Analysis of farm household incomes in
OECD countries Master in Agricultural, Food and Environmental Policy
AnalysisUniversité catholique de
Louvain University of Bonn
Supervisor: Prof. Bruno Henry de Frahan
Laura Borge del Rey
2
Outline
IntroductionResearch objectives and HypothesisComparison of farm/non-farm household income levelsComparison of farm/non-farm hh income inequalitiesMethodologyEconometric ResultsConclusions
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Introduction (1)
4
Introduction (2)
Gardner (1992) looks at the farm problem and identifies these key contributions to the problem:
Supply-demand model based on commodity market conditions
Disequilibrium between the farm and non-farm labour marketsIncome differences as a result of skill differences or non-wage aspects of farm/non-farm employments
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Introduction (3) The characteristics of the supply-
demand model of aggregate agricultural commodities are that for agricultural products:
Very inelastic D Very inelastic S D increases slowly over time S increases faster than D
declining and volatility of farm prices and low incomes for farm people
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Introduction (4) A disequilibrium between the farm and
non-farm labour markets that keeps farm people with lower incomes in the agri. sector.
In the short term : As a result of costs involved in labour movement such as job search and moving expenses.
In the long term: differences in education, lack of skills to work out of farm and age between farm and non-farm jobs. (Johnson (1953)).
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Introduction (5) Gardner (2002) proposes these factors to
explain growth in farm household incomes in the US since 1950:
Agricultural productivity growth; Saving and investment by farm people; Adjustment to disequilibrium through migration
of workers from farm jobs to non- farm jobs; Off-farm work opportunities for farm people; Improved skills of farm people; Government policies aimed to provide financial
aid to farm people and rural areas.
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Research objectives Assess whether the “farm income
problem” still prevails nowadays in OECD countries by providing the evolution of average farm hh incomes in comparison to average non-farm hh incomes from1971 to 2010.
Examine the inequality of farm/non-farm hh incomes by providing the evolution of the Gini index of farm hh incomes relative to the Gini index of non-farm hh incomes over the same period.
Examine whether the contributions identified in the literature are valid in explaining low farm income in OECD countries over the period 1971 to 2010.
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Research Hypothesis «Farm income problem» has diminished in
developed countries. Therefore, farm income levels have converged non-farm income levels.
Farm household incomes are less equally distributed than non-farm household incomes.
Commodity market conditions, labour market conditions, income differences as a result of skill and age disparities and other factors such as government intervention affect farm hh incomes in comparison to non-farm hh incomes.
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Comparisons farm/non-farm hh incomes(1) Luxembourg Income Study (LIS) Microeconomic data collected by countries
through national household-based budget surveys.
Criteria to select countries: > 3 waves of data survey in the LIS database. The surveys separate between farm self-
employment income and non-farm self-employment income.
The surveys contain a minimum of 30 farm hh.
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Comparisons farm/non-farm hh incomes(2)Country Survey WaveAustralia 1981, 1989, 1995, 2001, 2003Austria 1994, 1997, 2000Canada 1971,1975,1981,1987,1991,1994,1997,1998,2000,2004,2007Finland 1987, 1991, 1995, 2000, 2004France 1979,1984, 1989, 1994Germany 1973,1978, 1983, 1984, 1989, 1994, 2000Hungary 1991, 1994, 2005Ireland 1987, 1994, 1995, 1996, 2000, 2004Italy 1987,1989, 1991, 1993, 1995, 1998, 2000Luxembourg 1985, 1991, 1994Netherlands 1987, 1993, 1999Norway 1979, 1986, 1991, 1995, 2000, 2004Poland 1995, 1999, 2004Switzerland 1992, 2000, 2002United Kingdom
1979, 1986, 1991, 1995, 1999
United States 1974, 1979, 1986, 1991, 1994, 1997, 2000, 2004, 2007, 201016 countries 84 observations
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Comparisons farm/non-farm hh incomes(3) Defining farm/non-farm hh: Distinction
between farm and non-farm hh is made according to the source of income. According to this, farm hh are hh having farm self-employment income.
Following OECD(2001), narrow definition of farm hh is used: hh whose farm self-employment income is => than 50% of their factor incomes (paid employm. income+self-employm. income+capital income). /non-farm hh: hh whose farm self-employment income is null.
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Comparisons farm/non-farm hh incomes(4)
Defining income: Cash disposable household income (DPI) is used.
+ paid employment income+ self-employment income+ capital income+ social security transfers- taxes and social security contributions Ratio of average income (DPI) of farm
households narrowly defined to the average income (DPI) of non-farm households narrowly defined is computed for each country and survey wave.
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Comparisons farm/non-farm hh incomes(5)
Average DPI of farm households (narrow definition) to average DPI of non-farm households (%) in Australia, Canada, and USA.
25
75
125
100
50
150
1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010
Australia Canada United States
Source: LIS
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Comparisons farm/non-farm hh incomes(6)
Average DPI of farm households (narrow definition) to average DPI of non-farm households (%) in Finland, Ireland, Norway
and United Kingdom.
Source: LIS
25
75
125
100
50
150
1979 1982 1985 1988 1991 1994 1997 2000 2003
Finland NorwayIreland United Kingdom
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Comparisons farm/non-farm hh incomes(7)
Average DPI of farm households (narrow definition) to average DPI of non-farm households (%) in Austria,
Germany, Luxembourg, Netherlands and Switzerland.
Source: LIS
25
75
125
150
100
50
1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003
Germany LuxembourgAustriaSwitzerlandNetherlands
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Comparisons farm/non-farm hh incomes(8)
Average DPI of farm households (narrow definition) to average DPI of non-farm households (%) in France and Italy.
