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American Gothic – on the art of painting
the reality of farming
European insights for discussions in the USA
February 2017
Krijn J. Poppe
Grant Wood, 1930: American Gothic
 “An Iowa farmer and his wife”
 Based on a real cottage in Iowa, that
Wood found “pretentious”
 The Farmer was in reality his dentist
 The Wife is Wood’s sister (and much
younger than the dentist)
 Instantly a big hit, but Iowans weren’t
fans, to say the least
 Source: Mentalfloss.com
2
 Source: Bonnen, 1975 3
Agriculture and farming
 Management of biological processes (or nature)
 Not only Food or Feed: Fibre, Flowers, Pharma, Fuel, Fun,
Forests & nature; but not: yeast, microbes in sewage sludge
 Not necessarily land-based: glasshouses, pig farming
 Definition can be translated into a list with activities.
 Some discussions:
● farming – tree nursery – energy plantation –
forestry: where is the border?
● Farming – algae- aquaculture – fisheries: ibid
● Illegal activities: coca, marijuana (with a high value)
● Care farming with animals, management consultancy
with sheep (Boer Bos near Schiphol Airport)
4
Problems are due to organisational forms
 As we classify organisations, not their activities
 Specialisation: hiving off (cheese making to food
industry, contract work with machines, risk management
bureaus): one sector is contracting, other is growing.
● This is reality that we want to show, not correct it
● Are farms / states still comparable?: this is
interpretation and analysis, we should not change
definitions in taking a picture of reality
● Is agriculture more than farming ?
 Lack of specialisation: mixed enterprises (mixed farms,
integrated companies etc).
● Some examples on next slide
5
What is a farm / farmer ?
Dairy farm with 51% of sales in agri-tourism
Pig breeding farm buys a holding for pig fattening on
the other side of the road, or at 20 km distance...
…. Or just across the border in another country
Farm with a 75 year old farmer who earns 80% of
his income from a government pension
.. Or with a 40 year old farmer that earns 80% in a
job at a Renault car plant?
... Or even 110% with BMW and spends 10% on the
farm to have a nice living and social security / tax
facilities?
A slaughterhouse with own farms (or contractors?)
6
 Is the farmer the owner (the residual claimant) that
probably takes the strategic decisions on investment,
finance and structure of the farm ?
 Is the farmer the manager (operator?) that takes the
day-to-day operational decisions?
 Can a farm have several farmers? Can one farmer be the
most important one?
 Can a farmer have several farms?
 How do we handle situations that are mainly set up for
reasons of tax, risk management or policy purposes:
● Spouse that becomes juridically a farmer to benefit
from a tax credit
● Famer with 3 “farms” in separate limited companies
for managing risk or prevent capping CAP payments
7
Rules national accounts and need for
satellite accounts
 Like in classifications of type of farming (arable,
horticulture, permanent crops, grazing livestock, intensive
livestock pig and poultry): more than 50%, 66.67%, 80%
as allocation rule. An organisation is linked to a sector /
industry based on its majority of (estimated) sales (or
value added). To keep data collection simple.
 Due to that rule, and due to fact that agricultural policy
influences more than farming itself, additional data is
needed
● Estimate Agri-Business Complex: fertilizer plant
(chemical industry) is segment of ABC, like part of
Rabobank.
● Based on input-output tables
8
Value added of the total agro-complex, 2013
9
AgroBusinessComplex Bln. Euro % of national
economy
Inland and foreign raw material 48.0 8.3%
Based on foreign agricultural
products
16.1 2.8%
Linked to inland agricultural products 31.9 5.5%
Primary production (farming) 10.5 ~2%
Food processing 4.5
Input supply 12.8
Distribution 4.1
Definition of the farm - Eurostat
 A single unit, both technically and economically, which
has single management and which produces agricultural
products.
