This is a presentation about the determinants of off-farm employment participation among farmers in Ireland and Italy before and after the decoupling of direct payments in 2005.

1. JASON LOUGHREY*, THIA HENNESSY*,
KEVIN HANRAHAN*, TREVOR DONNELLAN*
VALENTINA RAIMONDI** AND
ALESSANDRO OLPER**
* R U R A L E C O N O M Y A N D D E V E L O P M E N T P R O G R A M M E ,
T E A G A S C
* * D E P A R T M E N T O F E C O N O M I C S , M A N A G E M E N T A N D
Q U A N T I T A T I V E M E T H O D S
U N I V E R S I T Y O F M I L A N O
2013 IATRC SYMPOSIUM
FACTOR MARKETS SESSION
TUESDAY JUNE 4TH 2013
Determinants of Farm Labour
Use: A Comparison between
Ireland and Italy
1

2. Background
 Off-Farm Labour
Participation more
common among Irish farm
operators at 36.3%
compared to 23% for
Italian farm operators
(average from 2002 to
2009)
 Farmers achieve higher
income and consumption
 Form of risk
management
 Recent studies have
focused on contribution
of government payments
 In the CAP decoupling of 2005,
both countries chose the
historical model over the
regional model
 Entitlements based on
reference period from 2000
to 2002
 Limited change to the
distribution of farm income
 Farmers required to
maintain the land ‘in good
agricultural and
environmental condition’
and land under permanent
pasture
2

3. Ireland Italy
 Teagasc National Farm Survey
 Average sample size of 1,184 farms
per year (2002-2009)
 Unbalanced panel – rate of attrition
is very low over eight year period
 Provide Irish farm income data to the
EU Commission in Brussels (FADN)
 Weights based upon system of
farming and size of the farm
 Provides micro-data on off-farm
employment data for the farm holder
and spouse where relevant
 The Farm Business Survey (REA)
carried out by the Italian Institute of
Statistics (ISTAT)
 Average sample of 3,573 farms per year
(2002-2009)
 Balanced panel - only farms surveyed
for the entire period
 Annual sample of agricultural holdings
representative of Italian agriculture,
stratified by regions, farm types and
economic size of holdings.
 Database includes household’s
composition variables and off-farm
employment variables.
Datasets
3

4. SUMMARY
STATISTICS
4

5. 2004 2007
-10 10 30 50 70
Lowest
2
3
4
Highest
Share of Total Farm Family Income
Share of Total Pillar 1 Direct Payments
-10 10 30 50 70
Lowest
2
3
4
Highest
Share of Total Family Farm Income
Share of Total Pillar 1 Direct Payments
Italy - Distribution of Farm Income and Pillar 1 Direct Payments by
Income Quintile Based on FADN Data (Severini and Tantori, 2012)
5

6. 2004 2007
-10 10 30 50 70
Lowest
2
3
4
Highest
Share of Total Family Farm Income
Share of Total Pillar 1 Funds
-10 10 30 50 70
Lowest
2
3
4
Highest
Share of Total Family Farm Income
Share of Total Pillar 1 Funds
Ireland - Distribution of Farm Income and Pillar 1 Direct
Payments by Income Quintile (Teagasc National Farm Survey)
6

7. 2004 2007
-10 10 30 50 70
Lowest
2
3
4
Highest
Off Farm Participation (Holder %)
Share of Total Family Farm Income
Share of Total Pillar 1 Funds
-10 10 30 50 70
Lowest
2
3
4
Highest
Off Farm Participation (Holder %)
Share of Total Family Farm Income
Share of Total Pillar 1 Funds
Ireland - Distribution of Farm Income and Pillar 1 Direct
Payments by Income Quintile (Teagasc National Farm Survey)
7

8. Outcome Variables
8
ITALY IRELAND
Dependent Variables Off-Farm
Employed
Sub-Sample
Full-
Sample
Off-Farm
Employed
Sub-Sample
Full-
Sample
Off Farm Job (Head) 23.0 36.3
Off Farm Hours Per
Annum 467 113 1572 571

