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Volatility of Farming and Operator’s Family Income of Canadian Farmers Kenneth Poon University of Guelph AGRI Research Group, Statistics Canada.

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Presentation on theme: "Volatility of Farming and Operator’s Family Income of Canadian Farmers Kenneth Poon University of Guelph AGRI Research Group, Statistics Canada."— Presentation transcript:

1 Volatility of Farming and Operator’s Family Income of Canadian Farmers Kenneth Poon University of Guelph AGRI Research Group, Statistics Canada

2 Farm Income Characteristics  Farming income highly variable compared to other sectors  Variability in production and price  Farm families are more financially vulnerable  Volatility as a measure of financial well-being  Volatility = variability over time

3 Support Program  Growing Forward  Objectives: Foster competitive and innovative sector  improve welfare of farm operators and families  Business Risk Management (BRM) Suite  Programs designed to reduce income / margin volatility  Catch-all program: no specific commodity/group targeted

4 Why Volatility?  Currently, no clear picture of income volatility for Canadian agricultural sector  Few datasets are formatted to examine volatility  Studying volatility can identify…  Any sectors are relatively more vulnerable  Trends in volatility  Factors related to volatility

5 Data Source  The Farm Micro-Longitudinal Dataset  Operator-level Panel data, 2001 - 2006  Source incorporated & unincorporated income tax  Data cleaned  NO T3 records (i.e. community farms)  NO duplicates: 1 operator per farm per family  NO entries with 0 revenue or expenses for all 6 years  NO entries labeled as ‘non-farm’ for 3+ consecutive years  Final Sample Size: 32692 operators  5355 operators dropped

6 Measuring Volatility  Volatility = variation over time  Measurement: Coefficient of Variation (CV)  Standard deviation over time / mean over same period  % variation from mean  CV=0: no volatility, CV=1: SD=mean, CV undefined: mean=0  Interested Variables  Net Operating Revenue (NOR)  Operator’s Family Income (OFI), unincorporated only

7 Relating Volatility  Relating volatility: Spearman Rank Correlation  Similarity in ranking of CV between NOR, OFI  Unweighted comparison between 2 variables  If Spearman’s rho =  1: ranking matches perfectly  0: non of the rankings match  -1: ranking exactly opposite

8 Typology  Typology based on AAFC definition  Determined by typology @ start of sample (2001) *Low income cutoff in 2001, for family with 2 parents, 2 children under 18 SOURCE: Farm Micro-Longitudinal Dataset, 2001-2006 TypologyLow IncomePensionHobby DefinitionTHI < $19,473* & REV <$250k Age ≥ 65 OR Age ≥ 60 with pension income REV <50k & Family off-farm income > $50k # of Records344158642235 TypologySmallMediumLargeVery Large DefinitionREV ≤ $99,999REV between $100k and $249,999 REV between $250k and $499,999 REV ≥ $500k # of Records4350600849815813

9 Commodity Groups determined by NAISC Commodity consist of >50% sales Determined @ start of sample (2001) Commodity Groups Oilseeds & Grains PotatoFruits & Tree Nuts Greenhouses, Nurseries & Floriculture Other Vegetables Other Crops # of Records 8945781 671 1131 12311806 Beef CattleDairy Cattle Hog and PigsPoultry & EggsOther Animals # of Records 77145015217016881540 SOURCE: Farm Micro-Longitudinal Dataset, 2001-2006

10 Typology vs. Commodity Groups SOURCE: Farm Micro-Longitudinal Dataset, 2001-2006

11 Volatility of Typology  CV ranked within typology, into quartiles  Max CV of 25 th, 50 th, 75 th percentile reported Volatility of NOR, 2001-2006 CV@ Low IncomePensionHobbySmallMediumLarge Very Large 25ptile 0.730.560.590.520.360.410.45 50ptile 1.341.001.070.950.680.740.83 75ptile 2.751.992.271.951.291.481.69 SOURCE: Farm Micro-Longitudinal Dataset, 2001-2006 0.73 1.34 2.75 0.36 0.68 1.29 CV of NOR at selected percentiles, 2001-2006

12 Weighted Annual Mean of NOR, 2001-2006 SOURCE: Farm Micro-Longitudinal Dataset, 2001-2006

13 Median 3-year CVs by Typology, 2001-2006 SOURCE: Farm Micro-Longitudinal Dataset, 2001-2006

14 Volatility of NOR by Commodity Groups CV atGrain & OilseedPotato Fruits and Tree Nuts Greenhouses, Nurseries, Floriculture 25ptile 0.58 0.540.570.49 50ptile 0.97 0.780.890.86 75ptile 1.901.701.712.23 CV atBeef CattleDairy CattleHogs and Pigs Poultry and Eggs 25ptile 0.630.210.50 0.41 50ptile 1.170.390.91 0.61 75ptile 2.380.821.721.09 CV of NOR at selected percentiles, 2001-2006 SOURCE: Farm Micro-Longitudinal Dataset, 2001-2006 0.21 0.39 0.82 0.63 1.17 2.38 0.49 0.86 2.23

