banks as of end-2003, and comparable indices for a subgroup of 68 central banks as of the end of the 1980s. The results confirm strong improvements in both economic and political CBA over the past couple of decades, although more progress is needed to boost political autonomy of the central banks in emerging market and developing countries. Our analysis confirms that greater CBA has on average helped to maintain low inflation levels. The paper identifies four broad principles of CBA that have been shared by the majority of countries. Significant differences exist in the area of banking supervision where many central banks have retained a key role. Finally, we discuss the sequencing of reforms to separate the conduct of monetary and fiscal policies. IMF Staff Papers (2009) 56, 263–296. doi:10.1057/imfsp.2008.25; published online 23 September 2008
We propose a new procedure to detect unit roots based on subspace me- thods. It has three main original aspects. First, the same method can be applied to single or multiple time series. Second, it uses a flexible family of information... more
We propose a new procedure to detect unit roots based on subspace me- thods. It has three main original aspects. First, the same method can be applied to single or multiple time series. Second, it uses a flexible family of information criteria, which loss functions can be adapted to the statistical properties of the data. Last, it does not require the specification of a sto- chastic process for the series analyzed. This procedure is consistent and a simulation exercise shows that it has good finite sample properties. Its ap- plication is illustrated with the analysis of several real time series.
Research Interests:
Research Interests:
We propose a new procedure to detect unit roots based on subspace me- thods. It has three main original aspects. First, the same method can be applied to single or multiple time series. Second, it uses a flexible family of information... more
We propose a new procedure to detect unit roots based on subspace me- thods. It has three main original aspects. First, the same method can be applied to single or multiple time series. Second, it uses a flexible family of information criteria, which loss functions can be adapted to the statistical properties of the data. Last, it does not require the specification of a sto- chastic process for the series analyzed. This procedure is consistent and a simulation exercise shows that it has good finite sample properties. Its ap- plication is illustrated with the analysis of several real time series.
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
We propose a new procedure to detect unit roots based on subspace methods. It has three main original features. First, the same method can be applied to single or multiple time series. Second, it employs a flexible family of information... more
We propose a new procedure to detect unit roots based on subspace methods. It has three main original features. First, the same method can be applied to single or multiple time series. Second, it employs a flexible family of information criteria, which loss functions can be adapted to the statistical properties of the data. Last, it does not require the specification of a stochastic process for the series analyzed. Also, we provide a consistent estimator of the cointegrating rank and the cointegrating matrix. Simulation exercises show that the procedure has good finite sample properties. An example illustrates its application to real time series.
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
We propose a simple and structured procedure for decomposing a vector of time series into trend, cycle, seasonal and irregular components. Contrary to common practice, we do not assume these components to be orthogonal conditional on... more
We propose a simple and structured procedure for decomposing a vector of time series into trend, cycle, seasonal and irregular components. Contrary to common practice, we do not assume these components to be orthogonal conditional on their past. However, the state-space representation employed assures that their estimates converge to values with null variances and covariances. Null variances are very important,