SURVEY OF RURAL DECISION MAKERS...SURVEY OF RURAL DECISION MAKERS 1 • Funded by MfE • 3 regions:...
Transcript of SURVEY OF RURAL DECISION MAKERS...SURVEY OF RURAL DECISION MAKERS 1 • Funded by MfE • 3 regions:...
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SURVEY OF RURAL DECISION MAKERS: TRUST, GOALS, & MANAGEMENT
Pike Brown
Senior Economist
Capability Leader, Economics and Land Use Modelling
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SURVEY OF RURAL DECISION MAKERS 1
• Funded by MfE • 3 regions: Canterbury,
Southland, Waikato • Conducted April 2013
• Funded by MBIE through VMO programme
• 13 regions • Conducted July 2013
SURVEY OF RURAL DECISION MAKERS 2
Purpose: Collect data to inform economic models
• Vetting: Independent farm systems scientists; Regional Councils;
NZIER; Beef + Lamb NZ, DairyNZ, HortNZ, Rural Support Trust, Hawke’s Bay Wine Grower’s Association
• Piloting: Farmers/foresters/growers in Northland, Waikato, Hawke’s Bay
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SURVEY OF RURAL DECISION MAKERS 1 131 questions
Topics: • respondent demographics; • farm characteristics; • succession plans; • risk tolerance; • production and profitability; • information sources; • operational objectives; • current and intended
management practices; • future intentions; • perceived behavioural control; • norms; • environmental attitudes
192 questions • 125 +/- questions from SRDM 1
Plus more information on: • ownership structure; • livestock sex and age; • crop types; • forestry type and practices; • apiculture; • land use changes; • additional information sources; • additional management practices; • reasons underlying intentions
SURVEY OF RURAL DECISION MAKERS 2
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SURVEY OF RURAL DECISION MAKERS: DESIGN
Internet surveys Benefits: • Less expensive and faster to implement • Facilitates using smart logic, reducing completion time Cost: • Lower response rates than alternatives • Requires a reliable means of contacting respondents
27. How many distinct, geographically separate blocks comprise this farm? __________ blocks If Question 27 = 1 then skip to question 29 28. Approximately how far away is the farthest part of your farming operation from your home, in km? _____ km 29. In what year did you begin working on this farming operation? __________
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SRDM: SAMPLE
Used AgriBase • AssureQuality • Developed in 1993 to track
foot and mouth disease • Evolved into a commercial
database of rural NZ properties
• Relies on voluntary reporting • Records e-mail addresses of
those who provide them • Median email address from 2008
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SURVEY OF RURAL DECISION MAKERS 1 Incentive
$10 donation to charity of the respondents’ choice:
Incentive
Random [$5, $10, $15, $20] donation to charity of the respondents’ choice:
or [no incentive]
SURVEY OF RURAL DECISION MAKERS 2
+ invitation to view results online
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SURVEY OF RURAL DECISION MAKERS 1 5,811 emails sent
• ? Emails had bad addresses
• 285 (5%) unsubscribed • 33 (1%) opted out via email • 250 (4%) did not complete
8,546 emails sent • Excluded small properties • 2,650 (31%) emails had bad
addresses
• We don’t know how many emails were opened, but we know that: • 609 (7%) unsubscribed • 70 (1%) opted out via email
• “I sold my farm over 10 years ago” • “I moved to Australia several years
back” • “I only have a lifestyle block”
• 275 (3%) did not complete
• 1,795 opened the email in the 1st week (61% response rate?)
SURVEY OF RURAL DECISION MAKERS 2
Final sample = 1037 minimum response rate 21%
Final sample = 536 minimum response rate = 16%
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Freq. Percent Cum.
