Population and Society Lectures 9 & 10

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Demographic Challenges and Opportunities in the Waikato
Region: An A-B-C Approach to Population Ageing
HAMILTON in Context
Natalie Jackson ©
Professor of Demography
Director,
Population Studies Centre
2010
1
NZ: Will grow, but..
Actual and Projected
Past
Projected
Stats NZ (2009 base)
2
Hamilton City – also projected to grow,
but..
250,000
200,000
High
Number
Medium
Low
150,000
100,000
50,000
Stats NZ (Projected TA, 2006 Base, Table 2)
2031
2026
2021
2016
2011
2006
0
Does NZ need 8 million?
…. A debate we don’t need to have
• he tangata
he tangata
he tangata
• Demographic
interpretation:
tis composition
tis composition
tis composition
4
As elsewhere, New Zealand is ‘ageing’
1966 (8.3% 65+)
2009 (12.8% 65+)
37
26
Percentage at each age
5
What does it mean to ‘age’?
Population Ageing in four dimensions
• Numerical Ageing
– Increase in numbers of elderly (primarily
caused by increased life expectancy)
• Structural ageing
– Increase in proportions of elderly (primarily
caused by low/falling birth rates)**
• Natural decline
– More elderly than children   more deaths
than births
• Absolute decline
– Inability of ‘replacement migration’ to replace the
‘lost’ births and increased deaths
6
NZ Elderly: Children
1,600,000
0-14 years
1,400,000
65+ years
1,200,000
Number
Projected
1,000,000
800,000
Crossover 2023
600,000
400,000
200,000
Projections: Stats NZ (2009) Medium Variant Series 5 (ANM 10,000; TFR 1.9)
2056
2046
2036
2026
2016
2009
2001
1991
1981
1971
1961
1951
1936
1921
1911
1901
0
7
Projected Change by Broad Age Group
Series 5
NZ
65+ Years
All other age
groups
combined
2009-2016
(7.3%)
26.4%
4.5%
2009-2026
(15.7%)
70.8%
7.6%
Stats NZ (2009) Series 5 = TFR 1.9; ANM 10,000
8
8
NZ Labour Market Entrants : Exits
700,000
15-24 years
600,000
55-64 years
500,000
Number
Projected
Crossover 2021-2051?
400,000
300,000
200,000
100,000
Projections: Stats NZ (2009) Medium Variant Series 5 (ANM 10,000; TFR 1.9)
2056
2046
2036
2026
2016
2009
2001
1991
1981
1971
1961
1951
1936
1921
1911
1901
0
9
Enter: a demographically tight
labour market
Australia 2007-200910
NZ: TA’s with negative entry/exit ratios
30
Percentage
29
39%
29
28
28
27
27
36%
26
2006
2007
2008
2009
11
Waikato Regions
Labour Market Entry/Exit Ratios
Stats NZ TableBuilder Estimated
Subnational Populations
12
13
The A-B-C of Population Ageing
• Accept
– Population ageing has
been unfolding for a
long time – it is coming
to a town near you
• Buffer
– Revisit /revise current
policies, practices, plans
(UN 2001)
• Celebrate
– We ‘know’ a lot about
this future; we can
strategise for it
positively; it will contain
many opportunities
14
Challenges and Opportunities
for the Waikato
A story in age structures
15
The growth forecast (Annual growth rates)
Waikato grows under all scenarios
Stats NZ (2006) Series 5 (TFR 1.9; ANM 10,000; medium mortality)
16
But the Waikato is also ageing
-just a little slower than total NZ
1996 (11% 65+)
2006 (12.5% 65+)
Percentage at each age
17
Almost all the growth is at older ages
Projected Waikato Region 2011-2021 and 2011-2031 (Medium Series 5)
120
2011-2021 (+7.1%)
Percentage Change
100
80
2011-2031 (+12.4%)
60
40
20
0
85+
80-84
75-79
70-74
65-69
60-64
55-59
50-54
45-49
40-44
35-39
30-34
25-29
20-24
15-19
10-14
5-9
0-4
-20
age
Stats NZ (2006) Series 5 = National TFR 1.9; ANM 10,000; medium mortality
18
Hamilton City – growth and ageing
16,000
14,000
Numbers
12,000
2011-2021 (+13%)
2011-2031 (+25%)
10,000
8,000
6,000
4,000
2,000
0
0–14
Stats NZ (Projected TA, 2006 Base, Table 4)
15–39
40–64
65+
The ageing forecast: Broad Age Groups
Series MEDIUM 65+ Years
Hamilton City
Waikato
All other age
groups
combined
2011-2021
(13%)
(7.1%)
41.3%
38.3%
9.5%
2.2%
2011-2031
(25%)
(12.4%)
88.4%
79.4%
17.3%
1.8%
Stats NZ (2006) Series 5 = National TFR 1.9; ANM 10,000; medium mortality
20 20
.. some of Waikato’s regions are ageing
faster than others:
Thames-Coromandel (23% 65+)
Percentage at each age
2009 (2006 unshaded)
Hauraki (19% 65+)
21
Also faster than Waikato average:
Matamata-Piako (16.5% 65+)
Percentage at each age
2009 (2006 unshaded)
Waipa (15.0% 65+)
22
Te Awamutu faster than Waipa..