 At least 1 ha. and those of less than 1 ha provided the
latter market a certain proportion of their output or
produce more than a specified amount of output
 Critiques:
● Can include ‘juridical farmers’, pensioners, private
plots
● Sometimes farmers hold more then one holding
(economically inter-twinned, but registered
separately: could be seen as a single unit?)
● Not in line National Accounts: includes mixed firms
10
Micro level: what is a farm?
 This means that the lower threshold is higher than in the
USA
● Where it is “potentially $ 1000 sales”
● Leading to increasing number of farms around
growing cities like Denver where some people want a
‘residential farm’ with two horses for the kids.
 Threshold in EU is not really harmonised. Sometimes
higher (e.g. DK 5 ha), sometimes a bit political influenced
 Also influenced by the method of counting. E.g. a register
also used for subsidies or not.
● In the NL 2016 saw a 10% drop in the number of
farmers as we changed to self registration at
Chamber of Commerce instead of register MoA and a
higher threshold (Euro 10.000).
11
Total income farmer and spouse, Finland
Compare ERS: on the average US-farm the income from non-
farming sources is larger than the income of non-farmers
Why Ministries of Agriculture need more
(adm.) data than in the general statistics
 General government policies: National accounts,
Population census etc.
 Agriculture sector and policy have additional needs:
● Adm. management of sector on public values: food
safety, animal diseases: you need every producer;
also mixed ones, for stamping out etc.
● Collective action for family farms: e.g. price statistics
to improve unbalanced, imperfect markets; cost
prices for extension / advisory service
● Analytical tools to investigate effects of government
policies (impact assessment)
● FADN / ARMS.: focus on policy targets.
13
FADN is an observatory for monitoring
 The Farm Accountancy Data Network (FADN) is an
instrument for evaluating the income of agricultural
holdings and the impacts of the CAP.
 Policy tries to influence management decision in such a
way that a better food supply, environmental impact
and/or income is realised.
 Policy evaluation asks for within-without analysis: what
difference does the policy make. Needs data on all
factors that potentially influences the management
decision on the same farm(s), including trade-offs
 Agricultural policy does not target hobby farms but
commercial farms.
 FADN is not the solution to everything. For some
statistics or research data a special survey suffices
14
Definition of the farm - FADN
 ‘Commercial’ farms:
A commercial farm is defined as a farm which is large
enough to provide a main activity for the farmer and a
level of income sufficient to support his or her family.
 In practical terms, in order to be classified as commercial,
a farm must exceed a minimum economic size. However,
because of the different farm structures and income levels
across the European Union, a different threshold is set for
each Member State.
 Field of observation: represent largest possible proportion
of farms with a market orientation.
● old rule of thumb: > 90% of production
● one third of farms is not in the field of observation
 An upper threshold officially not exists (but is defendable:
 CAP is not developed for very large farms)
15
Complex farms: firms or establishments ?
 Is a Farm:
● A Firm (“an organisation conducting a business
[..]. A firm may operate one place of business or
more”)
● An Establishment (“a single physical location
where a firm’s business is conducted..”)
 If a farm is an establishment we need another word for
the complex farms that are firms:
● Agricultural (family) firms ?
