Wojciech W. Charemza and Derek F. Deadman. New Directions in Econometric Practice, General to Specific Modelling, Cointegration and Vector Auto Regression.
Urooj, Amena
Wojciech W. Charemza and Derek F. Deadman. New Directions in
Econometric Practice, General to Specific Modelling, Cointegration and
Vector Auto Regression. Cheltenham, U.K.: Edward Elgar Publishing
Limited. 1997. Pages 360. 28.00 [pounds sterling] (Paperback).
Highly acclaimed and endorsed by leading econometricians, the book
"New Directions in Econometric Practice" is not new among the
econometrics and statisticians. It is more of a textbook for students of
econometrics and statistics at various levels. It impressively attempts
to address the main objective of explaining 'how to practice
econometrics'. It provides an accessible and user-friendly approach
to a new approach and methodology presented by David Hendry in his book,
'Dynamic Econometrics'. The book under review provides a
practical and hands-on illustration of Hendry's approach, enabling
students to use it for themselves in real world time-series econometric
problems. The second edition of the book attempts to address the
shortfalls identified by some reviewers in the first edition. By
providing practical guidelines in terms of empirical illustration of
each technique, using DHSY's suggested aggregated time series
consumption function on PC-Gives (8.1 Professional), it opens new trails
of research. The book is primarily designed for providing an intuitive
understanding of recent developments in econometrics to non-specialist
econometricians and is widely adopted by teachers, students and
practitioners alike.
The authors of the book articulate Hendry's framework, using
unconventional treatments of econometrics in resolving the key problem
of empirical econometrics, i.e. matching economic theory with observed
data features and developing empirically relevant models. Scrutinising
the properties of time series data, this book examines the procedures
and tools of contemporaneous econometrics and investigates systematic
application of econometric methods to economic data. The contents of the
book include a review of traditional methodology, data mining, origins
of modern methodology via DHSY consumption function, general to specific
modelling, cointegration analysis, vector auto regression, exogeneity
and non-nested models, encompassing, and model selection.
The first chapter gives introduction. The second chapter, which
deals with the issue of data mining, discusses the experimenter's
control over the tools of model selection criteria, namely t-ratios,
R-squared, adjusted R-squared, and other goodness of fit criteria. The
authors warn that the most commonly anticipated wish to use the fixed
data sample in some sequential way may lead to abuse the methodological
principles, especially if not applied carefully. The authors realise the
fact that some data mining is inevitable, besides they identify the
occurrence of Lovell Bias due to the difference between the true and the
nominal significance level leading to exaggerated claims of
significance.
Chapter 3 reconsiders the original DHSY analysis, with modified and
simplified explanations in light of the theory of consumption modelling,
aided with computer outputs. This is in recognition for the role this
article has played in development of new econometric approach and ideas.
The later chapters give a detailed and up-to-date account of these
recent developments. In line with Davidson, et al. (1978) approach to
empirical econometric modelling, Chapter 4 contains a detailed
discussion of general-to-specific modelling. The chapter gives the
mechanics of general-to-specific modeling by initialising general
Autoregressive Distributed Lag Model and gradually reducing it by
examining linear or nonlinear restrictions imposed on parameters. It
also describes a number of tools for examining these restrictions, for
example the Likelihood Ratio, Wald and Lagrange Multiplier tests.
It is noted that the general-to-specific modelling is a method of
discovery rather than of confirmation. Although using this technique one
may lead to multiple admissible models not nested in each other but the
alternative, i.e. the 'bottom up' approach has a major setback
in that extending the model may be based upon using erroneous
statistical procedures, which may lead, on that one hand, to a plethora
of models and excessive data mining, on the other.
The following chapters brilliantly present conceptually difficult
but significant ideas from advance econometrics. These ideas and
techniques are in focus of the recent advancements and development in
the field. Chapter 5 contains detailed discussion on cointegration. The
chapter starts with explaining the importance of distinguishing between
stochastic trends, with and without drift, and also between
deterministic and stochastic trends and seasonality, supplemented by
simulation results. It then presents a comprehensive debate on unit root
tests and determining the order of integration. Starting with the
Dickey-Fuller test, this discussion covers the detailed working of
Augmented Dickey Fuller and Integrated Durbin Watson tests. These are
aided with recomputed simulations for the Dickey Fuller statistics for
larger sample sizes and replications. Dickey Hasza Fuller, HEGY and
Dickey Pantula test for seasonal unit root are explained with newly
added tables. Special attention is given to Dickey Pantula approach and
the Perron's (1989) suggested 'additive outlier' test,
covering the treatment for unit root in the presence of structural
breaks. Later part of Chapter 5 contains a comprehensive discussion on
cointegration comprising of Engle-Granger type test, Cointegrated Durbin
Watson (CIDW) and its rule of thumb suggested by Banerjee (1986). Later
on, modelling of Cointegrated series through Error Correction Model is
explained. Finally, this all is supported by the empirical example of
DHSY model.
Chapter 6 studies the traditional and modern approaches for dealing
with the relationships described by the system of more than one
equation. Under modern approach Vector Autoregressive models (VAR) are
presented. VARs are considered as forecasting device for studying
causality and cointegration. Within the VAR framework, Johansen's
approach and Granger's representation for cointegration are
explained. It also contains the impulse response analysis of VARs models
and its illustrations. Identifying the problems of VAR models in real
world situation, especially when one wishes to handle more than four
variables, Chapter 7 sheds light on exogeneity modelling. Concepts of
weak exogeneity and strong exogeneity are thoroughly discussed, along
with the mathematical descriptions. This chapter also investigates
exogeneity properties and invariance properties for the variables in
DHSY model.
Problems in choosing between models and the concept of encompassing
are the focus of Chapter 8. Cases of nested and non-nested models are
identified in relation to encompassing. 'Encompassing' holds
when one econometric model can explain the behaviour of relevant
characteristics of other models. However, the term 'relevant
characteristics' in not possible to be identified in absolute
terms, making encompassing a bit complicated and requiring model
selection tests. [[bar.R].sup.2], Akaike Information Criteria, Schwarz
Bayesian Criteria and Final Prediction Error are discussed as model
selection criteria. However, these criteria do not aid in deciding which
model is better. In addition, J test is discussed for variance
encompassing of non-nested models.
Along with worked examples the book contains a large number of
working exercises, helping novices in aided learning. The clarity of
presenting intuitive accounts of modern advances of econometrics has led
this book to be widely adopted in courses of applied econometrics at
various levels, which it rightly deserves.
Amena Urooj
Pakistan Institute of Development Economics,
Islamabad.
REFERENCES
Davidson, J. E., D. F. Hendry, F. Srba, and S. Yeo (1978)
Econometric Modelling of the Aggregate Time-series Relationship Between
Consumers' Expenditure and Income in the United Kingdom. The
Economic Journal, 661-692.
Perron, P. (1989) The Great Crash, the Oil Price Shock, and the
Unit Root Hypothesis. Econometrica 99, 1361-1401.