The demography of agricultural supply and demand
Natalie Jackson ©
Professor of Demography
Director,
Population Studies Centre >>
National Institute of Demographic
and Economic Analysis
2010
1
Key points
• Older average age of farmers well known
– but seemingly invisible in debate over who may/
can / should buy NZ farms, farm prices etc
• Industry’s market focus is on size and growth
rates of national populations
– Yet markets are driven less by size than
composition (market ‘segment’ - age, sex, culture,
income, labour force/marital status etc)
• Population ageing will significantly affect both
2
Population Ageing
NZ 1976
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
Male
NZ 2010
Female
Internal
momentum of
increase
6.0
4.0
2.0
0.0
2.0
4.0
percentage at each age
6.0
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
Male
Female
Internal
momentum of
decline
6.0
4.0
2.0
0.0
2.0
4.0
6.0
percentage at each age
3
What has the ageing of farmers got
to do with foreign ownership?
Who may (can/should) buy NZ
farms?
Grain, Sheep and Beef Farmers
Male
65+
65+
60-64
60-64
55-59
55-59
50-54
50-54
45-49
45-49
age
age
Self-Employed and Employers
Male
Female
40-44
35-39
Self-Employed,
Without
Employees
30-34
25-29
Employer
Paid
Employee
Unpaid
Family
Worker
25-29
15-19
Not
Elsewhere
4,000 3,000 2,000 1,000
0
1,000 2,000
Number at each age
Number at each age
N=38,634; av 48 years
Employer
30-34
15-19
1,000 2,000
SelfEmployed,
Without
Employees
35-39
20-24
0
Female
40-44
20-24
4,000 3,000 2,000 1,000
Total
Stats NZ Customised Database
5
Dairy Farmers (2006)
Total
Self-Employed and Employers
Male
Female
60-64
60-64
55-59
55-59
50-54
50-54
45-49
45-49
40-44
35-39
30-34
30-34
25-29
25-29
20-24
20-24
15-19
15-19
500
500
1,500 2,500
2,500
Number at each age
N=33,507; av 41 years
SelfEmployed,
Without
Employees
Employer
Paid
Employee
40-44
35-39
2,500 1,500
Female
65+
Age
Age
65+ Male
Stats NZ Customised Database
Unpaid
Family
Worker
Not
Elsewhere
1,500
500
500
1,500
2,500
Number at each age
6
Other Livestock Farmers (2006)
Total
Self-Employed and Employers
Male
Age
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
Self-Employed,
Without
Employees
30-34
25-29
Employer
15-19
1,000 750
Number at each age
N=9,303; av 47.5 years
Paid
Employee
Unpaid
Family
Worker
25-29
15-19
250 500 750 1,000
Employer
30-34
20-24
0
SelfEmployed,
Without
Employees
35-39
20-24
1,000 750 500 250
Female
Not
Elsewhere
500
250
0
250
500
750 1,000
Number at each age
Stats NZ Customised Database
7
Who you ‘gonna call?
Males
Females
Demographic Dividend
Stats NZ Estimated Resident Population 2009, Waikato and NZ (unshaded)
8
Where are you farming?
Matamata-Piako (16.5% 65+)
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
Males
6
4
Waipa (15.0% 65+)
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
Females
2
0
2
4
6
Males
Males
6
Percentage at each age
2009 (2006 unshaded)
4
Females
2
0
2
4
6
9
NZ: TA’s with negative entry/exit ratios
30
29
39%
Percentage
29
28
28
27
27
36%
26
2006
2007
2008
2009
10
Enter: a demographically tight
labour market
Australia 2007-200911
Succession planning is critically
needed
Who ‘may’ buy NZ farms?
Who ‘can’ ?
Who [maybe] ‘should’ ?
12
What has population ageing got to
do with farming markets?
Who consumes what?
13
Who eats ice-cream? Who eats beef?
Let’s imagine..
