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The Prince and the Pauper:
Movement of Children Up and Down the Canadian Income Distribution
Peter Burton and Shelley PhippsDalhousie University
P. Burton and S. Phipps Dalhousie University
Acknowledgements
Lihui Zhang, for excellent research assistance
Atlantic Research Data Centre for access to the data
P. Burton and S. Phipps Dalhousie University
Introduction
Use Statistics Canada’s National Longitudinal Survey of Children and Youth (NLSCY) to study family income for a cohort of Canadian children between 1994 and 2004
Children 0 to 7 in 1994; 10 to 17 in 2004Longest panel of data yet available in CanadaLinks to sense of self, aspirations, well-being?
P. Burton and S. Phipps Dalhousie University
Five questions:
1. What happens to the level of family income as children grow up?
2. What happens to income inequality among children?
3. How much movement up and down the distribution takes place?
4. What are characteristics associated with being ‘stuck at the bottom’ or ‘secure at the top’ of the distribution?
5. What are the correlates of moving up or down the distribution?
P. Burton and S. Phipps Dalhousie University
DataNLSCY representative of Canadian child
populationInterviews every 2 years (6 cycles,
spanning 10 years)Use information provided by the ‘person
most knowledgeable’ about the childSelect 7,163 children with complete
income and family size dataLongitudinal weights; bootstrap for
complex survey design
P. Burton and S. Phipps Dalhousie University
Question 1. Trends in Income Levels?
Expect real growth, on average◦Parental life-cycle (finish education, gain
seniority with higher wages and more job security)
◦Mothers returning to paid work and/or increasing paid hours
But, odds of parental divorce also increase
P. Burton and S. Phipps Dalhousie University
Changes in family characteristics
Family sizeProbability of living in lone parent familyPaid work participation and hours of
participation‘High hours’ (greater than 80 per week for
two-parent families; greater than 40 for lone-parent families)
P. Burton and S. Phipps Dalhousie University
Changing Family Composition
1994 1996 1998 2000 2002 2004
Child Age Range0-7 2-9 4-11 6-13 8-15 10-17
Percent Lone Parent
14.3 15.5 14.9 16.8 19.0 20.4Mean Household Size
4.2 4.3 4.4 4.4 4.3 4.2
P. Burton and S. Phipps Dalhousie University
Paid Work in Two-Parent Families
1994 1996 1998 2000 2002 2004
Child Age Range0-7 2-9 4-11 6-13 8-15 10-17
Percent Two-Earner 55.7 71.4 76.2 79.8 79.6 83.8Mean Weekly Paid Hours (Mother + Father hours) 59.1 65.4 68.5 70.1 70.9 73.1
P. Burton and S. Phipps Dalhousie University
Paid Work Participation in Lone-Parent Families
1994 1996 1998 2000 2002 2004
Child Age Range 0-7 2-9 4-11 6-13 8-15 10-17
Percent with Paid Work
41.1 66.5 75.4 81.7 84.2 84.8Mean Paid Hours in Lone-parent families
14.1 23.3 26.3 30.7 32.1 32.8
P. Burton and S. Phipps Dalhousie University
Two parents more than 80 hours; lone parent more than 40 hours
1994 1996 1998 2000 2002 20040
5
10
15
20
25
30
35
40
18.3
22.4
27.4
31.9 32.935.5
% with ‘High
Hours’
P. Burton and S. Phipps Dalhousie University
Measure of Family Income‘Person most knowledgeable’ about the
child reports incomePre-tax annual income from all sources
including government transfersAdjust for differences in need for families
of different size using Luxembourg Income study ‘equivalence scale’ (square root of family size)
Actual income of $80,000 for family of 4 means ‘equivalent income’ of $40,000
P. Burton and S. Phipps Dalhousie University
Mean equivalent family income, in 2004 dollars
1994 1996 1998 2000 2002 20040
5000
10000
15000
20000
25000
30000
35000
40000
45000
29918 3070634373
37403 38082 38276
P. Burton and S. Phipps Dalhousie University
Is income growth the same at all points in the distribution?
Compute mean equivalent income in each year for each income decile
Decile cut points defined using the NLSCY (i.e., families with children)
1994 1996 1998 2000 2002 20040
20,000
40,000
60,000
80,000
100,000
120,000
P. Burton and S. Phipps Dalhousie University
Are children at the top ‘pulling ahead’ of those at the bottom?
