does not seem to be related to offshoring, shows no one is infallible in economic analysis. If Krugman, a leading trade theorist,makes such a mistake, everyone ought to exercise modesty and caution. Modesty does come through Blinder's arguments, but heseems quite convinced that offshoring will rock the U.S. economy as well as the rest of the English-speaking advanced economies.

Blinder, Freeman, and Kletzer look at the American jobs offshored so far and worry about the increasing vulnerability of U.S.workforce. The arguments that Bhagwati, Irwin, and Lawrence put forward are grounded more solidly in theory, history, andevidence. For example, implicit in Blinder's argument, Irwin notes, is the assumption that our demand for services is sufficient foroffshoring. But the supply of services is equally important. Irwin argues that since in the in-sourcing countries the labor supplycurve slopes upward, offshoring has its own limits. This is evident from the double digit wage increases in India in recent years.What is also ignored in the concern over offshoring is in-sourcing into the U.S. On September 25, 2007 theNew York Times reportedthat “Wipro and other Indian firms are outsourcing some work to…Idaho and Georgia, because it is cheaper to do it there” (p. 77).Irwin points out that wemust be wary of the dire predictions about American jobs given the fact that economists have a checkeredrecord of predicting economic events.

Although at this writing (March 2011) the anxiety over offshoring of American jobs seems to have moderately subsided,because of the stubbornly high unemployment rate in the U.S., quite likely offshoring will return as a major economic issue. Thatshould be reason enough for every student and scholar in economics to read this highly informative and provocative slim book(only 120 pages of narratives).

Farhad RassekhUniversity of Hartford

E-mail address: Rassekh@hartford.edu.

References

Bhagwati, Jagdish, Panagariya, Ravind, & Srinivasan, T. N. (2004). The Muddle over Outsourcing. The Journal of Economic Perspectives, 18(4), 93−114.Blinder, Alan S. (2006). Offshoring: The Next Industrial Revolution?”. Foreign Affairs, 85(2), 113−128.Leamer, Edward (2007). A Flat World, A Level Playing Field, a Small World After All, or None of the Above? Journal of Economic Literature XLV, March, 83—126.Mankiw, N. Gregory, & Philip, Swagel (2005). The Politics and Economics of Offshoring. American Enterprise Institute for Public Research, AEI Working Paper # 122.

doi:10.1016/j.iref.2011.03.002

Modeling ordered choices: A primer, William H. Greene, David A. Hensher, Cambridge University Press (2010)

This new book provides a thorough treatment of ordered choice models and related models. It is a valuable addition to theliterature because — in contrast to most textbooks that briefly discuss these commonly used models — the discussion here hasextraordinary breadth and depth. This book will help any advanced student or researcher interested in understanding thetheoretical motivation for ordered choice models, their relation to other models, the history of their development, and recentadvances.

Ordered choice models are used when the dependent variable is discrete and ordered. For example, consider the choice ofhealth status among excellent, good, fair, and poor. In this case the four possible health states are clearly ordered. However, becauseit is not easy to assign cardinal values to the health states, ordinary least squares is not appropriate. Ordered choice models areused in many disciplines, including economics, political science, sociology, and biostatistics. Ordered choice models are naturalgeneralizations of logit and probit models. They are also closely related to multinomial (unordered) models. As with most areas ofeconometrics, over the years there have been advances in understanding how to estimate and interpret ordered choice modelswith individual heterogeneity, using panel data, andwith endogenous covariates. Greene and Hensher provide a lucid explanationof all these important topics.

The book begins with a long chapter on modeling binary choices. The book is worth getting for this chapter alone. The chapterhas a comprehensive treatment of logit and probit models. Greene and Hensher start from a random utility motivation for thesebinary choice models, then proceed to estimation and inference. The discussion of partial effects shows clearly how the method ofcomputing marginal effects matters greatly in nonlinear models. The average of the marginal effects generally differs from themarginal effect computed at the average values, for example. There is an extensive explanation of measures of goodness of fit.Although I generally ignoremeasures of goodness of fit in practice because there is nothing as intuitive or useful as R-squared fromlinear regression, this book has the most comprehensive discussion of measures of fit for logit and probit that I have seen. Thechapter concludes with extensions for panel data, heterogeneity, the tricky issue of endogeneity of a right-hand side variable, andbivariate models.

An unanticipated chapter for such a modern technical text is “Antecedents and contemporary counterparts”. The authorsprovide a comprehensive review of articles as far back as the 1930s and 1940s, as well as over the last 50 years. This chapter servesseveral purposes. It provides a history of scientific discovery for a set of statistical models. I was interested to learn, for example,

850 Book Reviews

that the name “probit”was suggested as an abbreviation of “probability unit” by Chester Bliss in a 1934 Science article. The chapteralso carefully documents how the research questions and motivation for binary and ordered choice models changed over timefrom grouped to individual data, and how computational methods evolved from looking up numbers in normal tables to moderncomputational methods.

Although I am not a Bayesian statistician, I appreciate that the authors explain how to estimate binary and ordered choicemodels not only with maximum likelihood, but also with the EM algorithm and Bayesian (Markov Chain Monte Carlo) methods.Their explanation of Bayesian methods is clear and easy to compare with other methods.

Of all the limited dependent variable models, ordered choice models are probably most natural to graph. The ordering ofoutcomes on a single scale makes it easy to show interpretation graphically as well as in equations. The graphs in chapter 5(“Estimation, inference and analysis using the ordered choice model”) are especially nice. The authors graph results from a modelthat predicts self-reported health satisfaction. The graph nicely demonstrates how the threshold values (μ in this book) divide theassumed distribution of the error into different areas that correspond to probabilities of having each of the five health satisfactionscores. The reader can also see how changes in covariates shift the dividing lines, like the first-down markers at a football gamemarching up and down the field with the offense, but always 10 yards apart.

Each chapter has one or more empirical examples using real data. The examples are helpful in illustrating how to interpretthe models. I do find the tables a little difficult to read because they often have too many digits reported for the estimatedcoefficients and standard errors given the precision of the estimates. It would also be helpful if the data sets were easilyavailable for readers to download. Most of the data sets are available fromGreene's web site for another text (http://pages.stern.nyu.edu/~wgreene/Text/econometricanalysis.htm), although this was not mentioned in the book. Unlike books by Stata Press,this book does not attempt to be a how-to cookbook for estimation using a specific software package. Thus the book remainsgeneral and useful to all.

I do not have space to describe the rest of the contributions of the book in detail. Part of the motivation for writing the bookwas to develop a generalized model that is internally consistent, has random parameters, heterogeneous thresholds, andheteroskedasticity. The authors describe such amodel in Section 8.3. They also present extensions of the basic ordered choicemodelto deal with panel data, multiple simultaneous equations, and for two-part and selection models. The book is therefore up-to-datewith current developments.

In summary, this book is a terrific resource. I like the balance between intuition and equations and between historicaldevelopments and cutting edge material. This will be the definitive text on ordered choice models for years to come.

Edward C. NortonUniversity of Michigan, United States

E-mail address: ecnorton@umich.edu.

doi:10.1016/j.iref.2011.03.003

851Book Reviews