Lesson 5.6: Employment model

Icône de l'outil pédagogique Author

Eoghan Garvey


Icône de l'outil pédagogique The human picture

SEAMLESS models European agriculture at a number of levels – from the field to the region, to the continent as a whole. While the focus is mainly on economic and environmental factors, it is important also to look at the changing social and human picture. The employment model is one way in which SEAMLESS does this.

The employment model of SEAMLESS focuses on agricultural labour in regions across Europe. The main question that the model tries to answer is how labour inputs are allocated across the individual agricultural activities. Data on how much family and paid work is done on a farm is fairly commonplace but very little exists on how much labour is generally devoted to each production activity. We do not know very much, for example, about whether a hectare of wheat necessitates more labour in the north or south of Greece, or whether having 10 dairy cows necessitates more labour input in the east or west coast of Ireland. The employment model in SEAMLESS uses Bayesian econometric techniques to try to answer questions like these.


Icône de l'outil pédagogique Some data

The resulting activity specific data are called input coefficients. Input coefficients can be put to work in a number of interesting fields. Activityspecific income indicators may be derived, for example, which should facilitate analyzing broader SEAMLESS results. Labour coefficients can also be used to calculate per capita income in the agricultural sector and to help forecast employment changes. Input coefficients are of most use when integrated into the body of a sectoral model. The version of the CAPRI model to be used in SEAMLESS will contain much of the information on input coefficients yielded by the SEAMLESS employment model.

 


 

Austria

Germany

Denmark

Spain

 

Family Labour- Hours

Family Labour- Hours

Family Labour- Hours

Family Labour- Hours

Soft Wheat

56.789

36.776

24.117

23.228

 

4.02

1.153

0.681

0.785

Barley

69.049

44.724

28.015

23.969

 

4.351

1.182

0.552

0.462

Durum Wheat

54.689

0

0

20.37

 

14.001

0

0

0.894

Rye

65.005

32.13

25.959

35.893

 

8.836

1.448

1.477

3.095


Table 1. Selection of National Family Labour Input Coefficients for Cereals

 

Included also in the employment model are two useful additions. Work on gender in agriculture is underway, where the focus is to explore the gender balance in family labour, and how this differs across regions and activities.

 

Table 2. Percentage change in the family labour force 1995-2005.

 

% D 1995-2005

(Persons)

% D 1995-2005

(AWUs)*

Total

Females

Total

Females

Austria

-21.1

-19.6

-13.0

3.4

Belgium

-28.0

-30.9

-20.3

-9.1

Denmark

-32.8

-33.6

-45.3

-46.6

Finland

-38.9

-44.6

-44.4

-48.9

Greece

-3.6

-7.4

-11.4

-14.7

Ireland

-15.2

-20.2

-29.8

-39.7

Italy

-33.4

-30.9

-27.8

-26.4

Luxembourg

-23.2

-26.8

-28.4

-36.1

Netherlands

-24.6

-17.6

-27.9

-19.0

Portugal

-31.9

-31.8

-32.5

-34.1

Spain

-16.8

-12.2

-19.0

-20.3

Sweden

-1.7

4.7

-18.0

-13.9

UK

20.6

36.1

-6.8

9.1

* Annual Working Units

 

Also, a separate demographic module tracks demographic changes in farming over time at a regional level. This add-on to the employment model is useful on two fronts – for long term employment forecasting and, most especially, because it links agricultural employment to the wider economy.

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