CARERA The Impact of CAP Reform on the Employment Levels in Rural Areas

Xueqin Zhu & Alfons Oude LansinkBusiness Economics, Wageningen University

(8 June 2007, Uppsala)

D12 An Assessment of the Impact of CAP Reform on the Competitiveness of the Farming Sector (Field cropping)

Overview

Frontier model (Output distance function) and inefficiency effect model

Input and output variables Field cropping in four countries (GE,GR,NL & SW) Input and output prices Explanatory variables (z) of the efficiency effects model Frontier function & technical efficiency estimates Present activities and future plan

Output distance function and inefficiency effects model Translog

Inefficiency effects model

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Outputs and inputs specification 4 Outputs

Cereals Root crops (aggregated by potatoes and sugar beets) Other crops (10 remaining crops in FADN data) Other products (livestock products and other output)

6 Inputs 3 variable inputs

Seeds Chemicals (aggregated by fertilisers and pesticides) Other variable inputs (other specific inputs & farm overheads)

Three factors (labour, land and capital)

Composition of field crop outputs(%)

Germany Greece Netherlands Sweden

Cereals 25 20 8 25

Root crops 22 11 60 35

Other crops 14 66 19 11

Other output 39 3 13 29

Total 100 100 100 100

Composition of variable inputs (%)

Germany Greece Netherlands Sweden

Seeds 9 13 23 10

Chemicals 21 32 24 21

Other 70 55 53 69

Total 100 100 100 100

Tornqivist price indexes for outputs and inputs

Root crops aggregated by 2 EUROSTAT price indexes

Other crops aggregated by 7 EUROSTAT price indexes

Other output by 2 EUROSTAT price indexes Chemicals (input) by 2 EUROSTAT price indexes Other variable inputs by 3 EUROSTAT price

indexes

Price index of root crops1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

GE 145 105 106 126 116 100 116 110 126 107

GR 117 120 121 94 93 100 96 78 84 89

NL 219 136 137 213 197 100 138 139 136 129

SW 130 116 101 110 132 100 117 109 108 115

Price index of other crops1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

GE 109 109 111 113 93 100 111 110 116 110

GR 120 118 112 103 97 100 89 99 109 99

NL 94 98 104 103 102 100 99 94 94 89

SW 106 110 111 113 93 100 106 105 103 103

Explanatory variables in inefficiency effects model- exogenous factors z1 (composition of subsidy): coupled (crop) subsidy/

total subsidy z2 (composition of revenue): total subsidy/total

revenue z3: farm taxes z4:farm size z5 (crop specialization): crop output/total output z6 (family labour): unpaid labour/total labour z7 (ownership of land): rented land/total land z8 (long term debt):long term loans/total assets z9 (short term debt): short term loans/total assets

Explanatory variables in inefficiency effects model- regional Dummy’s 13 regions for GermanySchleswig-Holstein, Niedersachsen,Nordrhein-Westfalen,

Hessen, Rheinland-Pfalz, Baden-Württemberg, Bayern,Saarland, Brandenburg, Mecklenburg-Vorpommen,Sachsen, Sachsen-Anhalt, Thueringen

4 regions for GreeceMakedonia-Thraki, Ipiros-Pelponissos-Nissi Loniou,

Thessalia, Sterea Ellas-Nissi Egeaou-Kriti 3 regions for SwedenSlattbygdslan, Skogs-och mellanbygdslan, Lan i norra

Mean technical efficiency 1995-2004 Germany: 0.64 Greece: 0.52 Netherlands: 0.75 Sweden: 0.69

Technical efficiency over time1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

GE 0.59 0.65 0.65 0.61 0.64 0.69 0.68 0.67 0.60 0.61

GR 0.63 0.58 0.57 0.39 0.42 0.47 0.52 0.53 0.59 0.58

NL 0.73 0.75 0.75 0.74 0.75 0.76 0.75 0.77 0.77 0.78

SW 0.64 0.77 0.74 0.68 0.66 0.65 0.73 0.69 0.66 0.69

Regional technical efficiency Germany

1 2 3 4 5 6 7 8 9 10 11 12 13

TE 0.66 0.65 0.63 0.62 0.63 0.67 0.64 0.67 0.65 0.61 0.67 0.60 0.62

Fre. 108 1501 781 442 309 362 784 3 145 66 193 188 87

Regional technical efficiency Greece

Makedonia-Thraki

Ipiros-Pelponissos-Nissi Loniou

Thessalia Sterea Ellas-Nissi Egeaou-Kriti

Total

TE 0.51 0.60 0.54 0.50 0.52

Freq. 8616 346 2725 1408 13095

Regional technical efficiency Sweden

Regions Slattbygdslan

Skogs-och mellanbygdslan

Lan i norra

Total

TE 0.69 0.67 0.74 0.69

Freq. 646 79 20 745

Impacts of z variables on TE

GE GR NL SW

Z1 Crop subsidy -0.34* -0.12* -0.65 -0.68*

Z2 Total subsidy 0.21* 0.15* 0.15* 0.27*

Z3 Taxes -0.89* 0.38* -0.16* 0.50*

Z4 Farm size -0.70* -0.15 0.12* -0.44*

Z5 Crop specialization 0.25* -0.94* 0.13* 0.11*

Z6 Family labour -0.15 0.19 0.17 0.70

Z7 Ownership land 0.45** -0.23** -0.13* -0.28*

Z8 Long run debt 0.29 0.18* 0.17 -0.16**

z9 Short run debt 0.15* 0.17* 0.29 0.22

Present activites

Efficiency and productivity analysis: Calculation of production elasticity's of inputs Productivity analysis and decomposition into

technical change, technical efficiency change, allocative efficiency change and scale effects

Workpackage 6: Farmers’ survey Non-farmer stakeholders’ survey

Future plan

Interpretation of the results, especially the impact of subsidy’s on technical efficiency, and the regional differences, with cooperation with partners

Request to the partners: Comments on the selection of inputs and outputs The regional information (Local, national subsidy’s,

infrastructural conditions, market access etc.) which can explain the efficiency

Cost efficiency of the crop sector Further study on the dairy sector