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To study the degree to which depression indicators based on register data on hospital and antidepressant treatment suffer from differential misclassification with respect to gender, age and social group.Data on 7378 persons were obtained by linking a cross-sectional survey of Danish adults aged 40 and 50 years with population-based registers. Misclassification was analysed by comparing survey data to register data on major depression using the method proposed by Rothman and Greenland.Differential misclassification was found. Adjustment for misclassification reduced women's odds ratios from 2.18 to 1.00 for hospital treatment and from 1.70 to 1.10 for antidepressants. For the lower social group, the corresponding odds ratios increased from 1.18 to 3.52, and from 1.35 to 2.32 respectively, whereas odds ratios with respect to age remained almost unchanged.Differential misclassification should be considered when register-based information about hospital and antidepressant treatment are used as depression indicators.

We employ a regression-discontinuity design to identify effects on educational attainment after compulsory school of class size and the number of pupils per weekly teacher hour using administrative rules as instruments. We use Danish administrative panel data. Average class size is 20, about the same as in the US and most European countries. Restricting the sample to observations close to the enrolment discontinuity points where the administrative rules have greatest predictive power, instrumental variables estimates are consistently negative. Estimates from the preferred specification are marginally significant and indicate modest effects in line with earlier studies. Estimates for subgroups are less precise, but they indicate larger effects for pupils from less advantaged backgrounds.

This paper considers several tests of orthogonality conditions in linear models where stochastic errors may be heteroskedastic or autocorrelated. It is shown that these tests can be performed with Wald statistics obtained from simple auxiliary regressions. Copyright 1997 by Blackwell Publishing Ltd