Agustín Maravall
Biographic Data
| ID | 6288705 |
|---|---|
| NAME | Agustín Maravall |
| GIVEN NAMES | Agustín |
| FAMILY NAME | Maravall |
| SIGNATURE | MARAVALL A |
| AFFILIATIONS | Servicio de Estudios, Banco de España |
| VERIFIED | No |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 7 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1983 |
| LATEST PUBLICATION YEAR | 1998 |
| H-INDEX | 1 |
[New Capabilities and Methods of the X-12-Arima Seasonal-Adjustment Program]
Minimum Mean Squared Error Estimation of the Noise in Unobserved Component Models
In model-based estimation of unobserved components, the minimum mean squared error estimator of the noise component is different from white noise. In this article, some of the differences are analyzed. It is seen how the variance of the component is always underestimated, and the smaller the noise variance, the larger the underestimation. Estimators of small-variance noise components will also have large autocorrelations. Finally, in the context …
On Structural Time Series Models and the Characterization of Components
This article analyzes certain properties of a class of recently proposed structural time series models in which particular structures are imposed upon the unobserved components of an observed time series. It is shown how the overall model can be expected to fit series, such as those for which the X-11 or Airline models are appropriate. As for the components, identification of the model is achieved by assigning a certain amount of white noise vari…
Daniel Peña y Nicolás Sánchez-Albornoz
Daniel Peña y Nicolás Sánchez-Albornoz: Dependencia dinámica entre precios agrícolas: el trigo en España, 1857–1890. On estudio empírico, Madrid, Servicio de Estudios del Banco de España (Estudios de Historia Económica), 1983. - Volume 3 Issue 1
[Issues Involved with the Seasonal Adjustment of Economic Time Series]
Preliminary-Data Error and Monetary Aggregate Targeting
Preliminary monetary aggregate data are subject to subsequent revision because of errors from seasonal and nonseasonal sources that will only be known later. This article examines the characteristics of these revision errors and analyzes their possible effect on monetary policy. It is found that false signals, in the sense that the preliminary M1 growth rate falls within the tolerance band set monthly by the Federal Open Market Committee while th…
An Application of Nonlinear Time Series Forecasting
By means of a real application, it is seen how ARIMA forecasts can be improved when nonlinearities are present. The autocorrelation function (ACF) of the squared residuals provides a convenient tool to check the linearity assumption. Once nonlinearity has been detected, parsimonious bilinear processes seem rather adequate to model it. The detection of nonlinearity and the forecast improvement appear to be rather robust with respect to changes in …
Daniel Peña y Nicolás Sánchez-Albornoz
Daniel Peña y Nicolás Sánchez-Albornoz: Dependencia dinámica entre precios agrícolas: el trigo en España, 1857–1890. On estudio empírico, Madrid, Servicio de Estudios del Banco de España (Estudios de Historia Económica), 1983. - Volume 3 Issue 1
Preliminary-Data Error and Monetary Aggregate Targeting
Preliminary monetary aggregate data are subject to subsequent revision because of errors from seasonal and nonseasonal sources that will only be known later. This article examines the characteristics of these revision errors and analyzes their possible effect on monetary policy. It is found that false signals, in the sense that the preliminary M1 growth rate falls within the tolerance band set monthly by the Federal Open Market Committee while th…
An Application of Nonlinear Time Series Forecasting
By means of a real application, it is seen how ARIMA forecasts can be improved when nonlinearities are present. The autocorrelation function (ACF) of the squared residuals provides a convenient tool to check the linearity assumption. Once nonlinearity has been detected, parsimonious bilinear processes seem rather adequate to model it. The detection of nonlinearity and the forecast improvement appear to be rather robust with respect to changes in …
[Issues Involved with the Seasonal Adjustment of Economic Time Series]
On Structural Time Series Models and the Characterization of Components
This article analyzes certain properties of a class of recently proposed structural time series models in which particular structures are imposed upon the unobserved components of an observed time series. It is shown how the overall model can be expected to fit series, such as those for which the X-11 or Airline models are appropriate. As for the components, identification of the model is achieved by assigning a certain amount of white noise vari…
Daniel Peña y Nicolás Sánchez-Albornoz
Daniel Peña y Nicolás Sánchez-Albornoz: Dependencia dinámica entre precios agrícolas: el trigo en España, 1857–1890. On estudio empírico, Madrid, Servicio de Estudios del Banco de España (Estudios de Historia Económica), 1983. - Volume 3 Issue 1
Minimum Mean Squared Error Estimation of the Noise in Unobserved Component Models
In model-based estimation of unobserved components, the minimum mean squared error estimator of the noise component is different from white noise. In this article, some of the differences are analyzed. It is seen how the variance of the component is always underestimated, and the smaller the noise variance, the larger the underestimation. Estimators of small-variance noise components will also have large autocorrelations. Finally, in the context …
[New Capabilities and Methods of the X-12-Arima Seasonal-Adjustment Program]
Econometrics (6 works) · Mathematics (6 works) · Computer Science (5 works) · Statistics (5 works) · Economics (4 works) · Time series (4 works) · Seasonal adjustment (3 works) · Autocorrelation (2 works) · Autoregressive integrated moving average (2 works) · Fault Detection and Control Systems (2 works)