How to measure the CMEF R2 Indicator about Gross Value Added in agricultural holdings without reliable accounting data ? A methodological proposal applied to Marche RDP Francesco Felici, Stefano Mussi, Ecosfera VIC EAAE Seminar "Evidence-Based Agricultural and Rural Policy Making: Methodological and Empirical Challenges of Policy Evaluation", February 2011, Ancona

Introduction Monitoring Programme Implementation Monitoring the progress, efficiency and effectiveness of RDP in relation to their objectives shall be measured by means of indicators measuring the variation between the baseline situation against the actual results of the programmes. The CMEF R2 Indicator According to the CMEF the R2 indicators is set to measure the increase in gross value added (GVA) of agricultural, food or forestry holdings/enterprises that have received financial support from the Programme. Gross effect measures the performance of the enterprise and not just the effect of the supported investment. At farm level, several data are provided in the application form Very seldom data are collected in the later stages of the project. GVA

Beneficiaries and couterfactual context The most interesting part of this research is to assess whether the beneficiary enterprises have produced a different result from those, operating in the same business environment, who have not received the support. VARIATION VALUE ADDED AT CURRENT PRICE IN AGRICULTURE IN MARCHE AND ITALY

Methodologies and practices According to the latest CMEF methodology, the calculation of R2 should be done using accounting data that comply with the International Accounting Standard (IAS 40). In Italy detailed accounting data are available only for the limited liability companies that are very rare among agricultural holdings. Additional data can be gathered through FADN and for the food industry through the database called AIDA that collects data from the chambers of commerce network

Methodologies and practices AGRICULTURE & FORESTRY FIELD SURVEY FOOD INDUSTRY AIDA FADN ? MACRO-MICRO Analysis

1 Analysis of secondary data: AIDA Selection of 718 enterprises of the agricultural, forestry and agri-food sector of the Marche Region available at AIDA Cross checking the above results with the data related to the beneficiaries of the Measure 121 that have received the payment in 2007 (ex A Measure of RDP ) and with the 63 companies of Measure 123 (Ex Measure G and M of RDP ). Positive results for Measure 123 Negative results for Measure 121 the number of beneficiaries that are included in both lists is too limited to be representative

2 Analysis of secondary data: FADN In close co-ordination with the INEA Regional Unit we have tested the methodology using data for the years Observed Results: Delta GVA calculated through the sample is 17 millions Euro. This amount reverts the negative trend observed at macro level in the period amounting at -30 Million Euro. Theoretical assumption: Delta GVA at farm level is more affected by exogenous than endogenous variables Given the limited number of RDP beneficiaries in the FADN database, the sample was sorted out among those holdings having similar characteristics of the beneficiaries (potential beneficiaries) The Gross Value Added observed on the above sample was then referred to the beneficiaries of Measure A of the RDP Marche

3 Analysis of sec.data: Macro-Micro Theoretical assumption: Delta GVA at farm level is more affected by exogenous than endogenous variables This methodology foresees the calculation of the delta GVA based on the MACRO variation of the prices elapsed during the period The delta GVA of the beneficiaries (based on the beneficiaries of the Measure A of RDP ) is calculated according to the above mentioned variation Observed Results: Delta GVA calculated through the present methodology shows a negative result of – Euro

4 Analysis of secondary data: Field Survey Given the contrasting results obtained through the adoption of the two above mentioned methodologies, a sample of 100 agricultural holding, out of 494 beneficiaries, has been selected with the twofold objective of: a) provide information to answer the Evaluation Questions foreseen in the CMEF; b) to assess the trend of the GVA among the beneficiaries.

Grouping of supported agricultural holdings in 4 farm patterns (OTE):  Arable crops;  Permanent crops;  Livestock farming;  Others. Grouping of supported agricultural holdings according to economic size (ESU):  Less than 40 ESU;  More than 40 ESU. Grouping of supported agricultural holdings according to 3 types of RDP zone :  Less rural (A+C1);  Intermediate (C2);  Highly rural (C3+D). 4 The sampling methodology adopted

Results The observed average increase in GVA for beneficiary holding was ca euro, corrisponding to a total amount of 5,2 million euro. The observed increase in GVA is due mostly to permanent crops in area C2 (intermediate areas according to RDP land plan).

Results While there is a growth in permanent crops there is a decrease in GVA in the livestock breeding sector in the smaller holding located in marginal areas

Recommendations The implementation of field surveys has demonstrated to be the only possible way to precisely examine the variation of Gross Added Value for the agricultural and forestry holdings that have received support from the Programme As far as the agro-food industry is concerned, the database AIDA has demonstrated to provide useful and reliable data Being the indicator R2 the result of the sum of individual data, particular care should be posed in the selection of the sample. This is because if the sample is not balanced in terms of size of the holdings, the presence of large enterprises, as this may be the case of large food processing operations, could hamper the significance of the assessment

How to measure the CMEF R2 Indicator about Gross Value Added in agricultural holdings without reliable accounting data ? A methodological proposal applied to Marche RDP Francesco Felici, Stefano Mussi, Ecosfera VIC EAAE Seminar "Evidence-Based Agricultural and Rural Policy Making: Methodological and Empirical Challenges of Policy Evaluation", February 2011, Ancona