Juliana Jaramillo Echeverri

Economic historian

Fertility decline in Colombia

Research on the Colombian fertility transition

Simultaneous and Widespread: Colombia’s Fertility Transition - R&R in Population, Space and Place

Colombia experienced one of the fastest declines in fertility in the world: children per woman fell from 7 in 1960 to 3 in 1985. Despite the stark inequalities of the country, the regional character of the decline has been neglected in previous research. This paper fills this gap and brings a detailed empirical perspective of Colombia’s rapid decline in fertility focusing on the sub-national level. The results show that before the fertility transition, variations in fertility patterns were linked to differences in historical legacies that derive from differences in geographical endowments. Then, I provide new estimations of fertility rates at the departmental level and for indigenous women. The results show that from 1964, fertility began to decline simultaneously in almost all regions, regardless of their traditional fertility levels. You can find a version of the most recent working paper here and a poster here.

Waves of change? Radio announcements and fertility decline

Can radio campaigns affect fertility preferences? I investigate this question by studying a national radio campaign in the late 1960s in Colombia. In 1969 Profamilia, one of the largest family planning organisations in the world, started a national radio campaign to spread the idea of family planning. The results suggest that the effects of the radio campaign were limited.

Can female education explain the fertility decline?

Across the world educated women tend to have fewer children than their less-educated peers. This chapter provides new stylised facts about the long-run relationship between women’s education and fertility at the national, sub-national, and individual level. The findings caution that the relationship between fertility and women’s education is not always monotonic, and that this relationship changes significantly depending on the level of aggregation of the data.