Econometric Models of Fertility

Arbeitspapier

This paper reviews some key contributions to econometric analysis of human fertility in the last 20 years, with special focus on discussion of prevailing econometric modeling strategies. We focus on the literature that highlights the role of the key drivers of the birth outcomes, including age at entry into motherhood, the number of children, and the time between births. Our overall approach is to highlight the use of single equation reduced form modelling, which has important advantages but has the limitation of typically being unable to shed light on detailed causal mechanisms through which exogenous factors such as birth control and infant mortality, and policy variables such as child allowances and tax incentives, impact fertility. Structural models that embed causal mechanisms explicitly are better suited for this objective. We start with a description of the subject matter, including a brief review of existing theories of fertility behaviour and a detailed discussion of the sources of data that are available to the analyst. At this point we stress the intrinsic dynamic nature of fertility decisions and how such dynamics create data with empirical features that pose important challenges for modelling. Once the nature of the problem and the characteristics of the data are spelled out, we proceed to review the different econometric approaches that have been used for modelling fertility outcomes with cross-section and panel data.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: IZA Discussion Papers ; No. 13357

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions ; Single Equation Models; Single Variables: Panel Data Models; Spatio-temporal Models ; Duration Analysis; Optimal Timing Strategies ; Fertility; Family Planning; Child Care; Children; Youth
• Subject: econometrics of fertility ; cross-section and panel data models ; count data models ; hazard (survival) models

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Miranda, Alfonso ; Trivedi, Pravin K.
• Event: Veröffentlichung
• (who): Institute of Labor Economics (IZA)
• (where): Bonn
• (when): 2020

Further information

• Handle: http://hdl.handle.net/10419/223799
• Last update: 10.03.2025, 11:45 AM CET