This paper considers the formulation and estimation of simultaneous equation models with both discrete and continuous endogenous variables.The statistical model proposed here is sufficiently rich to encompass the álassjcai simultaneous equation model for continuous endogenous variables and more recent models for purely discrete endogenous variables as special cases of a more general model.Interest in discrete data has been ftsledby a rapid growth in the availability of microeconomic data sets coupled with a growing awareness of the importance of discrete choice models for the analysis of uiicroeconomic problems (see McFadden, 1976).To date, the only available statistical models for the analysis of discrete endogenous variables have been developed for the purely discrete case.The log-linear or logistic model of Goodman (1970) as expanded by Raberman (1974) and Nerlove and Press (1976) is one Vol.II, 1967; Lord and Novick, cbs.16-20, 1967.)It is argued in this paper that this class of statistical models provides a natural framework for generating simultaneous equation models with both discrete and continuous random variables.In contrast, the framework of Goodman, while convenient for formulating descriptive models for discrete data, offers a much less natural apparatus for analyzing econometric structural equation models.This is so primarily because the simultaneous equation model is inherently an unconditional representation of behavioral equations while the model of Goodman is designed to facilitate the analysis of conditional representations, and does not lend itself to the unconditional formulations required in simultaneous equation theory.The structure of this paper is in four parts.in part one general models are discussed.Dummy endogenous variables are introduced in two distinct roles: (1) as proxies for unobserved latent variables and (2) as direct shifters of behavioral equations.Five models incorporating such dummy variables are discussed.Part two, also the longest section, presents a complete analysis of the most novel and most general of the five models presented in part one.This is a model with both continuous and discrete endogenous variables.The issues of identification and estimation are discussed together by proving the existence of consistent estimators.Maximum likelihood estimators and alternative estimators are discussed.In part three, a brief discussion of a multivariate probit model with structural shift is presented.Part four presents a comparison between the models developed in this paper and the models of Goodman and Nerlove and Press.

This paper discusses how randomized social experiments operate as an instrumental variable. For two types of randomization schemes, the fundamental experimental estimation equations are derived from the principle that experiments equate bias in control and experimental samples. Using conventional econometric representations, we derive the orthogonality conditions for the fundamental estimation equations. Randomization is a multiple instrumental variable in the sense that one randomization defines the parameter of interest expressed as a function of multiple endogenous variables in the conventional usage of that term. It orthogonalizes the treatment variable simultaneously with respect to the other regressors in the model and the disturbance term for the conditional population. However, conventional `structural' parameters are not in general identified by the two types of randomization schemes widely used in practice.

In this paper, we discuss statistical problems that arise in studying sequences of quantal responses (e.g., labor force participation) in panel data on heterogeneous populations (i.e., populations in which there is unobserved variation in response probabilities). Assuming that response probabilities are governed by a beta distribution, we derive a generalization on of the cross-section logit model to enable it to deal with sequences of discrete events in panel data. This model is applied to panel data on labor force participation of married women. One of our findings is that the distribution of participation probabilities is U shaped, indicating that most women have participation probabilities near zero or near one.

This paper examines the relationship between placement of publications in top five (T5) journals and receipt of tenure in academic economics departments. Analyzing the job histories of tenure–track economists hired by the top 35 US economics departments, we find that T5 publications have a powerful influence on tenure decisions and rates of transition to tenure. A survey of the perceptions of young economists supports the formal statistical analysis. Pursuit of T5 publications has become the obsession of the next generation of economists. However, the T5 screen is far from reliable. A substantial share of influential publications appear in non-T5 outlets. Reliance on the T5 to screen talent incentivizes careerism over creativity.

Using three sources of data, this article examines the direct economic return to General Educational Development (GED) certification for both native and immigrant high school dropouts. One data source—the Current Population Survey (CPS)—is plagued by nonresponse and allocation bias from the hot deck procedure that biases the estimated return to the GED upward. Correcting for allocation bias and ability bias, there is no direct economic return to GED certification. An apparent return to GED certification with age found in the raw CPS data is due to dropouts becoming more skilled over time. These results apply to both native‐born and immigrant populations.

This article decomposes the participation process of a prototypical program into eligibility, awareness, application, acceptance, and enrollment. With this decomposition, we determine the sources of unequal participation for different groups and demonstrate that variables often have very different effects at different stages in the participation process. Our analysis shows that personal choices substantially affect participation and that awareness of program eligibility is a major source of variation in participation.

This article analyzes the causes and consequences of the growing proportion of high-school-certified persons who achieve that status by exam certification rather than through high school graduation. Exam-certified high school equivalents are statistically indistinguishable from high school dropouts. Whatever differences are found among exam-certified equivalents, high school dropouts and high school graduates are accounted for by their years of schooling completed. There is no cheap substitute for schooling. The only payoff to exam certification arises from its value in opening postsecondary schooling and training opportunities, but completion rates for exam-certified graduates are much lower in these activities than they are for ordinary graduates.