9. 9
ITALY IRELAND
Independent Variables Off-Farm Employed Full-Sample Off-Farm Employed Full-Sample
Age 53.40 55.78 48.98 54.35
Sex (= 1 male; 2 female) 1.29 1.34 1.03 1.05
Specialist Dairy 0.0927 0.1388 0.0540 0.1571
UAA (ha) 15.11 24.18 27.47 36.72
Spouse (= 1 if work off-farm ) 0.1146 0.0656 0.4190 0.3167
Married (= 1 if married) 0.3709 0.4114 0.7449 0.6730
Number of young in the family farm 0.0801 0.0465 0.8318 0.6278
Number of family members living in
the farm
1.8457 1.9466 3.6214 3.2889
Number of family members working
in the farm
0.2409 0.3482 N/A N/A
Hired (= 1 if presence of hired
workers)
0.2099 0.2617 0.1097 0.1827
Number of bovine per UAA 0.7564 0.8798 1.1429 1.3093
Decoupled payments 2,529 5,441 7,237 9,059
Coupled Income 2,517 3,936 2,636 7,780
Other subsidies (investment aids,
organic payments …)
442 630 2,676 2,764

10. Off Farm Employment Rates in Ireland 2002-2009
Teagasc National Farm Survey
10
20
25
30
35
40
45
50
55
60
2002 2003 2004 2005 2006 2007 2008 2009
% of Operators with an
off-farm employment
% of farms where spouse
has an off-farm
employment
% of farms where
operators and/or spouse
has off-farm
employment

11. Off Farm and Coupled Farm Wage Rates in Ireland
11
-5
0
5
10
15
20
25
2002 2003 2004 2005 2006 2007 2008 2009
Average On-Farm Wage
Rate
Average Construction
Wage Rate (All Manual
Employees)
National Minimum
Wage
Average Industry Wage
Rate

12. METHODOLOGY
12

13. Neo-Classical Framework
 Households behave to maximise their utility subject to budget
and time constraints
 Becker (1965) A theory of the Allocation of Time
 Drawed upon earlier work of Schultz (1960) on education
decisions
 The time intensity of consumption goods
“Everyone would agree that even dining take time, just as
schooling does, time that could have been used productively”
 Lee (1965) Allocating Farm Resources between Farm and
Nonfarm uses
 Extend the labour-leisure model for the special case of farm
operator households
 Heckman (1979) Sample Selection Bias as a Specification Error
 Provided a two-step method that can potentially correct for sample
selection bias
13

14. Neo-Classical Applied Literature
14
 Sumner (1982) - incorporated
sample selectivity bias into off-
farm labour supply modelling
 Ahearn, El-Osta and Dewbre
(2006) - Negative effect of
government payments greater
in 1996 than 1999
 Attributed this to the
size of the payments
rather than the policy
mix of payments
 A $10,000 increase in
actual payments
reduces the likelihood of
farm operator working
off-farm by 9.8% in
1996 and 4.63% in 1999
 El-Osta, Mishra, Morehart (2008)
 Multinomial logit model with
four possible strategies for
husband and wife
 $10,000 increase in expected
payments reduces likelihood of
both husband and wife working
off-farm by 8.6%
 Corsi and Salvioini (2012)
 Impact of 2005 CAP reform on
off-farm labour participation
among 437 cereal, oilseed and
protein crop farmers in Italy.
 The single farm payment is
found however not to be a
significant driver of
participation

15. Decoupling - Relative Wage Effect
Coupled Farm Wage
Relative Attractiveness of Off Farm Work
Off-Farm Labour Supply
15

16. Decoupling – Wealth Effect
Non-Labour Income
Leisure is a Normal Good
Therefore Demand for Leisure
Off-Farm Labour
16

