1. STATE AND COUNTY CHARACTERISTICS ESTIMATES A DETAILED DESCRIPTION OF THE VINTAGE 2003 METHODS AND PROCESSING

2. 2 Workshop Overview Introduction History and general concepts State age-sex method and processing State and county characteristics method and processing Summary and discussion

3. 3 History and General Concepts: History 1970s –Started producing state estimates by selected age groups in the 1970s; added sex later in the ’70s 1980s –Started producing state estimates by single years of age and sex using the current method Early 1990s –Released first set of state estimates by age, sex, race, and Hispanic origin produced by the current method

4. 4 History and General Concepts: History (cont.) 2000s –Released first set of county age, sex, race, and Hispanic origin estimates produced by the current method

5. 5 History and General Concepts: General Concepts Universes –Resident –Civilian vs. Military –Household vs. GQ –Institutional vs. Noninstitutional Migration –International, Domestic, and Total –Ins, Outs, and Net –Interstate and Intrastate

6. 6 History and General Concepts: General Concepts (cont.) Proportional Distribution Technique –Basic method 1.Develop initial version of new estimates 2.Create proportions from new estimates that correspond to the estimates to be distributed 3.Multiply the proportions by the estimates to be distributed –Distributing two sets of estimates 1.This procedure is done first to one set then to another 2.Typically, it is necessary to repeat the back-and-forth procedure several times

7. 7 History and General Concepts: General Concepts (cont.) Example –States age sex estimates – 1 iteration –Step 1: Distributing national estimates 1.Produce an initial set of state estimates by age and sex 2.Sum state estimates [from #1] to the national level by age and sex 3.Calculate proportions by dividing each state age-sex cell [from #1] by the corresponding cell from the National sum [from #2] 4.Calculate intermediate state age-sex estimates by multiplying the proportions [from #3] by the actual national estimates *

8. 8 History and General Concepts: General Concepts (cont.) Example (cont.) –Step 2: Distributing state total estimates 1.Take state age-sex estimates from first iteration 2.Sum age-sex estimates [from #1] to state totals 3.Calculate proportions by dividing each state age-sex cell [from #1] by the corresponding state total [from #2] 4.Calculate final state age-sex estimates by multiplying the proportions [from #3] by the actual state totals estimates *

9. 9 History and General Concepts: General Concepts (cont.) Approaches to creating time-series –Whole interval approach: the beginning population for the estimate of each year in the time-series is Census 2000 –Year-to-year approach: the beginning population for the estimates of each year in the time-series is the estimates for the previous year of the time- series

10. 10 History and General Concepts: General Concepts (cont.) Acronyms used in this presentation –ASRO: Age, Sex, Race, and Hispanic Origin –SYA: Single Years of Age –HH: Household –GQ: Group Quarters

11. 11 State Age-Sex: Overview The basics The general method: Ages 0 – 64 –Beginning populations –Deaths –Migration The general method: Ages 65+

12. 12 State Age-Sex: The Basics State population –Single years of age (0 – 84) and 85+ by sex Whole interval approach to creating time- series

13. 13 State Age-Sex: The General Method 1.Calculate preliminary population estimates a.Calculate the civilian beginning populations and add births* b.Subtract deaths* c.Calculate estimated net migration and add* d.Apply sex proportions to get population by sex e.Add military to get resident population f.Estimate the 65+ population* 2.Calculate proportions 3.Use proportions to distribute estimates a.National estimates by age and sex b.State totals estimates * will be discussed in detail in this workshop

14. 14 State Age-Sex: Beginning Population 1.Start with GUSSIE resident base population By single years of age and sex 2.Shift the age of the base population to age in estimate year 3.Add male and female population together 4.Add birth data to the youngest ages 5.Subtract out the military population to get the final civilian beginning population

15. 15 State Age-Sex: Deaths 1.Calculate preliminary estimates of deaths a.Begin with deaths to the resident population by SYA (0-84, 85+) and sex b.Collapse into both-sexes deaths by age c.Sum deaths to estimate intervals (Census date to estimate date) d.Subtract military deaths to obtain preliminary civilian deaths by age 2.Calculate proportions 3.Use proportions to distribute national civilian deaths by SYA from National Estimates

16. 16 State Age-Sex: Migration, Ages 0 - 16 1.Develop an estimate of the total school age population (ages 6 to 14) for each estimate year Distribute the national estimates for ages 6-14 to the states using proportions developed from school enrollment data