Auckland 48 3.07 3.07
Bay of Plenty 84 5.37 8.44
Canterbury 278 17.77 26.21
Gisborne 38 2.43 28.64
Hawke's Bay 131 8.38 37.02
Marlborough 89 5.69 42.71
Manuwatu-Whanganui 104 6.65 49.36
Nelson 5 0.32 49.68
Northland 83 5.31 54.99
Otago 200 12.79 67.77
Southland 134 8.57 76.34
Tasman 100 6.39 82.74
Taranaki 67 4.28 87.02
Waikato 116 7.42 94.44
Wellington 56 3.58 98.02
West Coast 31 1.98 100
Total 1,564 100
1,564 respondents
16 regions
SRDM: SAMPLE COVERAGE
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SURVEY OF RURAL DECISION MAKERS 1 Incentive
$10 donation to charity of the respondents’ choice:
Incentive
Random [$5, $10, $15, $20] donation to charity of the respondents’ choice:
or [no incentive]
SURVEY OF RURAL DECISION MAKERS 2
+ invitation to view results online
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SRDM: SHARE WITH EACH PRIMARY LAND USE Region sheep,beef dairy
deer, other
hort/vit arable forestry dairy
support other
Auckland 41.67 14.58 6.25 10.42 0 8.33 6.25 12.5 BOP 17.86 33.33 1.19 38.10 1.19 5.95 1.19 1.19 Canterbury 49.28 14.75 4.68 3.60 13.31 2.52 9.71 2.16 Gisborne 65.79 2.63 0 18.42 2.63 5.26 0 5.26 Hawke's Bay 64.12 3.05 3.82 20.61 0.76 3.82 1.53 2.29
Marlborough 35.96 1.12 2.25 35.96 1.12 16.85 2.25 4.49
Manuwatu-Whanganui
47.12 25.00 3.85 2.88 0 11.54 0.96 8.65
Northland 27.71 37.35 1.20 19.28 0 9.64 1.20 3.61 Otago 58.50 10.00 4.50 6.50 0 11.00 2.00 7.50 Southland 58.96 16.42 3.73 0 2.24 2.24 13.43 2.99 Tasman & Nelson
39.05 5.71 4.76 12.38 0 23.81 2.86 11.43
Taranaki 19.40 61.19 1.49 0 0 5.97 2.99 8.96 Waikato 20.69 61.21 3.45 6.03 2.59 0.86 3.45 1.72 Wellington 50.00 17.86 0 3.57 0 14.29 1.79 12.5 West Coast 22.58 58.06 3.23 0 0 9.68 3.23 3.23 Total 44.37 20.91 3.45 10.68 3.01 7.93 4.48 5.18
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SRDM: SAMPLE REPRESENTATIVENESS
Canterbury Southland Waikato
AgriBase (2008)
Sheep and/or beef 57.4% 64.9% 38.19%
Dairy & Dairy Support 16.8% 23.3% 50.10%
Deer & Other Livestock 8.8% 8.4% 3.31%
Hort & Viticulture 4.3% 0.4% 3.36%
Arable 8.9% 0.8% 1.97%
Forestry 3.9% 2.3% 2.67%
Survey
Sheep and/or beef 49.3% 59.0% 20.7%
Dairy & Dairy Support 24.5% 27.9% 64.7%
Deer & Other Livestock 4.7% 3.7% 3.5%
Hort & Viticulture 3.6% 0.0% 6.0%
Arable 13.3% 2.2% 2.6%
Forestry 2.5% 2.2% 0.9%
In SRDM 2:
79% of those who shifted into dairy shifted out of sheep and beef
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LANDCARERESEARCH.CO.NZ SEARCH FOR “SRDM”
http://www.landcareresearch.co.nz/science/portfolios/ enhancing-policy-effectiveness/srdm
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mean=56.5
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SRDM: AGE
mean=56.5
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SRDM: GENDER
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SRDM: GENDER
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41.35%
25.07%
33.57% 38.23%
36.7%
25.08%
46.3%
14.81%
38.89%
35.93%
33.53%
30.54%
51.06%
17.02%
31.91% 25%
27.42%
47.58%
50%
18.57%
31.43% 33.33%
27.16%
39.51% 39.26%
27.81%
32.93%
sheep and/or beef dairy deer & other stock
hort & vit arable forestry
dairy support other Total
secondary diploma
uni
Graphs by primary land use
SRDM: EDUCATION
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28=highest*** 19=lowest**
28=highest*** 28=highest***
mean=25
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SRDM: EXPERIENCE 0
.2.4
.60
.2.4
.60
.2.4
.6
0 20 40 60 0 20 40 60 0 20 40 60
0 20 40 60 0 20 40 60 0 20 40 60
0 20 40 60 0 20 40 60 0 20 40 60
sheep and/or beef dairy deer & other stock
hort & vit arable forestry
dairy support other Total
Fra
ctio
n
years of experienceTotal shows the unweighted distribution.
