The latter have no responsibility for the veritable industry that has sprung to life as diskettes spread through the world data that had been put together by patient marriages of snippets of data with uncertain guesses. Cross-country regression results must be viewed critically. As Syrquin notes (1 :7:ZZO), they are reduced-form estimates of far more complicated models and do not provide reliable evidence on causality. Two approaches have been used, which are both dubious. Quick and dirty single regressions have been widely used, but their results are subject to overwhelming "missing variables" biases; complex specifications would be more trustworthy but they are sensitive to the choice of proxies and dummies that take account of hard-to-measure effects. Such regressions may point to interesting mechanisms but to produce reliable conclusions, they should be complemented by deeper study at the country level and validated by a credible theory.

It is crucial to be aware of the extremely poor quality of much of this data. Angus Deaton's chapter 33, which draws on a survey edited by Srinivasan20, discusses evidence on this score. Summers and Hestorn themselves assign a score of D+ to D to data for 66 out of 138 countries (Srinivasan 3:2493). Given the tendency of newspapermen to view development as a GNP race, it is good that the _Handbook_ calls attention the large influence on growth rates on the quite arbitrary estimates of official statisticians on the size and growth rates of the informal sector, and about the lack of reliability of data for the African countries, which account for so 21 many of the data points in cross-country regressions. John Strauss and Duncan Thomas make a similar point in chapter 34.

# 7.3) Survey-Based Studies Data and the New Micro Econometrics

The doubts that are warranted with respect to the macroeconomic data lend importance to the information provided by sample surveys. Here development economists owe a debt to the initiatives of the great Indian statistical school, to which we also owe important theoretical insights. Both Deaton and Strauss and Thomas discuss the figures collected by such surveys as the very early Additional Rural Incomes Surveys, as well as the intensive ICRISAT surveys of the International Crops Institute for Semi Arid Tropics, carried out by investigators who live in the sample villages, and of the very useful data generated by the World Bank's Living Standards surveys, which cover for an increasing number of countries a broad array of variables in addition to the standard budget data. The _Handbook_ authors stress that there is no reason to question the quality of the sample data, whose accuracy matches that for developed countries. Such surveys are still few in number unfortunately, and have all too often been stopped after a few years; expansion of this work is desirable.

This development has been complemented by significant progress in "micro econometric" methods which both Deaton's and Strauss and Thomas's chapters describe. New statistical techniques have evolved, and valuable experience has accumulated about how to control selection and other types of bias. Thanks to this work we are now much better informed about such important topics as the impacts of education on productivity, and of investment in hospital facilities on health.

- 20 Srinivasan (1994); on the China/India growth race; see Timberg (1997), which comments on a volume comparing the two countries, edited by Srinivasan (1993).

- 21 The recent Boskin report (1996), co-authored by economists with a high reputation, which suggests that US national accounts data has underestimated by 1.3 percent the rate of growth of consumption, shows that GDP growth rates are subject to doubt even in countries whose statistical system is highly developed.

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