Incluye referencias bibliográficas (páginas 257-269) e índice.

Introduction: 1 Review of the general linear model: 1.1 Economic and statistical models ; 1.2 Time series and stochastic processes ; 1.3 Properties of stochastic processes ; 1.4 Properties of estimators ; 1.5 The general linear model ; 1.6 Departures from the classical assumptions ; 1.7 Conclusion ; Notes -- 2 Maximum likelihood estimations: 2.1 The conceptual approach ; 2.2 Non-linear optimization procedures ; 2.3 Special forms of likelihood functions ; 2.4 Empirical applications using maximum likelihood ; 2.5 Summary -- 3 Time series modelling: 3.1 Autoregressive time series models ; 3.2 Moving average time series models ; 3.3 ARMA and ARRIMA process ; 3.4 Wold’s decomposition ; 3.5 Autocovariance and autocorrelation functions ; 3.6 The correlogram ; 3.7 The partial autocorrelation function ; 3.8 Common factors ; 3.9 Model selection: the Box-Jenkins approach ; 3.10 Model identification ; 3.11 Estimation ; 3.12 Conclusion -- 4 Dynamic-modelling – the general to specific methodology: 4.1 The conceptual approach ; 4.2 Testing the dynamic model ; 4.3 An application to the demand for M2 in three European countries ; 4.4 Conclusion ; Notes -- 5 Non-stationary and cointegration: 5.1 Stationary ; 5.2 Unit roots and orders of integration ; 5.3 Cointegration ; 5.4 The Granger representation theorem ; 5.5 Estimating the cointegrating vector ; 5.6 Testing for cointegration and drawing inference ; 5.7 Inference on parameter values ; 5.8 Exogeneity and cointegration ; 5.9 Three-step estimation ; 5.10 Long-run purchasing power parity in the 1920s ; 5.11 A maximum likelihood approach to cointegration ; 5.12 Testing linear restrictions on the cointegrating parameters ; 5.13 Example: The demand for broad money during the gold standard ; 5.14 Summary ; Appendix: The Johansen procedure -- 6 Rational expectations: 6.1 The economics of expectations models and the RE hypothesis ; 6.2 The EVM and extrapolative predictors ; 6.3 Serially correlated errors and expectations variables ; 6.4 Empirical work on expectations models ; 6.5 Rational expectations: cross-equation restrictions ; 6.6 Sumary -- 7 State –space models and the kalman filter: 7.1 Expectations and learning and the state-space form ; 7.2 The econometrics of the kalman filter ; 7.3 Maximum likelihood and the kalman filter ; 7.4 Applied work using the kalman filetr ; 7.5 Summary ; Notes ; Appendix -- 8 Using large non-linear models: 8.1 Model solution procedures ; 8.2 Types of deterministic model solution ; 8.3 Rational expectations and non-linear models ; 8.4 The analysis of stochastic models ; 8.5 Optimal control of non-linear models ; 8.6 Summary.