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County-to-County Migration Flows: Examining the Assumption that Households Migrate Together Lucinda Pearson and Douglas Sater Population Division U.S.

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Presentation on theme: "County-to-County Migration Flows: Examining the Assumption that Households Migrate Together Lucinda Pearson and Douglas Sater Population Division U.S."— Presentation transcript:

1 County-to-County Migration Flows: Examining the Assumption that Households Migrate Together Lucinda Pearson and Douglas Sater Population Division U.S. Census Bureau

2 Description of Return-Based IRS sends tax file to Census Bureau County codes assigned to each return Compare county codes on matching returns: This defines the migration!! Tally exemptions/return Net internal migration rate for household pop, under 65= (Ins-Outs)/(Nons+Outs)

3 Potential bias from exclusion of non-filers and non-matched returns Potential bias in assumption that spouses and dependents have same migration as filer Limitations of Return-Based

4 Description of People-Based Records created for each filer, spouse of filer, and all dependents regardless of exemption status; one record/SSN selected Records then county coded and matched year to year

5 People-Based Record Types Filer Spouse Dependent

6 Divorce Scenario 1F 1 F 1Non-Migrant 1Non-MigrantCty A 1 S 1 F Non-Match 4 Migrants 3 D Cty ACty B Y1 Y2 Return-Based People-Based

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8 Differences in Records Included Filer 1 D or S Filer 2 D or S Filer 1 D or SFiler 2 and Vice Versa

9 Match Rate Comparison for 1997-1998 Migration Year

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12 Counties with Greatest Numeric Differences 25 counties with diff of + or - 1,000: 17 counties have # diff of 1,000+ 8 counties have # diff of -1,000 5 TX4 CA4 NY All are metropolitan US mean county pop size: 86,066 vs. 140,000+ for the top 25 19/25 “Central county of metropolitan area with 1 million+ residents”

13 Counties with Greatest Numeric Differences (Cont’d) 9/25 had % GQ > US county mean of 3.1% All 25 have a % total pop aged 18-30 > US mean of 16% 24/25 had % minority > US county mean of 17%; all but 3 were 27%+

14 Counties with Greatest Numeric Differences (Cont’d) HOUSEHOLD COMPOSITION: 7/25 had proportion married with children > US county mean of 29% 23/25 had proportions never married > US county mean of 18% 22/25 had proportions of single parent HH > US mean of 8%

15 Counties with Greatest Rate Differences 29 had an absolute difference of 1.0 27 are nonmetro 13 in Texas US Mean County Pop Size: 86,066 vs. 2/29 with pop >11,000 12/29 are nonmetro farming-dependent 19/29 “nonmetro county with no urban place that is not adjacent to a metro county”

16 Effect of People-Based on NYC

17 Effect of People-Based on Boston

18 Next Steps Zero Exemption Returns Stratify by Pop Size Time Series 0-64 vs. 65+ Examine if people who change status have different patterns and rates from those who do not

19 Next Steps (Cont’d) Compare Population Estimates Produced by Two Methods and to Census 2000 Estimates with Demographic Detail (i.e. age, race, sex, and Hispanic origin)


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