● Agricultural Economic Entities (AEE – Dutch FADN)
16
Data model for the traditional farm
1 farm = 1 farmer = 1 household = 1 place
Farm
Holding,
Household
and
Family
Family Member
* Entrepreneur
yes/no
Works
in
Related
to
Data model of farm in the FADN tables
[Agricultural]
Holding
•Number
Location
Altitude
Legal structure
Unpaid labour
•Holder /
manager
Family relation
Regular / casual
Spouse yes/no
Year of birth
Works
at
Assets and
Liabilities
•Name
Value
Activity
•Size (ha)
Turnover €
Period
Classification /
Typology
•Farm type
Labor
Capital (land)
Management
Farm Operators
&
Households
Supply
Farm
Business
Earn
Income
Increases in
Asset & Equity
Values
Factor markets
Agricultural
chaincontracts
• specialization family members
• pluri-activity
• asset management
• rural housing and hobby farming
• increasing scale
• risk management
• chain management by contracts
• transaction costs shapes structure
• separation management and work
Influences
Allocation
decisions
Influences:
Management structure
Decision making process
Claims on returns
Farm-households allocate resources to farm and non-farm uses
and source inputs from multiple farm, household, and non-farm businesses
Krijn Poppe [LEI], James Johnson [USDA-
ERS], Mitchell Morehart [USDA-ERS], David
Culver [AAF Can.], Cristina Salvioni
[Un.Pescara]
Household: principal operator
Households: family members
Household: non-family members
Businesses and other entities
Farm Ownership Structure
Farm Management Structure
Principal operator
Principal operator’s spouse
Principal operator’s household
members
Operators outside principal
operator’s household, e.g.,
partners, shareholders
Hired operators or managers
Joint ownership
and
other ventures
Contracts
Business Arrangements
Introduce Participants to
Decision Making Process
Farm Organizational/
Governance Structure
Owners: from one to many
Managers/Operators: from
one to many
Contracts/business
arrangements may alter
decision processes
--
--
--
Informal participants or
other managers
Farm Organizational/Governance Structures May Range
from One to Many Owners and Operators
Organizational
structure affects
claims on returns
• Fixed return
or payment
• Physical output
claim
• Wages & dividends
• Net income
Chain organisation changes (©Gereffi et al., 2005)
inputsEndproduct
PRICE
Shops
Complete
Integration
Lead
company
Lead
company
Turnkey
supplier
Relational
supplier
Market Modular Relational Captive Hierarchy
Low Degree of explicit coordination and power asymmetry High
Lead
company
Farmers
Development of farm systems
Net value
/ ha
Time
Agricul-
tural
Family
Firms
(sme)Family
farming
Lati-
fundia
socialist
state
farms
Subsis-
tence
farming
Ag. policy
AKIS.gov
Food supply networks
3rd gen. uni
Urban
farming
Residen
-tial
farming
Metropolitanagriculture
Data model to support fact finding (used
in the Dutch FADN):
[Agricultural]
Holding
•Name
•Number
Natural Person
•Name
•Family relation
•Year of birth
Household
•Name
Works
at
Legal structure
•Legal form
Location
•GIScode
•ZIPcode
Assets and
Liabilities
•Name
•ValueActivity
•Size (ha)
•Turnover €
•Period Classification /
Typology
•Farm type
Non-agr.
business
•type
Off farm in-
come source
•Type
•Regular y/n
•Income in €
Owns
Family relation
•Type
Type of legal form eg:
Partnership, co-
operative, individual
Owns
Lives
in
0
10
20
30
40
50
sole proprietor partnership
man/spouse
other
partnerships
limited
partnership
limited
company
farms production subsidies investment capacity
Share (%) of the types of farms by legal organization in production,
subsidies and total flow of funds (investment capacity) the
Netherlands, 2007
Source: Dutch FADN, 2007
Conclusions
 Changes in organisational forms create issues for
statistics, but not much for agricultural accounts,
agricultural censuses (and descriptors in general statistics)
 Policy needs determine the data needs in agriculture
● Full registers for public management (animal
diseases, food safety)
● Data sets to help (family) farmers to take decisions
or promote functioning of markets (prices, stocks)
● Data set(s) like FADN (and ARMS?) as an observatory
of farm management decisions for policy impact
analysis (‘what – if’?).
● not an instrument to create statistics
● hobby farms and very large (international) farms are not
the target group of ag. policy.
25
Conclusions and future work
 Modern databases support more complicated tables
than an A4 form to paint the reality and enrich policy
analysis.
