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Evaluation of Person-based Migration Methodology. Presented to FSCPE Meeting Internal Migration Processing Team Local Area Estimates and Migration Processing Branch U.S. Census Bureau September 26, 2006. Contents of Presentation. Description of Return-based and Person-based

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Evaluation of person based migration methodology

Evaluation of Person-based Migration Methodology

Presented to FSCPE Meeting

Internal Migration Processing Team

Local Area Estimates and Migration Processing Branch

U.S. Census Bureau

September 26, 2006


Contents of presentation
Contents of Presentation

  • Description of Return-based and Person-based

  • Summary of Issues and Recommendations

  • Evaluations

  • Future R/Ds


Return-Based Method

  • Internal Revenue Service sends tax extract file to Census Bureau

  • Drop names and assign unique Person Identification Keys (PIK) derived from SSNs

  • Run edit process and assign county code to each return based on ZIP+4

  • Two consecutive years of tax data are matched on primary filer’s PIK


Return-Based Method(Cont’d)

  • Compare county codes on matched returns to define migration

  • Tally exemptions for in-, out-, and non-migration components

  • Compute Net Internal Migration Rate (NMR) for Under 65 household population:

    NMR = (In-migrants – Out-migrants) /

    (Non-migrants + Out-migrants)


Return-Based Method(Cont’d)

  • Match Year-1/Year-2 matched IRS file to PCF to obtain demographic characteristics for primary filers

  • Demographic characteristics for the spouse and dependents are imputed based on the characteristics of the primary filer

  • Migration status is assigned based on the migration status of the primary filer

  • Produce state and county migration data by age, race, sex, and Hispanic origin


Limitations of return based
Limitations of Return-Based

  • Underestimate the moves associated with life-events (e.g., divorce, marriage, first job etc.,)

  • Demographic characteristics of spouse and dependents are imputed based on the characteristics of the filers

  • Migration status of spouse and dependents depends on the filer.


Person based method
Person-Based Method

  • Start with the return-based edited file

  • Records created for filer, spouse, and all dependents (up to 4); one record per each individual on the tax return

  • Unduplicate the records by applying selection rules

  • Assign county code to each record

  • Matched across two consecutive tax years on PIK


Person based method cont d
Person-Based Method(Cont’d)

  • Compare county codes on matched returns to define migration

  • Tally exemptions for in-, out-, and non-migrants

  • Compute Net Migration Rate (NMR) for Under 65 household population:

    NMR = (in-migrants – out-migrants) /

    (non-migrant + out-migrants)


Person based method cont d1
Person-Based Method(Cont’d)

  • Match Year-1/Year-2 matched IRS file to PCF to obtain demographic characteristics for filer, spouse, and dependents (No imputation!!)

  • Migration status is individually assigned to filer, spouse, and dependents based on the assigned county codes (No imputation!!)

  • Produce state and county migration data by age, race, sex, and Hispanic origin


Issues requiring decision making rules
Issues requiring decision making rules

Issue 1. Duplicate Records/Zero Exemptions:

  • Multiple records are created for one person if the person’s SSN is claimed on more than one tax return, including zero exemption returns

  • Need to decide which records to keep


Zero exemption
Zero Exemption

  • Filed when a dependent child has enough income to report to the IRS

  • The parent claims separately the dependent on his or her tax return

  • 87 percent of the duplicate records involve zero exemptions returns


Issues requiring decision making rules1
Issues requiring decision making rules

Issue 2. Excess exemptions:

  • The number of SSNs recorded on a tax return does not match the number of exemptions claimed on the same return

  • We need to decide whether we create a dummy record for each excess exemption


Summary of issues zero exemptions
Summary of IssuesZero exemptions

  • Retain the zero exemption record and drop the dependent record

  • Addresses on zero exemption returns are likely to be more accurate


Summary of issues other duplicate records
Summary of Issues Other duplicate records

  • Filer record trumps all!

  • Retain primary filer records and drop spouse and dependents records


Summary of issues excess exemptions
Summary of Issues Excess Exemptions

  • Fewer SSNs than exemptions claimed

  • Exclude excess exemptions

    2. More SSNs than exemptions claimed (i.e., negative excess exemptions)

  • Include the provided SSNs and ignore negative negative excess exemptions


Divorce scenario
Divorce Scenario

Year 1 Year 2

Return-Based Person-Based

1 Non-Migrant 1 Non-Migrant

Non-Match 4 Migrants

1 Filer 1 Filer

Cty A Cty A

1 Spouse 1 Filer

3 Deps 3 Deps

Cty A Cty B


Student scenario

Student Scenario

Year 1 Year 2 Return-Based Person-Based

1 Deps 1 Filer 1 Non-Match 1 Migrant

Cty A Cty B


Evaluation match rates definition
EvaluationMatch Rates - Definition

Year-1/Year-2 Match Rate

= (Year-1 and Year-2 Matched Record Count) * 100 / Total Year-1 Record Count

PCF Match Rate

= (Year1,Year2, and PCF Matched Count) * 100 / (Year1 andYear2 Matched Count)


The 10 Lowest Year1-Year2 Match Rates from Return-Based Records from Years 2000 through 2004 (National Average = 90.5%)


The 10 Lowest Year1-Year2 Match Rates from Person-Based Records from Years 2000 through 2004 (National Average = 94%)


Pcf match rates
PCF Match Rates Records from Years 2000 through 2004

  • The match rates from the person-based records were almost the same as the match rates from the return-based records (> 99%).



Matched Y1-Y2 Under-Age-65 Exemptions: Percent of Exemptions Migrating by Exemption Status (10 Percent Sample)


Migration base person based vs return based
Migration Base: Exemptions Migrating by Exemption Status Person-based vs. Return-based


Coverage analysis by state
Coverage Analysis by State Exemptions Migrating by Exemption Status

  • Coverage patterns are consistent across states and years

  • Person-based coverage was consistently lower than return-based coverage

  • The states with the most extreme coverage rates under return-based processing maintained the same pattern under person-based processing

  • The difference in coverage declined for every state between 2000 and 2004. The highest difference was –5.30 in 2000 and –0.48 in 2004


Number of inter county migrants person based vs return based
Number of Inter-county Migrants: Exemptions Migrating by Exemption Status Person-based vs. Return-based


Inter county migration percent person based vs return based
Inter-county Migration Percent: Exemptions Migrating by Exemption Status Person-based vs. Return-based


Race and hispanic origin distribution person based vs return based
Race and Hispanic Origin Distribution Exemptions Migrating by Exemption Status :Person-based vs. Return-based


Age distribution person based vs return based
Age Distribution Exemptions Migrating by Exemption Status :Person-based vs. Return-based


Migration rate outliers definition
Migration Rate Outliers Definition Exemptions Migrating by Exemption Status

Outliers

95% Confidence Interval

Outliers


Findings from outlier analysis
Findings from Outlier Analysis Exemptions Migrating by Exemption Status

  • The person-based method had significant effect on the migration flows from the counties with small population to the counties with large population

  • The new method had the largest impact on individuals in their early 20s


Summary of findings
Summary of Findings Exemptions Migrating by Exemption Status

  • The person-based method will produce more accurate migration estimates.

  • The characteristics from the person-based records will be more accurate than the return-based.


Future r ds
Future R/Ds Exemptions Migrating by Exemption Status

  • Integration of Electronic File to enhance the coverage of child dependent

  • Integration of Medicare data at the micro level to produce the migration data for the 65+


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