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The Economics of Land Degradation and the
           Costs of Action versus Inaction
  Nicolas Gerber, Center for Development Research (ZEF),
               University of Bonn, Germany

   UNCCD 2nd Scientific Conference, Bonn, April 10th 2013

Joint work by ZEF and the International Food Policy Research
Institute (IFPRI), 2010-11 and 2012-14, funded by the German
Federal Ministry for Economic Cooperation and Development.
First phase (2010-11) - Main
outputs
• State of the art in global
   assessments of land
   degradation
• Methodology toward a total
   economic valuation of land
   degradation
• Case studies: Uzbekistan,
   Niger, Peru, India, Kenya
   (agricultural production –
   action cheaper than inaction)
• Partnership concept for a
   global ELD assessment.
Condensed and up-dated version:
www.zef.de/fileadmin/webfiles/downl
oads/zef_wp/wp109.pdf
Relationship between poverty (IMR)
           and land degradation




                                                                                       Source: von Braun et al. 2013


Variable        Resolution    Baseline   End line   Source of data
NDVI            8km x 8km     1982–84    2003–06    Global Land Cover Facility (www.landcover.org), Tucker, Pinzon, and
                                                    Brown 2004); NOAA AVHRR NDVI data from GIMMS
Infant         Sub-district              2005
Mortality Rate
Relationship between change in vegetation
 cover and change in population density




Variable     Resolution    Baseline   End line   Source of data
NDVI         8km x 8km     1982–84    2003–06    Global Land Cover Facility (www.landcover.org), Tucker, Pinzon,
                                                 and Brown 2004); NOAA AVHRR NDVI data from GIMMS
Population   0.5o x 0.5o   1990       2005       CIESIN (2010)
density

                                                                                    Source: Nkonya et al. 2011
Relationship between change in vegetation
     cover & change in gov’t effectiveness




Variable        Resolution   Baseline   End line   Source of data
NDVI            8km x 8km    1982–84    2003–06    Global Land Cover Facility (www.landcover.org), Tucker, Pinzon, and
                                                   Brown 2004); NOAA AVHRR NDVI data from GIMMS
Government      Country      1996–98    2007–09    Worldwide Governance Indicators:
effectiveness                                      http://info.worldbank.org/governance/wgi/index.asp

                                                                                         Source: Nkonya et al. 2011
2nd Phase Research Project:
 The Economics of Land Degradation,
  2012-2014, www.zef.de/eld.html
• ZEF and IFPRI engage with other scientific
  partners in open partnership
• Operationalize the methodology outlined in
  Nkonya et al. 2011 – methods paper out for
  discussion
 http://www.zef.de/fileadmin/media/news/2135_eld_methods07042013.pdf

• Selected case studies and a standard
  methodology to form a template for future
  ELD assessments.
Sampling Framework for Case Studies
Three steps:
1. Clustering based on key socio-economic and
   institutional underlying factors (Nkonya et al.
   2011)
2. Validation of clusters using additional socio-
   economic and biophysical variables
3. Case studies selected from each cluster,
   based i) regional representativeness, ii)
   availability of data required for the ELD
   assessment
                                   Source: Nkonya et al (2013)
Clustering and validation results




                       Source: Nkonya et al (2013)
Clustering Results




1
2
3
4
5
6
7




                    Source: Nkonya et al (2013)
Empirical Research Framework
• Core ELD research methods: standard research methods to be
  applied in all case studies to fulfill the minimum
  methodological requirements for globally comparable and
  rigorous ELD assessment,
• Desirable ELD approaches: methods seeking to address the
  key challenges specific in each context and to complement,
  cross-validate and triangulate, in general, test the robustness
  of the results obtained from the core research.
• Sophisticated ELD methods for expanding the research
  frontiers in ELD research. They aim to build and expand on the
  cutting-edge of interdisciplinary land degradation research.


                                             Source: Nkonya et al (2013)
Examples of three categories of ELD
      research approaches




                         Source: Nkonya et al (2013)
Key variables and datasets required




                         Source: Nkonya et al (2013)
Key variables and datasets required




                         Source: Nkonya et al (2013)
Thank you!

www.zef.de/eld.html

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Nicolas GERBER "The economics of land degradation and the costs of action versus inaction"

