4 Dynamics and Interdependence

4.1 Nonsense regressions
4.2 Analysing nonsense regressions
4.3 Spurious detrending
4.4 First-order autoregressive dynamics
4.5 Reduction and dynamics
4.6 Interdependence
4.7 Cointegration
4.8 Bivariate dynamics
4.9 A solved example
4.10 Exercises

5 Exogeneity and Causality

5.1 What are 'exogenous variables'?
5.2 Two counter-examples
5.3 Weak exogeneity
5.4 A cobweb model
5.5 The counter-examples reconsidered
5.6 An ambiguity in strict exogeneity
5.7 Can the model mis-specification be detected?
5.8 Strong exogeneity
5.9 Super exogeneity
5.10 An illustration of super exogeneity
5.11 Causality
5.12 Two solved examples
5.13 Weak exogeneity and unit roots*
5.14 Exercises

6 Interpreting Linear Models

6.1 Four interpretations of Yt = β' Zt + Et
6.2 Expectations formation
6.3 Autocorrelation corrections
6.4 A simple dynamic model: AD(1,1)
6.5 Lags and their measurement
6.6 A Monte Carlo study of the AD(1,1) model
6.7 An empirical illustration
6.8 A solved example
6.9 Exercises

7 A Typology of Linear Dynamic Equations

7.1 Introduction
7.2 Static regression
7.3 Autoregression
7.4 Differenced-data model
7.5 Leading indicator
7.6 Partial adjustment
7.7 Common factor
7.8 Finite distributed lags
7.9 Dead-start models
7.10 Equilibrium correction
7.11 Solved examples
7.12 Summary and conclusion
7.13 Exercises

8 Dynamic Systems

8.1 Introduction
8.2 Statistical formulation
8.3 Theoretical formulation
8.4 Closed linear systems
8.5 Open linear systems
8.6 Modelling dynamic systems
8.7 A typology of open linear dynamic systems
8.8 Models of linear systems
8.9 Analysing dynamic systems
8.10 Exercises

9 The Theory of Reduction

9.1 Introduction
9.2 Data transformations and aggregation
9.3 Parameters of interest
9.4 Data partition
9.5 Marginalization
9.6 Sequential factorization
9.7 Mapping to 1(0)
9.8 Conditional factorization
9.9 Constancy
9.10 Lag truncation
9.11 Functionalform
9.12 The derived model
9.13 Econometric concepts as measures of no information loss
9.14 Implicit model design
9.15 Explicit model design
9.16 A taxonomy of evaluation information
9.17 Exercises

II Statistical Tools for Econometric Analysis

10 Likelihood

10.1 Review of Part I
10.2 The statistical model
10.3 Estimation criteria and estimation methods
10.4 The likelihood function
10.5 Maximum likelihood estimation
10.6 Properties of the score
10.7 Properties of maximum likelihood estimators
10.8 Large-sample properties of MLEs
10.9 Two solved examples
10.10 Misleading inference
10.11 Derived distributions
10.12 Asymptotic equivalence
10.13 Concentrated likelihood functions
10.14 Marginal and conditional distributions
10.15 Estimator generating equations
10.16 An EGE for common-factor dynamics
10.17 Exercises

11 Simultaneous Equations Systems

11.1 Introduction
11.2 The statistical system
11.3 System dynamic specification
11.4 System estimation
11.5 System cointegration estimation
11.6 System evaluation
11.7 Empirical cointegration illustration
11.8 The econometric model
11.9 Identification
11.10 An EGE for simultaneous equations estimation
11.11 A solved example
11.12 Simultaneous equations modelling
11.13 Derived statistics
11.14 Empirical model estimates
11.15 Exercises

12 Measurement Problems in Econometrics

12.1 Introduction
12.2 Errors in variables
12.3 Dynamic latent-variables models
12.4 Revisions to I(1) data
12.5 The impact of measurement errors on ECMs
12.6 Exercises

13 Testing and Evaluation

13.1 The statistical framework
13.2 Non-central X2 distributions
13.3 Large-sample properties of tests
13.4 Understanding the non-central X2 distribution
13.5 Test power
13.6 Likelihood-ratio, Wald, and Lagrange-multiplier tests
13.7 Comparing the tests
13.8 A solved example
13.9 Non-linear restrictions
13.10 Some methodological considerations
13.11 Exercises

III Empirical Modelling

14 Encompassing

14.1 Introduction
14.2 Augmenting the conventional testing strategy
14.3 Encompassing and mis-specification analysis
14.4 Formalizing encompassing
14.5 Levels of analysis
14.6 Parsimonious encompassing
14.7 A simple example
14.8 Nesting and encompassing
14.9 Encompassing in linear regression
14.10 Encompassing in stationary stochastic processes
14.11 A solved example
14.12 An empirical illustration
14.13 Encompassing the VAR
14.14 Testing the Lucas critique
14.15 The applicability of the critique
14.16 Tests for super exogeneity
14.17 Encompassing implications of feedback versus feedforward models
14.18 Empirical testing of invariance
14.19 Exercises

15 Modelling Issues

15.1 Data mining
15.2 Theory dependence versus sample dependence
15.3 Progressive research strategies
15.4 Pyrrho's lemma
15.5 Dummy variables
15.6 Seasonal adjustment
15.7 Approximating moving-average processes
15.8 A solved example: modelling second moments
15.9 Populations and samples
15.10 Exercises

16 Econometrics in Action

16.1 The transactions demand for money
16.2 Economic theories of money demand
16.3 Econometric formulation
16.4 Financial innovation
16.5 Data description
16.6 A small monetary system
16.7 Cointegration analysis
16.8 Modelling the 1(0) PVAR
16.9 Evaluating the model
16.10 A single-equation money-demand model
16.11 Transformation and reduction
16.12 Post-modelling evaluation
16.13 Testing the Lucas critique
16.14 Post-sample evaluation
16.15 Policy implications
16.16 Data definitions

IV Appendices

A1 Matrix Algebra
A2 Probability and Distributions
A3 Statistical Theory
A4 Asymptotic Distribution Theory
A5 Numerical Optimization Methods
A6 Macro-Econometric Models

References
Common Acronyms Glossary
Author Index
Subject Index