This is line with the well known stylized fact of prevailing liquidity constraints in international migration (Lopez and Schi¤, 1998; Mayda, 2006).

The intensity of South-South migration is important for our analysis for two reasons. First, it suggests that migrants are by no means concentrated in OECD countries. Therefore, the fertility norms that they will transmit from abroad are much more heterogeneous that one would expect if most migrants were located in OECD countries. Second, it suggests that the impact of fertility norms might work in both directions. In fact, 83 countries have an average fertility at destination that is higher than the one prevailing at home (i.e. 40 percent of the full sample of 208 countries). If we consider only developing countries, this situation is observed in 44 cases (i.e. 28 percent of the sample of 155 developing countries) Combining the fertility data with the bilateral migration matrix allows us to compute weighted average fertility rate at destination, as in equation (18). As expected from the observed patterns of migration and the importance of South-South migration as well as the range of fertility rates, the average fertility rates at destination <u>n</u><sup>~~d~~</sup> exhibit a high degree of variability, ranging from 1.40 to 5.58.

Table 1 describes the distribution of the fertility rates by country groups. The countries are classi...ed along di¤erent criteria: income (high income vs developing countries), data availability regarding important variables such as the remittances, geographical location and religion. In 2000, the fertility rates vary signi...cantly across location of the country, from 4.8 children per woman in Africa to 1.4 in Europe. At the world level, the fertility rate is equal to 3.2 children per woman on average and ranges from 0.9 in Macau to 7.95 in Niger. Table 1 also provides fertility rates at destination, i.e. values for <u>n</u><sup>~~d~~</sup> : The fertility rates at destination are signi...cantly higher for Sub Saharan countries and to a lesser extent Islamic countries. This might be explained by their emigration patterns. In Sub-Saharan Africa, a large share of the migration ‡ows is towards neighboring countries that also display high fertility levels. In Islamic countries such as Egypt of Pakistan, a lot of workers migrate to Gulf countries in which the fertility rates are relatively high.

Data on human capital (Ht) on positive selection in emigration (St), proxied by the skilled-to-unskilled ratio of emigration rates to rich countries, are computed by Docquier et al. (2007). Emigration rates (p0) are also computed from the Parsons et al. (2007) database. Data on remittances are taken from the IMF database. In our set of controls, we include the urbanization rate (available in the World Development Indicators)<sup>7</sup> , regional and religious dummies. Regional dummies are consistent with the World Bank de...nition. Given the low number of countries (8) in South Asia, we join those countries with the Europe and Central Asia (ECA) region. Religion variables are measured in two ways. We ...rst use the proportion of Catholics and Muslims living in the country. Alternatively, we introduce a dummy for countries belonging to the organization of the Islamic Conference.

> 7Sato (2007) and Sato and Yamamoto (2005) discuss the e¤ect of agglomeration and urbanization on fertility rates.

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