  • 1. The Economics of Land Degradation and the Costs of Action versus Inaction Nicolas Gerber, Center for Development Research (ZEF), University of Bonn, Germany UNCCD 2nd Scientific Conference, Bonn, April 10th 2013 Joint work by ZEF and the International Food Policy Research Institute (IFPRI), 2010-11 and 2012-14, funded by the German Federal Ministry for Economic Cooperation and Development.
  • 2. First phase (2010-11) - Main outputs • State of the art in global assessments of land degradation • Methodology toward a total economic valuation of land degradation • Case studies: Uzbekistan, Niger, Peru, India, Kenya (agricultural production – action cheaper than inaction) • Partnership concept for a global ELD assessment. Condensed and up-dated version: www.zef.de/fileadmin/webfiles/downl oads/zef_wp/wp109.pdf
  • 3. Relationship between poverty (IMR) and land degradation Source: von Braun et al. 2013 Variable Resolution Baseline End line Source of data NDVI 8km x 8km 1982–84 2003–06 Global Land Cover Facility (www.landcover.org), Tucker, Pinzon, and Brown 2004); NOAA AVHRR NDVI data from GIMMS Infant Sub-district 2005 Mortality Rate
  • 4. Relationship between change in vegetation cover and change in population density Variable Resolution Baseline End line Source of data NDVI 8km x 8km 1982–84 2003–06 Global Land Cover Facility (www.landcover.org), Tucker, Pinzon, and Brown 2004); NOAA AVHRR NDVI data from GIMMS Population 0.5o x 0.5o 1990 2005 CIESIN (2010) density Source: Nkonya et al. 2011
  • 5. Relationship between change in vegetation cover & change in gov’t effectiveness Variable Resolution Baseline End line Source of data NDVI 8km x 8km 1982–84 2003–06 Global Land Cover Facility (www.landcover.org), Tucker, Pinzon, and Brown 2004); NOAA AVHRR NDVI data from GIMMS Government Country 1996–98 2007–09 Worldwide Governance Indicators: effectiveness http://info.worldbank.org/governance/wgi/index.asp Source: Nkonya et al. 2011
  • 6. 2nd Phase Research Project: The Economics of Land Degradation, 2012-2014, www.zef.de/eld.html • ZEF and IFPRI engage with other scientific partners in open partnership • Operationalize the methodology outlined in Nkonya et al. 2011 – methods paper out for discussion http://www.zef.de/fileadmin/media/news/2135_eld_methods07042013.pdf • Selected case studies and a standard methodology to form a template for future ELD assessments.
  • 7. Sampling Framework for Case Studies Three steps: 1. Clustering based on key socio-economic and institutional underlying factors (Nkonya et al. 2011) 2. Validation of clusters using additional socio- economic and biophysical variables 3. Case studies selected from each cluster, based i) regional representativeness, ii) availability of data required for the ELD assessment Source: Nkonya et al (2013)
  • 8. Clustering and validation results Source: Nkonya et al (2013)
  • 9. Clustering Results 1 2 3 4 5 6 7 Source: Nkonya et al (2013)
  • 10. Empirical Research Framework • Core ELD research methods: standard research methods to be applied in all case studies to fulfill the minimum methodological requirements for globally comparable and rigorous ELD assessment, • Desirable ELD approaches: methods seeking to address the key challenges specific in each context and to complement, cross-validate and triangulate, in general, test the robustness of the results obtained from the core research. • Sophisticated ELD methods for expanding the research frontiers in ELD research. They aim to build and expand on the cutting-edge of interdisciplinary land degradation research. Source: Nkonya et al (2013)
  • 11. Examples of three categories of ELD research approaches Source: Nkonya et al (2013)
  • 12. Key variables and datasets required Source: Nkonya et al (2013)
  • 13. Key variables and datasets required Source: Nkonya et al (2013)

Editor's Notes

  1. funded by the German Federal Ministry for Economic Cooperation and Development (BMZ) and in collaboration with UNCCD
  2. Need to look at ELD where it matters to people, and the sort of indicators of LD which are connected to the human dimensions of the LD (NDVI little removed from that), and- High human costs of LD, as 42% of the world‘s very poor rely on degraded land (food & income)- Costs of LD as much as 10% of GDP in SSA
  3. The Worldwide Governance Indicators (WGI) project (The WB Group) reports aggregate and individual governance indicators for 213 economies over the period 1996–2010, for six dimensions of governance, incl. Government Effectiveness. It is capturing perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies.
  4. funded by the German Federal Ministry for Economic Cooperation and Development (BMZ)
  5. Need to take into account a wide heterogeneity of land degradation, socio-economic and institutional contextsRandom probability sampling is not the best approach in this contextThis sets appart case studies under ELD research project and any other colection of case studies, together with the common analytical frame exposed later!!key socio-economic and institutional underlying factors: GDP per capita, population density, government effectiveness and agricultural intensification (Nkonya et al. 2011)Validation of clusters using long-term changes in NDVI values, share of rural population in the total, share of agriculture in GDP, average cereal yields per hectare