Prescribed conditional interaction structure models with application to the analysis of mobility tables

The present paper considers some new models for the analysis of multidimensional contigency tables. Although the theoretical background used here appeared already in Haberman (1974), prescribed conditional interaction (PCIN) models were introduced by Rudas (1987) and their mathematical properties were worked out by Leimer and Rudas (1988). These models are defined by prescribing the values of certain conditional interactions in the contingency table. Conditional interaction is defined here as the logarithm of an appropriately defined conditional odds ratio. This conditional odds ratio is a conditional version of a generalization of the well known odds ratio of a 2×2 table and that of the three factor interaction term of a 2×2×2 table and applies to any number of dimensions and any number of categories of the variables. The well known log-linear (LL) models are special PCIN models. Estimated frequencies under PCIN models and tests of fit can be computed using existing statistical software (e.g. BMDP). The paper describes the class of PCIN models and compares it to the class of association models of Goodman (1981). As LL models are widely used in the analysis of social mobility tables, application of more general PCIN models is illustrated.     

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.