Cities in the 21st century

Cities in the 21st century

124 Book reviews estimated from outside sample forecast errors. For correctly specified models the expected value of the difference of these is zer...

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124

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reviews

estimated from outside sample forecast errors. For correctly specified models the expected value of the difference of these is zero, and so this may be used as a basis for tests of the presence of misspecification. In practice the procedure is expensive, since it requires successive re-estimation and stochastic simulation of a model. As in other chapters, the procedures are extensively illustrated using the alternative econometric models described earlier. In the main, these illustrations are most useful in establishing the techniques, since the results do not have obvious implications for sources of misspecification in the models. This is a pity, though perhaps not surprising since the procedures for analysing complete models in this way are still relatively new. On the whole though, the exercises appear to confirm the superiority of the Fair US model over the alternative models. Stochastic simulations again figure heavily in the evaluation of dynamic properties of models, which provides calculations of the standard errors of model simulations. Evaluating the uncertainty of the dynamic properties of estimated models in this way is a welcome feature of this book. This is particularly so when it is appreciated that policy simulations have been increasingly used in public controversies, especially over the use of fiscal policy, most often without any appraisal of the uncertainty surrounding these simulation properties. Indeed, Professor Fair’s high standards here contrast with one rather depressing trend in the UK, which is the use of simulation results to buttress policy analysis, using models where substantial parts have not been estimated at all but have been imposed. It would be interesting to speculate on what the statistical properties of these latter dynamic analyses are! Professor Fair, somewhat characteristically, concludes by noting that he is unwilling to draw strong implications from his work, his motto being one of ‘wait and see’. That one of our most able modellers adopts such a degree of circumspection is a timely warning to those who would draw powerful policy conclusions from econometric models. But as guides to quantitative assessment of economic policy, econometric models are one of the better - albeit highly imperfect - vehicles which are available to us. Improvements in the performance of these models comes slowly, but one reason there is progress at all is the existence of academics like Fair who are willing to establish just what the limits of quantitative analysis using macroeconometric models are. His exacting procedures set a standard that other model users would do well to emulate. S.G.B. Henry National Institute of Economic and Social Research, London, U.K.

Gary Gappert and Richard V. Knight, Cities in the 21st Century (Urban Affairs Annual Reviews, vol. 23) (Sage, Beverley Hills, CA and London, 1982) $28.00/&19.50 (hard)/&9.75 (paper), pp. 320. Rarely, after some quarter-century in the academic reviewing trade, an old hand has to admit defeat. This is one such time. Certain categories of book are intrinsically unreviewable. One such is almost all symposia. Another is almost all books on the future. This one happens to be both. Strictly, it consists of nineteen essays by academics and related persons at a variety of American institutions, chiefly one called the Institute for Futures Studies and Research at the University of Akron (whence hail the editors). Most are about the future, but many are about the present and one or two about the recent past. The last-named are the most heavily empirical, in that they do refer to demonstrable social or economic trends that can be backed up by hard information: Harold Rose on black ghettos and Sally Engle Merry on urban danger are examples. Most of the remaining essays are short on fact and very long on speculation. They are also very long on words, especially buzz words with lots of syllables: synergistic,

Book

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125

androgynous, post-affluent, multidimensional nature of the self all appear in the first twenty pages, with lots more to come. It’s the kind of stuff that’s OK in a lecture - the opening contribution carries a footnote that it is available as a forty-minute slide presentation - but it doesn’t wear well in a less ephemeral medium. Taken as a group, the papers appear to have been written in a hurry and forgotten soon afterwards. This impression is only fortified by the almost unbelievable sloppiness with which the symposium appears to have been launched into print. No reviewer expects perfection (save of the King James Bible), but there are limits to indulgence. Not only do the references contain scores of mis-citations (Schumpter for Schumpeter, Gershung for Gershuny, K. Appleyard and D. Lynch for D. Appleyard and K. Lynch, S. Perloff for Harvey Perloff, to mention a few); the text actually manages to n&-spell leading American cities (Houstin for Houston, Tuscan for Tucson), and at one sublime point to get the title of a paper wrong. Add to this a contributors’ list that is out of alphabetical order (evidently they transposed two pages of text) and the impression of a publishing Fuwlty Towers is well-nigh complete. If the 21st Century is going to look like this, better take some Band Aids. Peter Hall University of Reading, U.K. University of California, Berkeley, CA

David A. Ratkowsky, Nonlinear Regression Modelling: York, 1983) $39.00, pp. 276. This book provides an excellent practical introduction estimating nonlinear regression models of the form yr=f(xrp

A Unified Practical Approach (Dekker, New

to the Ratkowsky method for identifying

and

x,2,. . . ?X,kr PI? I-%, . . . qJ+%

where the e, are independently normally distributed with zero means and common variance u2. The practitioner should be able to use the Fortran program in the appendix to reproduce the results of the worked examples in chapters 3, 4 and 5 before applying the technique to problems of his own choosing. I have certain reservations about the theoretical properties of this technique, but welcome it. in the spirit in which it is offered, as a valuable addition to the practitioner’s toolkit. R.W. Farebrother University of Manchester, U.K.

Peter Whittle, Prediction and Regulation by Linear Least-square Methods (Blackwell, Oxford, 1983) second revised ed., E17.50, pp. XV + 187. Peter Whittle’s neat little book on the theory of time series prediction and control by least squares methods has been regarded as a classic in its field, and rightly so, ever since it was first published 22 years ago. However it has long been out of print and it is particularly welcome (especially for those of us of a younger generation) to find it available again. Part of the book’s attraction is undoubtedly the elegance, lucidity and conciseness of the presentation. Part of the attraction is also the breadth of the