Incluye referencias bibliográficas (páginas 437-448) e índice.

Chapter 1: A history of the idea of unobserved components in the analysis of economic time series: 1. Introduction ; 2. Background ; 3. Origins ; 4. Nineteenth century contributors ; 5. Recent developments ; 6. Application to seasonal adjustment and “current analysis” ; 7. Application to the historical analysis of business cycles -- Chapter II: Introduction to the theory of stationary time series: 1. Introduction ; 2. What is stationary time series? Ergodicity ; 3. The world decomposition theorem -- Chapter III. The spectral representation and its estimation: 1. Introduction ; 2. Covariance generating functions ; 3. The spectral representation of a stationary time series ; 4. The cross-spectral distribution functions of two jointly stationary time series and filtering ; 5. Estimation of the autocovariance function and the spectral density function -- Chapter IV. Formulation and analysis of unobserved-components models: 1. Introduction ; 2. Unobserved-components models and their canonical forms ; 3. Digression on a general methods for the determination of the autocovariance or a mixed moving-average autoregressive process -- Chapter V. Elements of the theory of prediction and extraction: 1. Introduction ; 2. Prediction ; 3. Examples of the application of minimum mean square error forecasts ; 4. Signal extraction ; 5. Examples of minimum mean square error signal extraction -- Chapter VI. Formulation of unobserved-components models and canonical forms: 1. Introduction ; 2. Determining the form of a univariate time-series ARMA model ; 3. Determining the form of a univariate time-series unobserved-components model ; 4. The analysis of a time series by more than its own past -- Chapter VII. Estimation of unobserved-components and canonical model: 1. Introduction ; 2. ARMA model estimation in the time domain ; 3. UC model estimation in the frequency domain ; 4. ARMA model estimation in the frequency domain ; 5. Unobserved-components model estimation in the frequency domain ; 6. Hypothesis testing ; 7. Estimation of multiple time-series models -- Chapter VIII. Appraisal of seasonal adjustment techniques: 1. Criteria for “optimal” seasonal adjustment ; 2. Choice of models ; 3. Some results ; 4. Seasonal adjustment and t he estimation of structural models ; 5. Conclusion -- Chapter IX. On the comparative structure of serial dependence in some U.S. price series: 1. Introduction ; 2. Brief characterization of selected nonindustrial price series of the bureau of labor statistics ; 3. Buyer’s prices and seller’s prices: the national bureau of economic research series and the Stigler-Kindahl study ; 4. Conclusions -- Chapter X. Formulation and estimation of mixed moving-average autoregressive models for single time series: examples: 1. Introduction ; 2. The formulation procedure of box and jenkis ; 3. An alternative method for the formulation of an ARIMA model ; 4. The detailed examples ; 5. Comparison between estimation methods in the frequency and time domains -- Chapter XI. Formulation and estimation of multivariate mixed moving-average autoregressive time-series models: 1. Introduction ; 2. A single-equation approach ; 3. A simultaneous-equations approach ; 4. Estimation of multiple time-series models for interrelated agricultural prices -- Chapter XII. Formulation and estimation of unobserved-components models: examples: 1. Introduction ; 2. Formulation of the models: trend reduction ; 3. Estimation of the models in time and frequency domains ; 4. Predictive properties of unobserved-components models -- Chapter XIII. Application to the formulation of distributed-lag models: 1. Introduction ; 2. Prediction and expectation-formation models ; 3. Signal extraction ; 4. Distributed lags in dynamic models ; 5. Estimation -- Chapter XIV. A time-series model of the U.S. cattle industry: 1. Introduction ; 2. The cattle industry ; 3. Tettleman behavior: a simple example ; 4. Cattleman behavior: a quarterly model ; 5. Test of the model with quasi-rational expectations -- Appendix A. The work of buys ballot -- Appendix B. Some requisite theory of functions of a complex variable: 1. Complex numbers ; 2. Simple functions of a complex variable ; 3. Limits, continuity, derivatives, singularities, and rational functions ; 4. Complex integration: Cauchy’s theorem ; 5. Series expansions: Taylor’s series: Laurent’s series ; 6. The reside theorem and its application -- Appendix C. Fourier series and analysis: 1. Introduction ; 2. Periodic functions and trigonometric series of a periodic functions ; 3. Orthogonal systems of functions ; 4. Questions of convergence and goodness of approximation ; 5. Fourier transforms and “Windows” -- Appendix D. Whittle’s theorem -- Appendix E. Inversion of tridiagonal matrices and method for inverting Toeplitz matrices -- Appendix F. Spectral densities, actual and theoretical, eight series -- Appendix G. Derivation of a distributed-lag relation between sales and production: a simple example.