Demo analysis05 02
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  • Defacto - all the people actually present in a given area at a given time Dejure - all the people who “belong” to a fiven area at a given time by virtue of legal residence, usual residence, or similar criterion Usual place of residence - U.S. standard for Decennial Census more closely represents dejure count - the geographic place where the enumerated person usually resides. - dual residences - special populations: college, prison, armed forces - travelers - persons with no usual residence
  • Defacto - all the people actually present in a given area at a given time Dejure - all the people who “belong” to a fiven area at a given time by virtue of legal residence, usual residence, or similar criterion Usual place of residence - U.S. standard for Decennial Census more closely represents dejure count - the geographic place where the enumerated person usually resides. - dual residences - special populations: college, prison, armed forces - travelers - persons with no usual residence
  • Defacto - all the people actually present in a given area at a given time Dejure - all the people who “belong” to a fiven area at a given time by virtue of legal residence, usual residence, or similar criterion Usual place of residence - U.S. standard for Decennial Census more closely represents dejure count - the geographic place where the enumerated person usually resides. - dual residences - special populations: college, prison, armed forces - travelers - persons with no usual residence

Transcript

  • 1. Course Objectives
    • Provide a general understanding of demographic processes
    • Relate this to available data sources
    • Understand limitations of methods and data
    • Understand how the Cohort Component method for population projections works
    • Understand why we use the Cohort Component method
    • Leave with a model that allows you to prepare county level population projections
  • 2. Objectives of Participants
    • Problems faced:
      • what is “best” method for pop. Projections
      • need to defend methodology and validity of projections
    • What application areas do demographic projections impact:
      • education
      • health planning
      • transportation
      • watershed buildout
  • 3. Objectives of Participants
    • What demographic data do you need
      • sub-county projections by age and race
      • sub-county income and poverty estimates
    • Do you buy demographic data - NO
    • Decisions/Recommendations
      • grant applications
      • research
      • future needs
    • What do you hope to learn
      • understand methodology/variables to be used
      • advantages of different methods
  • 4. Measuring Population Change
    • Some definitions:
      • Residence (defacto, dejure)
      • Residents (total, non-institutional, GQ, HH pop)
      • Time period (monthly, annual, 5-year, 10-year)
      • Geographic area
      • Coverage
      • Age
        • age heaping
        • grouped data
  • 5. Some Statistical Terms
    • Proportions: the number of observations of a subgroup divided by the total number of observations. The value in the numerator is a part of the denominator.
      • What’s the proportion of women in the population ??
    • Total Females / Total Population
    • Percentage: a proportion expressed per 100 cases
      • What percentage of the population is female?
    • Total Females / Total Population * 100
  • 6. Some Statistical Terms
    • Rate: the number of events in a given time period divided by the population (usually the average over the period of time - midpoint, often expressed per 1000 population)
      • What’s New York’s birth rate?
      • No. of Births / Total Population * 1000
    • Probability: a rate expressed for the population at the beginning of the period - the population at risk
      • What is the probability of a person exact age 23 dying before reaching their 30th birthday?
      • You don’t really want the formula!!
  • 7. Population Change
    •  = P 1 - P 0
    • New York State, 1990 to 2000
    • 985,679 = 18,976,457 - 17,990,778
    • Average Annual Change
    • 98,568 = 985,679 / 10
    • Assumes that change is linear
  • 8. Population Change - Linear
    • Percent Change
    • %  =  / P 0 * 100
    • 5.4788 = 985,679 / 17,990,778 * 100
    • Average Annual Percent Change
    • .5479 = 5.4788 / 10
    • Average Annual Growth Rate
    • r =  / (1/2 (P 0 + P 1 ))
    • r = (985,679 / 18,483,617) / 10
    • r = 0.0053327
  • 9. How Does Population Change
    • 1. People are born into a population
    • 2. People die and leave the population
    • 3. People migrate to and from areas
  • 10. Components of Change The Balancing Equation
    • Closed Population
    • P 1 = P 0 + (B - D) + e
    • Opened Population
    • P 1 = P 0 + (B - D) + (I - O) + e
    • P 1 = P 0 + (B - D) + (NM) + e
  • 11. Components of Change
    • Births and Deaths
      • Vital Statistics Registration System - Vital Events
      • Birth, Death, Induced Termination, Marriage, Divorce
      • Place of residence vs. place of occurance
      • Reported to county office of vital statistics
      • Compiled by State Department of Health, National Center for Health Statistics (NCHS)
      • 1 to 2 year reporting lag
  • 12. Components of Change
    • Migration
      • Few direct measures
      • Decennial Census: residence 5 years earlier
      • Internal Revenue Service: address changes on tax returns
      • Residual Estimates: what’s left over
  • 13. New York State Components of Change
    • P 1 = P 0 + (B - D) + NM
    • 18,976,457 = 17,990,778 +
    • Births 1 : 2,943,192 -
    • Deaths 1 : 1,740,620 +
    • Net Migration: -216,893
    • 1 - estimated from NYS DOH/NCHS
  • 14.  
  • 15. Declining County - Clinton Components of Change
    • P 1 = P 0 + (B - D) + NM
    • 79,894 = 85,969 +
    • Births 1 : 9,904 -
    • Deaths 1 : 6,136 +
    • Net Migration: -9,843
    • 1 - estimated from NYS DOH/NCHS
  • 16.  
  • 17. Stable County - St. Lawrence Components of Change
    • P 1 = P 0 + (B - D) + NM
    • 111,931 = 111,974 +
    • Births 1 : 13,398 -
    • Deaths 1 : 10,194 +
    • Net Migration: -3,247
    • 1 - estimated from NYS DOH/NCHS
  • 18.  
  • 19. Growing County - Richmond Components of Change
    • P 1 = P 0 + (B - D) + NM
    • 443,728 = 378,977 +
    • Births 1 : 60,890 -
    • Deaths 1 : 34,246 +
    • Net Migration: 38,107
    • 1 - estimated from NYS DOH/NCHS
  • 20.  
  • 21. The Balancing Equation - Refined
    • For females, 20 to 24 years old
    • P 1 20-24,f = P 0 20-24,f + (B 0,1 20-24,f - D 0,1 20-24,f ) + NM 0,1 20-24,f
    P 1 = P 0 + (B - D) + NM
    • For population sub-groups:
    • P 1 a,s,r = P 0 a,s,r + (B 0,1 a,s,r - D 0,1 a,s,r ) + NM 0,1 a,s,r
    P 1 20-24,f = P 0 15-19,f + (B 0,1 20-24,f - D 0,1 15-19,f ) + NM 0,1 15-19,f
  • 22. Population Change
    • Period Analysis vs. Cohort Analysis
    • Cohort Statistics - a population subgroup that shares a common demographic event, e.g. age cohort, marriage cohort
    • Period Statistics - a combination of cohorts observed at a given point in time
  • 23.  
  • 24. Birth Year Age Progression
  • 25. Population Change by Age
  • 26. Population Pyramid
  • 27. Cohort Component Model (cont’d)
  • 28. Cohort Component Model (cont’d)
  • 29. Cohort Component Model (cont’d)
  • 30. Cohort Component Model (cont’d)
  • 31. Cohort Component Model (cont’d)
  • 32. Cohort Component Model (cont’d)
  • 33. Cohort Component Model (cont’d)
  • 34. Cohort Component Model (cont’d)