Real growth in all decilesConsiderable inequality among children,
but ratio of mean income in top decile to mean income in bottom decile 9.42 in 1994; 9.39 in 2004
P. Burton and S. Phipps Dalhousie University
Question 2. Trends in Inequality?
Inequality among children would be expected to increase over time as some parents ‘make it’ in the labour market while others fall behind
On the other hand, some families may catch up as mothers increase paid hours
P. Burton and S. Phipps Dalhousie University
Compute standard measures of income inequality for each year for our cohort of children
Choose measures sensitive to different parts of the distribution (CV is sensitive to the top; Gini to the middle and Atkinson to the bottom)
Also compute all measures using six-year average income
P. Burton and S. Phipps Dalhousie University
Measures of Income Inequality
1994 1996 1998 2000 2002 2004
Long-run
Average Income
Coefficient of variation 0.679 0.788 0.753 0.801 0.716 0.701 0.622
Gini coefficient 0.334 0.345 0.328 0.339 0.325 0.321 0.293
Atkinson (eps =2) 0.335 0.340 0.317 0.314 0.326 0.328 0.247
Theil 0.188 0.214 0.196 0.214 0.189 0.186 0.150
P. Burton and S. Phipps Dalhousie University
Key findingsNo obvious trend in annual income inequality
for this cohort of children◦High-end sensitive CV shows highest inequality in
middle years◦Low-end sensitive Atkinson shows lowest inequality
in middle years
Inequality among children less than in population over-all; these inequality measures slightly higher because for pre-tax income
P. Burton and S. Phipps Dalhousie University
Annual versus ‘permanent’ income inequality
Inequality of six-period income lower than inequality in any particular year
True for all measures of inequality and regardless of comparison year
P. Burton and S. Phipps Dalhousie University
Theil Decomposition
Theil index allows de-composition of total inequality into ‘within group’ inequality plus ‘between group’ inequality
In our application, ‘within group’ is for the same child across six cycles; ‘between group’ is permanent income across different children
De-composition suggests inequality of ‘permanent income’ about 75 percent of total
P. Burton and S. Phipps Dalhousie University
Question 3. Are the Same Children Always at the Bottom (or Top) of the Income Distribution?What percent of children who start in
bottom quintile in 1994 are again in bottom quintile in 2004?
What percent of children who start in top quintile in 1994 are again in top quintile in 2004?
Considerable ‘stickiness’ of position evident
P. Burton and S. Phipps Dalhousie University
1994 to 2004 Transition Matrix
Bottom Quintile 2004
2nd Quintile 2004
3rd Quintile 2004
4th Quintile 2004
Top Quintile 2004
Bottom Quintile 1994
0.51 0.25 0.14 0.06 0.04
2nd Quintile 1994
0.26 0.28 0.25 0.14 0.07
3rd Quintile 1994
0.12 0.25 0.30 0.23 0.10
4th Quintile 1994
0.07 0.14 0.22 0.34 0.24
Top Quintile 1994
0.03 0.08 0.08 0.24 0.58
P. Burton and S. Phipps Dalhousie University
Transition Matrix for Children of Immigrants
Bottom Quintile 2004
2nd Quintile 2004
3rd Quintile 2004
4th Quintile 2004
Top Quintile 2004
Bottom Quintile 1994
0.67 0.15 0.07 0.07 0.05
2nd Quintile 1994
0.18 0.31 0.34 0.07 0.10
3rd Quintile 1994
0.12 0.39 0.22 0.16 0.10
4th Quintile 1994
0.14 0.08 0.23 0.35 0.19
Top Quintile 1994
0.02 0.06 0.11 0.23 0.58
P. Burton and S. Phipps Dalhousie University
‘Lenses’
What happens during intervening years?
How many children ever exposed to a position of low income?
How many children always (in all six cycles) in a position of low income?
