THE TOWN WITH NO POVERTY Evelyn L. Forget Community Health Sciences University of Manitoba.
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THE TOWN WITH NO POVERTY
Evelyn L. ForgetCommunity Health Sciences
University of Manitoba
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PROJECT TEAM
• Evelyn Forget• Noralou Roos• Derek Hum• Ron Hikel
• Wayne Simpson• Richard Lobdell• Hugh Grant• Charles Burchill• Pat Nichol
We gratefully acknowledgeFinancial support: Canadian Institutes for Health Research MOP2005Data Access: Manitoba Health
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1974
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1974
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1979
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IN MANITOBA
• Ed Schreyer (age 39) was premier
• Roland Penner, subsequently Attorney General, was banned from travel to the US because of his communist sympathies
• The “RED Committee” of Cabinet [resources and economic development] sought social justice
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In Winnipeg
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DAUPHIN MANITOBA
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DAUPHIN MANITOBA1974
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DAUPHIN MANITOBA2005
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DAUPHIN MANITOBA1954 and 1974 and 2005
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Map: River CityNW NECourt house
High School
Communitycentre
Ukrainian OrthodoxChurch
Ukrainian CatholicChurch
Hospital
RR Station
Grain elevators
Arts Centre
“LittleChicago”
River
Railroad Tracks
MainStreet
Darla Rhyne,1979
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WHERE DID THE RED COMMITTEE LOOK FOR
INSPIRATION?
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A GUARANTEED ANNUAL INCOME
• Would save money because it would eliminate the duplicated bureaucracies of all the different social agencies
• Would be “just” because all people would be treated equally no matter what social programme they fell under– Horizontal equity– Vertical equity
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A GUARANTEED ANNUAL INCOME
• Would let people get beyond just “making ends meet”
• Would lengthen time horizon– Should a potentially useful adolescent son stay in
high school?– Can I afford adequate child care rather than expose
my kids to dangerous farm equipment?
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BUT
• If you pay them anyway, would people stop working?
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• Between 1965 and 1980, the US government funded 4 GAI social experiments
• The Canadian government funded one
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THE CANADIAN EXPERIMENT
• 2 sites
– A dispersed sample in Winnipeg– A saturation site in Dauphin MB
• The Dauphin site was the only saturation site in any of the 5 experiments
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A Dispersed Sample
• Allows you to get precise estimates of the impact of changes in the payout and tax-back rates without confounding
• Your subject is the only one who knows s/he is receiving payments and probably no one else of her acquaintance is in the experiment
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BUT
• If a social programme were to be implemented universally, the results of a dispersed sample might be highly misleading
• Subjects are in a highly artificial setting. They are receiving support, but not their friends and relatives
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A Saturation Site
• By definition has all kinds of confounding, because everyone is enrolled in the experiment, and knows that their friends and neighbours are also participating
• Social attitudes and behaviours are likely to change, which will affect the subjects’ behaviour independently of the support received
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How were MINCOME support levels determined?
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• In 1972, average income per taxpayer in Parklands was $3,820
• 69.6% of the provincial average
• $17,576 in today’s dollars
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MINCOME SUPPORT LEVELS RELATIVE TO CANADIAN INDICATORS OF LOW INCOME (2004 dollars)1
MINCOME MINCOME StatCan Family Size Median Income2 minimum3 breakeven4 LICO5 1 15089 5685 11370 9558 2 37246 10623 21246 15927 3 46491 13164 26328 19112 4 50890 14954 29908 222976 5 53481 17980 35960 25486
1 All financial figures were converted from their original levels to 2004 dollars using the Consumer Price Index. 2 See Income Distribution by Size in Canada: Preliminary Estimates, 1972. Statistics Canada Cat. No. 13-206, p. 9 3 These MINCOME support levels represent the minimum annual income a family would get under the MINCOME scheme. They represent the guarantee; if any member of the family earned any income from employment, self-employment or other sources, their actual family income would be higher because the “tax-back rate” is only 50%. For example, a family of 4 with $10,000 of earned income would actually have an annual income of $19,954 under MINCOME. That is, they would receive $9,954 under the scheme to supplement their labour market earnings. 4 This is the 2004 equivalent income at which no further benefits would be received. Families earning less than this limit would still receive supplemental payments from the scheme. 5 These limits were established by JR Podoluk (see Incomes of Canadians, Queen’s Printer, 1968, p. 185) and were used as low-income cut-offs by Statistics Canada in its Consumer Finance Survey Reports. That is, this is the period-specific LICO inflated by the Consumer Price Index to 2004 dollars. 6 For comparison purposes, the Year 2000 Market Basket Measure of Poverty for Rural Manitoba sets the unofficial poverty line at $22,932 for a family of 2 adults and 2 children.