• That kids eat most
of the ice-creams *
• That adults eat most
of the beef **
14
China’s age structure 2000-2010
2000
100+
95-99
90-94
85-89
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
2010
Male
6.0
4.0
Female
2.0
0.0
2.0
4.0
6.0
percentage at each age
Source: US Census Bureau International Database
http://www.census.gov/ipc/www/idb/
100+
95-99
90-94
85-89
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
Male
6.0
4.0
Female
2.0
0.0
2.0
4.0
6.0
percentage at each age
15
China’s age structure 2020-2030
2020
100+
95-99
90-94
85-89
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
2030
Male
6.0
4.0
Female
2.0
0.0
2.0
4.0
6.0
percentage at each age
Source: US Census Bureau International Database
http://www.census.gov/ipc/www/idb/
100+
95-99
90-94
85-89
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
Male
6.0
4.0
Female
2.0
0.0
2.0
4.0
6.0
percentage at each age
16
Projected Population of China
1.6
1.4
Billion
1.2
1.0
0.8
0.6
0.4
0.2
Source: US Census Bureau International Database
http://www.census.gov/ipc/www/idb/
2050
2045
2040
2035
2030
2025
2020
2015
2010
2005
2000
0.0
17
Ice-cream consumption in China
projected by crude and age-weighted rates
2.5
crude rate
2.0
age-weighted
1.5
1.0
Assumption: 2 ltr per capita per year
2050
2045
2040
2035
2030
2025
2020
2015
2010
0.0
2005
0.5
2000
litres (billion)
3.0
Beef consumption in China
projected by crude and age-weighted rates
3.0
crude rate
2.5
age-weighted
2.0
1.5
1.0
Assumption: 2 kg per capita per year
2050
2045
2040
2035
2030
2025
2020
2015
2010
0.0
2005
0.5
2000
kg (billion)
3.5
India (2000 and 2010)
2000
100+
95-99
90-94
85-89
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
2010
Male
6.0
4.0
Female
2.0
0.0
2.0
4.0
6.0
percentage at each age
Source: US Census Bureau International Database
http://www.census.gov/ipc/www/idb/
100+
95-99
90-94
85-89
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
Male
6.0
4.0
Female
2.0
0.0
2.0
4.0
percentage at each age
6.0
India (2020 and 2030)
2020
100+
95-99
90-94
85-89
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
2030
Male
6.0
4.0
Female
2.0
0.0
2.0
4.0
percentage at each age
6.0
100+
95-99
90-94
85-89
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
Male
6.0
4.0
Female
2.0
0.0
2.0
4.0
percentage at each age
6.0
India will overtake China
Billions
1.8
1.6
India
1.4
China
1.2
1.0
0.8
0.6
0.4
0.2
2000
2003
2006
2009
2012
2015
2018
2021
2024
2027
2030
2033
2036
2039
2042
2045
2048
0.0
Source: US Census Bureau International Database
http://www.census.gov/ipc/www/idb/
22
Ice-cream consumption in India
projected by crude and age-weighted rates
3.0
crude rate
2.5
age-weighted
2.0
1.5
1.0
Assumption: 2 ltr per capita per year
2050
2045
2040
2035
2030
2025
2020
2015
2010
0.0
2005
0.5
2000
litres (billion)
3.5
23
crude rate
Assumption: 2 kg per capita per year
2050
2045
2040
2035
2030
2025
2020
2015
2010
age-weighted
2005
4.5
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
2000
kg (billion)
Beef consumption in India
projected by crude and age-weighted rates
24
Japan….
2010
100+
95-99
90-94
85-89
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
2020
Male
6.0
Female
4.0
2.0
0.0
2.0
4.0
percentage at each age
Source: US Census Bureau International Database
http://www.census.gov/ipc/www/idb/
6.0
100+
95-99
90-94
85-89
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
Male
6.0
Female
4.0
2.0
0.0
2.0
4.0
6.0
percentage at each age
25
Russia…*
2010
100+
95-99
90-94
85-89
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
2020
Male
6.0
4.0
Female
2.0
0.0
2.0
4.0
100+
95-99
90-94
85-89
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
6.0
percentage at each age
Source: *as defined by US Census Bureau International Database
http://www.census.gov/ipc/www/idb/
Female
Male
6.0
4.0
2.0
0.0
2.0
4.0
6.0
percentage at each age
26
Projected Population of Russia*
160
140
Million
120
100
80
60
40
20
Source: *as defined by US Census Bureau International Database
http://www.census.gov/ipc/www/idb/
2050
2045
2040
2035
2030
2025
2020
2015
2010
0
27
Summary
• Pay attention to age structure. Population
ageing changes the consumption patterns of
the population; slows, then stops growth
– In the short to medium term, significant growth at middle to
older ages assured
– Need to follow the target / tailor the product
• Population ageing means competition for
labour and industry participation of the young
– Labour supply will be short – and cost more
– The lack of sufficient numbers of young farmers in the
pipeline needs to be considered when deliberating who
may/can/should buy NZ farms..
28
Thankyou
• Population Studies Centre /
• National Institute of Demographic and Economic Analysis (NIDEA)
• [email protected]
29
Why do populations age and stop growing?
• Increasing life expectancy causes more
babies to live ~ eventually they turn into
more elderly
• Declining fertility rates cause the base of the
population pyramid to compress >> the top
to expand
• Eventually the elderly outnumber the young,
growth slows and stops because deaths first
match, then exceed, births
30
Assumptions (Ice-Cream) (Beef)
Ice-Cream (%)
Beef (%)
0-4
5
1
5-9
10
2
10-14
20
4
15-19
20
8
20-24
15
10
25-29
10
10
30-34
5
10
35-39
5
10
40-44
5
10
45-49
2
10
50-54
1
10
55-59
1
10
60-64
1
1
65-69
1
70+
1
75-79
1
80+
1
TOTAL
100
100