15 Weighted Annual Mean of NOR, 2001-2006 SOURCE: Farm Micro-Longitudinal Dataset, 2001-2006

16 Median 3-Year CVs by Commodity, 2001-2006 SOURCE: Farm Micro-Longitudinal Dataset, 2001-2006

17 Volatility by Typology Volatility of OFI, 2001-2006 CV at Low IncomePensionHobbySmallMediumLarge Very Large 25ptile 0.460.170.150.200.240.300.41 50ptile 0.760.370.310.350.390.510.71 75ptile 1.210.630.570.580.630.871.20 SOURCE: Farm Micro-Longitudinal Dataset, 2001-2006 0.46 0.76 1.21 0.41 0.71 1.20 0.15 0.31 0.57 0.20 0.35 0.58

18 Weighted Annual Mean of OFI, 2001-2006 SOURCE: Farm Micro-Longitudinal Dataset, 2001-2006

19 CV of Total Household Income SOURCE: Farm Micro-Longitudinal Dataset, 2001-2006

20 Volatility of Commodity Groups CV atGrain & OilseedPotato Fruits and Tree Nuts Greenhouses, Nurseries, Floriculture 25ptile 0.200.290.180.16 50ptile 0.390.420.370.30 75ptile 0.660.750.640.55 CV atBeef CattleDairy CattleHogs and Pigs Poultry and Eggs 25ptile 0.210.200.240.17 50ptile 0.410.330.460.37 75ptile 0.720.570.730.61 Volatility of OFI, 2001-2006 SOURCE: Farm Micro-Longitudinal Dataset, 2001-2006 0.29 0.42 0.75 0.24 0.46 0.73 0.20 0.33 0.57 0.16 0.30 0.55

21 Weighted Annual Mean of OFI by Commodity Group, 2001-2006 SOURCE: Farm Micro-Longitudinal Dataset, 2001-2006

22 3-year CVs of OFI by Commodity Group, 2001-2006 SOURCE: Farm Micro-Longitudinal Dataset, 2001-2006

23 Correlation between CV of NOR & THI Spearman’s rho between NOR & OFI by typology, 2001-2006 Low IncomePensionHobbySmallMediumLarge Very Large rho 0.490.400.170.410.680.800.86 Grain & OilseedPotato Fruits and Tree Nuts Greenhouses, Nurseries, Floriculture rho 0.480.640.350.46 Beef CattleDairy CattleHogs and Pigs Poultry and Eggs rho 0.450.780.640.69 Spearman’s rho between NOR & OFI by commodity groups, 2001-2006 SOURCE: Farm Micro-Longitudinal Dataset, 2001-2006 All positive, significant at 5% 0.170.80 0.35 0.78

24 Volatility & Correlation: NOR vs OFI Coefficient of Variation (CV)Net Operating Revenue Total Household Income By Typology Highest VolatilityLow-Income Farms Lowest VolatilityMedium FarmsHobby Farms By Commodity Group Highest VolatilityBeef CattleHogs and Pigs Lowest VolatilityDairy CattleGreenhouses Spearman’s Rank Correlation (rho) By Typology Highest CorrelationVery Large Farms Lowest CorrelationHobby Farms By Commodity Group Highest CorrelationDairy Cattle Lowest CorrelationFruits and Tree Farms SOURCE: Farm Micro-Longitudinal Dataset, 2001-2006

25 Major Trends in Volatility  Volatility of NOR, OFI increasing over time  OFI volatility increases with farm size  NOR volatility lowest for medium farms  High volatility not always linked with low NOR or OFI  Operators of very large farms have high volatility and NOR  Correlation Between NOR and OFI volatility increases with farm size

26 Possible Explanation for Trends Farm size vs OFI Volatility – Operators of smaller farms more likely to adopt off-farm work, stabilize off-farm income – Large-farm operators likely take on higher risk, specialize, reliant on farming as main source of income – Low-income farm operators may not have time/resource for effective risk management, relies on farming as main source of income

27 Possible Explanation for Trends  Correlation Between NOR, OFI volatility increases with farm size  Large-farm operators likely more reliant on farming as main source of income  Operators of smaller farms likely have off-farm work  Medium farms have lowest volatility in NOR  Dairy operators make up majority of medium farm operators  Efficiency of scale? Best combination of diversification & risk management?

28 Further Research  Relationship between size, volatility, and correlation  Explain by off-farm work opportunities?  Regression between CV & size, farm type, typology, off-farm labour market characteristics  Low-income farm operators financially vulnerable  How does current support programs affect household income for these individuals?


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