 Modern (ICT-based) options for data collection can
help to fill such databases
 Potential future contributions to the panel:
● A paper based on this powerpoint, with some
updated data for the Netherlands
● Some extensions with e.g. Statistics
Netherlands and Statistics Sweden on use of
registers in the agricultural census
● The use of ICT in data collection in the FADN
26
Thanks for your
attention
krijn.poppe@wur.nl
www.wur.nl
Thanks to
Dr. Hans Vrolijk
(Wageningen
Economic Research)
for comments and
contributions

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American gothic on farm definitions

  • 1. American Gothic – on the art of painting the reality of farming European insights for discussions in the USA February 2017 Krijn J. Poppe
  • 2. Grant Wood, 1930: American Gothic  “An Iowa farmer and his wife”  Based on a real cottage in Iowa, that Wood found “pretentious”  The Farmer was in reality his dentist  The Wife is Wood’s sister (and much younger than the dentist)  Instantly a big hit, but Iowans weren’t fans, to say the least  Source: Mentalfloss.com 2
  • 4. Agriculture and farming  Management of biological processes (or nature)  Not only Food or Feed: Fibre, Flowers, Pharma, Fuel, Fun, Forests & nature; but not: yeast, microbes in sewage sludge  Not necessarily land-based: glasshouses, pig farming  Definition can be translated into a list with activities.  Some discussions: ● farming – tree nursery – energy plantation – forestry: where is the border? ● Farming – algae- aquaculture – fisheries: ibid ● Illegal activities: coca, marijuana (with a high value) ● Care farming with animals, management consultancy with sheep (Boer Bos near Schiphol Airport) 4
  • 5. Problems are due to organisational forms  As we classify organisations, not their activities  Specialisation: hiving off (cheese making to food industry, contract work with machines, risk management bureaus): one sector is contracting, other is growing. ● This is reality that we want to show, not correct it ● Are farms / states still comparable?: this is interpretation and analysis, we should not change definitions in taking a picture of reality ● Is agriculture more than farming ?  Lack of specialisation: mixed enterprises (mixed farms, integrated companies etc). ● Some examples on next slide 5
  • 6. What is a farm / farmer ? Dairy farm with 51% of sales in agri-tourism Pig breeding farm buys a holding for pig fattening on the other side of the road, or at 20 km distance... …. Or just across the border in another country Farm with a 75 year old farmer who earns 80% of his income from a government pension .. Or with a 40 year old farmer that earns 80% in a job at a Renault car plant? ... Or even 110% with BMW and spends 10% on the farm to have a nice living and social security / tax facilities? A slaughterhouse with own farms (or contractors?) 6
  • 7.  Is the farmer the owner (the residual claimant) that probably takes the strategic decisions on investment, finance and structure of the farm ?  Is the farmer the manager (operator?) that takes the day-to-day operational decisions?  Can a farm have several farmers? Can one farmer be the most important one?  Can a farmer have several farms?  How do we handle situations that are mainly set up for reasons of tax, risk management or policy purposes: ● Spouse that becomes juridically a farmer to benefit from a tax credit ● Famer with 3 “farms” in separate limited companies for managing risk or prevent capping CAP payments 7
  • 8. Rules national accounts and need for satellite accounts  Like in classifications of type of farming (arable, horticulture, permanent crops, grazing livestock, intensive livestock pig and poultry): more than 50%, 66.67%, 80% as allocation rule. An organisation is linked to a sector / industry based on its majority of (estimated) sales (or value added). To keep data collection simple.  Due to that rule, and due to fact that agricultural policy influences more than farming itself, additional data is needed ● Estimate Agri-Business Complex: fertilizer plant (chemical industry) is segment of ABC, like part of Rabobank. ● Based on input-output tables 8
  • 9. Value added of the total agro-complex, 2013 9 AgroBusinessComplex Bln. Euro % of national economy Inland and foreign raw material 48.0 8.3% Based on foreign agricultural products 16.1 2.8% Linked to inland agricultural products 31.9 5.5% Primary production (farming) 10.5 ~2% Food processing 4.5 Input supply 12.8 Distribution 4.1