Te Awamutu (19.7% 65+)
Percentage at each age
2009 (2006 unshaded)
Waipa (15.0% 65+)
23
Some are ageing slower:
Franklin (11.5% 65+)
Otorohanga (11.4% 65+)
Percentage at each age
2009 (2006 unshaded)
24
And somewhat slower again:
Hamilton City (10.4% 65+)
Waikato District (10.7% 65+)
Percentage at each age
2009 (2006 unshaded)
25
26
So.. what would the ‘Tight 5’ and ‘Big 11’ look like?:
Tight Five (12.0% 65+)
Percentage at each age
2009 (2006 unshaded)
Big 11 (13.1% 65+)
27
How well would such amalgamations
serve the underlying demographic
constituencies?
Competition for workers
End of unemployment?
Workers: who you ‘gonna call?
Males
Females
Demographic Dividend
Stats NZ Estimated Resident Population 2009, Waikato and NZ (unshaded)
30
A
challenge..
and an
opportunity
31
Who will be the workers?
2006 Census: Waikato, European and Maori percentage by age
European/NZ (14.2% 65+)
Maori (4.2% 65+)
38
23
Percentage at each age Census 2006
33
Waikato Region by Ethnicity* 2006
Male
Female
*Stats NZ Multiple Count Ethnicity
34
Hamilton City by Ethnicity* 2006
Male
Female
*Stats NZ Multiple Count Ethnicity
35
And what will be the industry?
Waikato’s Grain, Sheep and Beef
Farmers (5,000)
Self-Employed and Employers
65+
Male
Female
All grain, sheep, beef
65+
60-64
60-64
55-59
55-59
50-54
Self-Employed,
Without
Employees
45-49
40-44
Employer
35-39
Male
Female
SelfEmployed,
Without
Employees
Employer
50-54
45-49
Paid
Employee
40-44
35-39
30-34
30-34
25-29
25-29
20-24
20-24
15-19
15-19
600 500 400 300 200 100
0
100 200 300 400 500
Unpaid
Family
Worker
Not
Elsewhere
Included
600 500 400 300 200 100
Number at each age
Stats NZ Customised Database
0
100 200 300 400 500
Number at each age
Waikato’s Dairy Farmers (11,000)
All dairy workers
Self-Employed and Employers
Female
65+
Male
Female
65+
60-64
60-64
55-59
55-59
50-54
50-54
45-49
45-49
40-44
40-44
35-39
35-39
30-34
SelfEmployed,
Without
Employees
Employer
25-29
20-24
15-19
1,000
800
600
400
200
0
200
Number at each age
400
Male
SelfEmployed,
Without
Employees
Employer
Paid
Employee
Unpaid
Family
Worker
30-34
25-29
Not
Elsewhere
Included
20-24
15-19
1,00
0
800
Stats NZ Customised Database
600
400
200
0
200
400
Number at each age
600
800
Waikato’s Medical and Dental
(1,695)
All medical and dental
65+
Male
Female
SelfEmployed,
Without
Employees
Employer
60-64
55-59
50-54
45-49
Paid
Employee
40-44
35-39
Unpaid
Family
Worker
30-34
25-29
Not
Elsewhere
Included
20-24
15-19
200
150
100
50
0
50
100
Number at each age
Stats NZ Customised Database
150
200
Watch this
space..
Accept
Buffer
(revisit those
policies)
Celebrate
(advance warning)
40
There is more to population ageing
than meets the eye
41
Thankyou
• Population Studies Centre
• will become NIDEA – The National Institute for
Demographic and Economic Analysis – on
November 24th 2010
• natalie.jackson@waikato.ac.nz
42
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