Agroscope, Institute

of

Sustainability

Sciences

|

2016 (7

th

Int. Conf. of Agricultural Statistics, Rome, 26.

-

28.10.2016)

Data

The

analysis

is

based

on

data

from

the

Swiss

Farm

Accountancy

Data

Network

(FADN)

from

the

years

2010

to

2014

including

874

non

-

organic

farm

observations

(from

317

different

farms)

and

3308

enterprise

observa

-

tions

.

All

farms

are

located

in

the

plain

region

and

belong

to

the

type

of

combined

dairy

/

arable

crop

farms

.

Average

exchange

rate

2010

-

2014

:

1

EUR

=

1

.

25

CHF

Methods

By

means

of

a

maximum

e

ntropy

model,

indirect

costs

(or

joint

costs)

are

allocated

to

the

enterprises

of

farms

.

The

1

%

best

and

worst

performing

enterprise

observations,

according

to

the

remuneration

of

labour,

are

excluded

from

the

analysis

because

their

extreme

performance

probably

results

from

special

accountancy

issues

.

Mean

values

are

calculated

for

each

sample

of

enterprises

.

Bread

cereals

are

further

analysed

:

Mean

values

are

cal

-

culated

for

the

weak

performing

group

(

1

%

to

25

%

quantile

according

to

remuneration

of

labour)

and

the

strong

performing

group

(

75

%

to

99

%

quantile)

.

The

whole

procedure

is

done

separately

for

each

year

.

Thereafter

unweighted

overall

means

are

presented

.

Results

Except

for

potatoes,

machinery

costs

are

the

most

impor

-

tant

cost

item

in

the

production

of

crops

while

labour

is

most

important

for

milk

production

.

The

economically

well

performing

enterprises

in

crop

production

generate

consi

-

derably

more

revenues,

while

successful

milk

producers

mainly

profit

from

low

production

costs

.

Conclusions

The

analysis

reveals

huge

differences

in

the

overall

economic

performance

within

each

sample

of

enterprises

.

The

realization

of

average

losses

in

some

weak

per

-

forming

groups

of

enterprises

highlights

the

partially

low

profitability

in

Swiss

agriculture

.

The

heterogeneity

within

the

sample

points

out

the

need

for

further

analyses

in

order

to

better

understand

economic

success

factors

in

agricultural

production

.

References

Lips,

M

.

(

2016

)

Disproportionate

Allocation

of

Indirect

Costs

at

Individual

-

Farm

Level

Using

Maximum

Entropy

.

Working

paper,

Agroscope,

Ettenhausen

.

Total production costs at the enterprise level

Daniel Hoop, Markus Lips, Alexander Zorn, Christian Gazzarin

Agroscope, CH

-

8356

Ettenhausen

;

www.agroscope.ch

Trimmed

sample

Cost

share

(%)

Weak

performing

group

Well

performing

group

Fodder

cereals

Rape

Sugar

beets

Potatoes

Milk

Number of enterprises

707

174

173

626

332

413

288

852

Total revenues

4944

4403

5420

4342

5798

9940

15623

6076

Seeds

263

6

288

249

188

151

361

2789

89

Fertilizer

300

7

321

273

270

493

463

799

98

Pesticides

209

5

232

185

253

404

624

953

34

Land costs

685

16

685

685

685

685

685

685

389

Total direct costs

1728

39

1791

1673

1623

2068

2271

5733

2107

Labour costs

926

21

962

843

933

811

1164

4307

4298

Machinery

1424

32

1669

1240

1447

1143

2293

3318

1255

Buildings & other joint costs

329

8

341

314

329

216

370

697

1266

Total joint costs

2679

61

2972

2397

2709

2170

3827

8321

6819

Total costs

4406

100

4762

4070

4332

4238

6098

14054

8925

Calculatory profit/loss

537

-360

1349

10

1560

3842

1570

-2850

Labour wages [CHF/h]

41.9

16.6

68.9

26.8

77.4

113.9

36.2

8.9

Mean values for bread cereals

Mean values of trimmed sample

Table 1:

Income

statement in Swiss francs

per

hectare

(or per livestock unit for milk).

Mean

values and cost shares

.

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