Productive behavior through the life course: An essay on the quality of life

Present patterns of productive activity are neither well recognized, optimal for society, nor in accordance with individual prefence. Although a great deal of attention has been given to meeting people's needs for income, medical care, and other services, the quality of their lives must also be defined by what they do for themselves and for others. In discovering present patterns of productive activity throughout the life course and optimizing those patterns, we will raise the quality of American life. To accomplish this task, two great changes are needed: we must recognize the full range of productive activities throughout the life course and give people the opportunity to modify the allocation of paid employment.     

Regression using mixed annual and quarterly data

By consideration of either Generalised Least-Squares of Theil-Goldberger estimates of equations for which data on the dependent variable is available for a subset of the sample period on only an annual basis, it is shown that best estimates of the equation coefficients may be obtained by Ordinary Least-Squares estimation over the complete set of quarterly observations with quarterly averages substituted for the missing quarterly data, and symmetrically for the corresponding observations on the regressor variables. The approach is extended to the Two-Stage Least-Squares case, and to the (structurally or stochastically) autoregressive case.     

Forecasting first births

This study is concerned with one aspect of the family cycle, namely, the transition from young married to young married with small children. The focus is on developing models to forecast entries into this latter stage for the purpose of marketing research. "Using ordinary least squares, forecasting models were estimated for (1) total number of first births, (2) number of white first births, and (3) number of nonwhite first births." Models are estimated for both the United States and California using data from official sources.     

Method in Experiment: Rhetoric and Reality

The methodological ideal of experimentalists, E, is easily stated: derive a testable hypothesis, H, from a well-specified theory, T; implement experiments with a design; implicitly in the latter are auxiliary hypotheses, A, that surface in the review/discussion of completed research reports (payoffs are 'adequate,' Ss are 'relevant,' instructions, context are 'clear,' etc.). We want to be able to conclude, if statistical test outcomes support not-H, that T is 'falsified.' But this is not what we do; rather we ask if there is a flaw in the test, i.e. not-A is supported, and we do more experiments. This is good practice—much better than the statistical rhetoric of falsificationism. Undesigned social processes allow E to accumulate technical and instrumental knowledge that drive the reduction of experimental error and constitute a more coherent methodology than falsificationism.