  • 10. Definition of the farm - Eurostat  A single unit, both technically and economically, which has single management and which produces agricultural products.  At least 1 ha. and those of less than 1 ha provided the latter market a certain proportion of their output or produce more than a specified amount of output  Critiques: ● Can include ‘juridical farmers’, pensioners, private plots ● Sometimes farmers hold more then one holding (economically inter-twinned, but registered separately: could be seen as a single unit?) ● Not in line National Accounts: includes mixed firms 10
  • 11. Micro level: what is a farm?  This means that the lower threshold is higher than in the USA ● Where it is “potentially $ 1000 sales” ● Leading to increasing number of farms around growing cities like Denver where some people want a ‘residential farm’ with two horses for the kids.  Threshold in EU is not really harmonised. Sometimes higher (e.g. DK 5 ha), sometimes a bit political influenced  Also influenced by the method of counting. E.g. a register also used for subsidies or not. ● In the NL 2016 saw a 10% drop in the number of farmers as we changed to self registration at Chamber of Commerce instead of register MoA and a higher threshold (Euro 10.000). 11
  • 12. Total income farmer and spouse, Finland Compare ERS: on the average US-farm the income from non- farming sources is larger than the income of non-farmers
  • 13. Why Ministries of Agriculture need more (adm.) data than in the general statistics  General government policies: National accounts, Population census etc.  Agriculture sector and policy have additional needs: ● Adm. management of sector on public values: food safety, animal diseases: you need every producer; also mixed ones, for stamping out etc. ● Collective action for family farms: e.g. price statistics to improve unbalanced, imperfect markets; cost prices for extension / advisory service ● Analytical tools to investigate effects of government policies (impact assessment) ● FADN / ARMS.: focus on policy targets. 13
  • 14. FADN is an observatory for monitoring  The Farm Accountancy Data Network (FADN) is an instrument for evaluating the income of agricultural holdings and the impacts of the CAP.  Policy tries to influence management decision in such a way that a better food supply, environmental impact and/or income is realised.  Policy evaluation asks for within-without analysis: what difference does the policy make. Needs data on all factors that potentially influences the management decision on the same farm(s), including trade-offs  Agricultural policy does not target hobby farms but commercial farms.  FADN is not the solution to everything. For some statistics or research data a special survey suffices 14
  • 15. Definition of the farm - FADN  ‘Commercial’ farms: A commercial farm is defined as a farm which is large enough to provide a main activity for the farmer and a level of income sufficient to support his or her family.  In practical terms, in order to be classified as commercial, a farm must exceed a minimum economic size. However, because of the different farm structures and income levels across the European Union, a different threshold is set for each Member State.  Field of observation: represent largest possible proportion of farms with a market orientation. ● old rule of thumb: > 90% of production ● one third of farms is not in the field of observation  An upper threshold officially not exists (but is defendable:  CAP is not developed for very large farms) 15
  • 16. Complex farms: firms or establishments ?  Is a Farm: ● A Firm (“an organisation conducting a business [..]. A firm may operate one place of business or more”) ● An Establishment (“a single physical location where a firm’s business is conducted..”)  If a farm is an establishment we need another word for the complex farms that are firms: ● Agricultural (family) firms ? ● Agricultural Economic Entities (AEE – Dutch FADN) 16
  • 17. Data model for the traditional farm 1 farm = 1 farmer = 1 household = 1 place Farm Holding, Household and Family Family Member * Entrepreneur yes/no Works in Related to
  • 18. Data model of farm in the FADN tables [Agricultural] Holding •Number Location Altitude Legal structure Unpaid labour •Holder / manager Family relation Regular / casual Spouse yes/no Year of birth Works at Assets and Liabilities •Name Value Activity •Size (ha) Turnover € Period Classification / Typology •Farm type