17. 17 State Age-Sex: Migration, Ages 0 – 16 (cont.) 2.Develop a set of state school age population estimates under the assumption of no migration Survive the cohorts that become the school age population in the estimates year from Census 2000 to each estimate year using deaths from vital registration 3.Migration = [#1] – [#2] 4.Distribute to SYA 0 to 16

18. 18 State Age-Sex: School-Age Migration Rates 1.Begin with the estimates of migration of the school age population from the previous step 2.Calculate an estimate of the mid-interval school-age population (6 to 14) for each estimate interval Subtract ½ of the estimate of the cumulative school-age deaths for each estimate interval from the Census 2000 school-age population

19. 19 State Age-Sex: School-Age Migration Rates (cont.) 3.Compute the school age migration rates Divide the estimates of school-age migration for each estimate interval by the corresponding mid-interval estimate of the school age population

20. 20 State Age-Sex: Migration Differentials 1.Begin with census data from 5-year residence question (ignoring sampling variability) 2.Calculate in and out migration rates by state and single year of age (0-84) and 85+ and smooth by age 3.Combine in and out rates into a net migration rate 4.Multiply net rates by a series of mid-interval populations over a 10-year interval to arrive at 10 annual estimates of migration per cohort *

21. 21 State Age-Sex: Migration Differentials (cont.) 5.Sum migrants by cohort and collapse summed migrants ages 6-14 into one group 6.Create new migration rates by dividing summed migrants ages 6-14 as a group and 17-64 migrants by SYA by the corresponding population at the beginning of the interval 7.Subtract school age migration rate from each SYA migration rate to get migration differentials. *

22. 22 State Age-Sex: Migration, Ages 17 - 64 1.Begin with school age migration rates 2.Calculate migration rates by SYA 17 to 64 by adding the SYA migration differentials to the school age migration rate 3.Calculate migration by SYA 17 to 64 by multiplying the single-year rates by an estimate of the mid-interval population –Mid-interval population = Base population + ½ interval deaths

23. 23 State Age-Sex: Population Estimates 65+ 1.Calculate preliminary population estimates a.Start with Medicare data by state, sex and 5- year age groups 65-84 and 85+ b.Extrapolate values for 4/1/00 and missing estimate years c.Control to Medicare totals used in state-county totals estimates d.Distribute by SYA using cohort distributions from Census 2000 e.Calculate implied population change since 4/1/00 (estimated population – beginning population) and add to beginning population

24. 24 State Age-Sex: Population Estimates 65+ (cont.) 2.Calculate proportions 3.Use proportions to distribute national estimates

25. 25 State Age-Sex: Summary 1.Calculate preliminary population estimates a.Calculate the civilian beginning populations and add births b.Subtract deaths c.Calculate estimated net migration and add d.Apply sex proportions to get population by sex e.Add military to get resident population f.Estimate the 65+ population 2.Calculate proportions 3.Use proportions to distribute estimates a.National estimates by age and sex b.State totals estimates

26. 26 State & County Characteristics: Overview The basics State –The general method –July 1, 2000 beginning population –Domestic migration IRS pre-processing State domestic migration –Race conversion (4 to 31) County –The general method –Domestic migration

27. 27 State & County Characteristics: The Basics State and county population by ASRO –SYA (0 – 84) and 85+ by sex, race (31 races), and Hispanic origin (Hispanic, non-Hispanic) Year-to-year approach to creating time- series Processed in two separate steps –State characteristics –County characteristics

28. 28 State & County Characteristics: The General Method – State 1.Calculate preliminary population estimates a.Produce July 1, 2000 beginning population* b.Add births, subtract deaths, add net international migration, and add military movement c.Add domestic in-migration and subtract domestic out-migration* 2.Calculate proportions 3.Use proportions to distribute estimates a.National ASRO b.State age-sex 4.Convert from 4 to 31 races* * will be discussed in detail in this workshop

29. 29 State & County Characteristics: The General Method - County 1.Calculate preliminary population estimates a.Produce July 1, 2000 beginning population* b.Add births, subtract deaths, add net international migration, and add military movement c.Add domestic in-migration and subtract domestic out-migration* 2.Calculate proportions 3.Use proportions to distribute estimates a.State ASRO b.County totals 4.Convert from 4 to 31 races* * will be discussed in detail in this workshop

30. 30 State & County Characteristics: July 1, 2000 Beginning Population 1.Calculate preliminary population estimates a.Begin with GUSSIE base b.Convert from 31 to 4 races* c.Remove GQ population to get HH population 2.Calculate proportions 3.Use proportions to distribute previous July 1, 2000 HH estimates a.State: National ASRO and state age-sex b.County: State ASRO and county totals 4.Add GQ population to get resident population * will be discussed in detail in this workshop

