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The Economic Costs of Climate Change in MENA Countries: A Micro-Spatial Analysis. FEMISE Team: Prof. Nicolas Péridy ( Université du Sud Toulon- Var , LEAD, France) Prof. Ahmed Ghoneim (Cairo University,Egypt )
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The Economic Costs of Climate Change in MENA Countries:A Micro-Spatial Analysis FEMISE Team: Prof. Nicolas Péridy (Université du Sud Toulon-Var, LEAD, France) Prof. Ahmed Ghoneim (Cairo University,Egypt) Research Assistants: Dr. Marc Brunetto and Dr. Mohamed Hazem (Université du Sud) FEMISE Program FEM34-03 Femise AnnualConference Marseille 15-16 December 2011
1a. Motivation • Climate change: • major issue for the world population and thus policy makers. Estimation of global warming: from 1.0°C to 4.5°C by the end of this century (IPPC (2007)). • The last forecasts (PNUE, 2011) are even more alarmists: from 2.5°C to 6.0°C. • Questions about the economic impact of climate change • New literature (Stern, 2008, Dell and al., 2009, Pindyck, 2010) • New data bases at micro-spatial level (TATP, 2009 and G-Econ 2009) • MENA countries are particularly concerned with CC
2a. Stylized facts: Temperature (moving av.) Algeria Egypt
3. Main questions to be addressed • Is there any evidence of climate change over the past decades in MENA countries, notably in terms of temperature and rainfall? • What is the impact of a rise in temperature and a decrease in precipitation on income and growth in these countries? • Which policies can be implemented in order to adapt to global warming?
4a. Methodology: a micro-spatial analysis • The use of micro-spatial databases: • Terrestrial Air Temperature and Precipitation (Matsuura and Willmott 2009); 808 geographical cells for MENA countries for the time period 1900-2088 (88,072 observ.) • G-Econ (Yale University): Gross cell product (GCP) is measured at a 1-degree longitude by 1-degree latitude resolution • Highlighting statistical evidence of climate change in MENA countries: • Regression of temperature and precipitations on time • Identification of structural changes (Chow and Cusum tests) • Calculating changes in temperature and precipitations before and after the structural change
4b. Methodology: a micro-spatial analysis • Testing the impact of climate change on the real economy: • On micro-spatial GDP and GDP per capita • With spatial conditional convergence models: Barroregression (Mankiw et al., 1992; Ramajo et al., 2008) • With an extended model at country level which accounts for other control variables (education, innovation, infrastructure, openness, etc…)
4c. Methodology: a micro-spatial analysis • Using spatial econometrics • Test of the spatial autocorrelation of the residuals (Moran-I-test) • Estimating: • spatial lagmodels: Y=rWy+Xb+e • spatial model with autocorrelated residuals: Y=bX+e Avec e=lWe+u
5a. Results: Global Warming (temperatures) • Table 1: Estimation of structural change
5b. Results: Global Warming (temperatures) • Table 2: Global warming in MENA countries (°C)
5c. Results: Global Warming (temperatures) • Figure 1: Global warming at micro-spatial level
5d. Results: Climate change (precipitations) • Table 3: Estimation results for the whole period at country level (1900-2008)
5c. Results: Climate change (precipitations) • Figure 1: changes in precipitations at micro-spatial level
6a. Impact on GDP and GDP per capita (spatial lag model) • Impact on GDP • Impact of GDP per capita
6b. Results of the conditional convergence model (spatial lag model)
7. conclusion • MENA countries have all experiencedsignificantclimate change, which has accelerated in the pastdecade • Comparedwithother countries, global warming in MENA countries is comparable to thatobservedat world level BUT with a significantdecrease in rainfalls. • There issomeevidence of a negative impact of global warming on GDP and GDP per capita to a lesser impact (1°C => -8.5% GDP per capita) • This raises the question about the role of policies: • To preventadditionalclimate change • To adapt to these changes