An empirical analysis of the determinants of the Rural Development policy spending

1. An empirical analysis of the determinants of the Rural Development policy spending for Human Capital • Beatrice Camaioni1, Valentina Cristiana Materia2 • DEAR, UniversitàdegliStudidellaTuscia, Viterbo, Italy • Department of Economics, UniversitàPolitecnicadelle Marche, Ancona, Italy 122nd European Association of Agricultural Economists Seminar Evidence-Based Agricultural and Rural Policy Making Methodological and Empirical Challenges of Policy Evaluation February 17th – 18th, 2011, Ancona (Italy) Centro Studi Sulle Politiche Economiche, Rurali e Ambientali associazioneAlessandroBartolastudi e ricerche di economia e di politica agraria Università Politecnica delle Marche

2. Outline • The aim of the paper • The Human Capital (HC) policy • overview in Rural Development (RD) plans • regional analysis of HC expenditure • Empirical analysis • Concluding remarks

3. A. The aim of the paper • Analyse the distribution of the Rural Development (RD) expenditure for specific measures related to Human Capital across EU • Investigate which factors weigh more in determining the expenditure for the Human Capital policy of the EU regions (Nuts 2 level)

4. B. The Human Capital (HC) policy • EU 2020 strategy: • smart growth (education, knowledge and innovation) • sustainable growth (a resource-efficient, greener and more competitive economy) • inclusive growth (high employment and economic, social and territorial cohesion) • RD policy framework: Generational change, training and education, and advisory services are associated with the enhancement of human capital in order to pursue the objective of competitiveness (Axis 1) • Vocational training and information actions (111) • Setting up of young farmers (112) • Early retirement (113) • Use of advisory services (114) • Setting up of management, relief and advisory services (115) Human capital and knowledge transfer

5. Overview in RD plans (1) Programming period 2007-2013 96.1 billion euro EAFRD available for RD policy 44.5% to Axis 2 – Agro-environment 33.6% to Axis 1 – Competitiveness 13.3% to Axis 3 – Diversification, 5.9% to Axis 4 – Leader 2% to Technical assistance HC: 7.8% of the entire budget for RD policy 71% Physical Capital and Innovation 23% HC and Knowledge transfer 2% Food&Processing modernisation, Innovation&Quality 4% other Axis 1 measures

6. Overview in RD plans (2) Relative importance of HC budget on total RD policy EU-27: 7,8%

7. Overview in RD plans (3) Member States allocation for HC measures

8. Regional analysis of HC expenditure Divergences btw MS may reflect: Difficulties in terms of capacity of spending? “Administrative” consequence? Legitimate political choice? The emerging picture for EU-15: The Continental regions show the highest capacity of spending and the highest value of HC expenditure/holdings The Northern regions show the highest value of HC expenditure/AWU The Southern regions show lagging value for both the indicators (but NOT Spain and Italy) AT, BE, DE, FR, LU, NL DK, FI, IE, SE, UK GR, PT

9. HC expenditure/holdings

10. HC expenditure/AWU

11. C. The empirical analysis Which factors might determine the differences btw regions in terms of spending for HC? Do they really explain the emerging distribution of expenditure? A set of relevant socio-economic (baseline and impact) indicators selected from CMEF: Dependent variable: HC expenditure (thousand euro) Year: 2007-2008 Several estimation attempts (OLS)

12. Some interesting findings... • First attempt of estimation: • we use the only CMEF indicators… but: • Significant: Age ratio (+) and % managers with a basic or full agricultural training (-) • Not significant: GDP and GVA/AWU • Second attempt: • we use a “proxy” for lab. Productivity... but: • Significant: GDP, AWU, age ratio, % managers with a basic or full agricultural training • Not significant: GVA At regional level, are there other variables, in any way related to CMEF, significant and influent as it seems?

13. Results of the last estimation • The age structure is the main factor of influence (+) • The fact that a region is Rural or Converg. seems not significant • AWU (+), UAA (+) • GVA is not significant (-)

14. D. Concluding remarks (1) • Although the relevance of the HC issue in light of the EU 2020 challenges, the budget dedicated to this policy is relative low (7.8%) with respect to the entire budget for the RD policy (2007-2013) • No homogeneity btw the EU countries in terms of spatial distribution of the spending for HC: Member States with a lower budget profile on HC, tend to invest in more complex and time consuming measures (vocational training), while countries allocating more funds to the HC policy invest more in generational turnover measures ( “premium” measures: early retirement and setting up of young farmers) • The empirical estimations demonstrate that at regional level the variable strictly associated to HC as suggested by the CMEF are not relevant

15. D. Concluding remarks (2) • Rather, other variables, in any way related to agriculture, are relevant in the decision of spending: • ... age structure and AWU are obviously relevant, in fact, they reflect the target of the beneficiaries the measures analysed are addressed to • ... but also the UAA, as indicator of the importance of agriculture in the regions, and the number of holdings have a great impact • TO DO... • extend this analysis to a longer series of data covering several years • repeat the analysis distinguishing by measures • apply an estimation by GWR techniques, in order to test the spatial effects

16. Thank you for your attention v.c.materia@univpm.it b.camaioni@univpm.it