17. RESULTS
17

18. Probit Results (Random Effects)
DEPENDENT
VARIABLE
IRELAND ITALY
Age 0.355*** 0.347*** 0.348*** 0.061*** 0.060*** 0.054***
Age Squared -0.005*** -0.005*** -0.005*** -0.001*** -0.001*** -0.001***
Sex -0.255 -0.276 -0.269 -0.140*** -0.143*** -0.151***
Specialist Dairy -1.389*** -1.347*** -1.379*** -0.478*** -0.481*** -0.548***
UAA (ha) -0.006** -0.005** -0.006** -0.004*** -0.005*** -0.003***
Spouse work off-farm 0.0309 0.0413 0.0369 1.486*** 1.487*** 1.482***
Married 0.657*** 0.676*** 0.664*** -0.696*** -0.698*** -0.703***
Number of young -0.223*** -0.231*** -0.228*** -0.029 -0.031 -0.032
Household Size 0.198*** 0.199*** 0.198*** 0.117*** 0.118*** 0.114**
No. Family Members
working on Farm
-0.220*** -0.222*** -0.219***
Hired Workers (1,0) -0.026 -0.028 -0.023 -0.200*** -0.204*** -0.196***
Number of bovine Per
UAA
-0.027*** -0.027*** -0.027*** -0.014** -0.014** -0.015*
Decoupled Pay
(in €10,000s)
-0.088 -0.003**
Coupled Income
(in €10,000s)
-0.030 0.001
Other subsidies -0.008 -0.001
_cons -7.410*** -7.243*** -7.263*** -1.655*** -2.517*** -2.123***
18

19. Hours Equation Results (Fixed Effects)
DEPENDENT VARIABLE IRELAND ITALY
Age 0.877*** 0.895*** 0.941*** 0.29*** 0.30*** 0.29***
Agesq -0.0132*** -0.0134*** -0.0140*** -0.00408*** -0.00417*** -0.00411***
Specialist Dairy -4.257*** -4.150*** -4.500*** 0.39 0.32 0.24
UAA (ha) -0.0203* -0.0180* -0.0226** 0.01 0.01 0.02
Spouse working off-farm -0.703*** -0.674*** -0.691*** 4.42*** 4.57*** 4.54***
Married 0.483 0.545 0.612 -1.86** -1.94** -1.96**
Number of young -0.364* -0.388* -0.412** -0.45* -0.46* -0.49*
No. family members
living in the farm
0.0143 0.0318 0.0463 0.51** 0.53** 0.56***
No. family members
working in the farm
-0.57* -0.60* -0.61**
Hired Workers (1,0) -0.217 -0.244 -0.214 0.15 0.12 0.12
Number of bovine on
UAA
-0.0571** -0.0597** -0.0636*** -0.08*** -0.09*** -0.07***
Decoupled pay
(x €10,000)
-0.0468 -0.17***
Coupled Income
(x €10,000)
-0.172*** 0.17***
Other subsidies -0.00333 0.13
Mills ratio 1.948** 2.050** 2.177** 1.13 1.26 1.23
_cons 2.791 2.396 1.389 -1.70 -2.27 -2.09
19

20. Ireland - Coupled Farm Wage Rate by System
Pre and Post Decoupling
-5 0 5 10 15 20
Dairying
Dairying and Other
Cattle
Cattle and Other
Mainly Sheep
Tillage
All Farms
2007
2004
20

21. Summary
21
 Decoupling has a significant negative effect on
participation in Italy (insignificant in Ireland)
 Decoupling has a significant negative effect on the
supply of labour hours in both countries
 Coupled Income has bigger negative impact than
Decoupled Payments on off-farm labour supply in
Ireland
 Unusual result for Italy in that coupled income has
positive association with off-farm labour supply

22. Policy
22
 Job-Specific Human Capital limits options
 Non-Pecuniary benefits of farming
 Relatively low income targets and strength of the wealth effects
 Loss of work experience outside of the farm inhibits re-entry to off-farm
employment
 In the case of Ireland, taking up an off-farm job is usually a very big
commitment
 Perhaps difficult to get employment with suitable hours combined with
inertia
 Dairy farmers an unlikely target group for off-farm employment except
those exiting sector
 Differences between countries in terms of farm type characteristics and
labour market conditions and at different points of the income distribution
 Does Italy have greater scope for higher off-farm employment given the
existing lower level?
 Participation under different distribution of direct payments?