Fertility and the size of the Mexican-born female population in the U.S.

摘要

This dissertation consist of three separate papers that address the (a) the fertility contribution of Mexican-born immigrants to the future U.S. population, (b) the impact of immigrants on high U.S. TFR and (c) the use of vital rates to estimate the size of the Mexican-born female population in the U.S. In the first paper a new method is proposed to project the contribution of immigration to a receiving country's population that obviates the need to project the number of immigrants by using the full sending-country birth cohort as the risk group to project their receiving-country childbearing. The new method is found to perform dramatically better than conventional methods when projecting to 1999 from selected base years in the past. Projecting forward from 1999, the research estimated the cumulative contribution of Mexican immigrant fertility from the 1980s to 2040 of 36 million births, including 25% to 50% more births after 1995 than are projected using conventional methods. The second paper consists of a decomposition analysis of the recent U.S. TFR into fertility and composition effects of Mexican-born and other foreign-born immigrants. The results show that 6% of the U.S. TFR is attributable to a higher ASFR of immigrant women. About 63% of the foreign-born effect in 1990 and 71% in 2000 is attributable to Mexican-born woman. Approximately 11% of the Mexican-born contribution to the TFR is due to an age composition of the Mexican-born that favors the high-ASFR ages. The large increase in the size of the foreign-born population in the U.S. from 1990-2000 is mostly offset by reduced TFR of both the foreign-born and the native-born population. Finally the dissertation explores the usability of vital rates in combination with registered number of vital events to estimate the Mexican-born population in the U.S. The results show that the intuitively simple and mathematically sound method is unsuitable for population estimates when mortality rates are bias and sampling error reduces the preciseness of fertility rates.