Statistical Foundations of Econometric Modelling.

Foreword David Hendry Preface Acknowledgements Part I. Introduction: 1. Econometric modelling, a preliminary view 2. Descriptive study of data Part II. Probability Theory: 3. Probability 4. Random variables and probability distributions 5. Random vectors and their distributions 6. Functions of random variables 7. The general notion of expectation 8. Stochastic processes 9. Limit theorems 10. Introduction to asymptotic theory Part III. Statistical Inferences: 11. The nature of statistical inference 12. Estimation I - properties of estimators 13. Estimation II - methods 14. Hypothesis testing and confidence regions 15. The multivariate normal distribution 16. Asymptotic test procedures Part IV. The Linear Regression and Related Statistical Models: 17. Statistical models in econometrics 18. The Gauss linear model 19. The linear regression model I - specification, estimation and testing 20. the linear regression model II - departures from the assumptions underlying the statistical GM 21. The linear regression model III- departures from the assumptions underlying the probability model 22. The linear regression model IV - departures from the sampling model assumption 23. The dynamic linear regression model 24. The multivariate linear regression model 25. The simultaneous equations model 26. Epilogue: towards a methodology of econometric modelling References Index.

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