Experience of decision maker
mean=25
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SRDM: EFFECTIVE LAND SIZE
Primary land use N mean sd min median max
sheep and/or beef 694 731.3 2,107.0 2 231 28,000
dairy 327 291.9 351.5 32 200 4,000
deer & other stock 54 146.9 395.2 2 40 2,831
hort & vit 167 38.8 106.4 2 10 882
arable 47 305.6 272.6 5 260 1,600
forestry 124 843.8 4,564.0 2 44.5 34,000
dairy support 70 307.4 423.2 7 173.5 2,500
other 81 35.6 60.6 2 10 267
Total 1,564 486.4 1,932.0 2 125.5 34,000
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SRDM: NUMBER OF ENTERPRISES
mean=1.7
1.9=most***
1.5=least***
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SRDM: PROFITABILITY
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SRDM: PROFITABILITY
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SRDM: IMPORTANCE OF PROFITABILITY
mean=6.4
new type of question
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SRDM: RISK TOLERANCE
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SRDM: RISK TOLERANCE
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SRDM: RISK TOLERANCE 0
.1.2
.30
.1.2
.30
.1.2
.3
0 5 10 0 5 10 0 5 10
0 5 10 0 5 10 0 5 10
0 5 10 0 5 10 0 5 10
sheep and/or beef dairy deer & other stock
hort & vit arable forestry
dairy support other Total
Fra
ctio
n
0 = don't like to take risks ... 10 = fully prepared to take risksTotal shows the unweighted distribution.
Are you generally prepared to take risks?
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PROFITABILITY IS IMPORTANT TO PEOPLE. MOST PEOPLE ARE RELUCTANT TO TAKE RISKS. HOW DO THEY MANAGE THEIR LAND?
* Reducing stocking rates * Reducing N-based fertiliser * Wintering off stock * Applying DCDs * Having a nutrient management plan * Adding or upgrading a water irrigation system * Constructing a feed pad * Upgrading the effluent system * Fencing streams * Constructing wetlands and/or sedimentation traps * Planting native bush or trees * Planting riparian buffers * Changing primary crops or changing crop rotation * Practices to reduce pugging * Practices to reduce soil erosion * Improving N efficiency through precision placement or timing * Reducing P-based fertiliser * Improving P efficiency through precision * Avoiding waterways when applying fertiliser * Adopting biological fertilisers * Reducing tillage and/or controlling trafficking * Use frost fans, freeze cloth, and other frost protection
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✓
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Mean=6.9
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0.610.52
0.41
0.55
0.74
0.46
0.2
.4.6
.81
Fra
ctio
n w
ho p
urs
ue
ma
na
ge
me
nt p
ractice
s
have nutrient mgmt plan reduce N-based fertiliser
reduce stocking rates plant riparian buffers
fence streams change crops/rotation
Do you currently pursue the following management practices?
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0.600.54
0.42
0.57
0.75
0.47
0.61
0.50
0.40
0.50
0.70
0.44
0.2
.4.6
.81
risk averse risk tolerant
have nutrient mgmt plan reduce N-based fertiliser
reduce stocking rates plant riparian buffers
fence streams change crops/rotation
Fra
ctio
n w
ho p
urs
ue
ma
na
ge
me
nt p
ractice
s
RISK TOLERANCE DOES NOT EXPLAIN ADOPTION.
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0
.05
.1.1
5.2
Fra
ctio
n
0 2 4 6 8 10
MOST PEOPLE ARE MORE LIKELY TO ADOPT NEW PRACTICES AFTER SEEING THEM DEMONSTRATED.
When I see new practices being successfully used, I am more likely to adopt them.
