life cycle patterns, farm performance and structural change: an empirical research
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Life cycle patterns, farm performance and structural
change: an empirical research
Steven Van Passel
Outline
• Objectives• Data• Empirical model• Results• Conclusion
Objectives
• To measure farm performance in Flanders: measuring firm-efficiency
• To test the impact of firm aspects on firm-efficiency:– Impact of age– Impact of succession– Impact of education– Impact of solvency
• To test the link between firm-efficiency and firm-growth
on farm-efficiency
Data
• FADN-data of 1018 Flemish farmers• Data available for the period 1989-2002• 8926 observations unbalanced panel data
• To measure the link between efficiency and growth, we use a balanced data set of 304 Flemish farms (4256 observations)
Empirical model
• Farm performance measuring firm-efficiency
• Measuring production frontier– Data envelopment analysis (DEA)– Stochastic frontier approach (SFA)– Aigner, Lovell & Schmidt(1977) and Meeusen &
Van de Broeck(1977) introduced:
Yit = α + f(xit , β) + vit - ui
Firm efficiency
X
Y
0
F
C
B
A
Empirical model
• Random effects panel data formulation with time-invariant inefficiency
• Inefficiency or not (ui = 0?)• Cobb-Douglas versus translog functional
form• Predictions of firm-level technical
efficiencies (Battese & Coelli, 1988)• To analyze the impact of firm-specific factors
on efficiency, we enlarge the stochastic production function with firm-aspects
Empirical model: results
• Farm-aspects affecting efficiency• Age and efficiency• Growth and efficiency
Impact farm aspects on efficiency
• Farm managers with a high education level are more efficient than managers with lower education levels;
• Older managers are less efficient;• Farms with a successor are more
efficient than farms without a successor;• Farmers with high solvency are less
efficient
Age and efficiency
• Age has an inverse impact on efficiency– What about experience?– Link solvency and age?– Link education and age?
• Expand our model with extra variables
-0,04
-0,035
-0,03
-0,025
-0,02
-0,015
-0,01
-0,005
0
20 24 28 32 36 40 44 48 52 56 60 64 68 72
Age
Efficiency
Impact of age on efficiency
0
0,02
0,04
0,06
0,08
0,1
0,12
0,14
0,16
20 30 40 50 60 70
Age
Efficiency
Impact of age on efficiency
Age: 39 years
Solvency = 1Diploma = 1
0
0,02
0,04
0,06
0,08
0,1
0,12
0,14
0,16
0,18
20 30 40 50 60 70
Age
Efficiency
Impact of age on efficiency
Diploma = 1
Solvency = 1
Solvency = 0
Impact of age on efficiency
0
0,02
0,04
0,06
0,08
0,1
0,12
0,14
0,16
0,18
20 24 28 32 36 40 44 48 52 56 60 64 68 72
Age
Efficiency
Diploma = 5(low education)
Diploma = 1 (high education) Solvency = 1
Growth and efficiency
• Sample of 304 farms (1989-2002)• Calculation of efficiency of each farm during
period 1989-1996• Farm-Growth = farm size(2002) – farm size
(1997)• Farm-growth ~ farm efficiency ?• 10 farms with highest growth in farm size
average efficiency of 85,2%
• 10 farms with highest decline in farm size average efficiency of 73,5%
Growth and efficiency
-10
0
10
20
30
40
50
0,4 0,5 0,6 0,7 0,8 0,9 1
firm-efficiency
firm-growth
Conclusion
• Measuring farm performance as efficiency, we observe a wide range in the level of technical efficiencies across all farms
• Higher education levels, presence of a successor and low solvency rates have a positive impact on farm-efficiency
Impact of age on efficiency– First a positive impact (‘learning effects’)– After certain age decreasing impact– High solvency rates, low education decrease
this critical age level
Conclusion
• More efficient farmers have in general a significant higher growth
• Further research– Constructing a growth model by incorporating
firm aspects as size, succession besides efficiency
growth = f(size,succession,education,efficiency)
– Problem: correlation between efficiency and those other aspects
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