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Population Projections: Applications in Immigration Research

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Presentation on theme: "Population Projections: Applications in Immigration Research"— Presentation transcript:

1 Population Projections: Applications in Immigration Research
Jennifer Van Hook Penn State University June 2019

2 Why use Projections in immigration research?
Data Limitations Unauthorized foreign-born population Population Lever Immigration Impacts Generational Change Starting points & mobility

3 Unauthorized foreign-born population
With Randy Capps, Julia Gelatt, and Anne Morse

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6 …Fazel-Zarandi, Feinstein and Kaplan’s approach is very sensitive to underlying assumptions…their estimates range widely and are too uncertain to be of value for policy purposes. …the knowledge base about key inputs for their model…is insufficiently developed to support their approach.

7 questions What accounts for the variation in estimates? Point estimates are interpreted literally: What is the margin of error? Tension: uncertainty, decision making

8 Unauthorized FB = Total FB – Legal FB
residual Method Unauthorized FB = Total FB – Legal FB

9 Converts Flows to Stocks
Ut = Unauthorized FB, post-1980 foreign-born arrivals Ct = ACS estimate, post-1980 arrivals – legal nonimmigrants Lt = LPRs (time t) = Admissions since Refugees who have not yet adjusted – Deaths – Emigrants etL = coverage error, legal foreign-born etU = coverage error, unauthorized foreign-born Converts Flows to Stocks

10 Cohort component method

11 Mexican Males Admitted and entered US in 1995 at age 20:
Admissions = 1,191 Year time in US age Cohort size, Jan 1 deaths emigrants Cohort size, Dec 31 1996 1 21 1,191 2 16 1,173

12 Mexican Males Admitted and entered US in 1995 at age 20:
Admissions = 1,191 Year time in US age Cohort size, Jan 1 deaths emigrants Cohort size, Dec 31 1996 1 21 1,191 2 16 1,173 1997 22 18 1,154

13 Mexican Males Admitted and entered US in 1995 at age 20:
Admissions = 1,191 Year time in US age Cohort size, Jan 1 deaths emigrants Cohort size, Dec 31 1996 1 21 1,191 2 16 1,173 1997 22 18 1,154 1998 3 23 19 1,133

14 Mexican Males Admitted and entered US in 1995 at age 20:
Admissions = 1,191 Repeat for ~500,000 admission cohorts (sex x age at arrival x year of entry x year of admission x country of birth x refugee status)

15 Ut = Unauthorized FB, post-1980 foreign-born arrivals Ct = ACS estimate, post-1980 arrivals – legal nonimmigrants Lt = LPRs (time t) = Admissions since Refugees who have not yet adjusted – Deaths – Emigrants etL = coverage error, legal foreign-born etU = coverage error, unauthorized foreign-born

16 Uncertainty and variation in Mortality

17 Probability distribution for Hazard Ratio, Hispanic men, 0-4 years in U.S.

18 Uncertainty and variation in Emigration

19 Probability distribution for FB Emigration (0-4 years in U.S.)

20 Uncertainty and variation in Coverage Error
OIS: 10% Pew: 13% Van Hook et al (2015): Mexican-born, 3 methods Death Registration Birth Registration Net Migration

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22 Probability distribution for UNAUTHORIZED COVERAGE ERROR, men 2016

23 Variation in ESTIMATES

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25 Possible constraints Internal Consistency
undercount cannot be negative undercount for LPRs must be less than unauthorized Should assumptions be correlated (across groups, across assumptions)? External Consistency with other estimates direct measurement, net migration from sending countries border apprehension/Visa overstay trends

26 Ethical quandaries Transparency Certainty Policy makers need to make decisions, want certainty Scientific disputes undermine public confidence. Yet transparency is essential for scientific advancements How can we discuss uncertainty, while still assuring people that our estimates are better than guessing?


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