Post on 26-Dec-2015
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Modeling Future Senior/Elder Populations:
Predicting Size, Ages, and Gender Makeup
Presented By:Senior Mobility Initiative on Cape Cod
(SMICC)
Dr. Alice E. SmithWarren K. Smith, BSEE, ASA
Saturday, March 10, 20072007 Joint Conference of The American Society on Aging and the
National Council on Aging
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Senior/Elder Population Modeling
An analytical tool that assists researchers to predict the future number, ages, and gender of senior/elder populations (state, region, county, city, town, or ZIP Code area).
Developed to assist senior/elder mobility services planners, such estimates are invaluable to anyone needing estimates of age 55+ populations for up to 30 years into the future.
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Why Do Predictions Ourselves?
• Why not use State Data Center predictions?– County- and Town –level only available– Crude knowledge of in/out migration
• Cape Cod’s justification:– ZIP Code-level population counts needed– “Retirement migration” needs to be
included– Need “What If’ modeling capability
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Simple Population Model
Starting Population
(1980 Census)
Ending Population
(1990 Census)
Births
Deaths
In Migration
Out Migration
“Cohort-Component Method”
(Developed by U.S. Census Bureau)
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Model ComponentsStarting Population:
U.S. Census Counts by 5-Year Age Group
Births:
Birth Certificate data
Deaths:
Death Certificate data
Migration: In ?? Out ??
Ending Population:
U.S. Census Counts By 5-Year Age Group
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Dilemma
Problem:
We Don’t Have Accurate Migration Data!
Solution:
We Have To Calculate It
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Concept of “Net Migration”
To Model a Population, Knowing The Net Number of In-Migrants and Out-Migrants by Age
Group is Sufficient
This Fact Simplifies Our Calculation
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Calculating Senior/Elder Net
Migration
Deaths
Starting Population
(1980 Census)
Ending Population
(1990 Census)
Births
Net Migration
Cohort-Component Method
(Can Ignore For Senior/Elder Age Ranges)
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Solving For Net Migration
of Seniors/EldersNet Migration: Ignoring Births, Net Migration is Simply The Difference Between Starting Population Minus All Deaths and The Ending Population Count;
Where: PEnd = PStart - D + MNet
Therefore: MNet = PStart - D - PEnd
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Studied Past Population Dynamics
Historic Senior/Elder Population Dynamics: 1980-2000
Determined Growth History For EACH Age Group:
Ages 40-44, 45-49, 55-59, 60-64, 65-69, 70-74, 75-79, 80-84, 85+
Calculated 20-Year AVERAGE Migration Factor For Each Age Group
1980 Census
Census 2000
1990 Census
Cohort-Component Method
Cohort-Component Method
(“Boomers” in their 30’s and 40’s) (“Boomers” in their 40’s and 50’s)
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Predicting Future Populations
Death Rates (by Age Group)
Starting Population Counts (by Age Group)
Historic 20-Year
AVERAGE Migration Rates
(By Age Group)
Ending Population Counts
(By Age Group)
Microsoft
EXCEL
Spreadsheet Model
“What If” Factors
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Result: Population Predictions
(Numbers of Persons by Age Group)
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Town-Level Predictions
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Q & A
** Discussion **
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Contact Information
Dr. Alice E. Smith– President, Family-Centered
Institute, Inc. 66 Massasoit Trail Brewster, MA 02631 alismith@clarku.edu
Warren K. Smith– Chairperson, Senior Mobility
Initiative on Cape Cod c/o Family-Centered
Institute, Inc. 66 Massasoit Trail Brewster, MA 02631
wsmithstat@aol.com
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Introductory Remarks:
Good Morning.
My name is Dr. Alice Smith and I am here with my colleague (and husband), Warren to tell you about a method that we have been using up on Cape Cod in Massachusetts to predict what our future senior/elder population will look like—10-, 15-, 20-, even 30-years into the future.
Briefly, we put historic Census statistics and other key demographic data into a computer spreadsheet (Microsoft EXCEL) and developed formulas that MODEL how our senior/elder population has changed in the past—the dynamics of it. From this retrospective MODEL, and some thoughtful assumptions about future changes, we have been able to predict the basic charac- teristics of our FUTURE senior/elder population—from 2010 out to the year 2035.
How do we use these predictions? Planners on Cape Cod are beginning to use this information as they develop long-range plans for a variety of programs and services for our rapidly growing “Baby Boomer” population—or should I say, “Senior Boomers”? Our local Area Agency on Aging (Elder Services of Cape Cod & Islands) and several of our municipal Councils on Aging are using these population predictions in their strategic planning. Also, we have had great interest from our regional emergency planning organizations, as well as Fire Chiefs and municipal EMS/EMT service planners. One of our larger towns (Falmouth) is using our population predictions to justify building a new multi-million dollar Senior Center. In addition, Grant writers are beginning to use this information as they develop county, state, and federal funding proposals.
In our own research, we use these population predictions as the basis of what we call our Senior MoAbility Indicators (presented in our Workshop yesterday morning). These Indicators are a set of twenty mobility characteristics that serve to generally describe the ability of seniors and elders to “get up, get out, and get about” in their community—again, a tool for planning future senior/- elder programs and services.
Now, my husband Warren is going to tell you briefly about how the future population prediction MODEL was developed, how it works and show you a few examples of how it is being utilized. Warren . . . .