Measuring the Impact of the RDP - Bernd Schuh

1,090 views
1,030 views

Published on

Presented at the Irish National Rural Network conference on the 1st of December 2009

Published in: Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
1,090
On SlideShare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
4
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Measuring the Impact of the RDP - Bernd Schuh

  1. 1. Measuring the Impact of the RDP<br />Issues being addressed at an EU level with regards to measuring the impact of the Rural Development programmes<br />B. Schuh<br />1<br />www.nrn.ie<br />
  2. 2. Content<br />Assessment of impacts in the RDPs – the basics<br />Process of assessing RDP impacts<br />Evaluation architecture/ challenges to overcome<br />The seven fields of impacts (econ. growth, employment creation, productivity, biodiversity, HNV, water quality, climate change)<br />www.nrn.ie<br />2<br />
  3. 3. Assessment of impacts in the RDPs – the basics:<br />CMEF – the „bible“<br />Intervention logic <br />Additional programme specific indicators<br />Evaluation questions<br />www.nrn.ie<br />3<br />reference for impact<br />supporting and counterproductive trends<br />
  4. 4. Process of assessing RDP impacts:<br />Gauging the evidence of change<br />Identifying the drivers of change<br />Understanding change and concluding on future interventions<br />www.nrn.ie<br />4<br />
  5. 5. Evaluation architecture/ challenges to overcome:<br />Factors determinig evaluation architecture:<br />Methodological challenges to overcome:<br />Dealing with uncertainties<br />Reducing complexity through a consistent approach<br />Constraints in utilization of the evaluation results – the evaluation and policy cycle<br />The counterfactual assessment of impacts  quasi-experimental design, non-experimental design; DiD method<br />Taking into account and cross-relating impacts at micro and macro level  e.g. econometric modeling, CGE models, system dynamics modeling<br />Netting out the programme effects by reducing deadweight, leverage, displacement, substitution and multiplier effects<br />data collection and processing  qualitative & quantitative data, FADN & Co<br />Bridging the gap between measuring impact indicators and providing answers on programme impacts  qualitative methods as add-ons – interviews, CS<br />www.nrn.ie<br />5<br />
  6. 6. The socio-economic impact indicators:<br />EconomicGrowth:<br />Calculation via DiD methods, quantification possible, micro-macro link through modeling approaches<br />Employment creation<br />Calculation via Propensity Score Matching, Standard regression model, Assessing employment effects at macro level - modelling<br />Time lag, Missing critical mass – CS, Welfare effects<br />Labour productivity<br /><ul><li>Calculation via DiD methods, quantification possible, micro-macro link through modeling approaches
  7. 7. Limitations concerning measuring labour productivity  Competitive Performance, Revealed Comparative Advantage, Growth Competitiveness Indicator, Domestic Resource Cost</li></ul>www.nrn.ie<br />6<br />
  8. 8. The environmental impact indicators – special issues:<br />Data availability <br />Systemic borders <br />Environmental impacts do evolve also from those measures, which do not deem that such impacts will occur <br />Conception of the environment within the evaluation (ecosystem functionsvs. ecosystem services)<br />Difficult to depict the full range of rather vast, complex fields of environmental phenomena like “climate change” or “Biodiversity loss”<br />“evaluation” vs. assessment – aggregation methods not easily applicable<br />Cumulative impacts – crossing effects between environmental impacts<br />www.nrn.ie<br />7<br />
  9. 9. The environmental impact indicators:<br />Biodiversity<br />Measured by Farmland Bird Index (FBI) – bottom-up aggregation of micro level observations<br />Crucial issue of regional/ national specifics, bottom-up assessment, additional information (‘control’ other influences), more than birds<br />High Nature Value farming/ forestry<br />Measured through:<br />Land cover characteristics, especially farmland with a high proportion of semi-natural vegetation and in some cases a diversity of land cover types.<br />Farming practices, especially a low use of inputs (including live­stock density) and specific practices such as shepherding, late hay-cutting, orchard grazing and arable fallowing.<br />Strong dependence on baseline data  comparison of baseline conditions, main challenge indicator as „work in progress“<br />www.nrn.ie<br />8<br />
  10. 10. The environmental impact indicators 2:<br />Waterquality<br />Measured as changes in gross nutrient balance (GNB), should be interpreted as a potential risk indicator for water quality only; assessment by bottom up approach – aggregation as methodological challenge (modelling – e.g. RAUMIS)<br />Many uncertainties remain  different land cover, land use and farming types & atmospheric N fixation and deposition - measuring water quality in agricultural catchment, net nitrogen balance as additional indicators<br />Climate change<br />Measured as net greenhouse gas emissions reduction and production of renewable energy<br />Limitations Additionality/net effects, Displacement of energy & production, Boundary issues, issue of the temporal attribution of longer-term impacts to the policy period of the spending<br />www.nrn.ie<br />9<br />

×