P. Burton and S. Phipps Dalhousie University
0 10 20 30 40 50 60 70 80 90100
0
10
20
30
40
50
60
70
80
90
100
26.1
42.2
54.3
65.1
73.9
81.987.8
92.997.0
100.0
0.01.3
4.79.9
16.6
24.2
34.8
46.5
60.9
78.2
100.0
Figure 2. Relative Income "Lens"
Always Below
Ever Below
Equivalent Income Percentile
Percentof Children
Link
P. Burton and S. Phipps Dalhousie University
Key points from lenses
More children ‘ever’ exposed to low income than cross-sectional data suggest (42 percent were ‘ever’ in bottom quintile)
Only about 5 percent ‘always’ in the bottom quintile, but this group of great policy relevance
Links to social exclusion?Note: children of immigrants especially
likely to be ‘stuck’ at bottom
P. Burton and S. Phipps Dalhousie University
0 10 20 30 40 50 60 70 80 90 1000
10
20
30
40
50
60
70
80
90
100
0.0
40.0
63.6
80.9
92.5
100.0
0.03.9
15.5
33.5
60.3
100.0
0.0
54.5
73.5
86.9
95.1100.0
0.0
9.1
22.7
42.3
64.3
100.0
Relative Income Lenses, Immigrants and NonIm-migrants
Immigrant, Always Below
Immigrant, Ever Below
NonImmigrant, Always Below
NonImmigrant, Ever Below
Equivalent Income Percentile
Percentof Children
P. Burton and S. Phipps Dalhousie University
Question 4a. Characteristics of Children ‘Exposed to’ or ‘Stuck’ at BottomEstimate probit models of the correlates of
‘ever’ and ‘always’ being in the bottom quintile
Dependent variable uses full six-cycle historyExplanatory variables ‘starting point risks’
(1994 values):◦Region◦Age, education, ethnicity, immigrant, marital and
employment/student status of parent◦Age of child and number of siblings
P. Burton and S. Phipps Dalhousie University
‘Ever’ Bottom Quintile
‘Always’ Bottom Quintile
Child age-0.017(0.013)
-0.047**
(0.020)
Number of siblings0.147***
(0.034)0.164**
(0.067)
Lone mother1.300***
(0.100)1.051***
(0.133)
Pmk Age-0.293***
(0.092)-0.002(0.012)
Pmk non-white0.168
(0.182)0.574*
(0.294)
Pmk Immigrant0.460***
(0.123)0.315
(0.264)
Pmk no paid hours0.651***
(0.067)0.922***
(0.157)
P. Burton and S. Phipps Dalhousie University
‘Ever’ Bottom Quintile
‘Always’ Bottom Quintile
Region
Atlantic 0.377***
(0.081)0.766***
(0.156)
Quebec 0.201**
(0.089)0.374**
(0.180) Manitoba/Saskatchewan
0.284***
(0.092)0.084
(0.229)
Alberta 0.054(0.115)
-0.038(0.291)
BC 0.244**
(0.101)0.165
(0.232)
P. Burton and S. Phipps Dalhousie University
‘Ever’ Bottom Quintile
‘Always’ Bottom Quintile
Pmk Education Less than High School
0.681***
(0.111)0.253
(0.198) Some Post-Secondary
-0.191**
(0.089)-0.204(0.193)
University -0.293***
(0.092)-0.411*
(0.236)
Pmk student -0.063(0.120)
-0.630***
(0.243)
P. Burton and S. Phipps Dalhousie University
Key results from probit regressions for ‘ever’ in bottom quintile:In order of size of association, a child is at
greatest risk of ‘ever’ being at the bottom of the distribution for his/her cohort if he/she:◦Lives in a lone-mother family ◦Parent has less than high-school education◦Parent has no paid hours◦Parent is an immigrant◦Family lives in Atlantic Canada
P. Burton and S. Phipps Dalhousie University
Key results from probit regressions for ‘always’ in bottom quintile:In order of size of association, a child is at
greatest risk of ‘always’ being at the bottom of the distribution for his/her cohort if he/she:◦Lives in a lone-parent family◦Has a parent with no paid work◦Lives in the Atlantic region◦Has a parent who is non-white
P. Burton and S. Phipps Dalhousie University
Simulated Probability of Always Being in the Bottom Quintile
Base Lone Parent Pmk Unpaid Atlantic Non-white0
0.5
1
1.5
2
2.5
3
3.5
4
P. Burton and S. Phipps Dalhousie University
Question 4b: Characteristics of Children ‘Exposed to’ or ‘Secure’ at the Top
Repeat probit analyses with 2 new dependent variables; same explanatory variables
Results mostly symmetric
P. Burton and S. Phipps Dalhousie University
Question 5. Which characteristics are associated with movements up or down?Estimated conditional logit models of
