ECONOMIC AND STATISTICAL MODELS OF LIFE-CYCLE FERTILITY

本项目将研究生育率如何在生命周期中进行调整， 对家庭累积的人口统计事件的反应。 的主要部分 研究工作将致力于开发和测试新的 危险率分析方法。 主要的创新在于 早期的方法是使用离散时间框架， 明确纳入重要的生物决定因素， 对异质性和内禀性的校正。 大量使用Monte 在经验模型的开发过程中， 大大提高了估计的可解释性。 虽然方法上的改进将具有相当大的价值， 许多应用程序，该项目将主要限于研究 法国农村的生育率转变。 自然生育力假说 可以被简化为关于内部动态的可测试的断言， 家庭建设，不涉及家庭以外的任何变量， 人口统计学史 在这个项目中开发的方法是独一无二的 非常适合充分利用生育史。 家庭 重建数据，就像研究所为法国建造的数据一样， 国家人口学研究，并在以前的工作中使用本 调查人员提供了丰富和比较完整的数据， 生育史，一般没有任何额外的信息。 在 结合，这里使用的数据和方法将产生强大的 生育假设的检验 当与其他组合使用时， 将生育历史与其他变量联系起来的数据集， 可以测试更具体的理论， 生育率的决定因素。

This project will investigate how fertility adjusts over the life cycle in response to the family's accumulated demographic events. A major part of the research effort will be devoted to the development and testing of new methodologies for the analysis of hazard rates. The main innovations over earlier methodologies are the use of a discrete time framework, the explicit incorporation of important biological determinants, and corrections for heterogeneity and endogeneity. Intensive use of Monte Carlo experiments during the development of the empirical model will greatly improve the interpretability of estimates. Although the methodological improvements will be of considerable value in many applications, this project will mainly be confined to a study of fertility transition in rural France. The hypothesis of natural fertility can be reduced to testable assertions about the internal dynamics of family-building, without reference to any variables outside the family's demographic history. The methods developed in this project are uniquely well-suited to making full use of fertility histories. Family reconstitution data, like that constructed for France by the Institut National d'Etudes Demographiques and used in previous work by the present investigators, provide abundant and comparatively complete data on fertility histories, generally without any additional information. In combination, the data and methods to be used here will produce powerful tests of the fertility hypothesis. When used in combination with other data sets linking fertility histories to other variables, the new methods can test more specific theories about the behavioral and biological determinants of fertility.