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Climate Change and Food Security: Research on Adaptation in Ethiopia. Salvatore Di Falco University of Geneva Switzerland salvatore.difalco@unige.ch. Outline. Background Use of survey data for policy relevant research

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climate change and food security research on adaptation in ethiopia

Climate Change and Food Security: Research on Adaptation in Ethiopia

Salvatore Di Falco

University of Geneva

Switzerland

salvatore.difalco@unige.ch

outline
Outline
  • Background
  • Use of survey data for policy relevant research
  • Case study => adaptation pay off and identification of the “best” strategies for food security
  • Data needs
  • Environment for Development (EfD): a success story
slide4

Current agreements to limit emissions, even if implemented, will not stabilize atmospheric concentrations of greenhouse gases and climate change

  • Crop productivity to decrease “for even small local temperature increases (1 – 2° C)” (IPCC 2007)
  • In many African countries => “yields from rain fed agriculture could be reduced by up to 50% by 2020” (IPCC 2007, p.10)
  • Serious implications for food security
slide6

Can we do without adaptation?

  • Probably not
  • The identification of climate change adaptation strategies is therefore vital in sub Saharan Africa
  • Autonomous adaptation => pay off?
  • What is the impact on food security of farmers’ decision to adopt some strategies in response to changes in temperature and/or precipitation?
  • What are the driving forces behind farmers’ decisions to adapt to climate change?
slide8
Agriculture accounts for about 40% of GDP, and 90% of exports, and 85% of employment (MoFED, 2007)
  • Ethiopian agriculture is heavily dependent on natural rainfall, with irrigation agriculture accounting for less than 1% of the total cultivated land in the country
  • Ethiopia suffers from extreme weather events:

- frequent droughts (1965, 1974, 1983, 1984, 1987, 1990, 1991, 1999, 2000, 2002, 2009);- recent flooding (1997, and 2006)

Food insecurity

slide9
Data

Partners: IFPRI, USA; Ethiopian Development Research Institute

1,000 crops farms (2,823 plots)

2004 and 2005 => Smallholders Agriculture

Area: Ethiopia Nile River Basin

Great survey on the issue!

Use of farm specific weather data

Thin Plate Spline methodof spatial interpolation for imputation of farm and plot specific rainfall and temperature

Perceptions and adaptation

Extension services, tenure security, information + others

In other 8 African countries

slide10

Issues for quantitative analysis

  • Systematically different between adapters and non adapters
  • Some farmers are better than others…
  • Unobservable characteristics of farmers and their farm may affect both the adaptation strategy decision and net revenues => inconsistent parameter estimates
  • Self selection
ideally we would like to have
Ideally, we would like to have…

Control Group

Treatment Group

Quantityproduced

by farmer X

if DID NOT adapt

Quantityproduced

by farmer X

if DID adapt

Compare the expected food productivity

under the actual and counterfactual cases

that farmer X adapted or not to climate change

Statistical tools: Di Falco et al. 2011

11

what adaption to climate change actually is
What Adaption to Climate Change actually is?

What are the “best” strategies that can be implemented to deal with climatic change in the field

What are the economic implications of

different strategies?

Identify the most successful strategies by

implementing a counterfactual analysis

strategies
Strategies

(1) changing crop varieties only;

(2) implementing only water strategies such as water harvesting, irrigation or water conservation;

(3) implementing only soil conservation;

(4) implementing water strategies and changing crop varieties;

(5) implementing soil conservation and changing crop varieties

(6) implementing water strategies and soil conservation

(7) implementing water strategies, soil conservation, and changing crop varieties;

(8) implementing other strategies.

switching regression model di falco et al 2011 di falco and veronesi 2012
Switching Regression Model (Di Falco et al. 2011; Di Falco and Veronesi; 2012)
  • Two stage procedure
  • We estimate the probability of choosing a particular strategy (selection model where a representative farm household chooses to implement a specific strategy)
  • The information stemming from the first step is used on farm revenue, where farm net revenues are regressed against climatic variables and other control variables
how do we get there
How do we get there?
  • First stage of the model tells you exactly that
  • Barriers and drivers for autonomous adaptation
  • Besides climate and past shocks
  • Trees as tenure security is important driver
  • The dissemination of information on changing crops and implement conservation strategies are very important – increase awareness
  • Extension services are very important in determining the implementation of adaptation strategies (also training)
future research needs
Future research needs
  • More (and better) surveys – involvement of local institutions (academia, research, training)
  • Going back to areas previously interviewed
  • Nile Basin: How things have changed
  • How perception have changed
  • How the barriers and drivers have changed
  • Dynamic implication of adaptation strategies
  • Long term vs short term responses
a platform is necessary efd
A platform is necessary: EfD
  • Environmental economics and advocacy in developing countries for 20 years => SIDA (Swedish Development funded)
  • Weak and underfunded academic institutions
  • Academic brain-drain
  • Government agencies unable to attract and maintain academic capacity for policy analysis
  • Weak interface between academia and government
  • Two pillars: building capacity (PhD programs and courses)
  • Policy relevant research => on the field
  • EfD centers
characteristics of efd centers
Characteristics of EfD centers
  • Strong research capacity and facilities
  • Connection to a graduate program
  • Strong policy interface
  • Efficient administration
  • Ethiopia – EDRI/Addis Ababa University
  • Kenya –University of Nairobi/KIPPRA
  • China - Peking University
  • Tanzania – University of Dar es Salaam
  • South Africa – University of Cape Town
  • Central America – CATIE
  • Sweden – EEU/UoG
  • USA – Resources for the Future
conclusions
Conclusions
  • Adaptation in the field => food security
  • Understanding what can be done to facilitate it
  • Combination of surveys, methods
  • Randomized controlled trials and field experiments can complement
  • Building capacity is essential to face challenges of climate change
  • Follow and expand experiences like EfD
slide22

Thank you very much

salvatore.difalco@unige.ch

multinomial endogenous switching regression model first stage
Multinomial endogenous switching regression model First Stage

if strategy j provides expected net revenues greater than any other strategy k  j

(2)

second stage multinomial endogenous switching
Second stage: Multinomial Endogenous Switching
  • if the error terms of the selection model ij are correlated with the error terms uij of the net revenues functions (3a)-(3m), the expected values of uij conditional on the sample selection are nonzero
  • Estimates will be inconsistent by OLS