movements into or out of the bottom quintile (14,790 movements in/out of bottom; 12,864 movements in/out top)
Procedure excludes children who never move in or out
Explanatory variables are now ‘changes’ (so ethnicity and immigrant status dropped)
P. Burton and S. Phipps Dalhousie University
Key results from conditional logit modelsIn order of size of association, the most important changes associated with moving into or out of the bottom quintile are:◦Divorce/re-marriage of parents◦Regional migration◦Changes in employment status of parent◦Parent finishing or returning to school◦Change in number of siblings
See odds ratios
P. Burton and S. Phipps Dalhousie University
Bottom Quintile Top QuintileRegion Atlantic 4.108* 0.200 Quebec 1.205 0.049 Man/Sask 10.684*** 0.634 Alberta 2.530 1.815 BC 5.319* 1.102Pmk Education Less than High School 1.048 1.075 Some Post-Secondary 0.893 1.339 University 0.686** 1.881***
Lone parent 17.017*** 0.052***
Pmk student 1.561** 0.710**
Number of siblings 1.304*** 0.542***
Pmk no paid hours 2.539*** 0.335***
P. Burton and S. Phipps Dalhousie University
Fixed Effects Estimates of Change in Percentile RankNot just ‘in or out’ of top/bottom, but ‘how
far’ up or down the relative income distribution does child move with particular change in co-variate?
Estimate fixed effects models for change in percentile position
Coefficient Standard Error Atlantic -11.810*** 2.183 Quebec -4.044 3.641 Manitoba/Saskatchewan -10.005*** 2.515 Alberta -3.972 2.813 BC -2.642 2.837 Less than High School -1.094 (0.950) Some Post-Secondary 0.788 (0.602) University 2.724*** (0.630)Lone parent -22.360*** (0.739)Pmk student -3.571*** (0.626)Number of siblings -2.827*** (0.283)Pmk no paid hours -7.062*** (0.489)
P. Burton and S. Phipps Dalhousie University
Key points:
Largest movements up/down the distribution associated with changes in marital status; regional migration
P. Burton and S. Phipps Dalhousie University
Conclusions
Use longitudinal data tracking a cohort of Canadian children from 1994 to 2004 (from ages 0 to 7 until ages 10 to 17)
Real growth at all points in income distribution; no trends in inequality as this cohort of children grows up
Lower measured inequality of ‘permanent income’
75 percent of inequality is attributable to ‘permanent income’
P. Burton and S. Phipps Dalhousie University
Considerable beginning to end of period ‘stickiness’ of relative income position
Only 5 percent ‘always’ in bottom quintile, but this is a group of particular policy concern
But, more exposure to low income than cross-sectional data suggest
Parental marital and employment status, region of residence and ethnicity key correlates of relative income position
Largest movements up/down the distribution associated with change in parental marital status and regional migration
P. Burton and S. Phipps Dalhousie University
P. Burton and S. Phipps Dalhousie University
0 10 20 30 40 50 60 70 80 90 1000
10
20
30
40
50
60
70
80
90
100
0.0 1.34.7
9.9
16.6
24.2
34.8
46.5
60.9
78.2
100.0
26.1
42.2
54.3
65.1
73.9
81.987.8
92.997.0
Relative Income Lenses: Actual
Ever Below
Always Below
Equivalent Income Percentile
Percent of Children
P. Burton and S. Phipps Dalhousie University
0 10 20 30 40 50 60 70 80 90 1000
10
20
30
40
50
60
70
80
90
100
0.1 0.4 1.64.7
11.8
26.2
53.1
0.0
46.9
73.8
88.2
95.398.4 99.6 99.9
Relative Income Lenses: Actual, Random
Ever Below
Always Below
Random Ever Below
Random Always Below
Equivalent Income Percentile
Percent of Children
P. Burton and S. Phipps Dalhousie University
0 10 20 30 40 50 60 70 80 90 1000
10
20
30
40
50
60
70
80
90
100
40
0
10
20
30
40
50
60
70
80
90
100
60
0.1 0.4 1.64.7
11.8
26.2
53.1
0.0
46.9
73.8
88.2
95.398.4 99.6 99.9
Relative Income Lenses: Actual, Random, Max and Min
Ever Below
Always Below
Random Ever Below
Random Always Below
Max Ever Below
Max Always Below = Min Ever Below
Min always Below
Equivalent Income Percentile
Percent of Children
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