Download By Amit Bhaduri

Chandan Mukherjee, Howard White and Marc Wuyts, Econometrics and Data Analysis for
Developing Countries. Priorities for Development Economics Series. London: Routledge,
1998.xvii+485pp. 23.99 paperback.
This is an excellent textbook on the application of statistical methods to economic data
typically available in developing countries. It is ideally suited for students and researchers
with only a modest previous exposure to elementary statistical theory, who now wish to move
on to see its usefulness and limitations in actual application. The book retains throughout the
flavour of being written by experienced practitioners in quantitative development economics,
and technicalities are introduced mostly through well-chosen and interesting examples from
the developing countries of Asia and Africa (Latin American examples are conspicuous by
their absence). In this way, the authors are able to emphasize the messy character of
available data in most developing countries and demonstrate to the reader the importance of
careful exploratory dataalysis with a single variable (chapters 1-3). Many similar textbooks
devote far too little space to this topic, which is actually of great importance in conducting
applied research. The present reviewer would go so far as to say that if there are `stylized
facts’ worth theorizing, they are mostly arrived at through this route. Thhe discussion on
statistical versus substantive significance (pp.70-1) might have gained if the authors had
referred to a few `stulized facts’ from the classic works of Kuznets. Colin Clark etc., as
illustrating substantive rather than statiscally significant propositions
Parts II and III of the book (chapers 4-9) deal essentially with simple and multiple regression
analysis using cross section data. Although the material dealt with here is fairly standard, it is
developed in an easy and readable way. I found the discussion on partial regression plot and
the `sweeping out’ technique (pp. 164-73) particularly valuable for explaining the transition
from simple to multiple regression. This kind of background analysis is especially important
these days, when mindless `data mining’ and running of multiple regression have become far
too easy with standard computer packages.
In a similar vein , the chapter on
heteroscedasticity (chapter 7) emphasizes the importance of using visual diagnostic tools, for
example, plots of various measures of residuals against the predicted values of the
dependent variable or against various regressors, apart from carrying out the standard formal
tests of heteroscedasticity. In two useful chapters (8 and 9) that follow, the authors explain to
the reader the various links among dummies, chi-square and logit analysis to test hypotheses
regarding associations among qualitative or `categorical’ variables. In the reviewer’s view
omissions of related probit model (cumulative normal function), and Spearman’s rank
correlation are not justified in this context. The latter could be used to analyse the usefulness
of the components of indices like human development or the `degree of openness’ of a policy
regime.
The final parts IV and V of the book (Chapters 10-14) deal with time series analysis and
simultaneous equation models. They introduce the reader in a readily accessible manner to
the more recent techniques of analysis of stationary, cointegration and error correction
models. The discussion enables more experienced researchers familiar with older techniques
used for similar purposes (for example, analysis `trend’ and `seasonality’), to easily identify
the advantages of these recent advances in the analysis of `casuality` and `exogeneity’ in
time series data, currently so fashionable in macroeconomic analyses. Nevertheless, the
present reviewer had the impression that these topics are dealt with somewhat more hurriedly
than the rest of the book. For instance, instead of the usual demand supply model the
example of the controversial monetarist link between the rate of inflation and money supply
(pp. 338-48) could have been discussed, perhaps more instructively and imaginatively in a
simultaneous system to illustrate the identification problem that arises from trying to estimate
structural parameters from reduced form parameters by including, for example, government
budget deficit as a shift parameter in money supply. This type of example might have
illustrated more clearly the link between model specification in econometric testing and some
ongoing controversies in economic theory.
For a book of this size with many formulae, printing errors are infrequent, but not entirely
absent (for example, equation 9.2, pp,304; 406; 423; 443). The authors could have been
more reader-friendly by providing a list of the abbreviations used so extensively throughout
this book. However, these minor criticisms should not obscure the fact that this is an
exceptionally well-written and well-produced book.mmIt deserves to be widely read and the
diskette provided can be used simultaneously for practice with the computer. This book sets
a very high standard and raises our expectations of the series, `Priorities in Development
Economics’ in which it appears.
Amit Baduri
Centre for Economic Studies and Planning, School of Social Sciences, Jawaharlal Nehru
Univerisity, New Campus, New Delhi 110 067, India.