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A nalysis of farm household incomes in OECD countries M aster in A gricultural , F ood and E nvironmental P olicy A nalysis Université catholique de Louvain University of Bonn Supervisor : Prof. Bruno Henry de Frahan. Laura Borge del Rey. Outline. Introduction (1). Introduction (2).
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Analysisof farm household incomes in OECD countriesMasterin Agricultural, Foodand Environmental Policy AnalysisUniversitécatholique de Louvain University of BonnSupervisor: Prof. Bruno Henry de Frahan Laura Borge del Rey
Introduction(2) • Gardner (1992) looks at the farm problem and identifies these key contributions to the problem:
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
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)).
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.
Researchobjectives • 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.
ResearchHypothesis • «Farmincomeproblem» has diminished in developedcountries. Therefore, farmincomelevelshave converged non-farmincomelevels. • Farm household incomes are less equally distributed than non-farm household incomes. • Commoditymarketconditions, labourmarketconditions, incomedifferences as a result of skill and agedisparities and otherfactorssuch as governmentinterventionaffectfarmhhincomes in comparisonto non-farmhhincomes.
Comparisons farm/non-farm hhincomes(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.
Comparisons farm/non-farm hhincomes(3) • Definingfarm/non-farmhh: Distinctionbetweenfarm and non-farmhhismadeaccordingtothesource of income. According to this, farm hh are hh having farm self-employment income. • Following OECD(2001), narrow definition of farm hhis used: hhwhose 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.
Comparisons farm/non-farm hhincomes(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.
Comparisons farm/non-farm hhincomes(5) Average DPI of farm households (narrow definition) to average DPI of non-farm households (%) in Australia, Canada, and USA. Source: LIS
Comparisons farm/non-farm hhincomes(6) Average DPI of farm households (narrow definition) to average DPI of non-farm households (%) in Finland, Ireland, Norway and United Kingdom. Source: LIS
Comparisons farm/non-farm hhincomes(7) Average DPI of farm households (narrow definition) to average DPI of non-farm households (%) in Austria, Germany, Luxembourg, Netherlands and Switzerland. Source: LIS
Comparisons farm/non-farm hhincomes(8) Average DPI of farm households (narrow definition) to average DPI of non-farm households (%) in France and Italy. Source: LIS
Comparisons farm/non-farm hhincomes(9) Average DPI of farm households (narrow definition) to average DPI of non-farm households (%) in Hungary and Poland. Source: LIS
Comp. farm/non-farmhh 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.
Comp. farm/non-farmhhinc. inequalities(2) 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
Comp. farm/non-farmhhinc. inequalities(3) Ratio of the Gini index of farm-households (narrow definition) to Gini index of non-farm households (%) in Finland, Ireland, Norway and United Kingdom. Source: LIS
Comp. farm/non-farmhhinc. inequalities(4) Ratio of the Gini index of farm-households (narrow definition) to Gini index of non-farm households (%) in Austria, Germany, Luxembourg, Netherlands and Switzerland. Source: LIS
Comp. farm/non-farmhh inc. inequalities(5) Ratio of the Gini index of farm-households (narrow definition) to Gini index of non-farm households (%) in France and Italy. Source: LIS
Comp. farm/non-farmhhinc.inequalities(6) Ratio of the Gini index of farm-households (narrow definition) to Gini index of non-farm households (%) in Hungary and Poland. Source: LIS
Methodology(1) • Econometricmodelto test whethercommoditymarketconditions, labourmarketconditions, income-differences as a result of education and agedisparities and other variables can explainaverageincomedifferencesbetweenfarm and non-farmhouseholds. • Unbalanced panel: 16 OECD countries from the LIS database covering the period 1971-2010.
Methodology(2) • Dependent variable: Ratio of theaverage income (DPI) of farm households to average income (DPI) of non-farm households.
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:
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
Methodology(6) Method: • Use as instrumentsfor • Use groupmeans of for • In thisstudy, Hausmand and Taylor approachis extended in ordertoalsoallowcorrelationbetweentheexplanatory variables and
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.
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.