31. 31 State & County Characteristics: July 1, 2000 Beginning Population (cont.) Race conversion: 31 to 4 –Equi-proportional assignment of persons in multi- race categories to single-race categories (31 to 5 categories) –Combine Asian and Native Hawaiian and other Pacific Islander categories into Asian and Pacific Islander (5 to 4 categories)

32. 32 State & County Characteristics: Domestic Migration - Overview 1.Pre-process IRS migration data* 2.State domestic migration* a.Calculate state out-migration b.Calculate state in-migration 3.County domestic migration* a.Recalculate interstate in- and out- migration b.Distribute interstate migration flows to counties c.Calculate intrastate migration rates & migrants d.Distribute intrastate migration totals to counties * will be discussed in detail in this workshop

33. 33 State & County Characteristics: IRS Pre-processing - Overview 1.Obtain administrative record data 2.Match across administrative record sources 3.Assign characteristics to filer and exemptions 4.Compare Y1 and Y2 FIPS codes 5.Define migration universe 6.Tally exemptions by demographic characteristics

34. 34 State & County Characteristics: Obtain Administrative Record Data Internal Revenue Service (IRS) 1040 files –Address in 2002 (Y1) –Address in 2003 (Y2) –Number of exemptions – filer, spouse, child, parent Social Security Numident File –Collapse records to Census Numident Person Characteristics File (PCF) –File contains modeled age, sex, race, and Hispanic origin for all persons with an SSN

35. 35 State & County Characteristics: Match Across Administrative Records Bureau committed to privacy and confidentiality –Convert SSN on tax records to Protected Identifier Key (PIK) Match Y1 and Y2 files by filer’s PIK Match Y1-Y2 file to PCF by filer’s PIK Convert filer’s return to individual records for filer, spouse, child, and parent exemptions on the tax return

36. 36 State & County Characteristics: Assign ASRO Assign ASRO for Y1-Y2 matched records that match the PCF –Age Filer and spouse exemptions are assigned filer’s age from PCF Child exemptions are assigned to a 19 and under age category Parent exemptions are assigned to a 65+ age category

37. 37 State & County Characteristics: Assign ASRO (cont.) –Sex Filer is assigned filer’s sex from PCF Spouse exemption is assigned opposite sex of filer Child and parent exemptions are assigned sex by random number generator –Race and Hispanic origin Filer, spouse, child, and parent exemptions are all assigned filer’s race and Hispanic origin from PCF –Y1 and Y2 State and County FIPS codes Filer, spouse, child, and parent exemptions are all assigned filer’s Y1 and Y2 state and county FIPS codes

38. 38 State & County Characteristics: Compare Y1 and Y2 FIPS Codes Compare by equivalent geography Outcomes of comparison –Y1 only –Y2 only –Foreign in- and out-movers –Inter-state movers –County to county movers (intra-state) –Non-movers

39. 39 State & County Characteristics: Define Migration Universe Exclude records: –where record appears only in Y1 or Y2 file –with a foreign address on either the Y1 or Y2 return –where Y1-Y2 IRS match does not match to PCF

40. 40 State & County Characteristics: Tallying Exemptions Three different measures are calculated from exemption data –Inter-state migration rates –Intra-state migration rates –County migration shares Exemption data come with the following characteristics –Age 0-19, SYA 20-64, 65+ –Sex –White, Black, AIAN, API, Hispanic See handout

41. 41 State & County Characteristics: State Domestic Migration – Out- Migration 1.Calculate a set of state out migration rates –Out-migration rate = # of exemptions leaving the state / # of exemptions in the state –If there are less than 30 exemptions for an ASRH combination, additional ages are included until the threshold of 30 exemptions is met 2.Expand to full ASRO distribution –Each ASRO cell within a collapsed category is assigned the rate of the category as a whole 3.Smooth the out-migration rates by age 4.Missing Step

42. 42 State & County Characteristics: State Domestic Migration – In- Migration Calculate a set of state to state migration rates –State to state migration rate = # of exemptions moving from state X to state Y / total # of exemptions in state X Calculate a set of preliminary estimates of in- migration by state –Preliminary state in-migrants for state X = ∑(state to state migration rate from state Y to state X * Vintage 2002 state population state Y)

43. 43 State & County Characteristics: State Domestic Migration – In- Migration (cont.) Sum all states’ in-migrant estimates to get total in-migration Calculate each state’s in-migration proportion –State in-migration proportion = preliminary state in-migrants / total in-migration Smooth the in-migration proportions by age

