Assisted Reproductive Technologies (ART) in a Model of Fertility Choice

This paper provides a simple theoretical framework to discuss the relationship between assisted reproductive technologies and the microeconomics of fertility choice. Individuals make choices of education and work along with decisions about whether and when to have children. Decisions regarding fertility are influenced by policy and labor market factors that affect the earnings opportunities of mothers and the costs of raising children. We show how observed differences in these economic factors across countries explain observed different fertility and childbearing age patterns. We then use the model to predict behavioral responses to biomedical improvements in assisted reproductive technologies, and hence the impact of these technologies on fertility.

Demographic Transitions: analyzing the effects of mortality on fertility

The effect of mortality reductions on fertility is one of the main mechanisms stressed by the recent growth literature in order to explain demographic transitions. We analyze the empirical relevance of this mechanism based on the experience of all countries since 1960. We distinguish between the effects on gross and net fertility, take into account the dynamic nature of the relationship and control for alternative explanatory factors and for endogeneity. Our results show that mortality plays a large role in fertility reductions, that the change in fertility behavior comes with a lag of about 10 years and that both net and gross fertility are affected. We find comparatively little support for explanations of the demographic transition based on economic development or technological change.

Pareto or log-normal? A recursive-truncation approach to the distribution of (all) cities

Traditionally, it is assumed that the population size of cities in a country follows a Pareto distribution. This assumption is typically supported by nding evidence of Zipf's Law. Recent studies question this nding, highlighting that, while the Pareto distribution may t reasonably well when the data is truncated at the upper tail, i.e. for the largest cities of a country, the log-normal distribution may apply when all cities are considered. Moreover, conclusions may be sensitive to the choice of a particular truncation threshold, a yet overlooked issue in the literature. In this paper, then, we reassess the city size distribution in relation to its sensitivity to the choice of truncation point. In particular, we look at US Census data and apply a recursive-truncation approach to estimate Zipf's Law and a non-parametric alternative test where we consider each possible truncation point of the distribution of all cities. Results con rm the sensitivity of results to the truncation point. Moreover, repeating the analysis over simulated data con rms the di culty of distinguishing a Pareto tail from the tail of a log-normal and, in turn, identifying the city size distribution as a false or a weak Pareto law.