PLENTIFUL reasons exist for seeking information on the determinants of child health. While the potential improvement in children's health provides sufficient justification in itself, research in human capital investment has demonstrated the further important influence of health, particularly child health, on cognitive development, schooling, hours of work, and wages.' Poor child health is likely to detract from human capital accumulation during childhood years, and is frequently associated with poor adult health, both of which impair an individual's adult market performance. Further, child health status is a primary determinant of the demand for medical care for children, leading those economists estimating medical services demand to focus attention increasingly on the determinants of child health.2 The existing research in child health determination has highlighted some important family influences, but the results have been limited. The object of this study is to use sibling and adoption data to explore the effects of family background on child health. The results are compared to those of the usual multivariate regression analysis. Sibling and adoption data analysis involves many difficulties, but is potentially valuable for indicating which areas need further exploration if a more adequate understanding of child health is to be achieved. Sibling data were used in economics as early as 1932. The early studies, and more recent studies in the human capital literature, utilize sibling and twin data to partially control family effects on adult earnings, enabling the pure economic returns to education to be estimated.3 The focus of this study is on the identification of the variance in the child health measure which can be attributed to family influences, rather than on the magnitude of a particular regression coefficient. The use of adoption data may then yield insight into the relative importance of various components of the family effect. In section II, an economic model of the household production of child health is presented and the data set described. An error components model of child health using the natural siblings data is estimated in section III, and this estimate is compared to a multivariate regression. Section IV presents an examination of whether genetics is an important influence in child health determination and is followed by concluding comments in section V.

Beach, Charles M., and James G. MacKinnon, Maximum Likelihood Procedure for Regression with Autocorrelated Errors, Econometrica 46 (1978), 51-58. Box, G. E. P., and D. R. Cox, An Analysis of Transformations, Journal of the Royal Statistical Society 26, Series B (1964), 211-243. Hall, Bronwyn H., and Robert E. Hall, Time-Series Processor Version 3.5 User's Manual, mimeographed, Stanford, California, 1980. Savin, N. E., and K. J. White, Estimation and Testing for Functional Form and Autocorrelation: A Simultaneous Approach, Journal of Econometrics 8 (1978), 1-12. Spitzer, John J., Primer on Box-Cox Estimation, this REVIEW 64 (May 1982), 307-313. Zarembka, Paul, Transformation of Variables in Econometrics, in Paul Zarembka (ed.), Frontiers in Econ?ometric.s (New York: Academic Press, 1974).

A monopolist may earn greater profits by setting a nonuniform price schedule (one in which the price varies with the quantity purchased) than by charging a uniform price. In general, the profit maximizing non-uniform price schedule and the welfare maximizing schedule do not coincide. Thus, there may be scope for improving market performance through regulation. The paper considers a regulator who has limited information and authority. The issues addressed centre around the question of whether the level of total market output can be taken as a measure of market performance. Conditions under which welfare is a monotonic function of the level of total output are derived. 1.

Abstract ABSTRACT: Microcomputer spreadsheet programs can ease both preparation and grading of accounting examination questions whose solutions involve lengthy, sequential calculations.

Abstract Reviews the book "Accounting Information Systems: A Cycle Approach," by Leonard A. Robinson, James R. Davis, and C. Wayne Alderman.

Abstract Reviews the book "Corporate Reporting: Its Future Evolution," by Edward Stamp.

In the public sector, commodity bundling involves an agenda setter exercising control over a governmental unit's budgetary mix—the allocation of the unit's total budget to its various subactivities—in order to manipulate electoral outcomes on other fiscal variables such as the total budget. This paper develops an analytical model of a political market in which a multi-activity governmental unit practices commodity bundling in order to advance the interests of the setter. Two institutional structures are considered, each involving a different voting process or set of electoral constraints and, hence, a different form of commodity bundling. The paper explores the impact of this form of monopoly power on such policy outcomes as the governmental unit's total budget, its budgetary mix, and the distribution of net benefits from collective action.