Source: LIS
25
75
125
100
50
150
1979 1982 1985 1988 1991 1994 1997 2000
ItalyFrance
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Comparisons farm/non-farm hh incomes(9)
Average DPI of farm households (narrow definition) to average DPI of non-farm households (%) in Hungary and
Poland.
Source: LIS
25
75
50
125
100
150
1990 1992 1994 1996 1998 2000 2002 2004
Hungary Poland
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Comp. farm/non-farm hh inc. inequalities(1) Luxembourg Income Study (LIS) Gini index as a measure of inequality. It
is 0-1, 0 means perfect equality and 1 perfect inequality.
Ratio of the of the Gini index of farm households narrowly defined to the Gini index of non-farm households narrowly defined is computed for each country and survey wave.
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Comp. farm/non-farm hh inc. inequalities(2)
90
110
100
130
150
170
120
160
140
19701973 1976197919821985 19881991199419972000 2003 20062009
Australia Canada United States
Ratio of the Gini index of farm-households (narrow definition) to Gini index of non-farm households (%) in
Australia, Canada and United States.
Source: LIS
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Comp. farm/non-farm hh inc. inequalities(3)
80
100
120
130
150
140
110
90
1979 1982 1985 1988 1991 1994 1997 2000 2003
Finland Ireland Norway United Kingdom
Source: LIS
Ratio of the Gini index of farm-households (narrow definition) to Gini index of non-farm
households (%) in Finland, Ireland, Norway and United Kingdom.
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Comp. farm/non-farm hh inc. inequalities(4)
65
75
85
95
105
115120
130
140
155150145
125
135
110
100
90
80
70
1973 1976 1979 1982 1985 1988 1991 1994 1997 2000 2003
Austria Germany LuxembourgNetherlands Switzerland
Source: LIS
Ratio of the Gini index of farm-households (narrow definition) to Gini index of non-farm
households (%) in Austria, Germany, Luxembourg, Netherlands and Switzerland.
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Comp. farm/non-farm hh inc. inequalities(5)
80
100
120
110
140
160
170
150
130
90
1979 1982 1985 1988 1991 1994 1997 2000
France Italy
Source: LIS
Ratio of the Gini index of farm-households (narrow definition) to Gini index of non-farm
households (%) in France and Italy.
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Comp. farm/non-farm hh inc.inequalities(6)
70
80
100
120
130
160
170
150
140
110
90
1990 1992 1994 1996 1998 2000 2002 2004
Hungary Poland
Source: LIS
Ratio of the Gini index of farm-households (narrow definition) to Gini index of non-farm
households (%) in Hungary and Poland.
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Methodology(1) Econometric model to test whether
commodity market conditions, labour market conditions, income-differences as a result of education and age disparities and other variables can explain average income differences between farm and non-farm households.
Unbalanced panel: 16 OECD countries from the LIS database covering the period 1971-2010.
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Methodology(2) Dependent variable: Ratio of the
average income (DPI) of farm households to average income (DPI) of non-farm households.Explanations Independent
VariablesExp. sign
Commodity market conditions
Agric. terms of trade
+
Labour market conditions
Standardized unemployment rate
-
GDP per capita -Population density -
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Methodology(3)Explanations Independent
VariablesExp. sign
Income-earning capacity
Low education ratio -High education ratio +Age ratio +/-
Government intervention
Farm direct payments
+
General agricultural services
+
Other factors Real long term interest rates
-
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Methodology(4) ECM:
for i=1,…N and t= 1,….T , where i=countries; t=years. country-specific error; : idiosyncratic error The log-log form adopted in this
study:
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Methodology(5) Correlation between some explanatory
variables and error components motivates the presence of endogenous variables.
The estimator proposed by Hausman and Taylor (1981) is used to take into account endogeneity between variables and .
Partition and , Where, and are exogenous and are endogenous
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Methodology(6)
Method: Use as instruments for Use group means of for
In this study, Hausmand and Taylor approach is extended in order to also allow correlation between the explanatory variables and
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Results(1)Independent variable
Coeff Std.Err P>ltl
Commodity market conditionsAgricultural terms of trade
0.177 0.159 0.272
Labour market conditions Standarised unemployment rate
0.049 0.069 0.480
GDP per capita -0.128 0.128 0.322Population density -0.024 0.022 0.286Number of observations
84
F-test of regression F (11,72)=6.48 Prob>F=0.000
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Results(2)Independent variable Coeff Std.Er
rP>ltl
Income-earning capacityLow education level ratio
-0.539 0.117 0.000
High education level ratio
-0.037 0.022 0.105
Age ratio 0.879 0.467 0.064
Government intervention
Farm direct payments 0.027 0.022 0.217
General agricultural services
0.001 0.029 0.961
Other variables
Real long term interest rates
-0.021 0.012 0.089
Time 0.047 0.011 0.000
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Conclusions (1) Average incomes of farm households
are close to or higher than those of non-farm households in most of the surveyed OECD countries from 1971 to 2010.
The Gini index (that estimates the degree of inequality in income distribution) show that farm household incomes are more unequally distributed than non-farm households in most of the surveyed OECD countries over the same time period.
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Conclusions (2) Econometric results suggest that income of
farm-households are more affected by the low education level, the age ratio and the real long term interest rates.
However, they are not influenced by commodity market conditions, labour market conditions and government intervention.
It was also found that the average farm household incomes have increased with respect to the average non-farm household incomes over the period 1971 -2010.
Thank you!
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