Estimation of a Stochastic Model of Reproduction: An Econometric Approach / James J. Heckman, Robert J. Willis.

Author
Heckman, James J. [Browse]
Format
Book
Language
English
Published/​Created
  • Cambridge, Mass. National Bureau of Economic Research 1974.
  • Cambridge, Mass. : National Bureau of Economic Research, 1974.
Description
1 online resource: illustrations (black and white);

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Subject(s)
Related name
Series
  • Working Paper Series (National Bureau of Economic Research) no. w0034. [More in this series]
  • NBER working paper series no. w0034
Summary note
In the past few years, there has been substantial progress in the application of the economic theory of household decision making to human fertility behavior. Theoretical emphasis has been given to the effects of the costs of parental tine and money resources devoted to rearing children on the demand for the total number of children in a static framework under conditions of certainty. Empirical work has focused on explaining variation in the number of children ever born to women, who have completed their childbearing, as a function of measures of the household's total resources and the opportunity cost of time, especially the value of the wife's time. One important objection to static theories of fertility is their failure to deal with the implications of the simple fact that reproduction is a stochastic biological process in which the number and timing of births and the traits of children (e.g. sex, intelligence, health, etc.) are uncertain and not subject to direct control. In this paper, we report some initial results of a study in progress whose goal is to develop an integrated theoretical and econometric model of fertility behavior within a sequential stochastic framework. The principal contribution of the paper is to the development of an appropriate econometric methodology for dealing with some new econometric problems that arise in such models.
Notes
February 1974.
Source of description
Print version record
Other title(s)
Estimation of a Stochastic Model of Reproduction
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