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