Abstract

Success in producing a population projection predominately depends on the accuracy of its migration rates. In developing an interregional, cohort-component projection methodology for the U.S. city of Boston, Massachusetts, we created an innovative approach for producing domestic migration rates with synthetic populations using 1-year, American Community Survey (ACS), and Public Use Microdata Samples (PUMS). Domestic in- and out-migration rates for Boston used 2007–2014 ACS data and developed synthetic Boston and United States populations to serve as denominators for calculating these rates. To assess the reliability of these rates, we compared the means and standard deviations of eight years of these rates (2007–2014) with synthetic populations by single-year ages for females and males to rates produced from two ACS samples using the same migration data in the numerator but the prior year’s age data in the denominator. We also compared results of population projections for 2015 using these different migration rates to several 2015 U.S. Census Bureau population estimates for Boston. Results suggested our preferred rates with synthetic populations using one ACS sample for each year’s migration rates were more efficient than alternative rates using two ACS samples. Projections using these rates with synthetic populations more accurately projected Boston’s 2015 population than an alternative model with rates using the prior year’s age data.

Highlights

  • By 1990, research clearly identified limitations with measures of net migration for population projections [1,2,3,4]

  • Standard deviations were lower for our preferred synthetic estimators that better identified the population at risk of migrating using one American Community Survey (ACS) sample (Equations (1) and (2)) than those using two ACS samples (Equations (3) and (4))

  • This research describes an innovative method to generate efficient migration rates with synthetic populations from a series of single-year ACS samples that clearly identified the population at risk of domestically migrating to and from Boston

Read more

Summary

Introduction

By 1990, research clearly identified limitations with measures of net migration for population projections [1,2,3,4]. Net migration reflects the difference between the number of in-migrants and out-migrants. Gross migration measures movement of people in and out of a region, and the magnitude of migrants. Net migration has several weaknesses that highlight why gross migration is a preferable measure for generating migration rates for a cohort-component projection model. Because net migration is an accounting procedure, a net migrant does not exist, and no true at-risk population of migration can be identified [5] Because net migration is an accounting procedure in the demographic equation, a net migrant does not exist, and no true at-risk population of migration can be identified [5]

Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call