0 = strongly disagree … 10 = strongly agree
disagree agree
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8.9%
47.0%19.2%
20.3%
4.6%
0 1-5
6-10 11-50
51+
DEMONSTRATION MATTERS. SO, HOW LARGE ARE FARMER NETWORKS?
With how many other farmers did you discuss operational practices,
systems change, or practices in the last 12 months?
5 or fewer: 56%
10 or fewer: 75%
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Bay of Plenty Marlborough Wellington Overall
Newspaper 4.74 (14) 5.09 (14) 5.02 (15) 5.05 (14)
Television 4.06 (18) 4.01 (18) 4.14 (18) 4.14 (18)
National radio 4.82 (13) 5.75 (11) 5.48 (12) 5.25 (13)
Internet 5.35 (12) 5.54 (12) 5.52 (11) 5.36 (12)
Fed Farmers etc. 6.57 (5) 6.36 (6) 6.21 (7) 6.30 (6)
Industry 6.65 (3) 6.55 (4) 6.14 (9) 6.34 (5)
Cooperatives 6.65 (3) 5.29 (13) 5.36 (13) 5.73 (11)
Central gov’t 4.70 (16) 4.63 (17) 4.75 (16) 4.60 (15)
Regional councils 4.71 (15) 4.76 (16) 5.14 (14) 4.54 (16)
District councils 4.43 (17) 4.87 (15) 4.23 (17) 4.48 (17)
Accountants 6.21 (9) 5.98 (9) 5.79 (10) 6.34 (4)
Farm consultants 6.30 (8) 6.18 (8) 6.30 (6) 6.21 (9)
Farmers forums 6.48 (6) 6.34 (7) 6.43 (4) 6.29 (7)
Other farmers 6.79 (2) 6.64 (3) 6.84 (2) 6.71 (2)
Scientists 6.44 (7) 6.75 (2) 6.61 (3) 6.37 (3)
Vets 7.12 (1) 7.04 (1) 6.95 (1) 7.13 (1)
Rural retailers 5.77 (10) 5.80 (10) 6.18 (8) 5.89 (10)
Universities 5.70 (11) 6.39 (5) 6.38 (5) 6.22 (8)
PEOPLE LIKE TO SEE DEMONSTRATION BEFORE ADOPTION,
BUT FARMER NETWORKS ARE SMALL. WHO ELSE IS TRUSTED?
![Page 38: SURVEY OF RURAL DECISION MAKERS...SURVEY OF RURAL DECISION MAKERS 1 • Funded by MfE • 3 regions: Canterbury, Southland, Waikato • Conducted April 2013 • Funded by MBIE through](https://reader035.fdocuments.us/reader035/viewer/2022081607/5ea5e1ac0ef7b871de4b02c2/html5/thumbnails/38.jpg)
PEOPLE LIKE TO SEE DEMONSTRATION BEFORE ADOPTION,
BUT FARMER NETWORKS ARE SMALL. WHO ELSE IS TRUSTED?
02
46
81
0
0 =
not
at
all
trustw
ort
hy .
.. 1
0 =
extr
em
ely
tru
stw
ort
hy
other farmers, farmers forums veterinarians
scientists financial advisors
orgs that rep primary industry cooperatives
newspapers, TV, radio, Internet central, regional, district government
How trustworthy do you consider the following sources of information
for making decisions related to environmental performance? 0 = not at all trustworthy … 10 = extremely trustworthy
6.5
7.1
6.4 6.3 6.3
5.7
4.9 4.5
![Page 39: SURVEY OF RURAL DECISION MAKERS...SURVEY OF RURAL DECISION MAKERS 1 • Funded by MfE • 3 regions: Canterbury, Southland, Waikato • Conducted April 2013 • Funded by MBIE through](https://reader035.fdocuments.us/reader035/viewer/2022081607/5ea5e1ac0ef7b871de4b02c2/html5/thumbnails/39.jpg)
• Cross-sectional survey: How do we know if policy is effective?
• Sampling: Can we do better?
• Survey fatigue: Can we work together to elicit better information?