44. 44 State & County Characteristics: State Domestic Migration Flows Final estimates of out- and in-migrants by state are calculated in the process of estimating the population –State out-migrants = state out-migration rate * state population at the beginning of the time interval –State in-migrants = state in-proportion * ∑(state out-migrants)

45. 45 State & County Characteristics: State Summary 1.Calculate proportions a.Produce beginning population b.Add births, subtract deaths, add net international migration, and add military movement c.Add domestic in-migration and subtract domestic out-migration d.Create proportions 2.Use proportions to distribute estimates a.National ASRO estimates b.State age-sex estimates

46. 46 State & County Characteristics: County Domestic Migration Recalculate state-level in- and out-migrants using out-rates and in-proportions from state domestic migration processing Calculate county migration proportions of state migration –In-migration prop. = ∑(tally 1) / tally 2 –Out-migration prop. = ∑(tally 3) / tally 4 –Intra-state in-migration prop. = ∑(tally 5) / tally 6 –Intra-state out-migration prop. = ∑(tally 5) / tally 6 *

47. 47 State & County Characteristics: County Domestic Migration (cont.) Multiply the county migration proportions by the appropriate state migration flow to get county-level migrants –In-migrants = in-migration prop * state in-migrants –Out-migrants = out-migration prop * state out- migrants –Intra-state in-migrants = intra-state in-migration prop * state intra-state migrants –Intra-state out-migrants = intra-state out-migration prop * state intra-state migrants *

48. 48 State & County Characteristics: County Domestic Migration (cont.) All calculations for county-level domestic migration are done by race and ethnicity –Non-Hispanic white –Non-Hispanic black –Non-Hispanic AIAN –Non-Hispanic API –Hispanic Each county migration flow is assumed to have the same age-sex distribution as the corresponding state migration flow across race and ethnicity *

49. 49 State & County Characteristics: County Interstate Domestic Migration State domestic migration is distributed to the county-level Two types of ratios are computed –Migration rate = # of migrating exemptions / # of exemptions –Migration share = # of migrating exemptions in the county / # of migrating exemptions in the state Migration rates are used to compute state- level migration with full detail *

50. 50 State & County Characteristics: County Interstate Domestic Migration (cont.) Three types of state-level migration are computed: in-migration, out-migration, and within-state migration County migration shares are used to divide state-level migration among counties by race and ethnicity County migration flows are assumed to have the same age and sex distribution as the corresponding state migration flows across race and ethnicity *

51. 51 State & County Characteristics: County Intrastate Domestic Migration County intrastate migration share = # of intrastate migrating exemptions in the county / # of intrastate migrating exemptions in the state *

52. 52 State & County Characteristics: Race Conversion (4 to 31) Calculate conversion factors for 31 to 4 race conversion from the Census 2000 GUSSIE population Apply conversion factors to population in each 4-race category to get population in each 31-race category

53. 53 State & County Characteristics: County Summary 1.Calculate preliminary population estimates a.Produce July 1, 2000 beginning population b.Add births, subtract deaths, add net international migration, and add military movement c.Add domestic in-migration and subtract domestic out-migration 2.Calculate proportions 3.Use proportions to distribute estimates a.State ASRO estimates b.County totals estimates 4.Convert from 4 to 31 races

54. 54 Characteristics Estimates: Comparison of the Methods Processing universes Controls Processing components Base population Estimated births Estimated deaths Estimated migration Use of Medicare data

55. 55 Issues for the Future: General Which universe(s) should we process in? What is the best method for using rates in the estimates? What are the appropriate geographic and ASRO levels for projecting components of change? What is the best way to calculate domestic migration?

56. 56 Issues for the Future: General (cont.) What is the best way to perform proportional distribution and controlled rounding? How should we estimate populations for which we have registries (school age population, 65+ population)?

57. 57 Issues for the Future: General (cont.) How can we maximize the resources of FSCPE members? –Information on components of population change? –Symptomatic indicators of population or component change? –State-produced population estimates? –Input from review?

58. 58 Issues for the Future: State Age-Sex Should we continue to process using the whole-interval approach? Should we process by sex as well as age?

59. 59 Issues for the Future: State & County Characteristics Can we move from 1990 race based processing to 2000 race based processing? Will person-based IRS migration give us better estimates of domestic movement than return-based migration?

60. 60 Issues for the Future: State & County Characteristics (cont.) Should we calculate intrastate migrants at the county level instead of calculating them at the state level and distributing to counties? Should we continue to use the previous vintage of estimates in intermediate processing?