  • 19. Labor Capital (land) Management Farm Operators & Households Supply Farm Business Earn Income Increases in Asset & Equity Values Factor markets Agricultural chaincontracts • specialization family members • pluri-activity • asset management • rural housing and hobby farming • increasing scale • risk management • chain management by contracts • transaction costs shapes structure • separation management and work Influences Allocation decisions Influences: Management structure Decision making process Claims on returns Farm-households allocate resources to farm and non-farm uses and source inputs from multiple farm, household, and non-farm businesses Krijn Poppe [LEI], James Johnson [USDA- ERS], Mitchell Morehart [USDA-ERS], David Culver [AAF Can.], Cristina Salvioni [Un.Pescara]
  • 20. Household: principal operator Households: family members Household: non-family members Businesses and other entities Farm Ownership Structure Farm Management Structure Principal operator Principal operator’s spouse Principal operator’s household members Operators outside principal operator’s household, e.g., partners, shareholders Hired operators or managers Joint ownership and other ventures Contracts Business Arrangements Introduce Participants to Decision Making Process Farm Organizational/ Governance Structure Owners: from one to many Managers/Operators: from one to many Contracts/business arrangements may alter decision processes -- -- -- Informal participants or other managers Farm Organizational/Governance Structures May Range from One to Many Owners and Operators Organizational structure affects claims on returns • Fixed return or payment • Physical output claim • Wages & dividends • Net income
  • 21. Chain organisation changes (©Gereffi et al., 2005) inputsEndproduct PRICE Shops Complete Integration Lead company Lead company Turnkey supplier Relational supplier Market Modular Relational Captive Hierarchy Low Degree of explicit coordination and power asymmetry High Lead company Farmers
  • 22. Development of farm systems Net value / ha Time Agricul- tural Family Firms (sme)Family farming Lati- fundia socialist state farms Subsis- tence farming Ag. policy AKIS.gov Food supply networks 3rd gen. uni Urban farming Residen -tial farming Metropolitanagriculture
  • 23. Data model to support fact finding (used in the Dutch FADN): [Agricultural] Holding •Name •Number Natural Person •Name •Family relation •Year of birth Household •Name Works at Legal structure •Legal form Location •GIScode •ZIPcode Assets and Liabilities •Name •ValueActivity •Size (ha) •Turnover € •Period Classification / Typology •Farm type Non-agr. business •type Off farm in- come source •Type •Regular y/n •Income in € Owns Family relation •Type Type of legal form eg: Partnership, co- operative, individual Owns Lives in
  • 24. 0 10 20 30 40 50 sole proprietor partnership man/spouse other partnerships limited partnership limited company farms production subsidies investment capacity Share (%) of the types of farms by legal organization in production, subsidies and total flow of funds (investment capacity) the Netherlands, 2007 Source: Dutch FADN, 2007
  • 25. Conclusions  Changes in organisational forms create issues for statistics, but not much for agricultural accounts, agricultural censuses (and descriptors in general statistics)  Policy needs determine the data needs in agriculture ● Full registers for public management (animal diseases, food safety) ● Data sets to help (family) farmers to take decisions or promote functioning of markets (prices, stocks) ● Data set(s) like FADN (and ARMS?) as an observatory of farm management decisions for policy impact analysis (‘what – if’?). ● not an instrument to create statistics ● hobby farms and very large (international) farms are not the target group of ag. policy. 25
  • 26. Conclusions and future work  Modern databases support more complicated tables than an A4 form to paint the reality and enrich policy analysis.  Modern (ICT-based) options for data collection can help to fill such databases  Potential future contributions to the panel: ● A paper based on this powerpoint, with some updated data for the Netherlands ● Some extensions with e.g. Statistics Netherlands and Statistics Sweden on use of registers in the agricultural census ● The use of ICT in data collection in the FADN 26
  • 27. Thanks for your attention krijn.poppe@wur.nl www.wur.nl Thanks to Dr. Hans Vrolijk (Wageningen Economic Research) for comments and contributions