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OUR INTERESTS
• Did the participants suffer less poverty under the GAI experiment?
• What would be the effects of less poverty?
• How long would the effects last after the intervention ended?
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In Particular,
• We know that health is a positive function of socio-economic status– Middle income people are healthier than poor people– High income people are healthier than middle income
people
• We know that overall health status is higher in a more equal society than in a less equal society
• But we don’t really know WHY or HOW income affects health
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HOW CAN WE DESIGN A PROJECT TO ANSWER OUR
QUESTIONS?
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CHALLENGE 1
• The data were never compiled and cleaned for analysis
• The health and social data were collected by survey from a subset of participants– Small samples
• The Federal Records Centre (on Inkster) has “1800 cubic feet of unspecified files” – and no finding guide
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SOLUTION
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BUT
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CHALLENGE 2
• We don’t know which of the people resident in Dauphin and its rural municipality during MINCOME actually received money
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SOLUTION
• Re-conceptualize the nature of a guaranteed annual income
• Income INSURANCE rather than income SUPPORT
• Hypothesis: Behaviour and health outcomes will be affected by the PROMISE that no one will have an income of less than the guaranteed rate
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SOLUTION
• EVERYONE in the saturation site received the treatment
• Some lives will be affected more than others
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CHALLENGE 3
• Many things happened since 1974
• How do we know that changes we find are the result of MINCOME?
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SOLUTION
• Create a contemporaneous control group
• Choose 3 or 4 Manitobans who do not live in Dauphin in 1974, and match them to people who do live in Dauphin
• Compare differences
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PROPENSITY MATCHING
• Individual: age, sex• Family: age of mother at birth of first child,
number of children, single parent female led
• Community: rural/small town; Socio-economic Status (income, education); geography
• Geography
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CHALLENGE 4
• Maybe Dauphin is just different
• Perhaps differences have nothing to do with MINCOME
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SOLUTION
• Create a second control
• Use “Dauphin” as a control for itself
• Match each experimental subject to 2 sex-matched Dauphin residents a few years older – town to town; rural municipality to rural municipality
• Compare age-specific outcomes
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SOLUTION
• Can we use sibling controls?
– 2 sex-matched siblings from Dauphin, so the older serves as a control for the younger
– A matched pair from out-of-Dauphin, so that the pair serves as a community control for the Dauphin pair
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CHALLENGE 5
• How do we convince a funding committee that we are likely to find something?– No one has used “income security” as we
have– MINCOME only distributed money for 3 years– No one has used administrative data the way
we propose
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SOLUTION
• A file survey done in Winnipeg during the winter of 1972-3 found:– 17% were on welfare less than 3 months, – 18.7% for 4-12 months,– 26.1% for 13-24 months, – 15.4% for 25-36 months, – 5% for 37-48 months,– 17.8% for more than 48 months
• That is: 3 years may be “long enough”
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SOLUTION
Grade 12 Enrolment as % Previous Year Grade 11 Enrolment
0.0
20.0
40.0
60.0
80.0
100.0
120.0
Dauphin
Winnipeg
Non-Winnipeg
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SOLUTION
• We acknowledge that, for most people, the effects of MINCOME will not persist for long after the payments stop
• But for those who receive support during vulnerable periods, the effect may be life-long (and may even affect their children)
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CHALLENGE 6
• How will we analyze the data?– Registry data from 1970 to present– Hospital files from 1970 to present– Physician files from 1970 to present– Birth outcomes from mid-70s– Pharmaceutical files from 1996 to present– School data from 1991 to present– Social services data from 1991 to present