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Green Factors, Dynamism and Happiness in Ethiopia Pasquale L. Scandizzo 1 , Federica Alfani 12 , and Sara Savastano 1

Green Factors, Dynamism and Happiness in Ethiopia Pasquale L. Scandizzo 1 , Federica Alfani 12 , and Sara Savastano 1 1 CEIS - University of Rome “Tor Vergata ”, 2 FAO. 17th ICABR Conference “INNOVATION AND POLICY FOR THE BIOECONOMY” Ravello , Italy, June 18-21, 2013. MOTIVATIONS .

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Green Factors, Dynamism and Happiness in Ethiopia Pasquale L. Scandizzo 1 , Federica Alfani 12 , and Sara Savastano 1

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  1. Green Factors, Dynamism and Happiness in Ethiopia Pasquale L. Scandizzo1, Federica Alfani12, andSara Savastano1 1CEIS - University of Rome “Tor Vergata”, 2FAO 17th ICABR Conference “INNOVATION AND POLICY FOR THE BIOECONOMY” Ravello, Italy, June 18-21, 2013

  2. MOTIVATIONS • Green growth is conceived as a way to foster economic growth and development through sustainable natural resource use, avoidance of environmental degradation and of biodiversity loss. • Land degradation, accelerated soil erosion, and nutrient depletion represent great threats to sustainable agricultural productivity, and thus food security and poverty. • GDP and common measures of welfare do not recognize environmental changes. • There is a need to identify further indicators that take into account “green factors” such as individual well being.

  3. Objectives of the study • To explore the role of environmental factors enhancing green growth, and their impact on satisfaction with life in rural Ethiopia. • To examine the link between reported subjective well being, on one hand, consumption, access to land and property rights, natural shocks and “green factors”, on the other.

  4. The Importance of ‘Green’ Factors • Plethora of works on the economics of happiness, limited applications to environmental issues and policy implications have to be further explored. • Results of research on happiness and life satisfaction have implications on: • Climatic conditions (Frijters and van Praag 1998; Rehdanz and Maddison, 2005; Brereton et al. 2008); • Droughts (Carrill et al., 2009); • Flooding (Luechinger and Raschky, 2009); • Air pollution (Welsch, 2002, 2005). • Policy Questions: • “How do environmental conditions affect human well- being”? and “How do individuals value these effects”?

  5. Green Growth in Rural Areas of Developing Countries • The large majority of population relies on land and natural resources for their income and livelihood. Pressure on land, water, forests, and the biodiversity resources, that are fundamental to sustainable food production, is critical and is likely togrow. • Land degradation, resulting from accelerated soil erosion and nutrient depletion represents one of the main problems that small farmers face(Sutcliffe 1995). • Land expansion through deforestation increase soil erosion. Soil conservation practices help at reducing land degradation (Brenner et al., 2013). • Farmers are vulnerable to climate change, need to adapt to environmental shocks, namely, changes in precipitation and temperature levels (Dejene, 2011).

  6. Estimationstrategy • Following the standard literature,we use an Ordered Probit Estimation Model on SWLS = Satisfaction with Life Scale (Dieneret al., 1985), interpreted as a categorical measure of overall utility for farmers. SWLS is composed by five statements scored from 1 (Strongly disagree) to 7 (Strongly agree): • In most ways, my life is close to ideal • The conditions of my life are excellent • I am completely satisfied with my life • So far, I have gotten the important things I want in life • If I could live my life over, I would change nothing 30-35 score: Extremely satisfied, much above average 25-29 score: Very satisfied, above average 20-24 score: Somewhat satisfied, average 15-19 score: Slightly dissatisfied, a bit below average 10-14 score: Dissatisfied, clearly below average 5-9 score: Very dissatisfied, much below average

  7. Estimationstrategy(cont’d) • We complement the standard approach using an OLSModel on2 Dimensions of Life Satisfaction, resulting from the PCA on a set of 14 variables; • We are able to identify two most relevant principal components: Personal satisfaction component (1st PC) associated to the private and more egoistic dimension of well-being. Social Satisfaction component (2nd PC) associated to social and interpersonal satisfaction, including honesty and trust.

  8. Data Source and Descriptive Statistics • Data from the 2009 Ethiopian Rural Households Survey (ERHS) including, inter alia, information on perception of poverty, well-being and trust; restricted sample of 1,511 households, out of which 46.36% declared to be somewhat satisfied with life. • .

  9. Ordered Probit Estimation Model Significant at 10%; ** Significant at 5%; *** Significant at 1%.

  10. Ordered Probit Estimation Model: Key Results • Family size has a positive effect on life satisfaction, but both the number of children and the number of women appear to have a marginal negative effect. • Per capita consumption has a positive and significant effect on life satisfaction, but the interaction effect between own and neighbors’ consumption is negative, probably due to social envy or the so called hedonic treadmill. • Proxy measure of land tenure security has a positive and significant effect on the probability of being on a higher step of SWL Scale. • Environmental shocks negatively affect life satisfaction, whereas, soil conservation measures and tree diversification have a positive and significant effect on SWL.

  11. Principal Component Analysis on Perception of Well-being and Trust • Principal component analysis (PCA) on 14 items and 1,511 obs. • Kaiser–Meyer–Olkin (KMO): 0.774 sampling adequate for the analysis • Bartlett’s test of sphericity : χ2 (91) = 9,895.66; p-value < .001

  12. Perception of Well-being and Trust: Results from PCA Components Loading from PCA

  13. Perception of Well-being and Trust: Results from PCA Components Loading from PCA IndividualComponent

  14. Perception of Well-being and Trust: Results from PCA Components Loading from PCA Social Component

  15. OLS Estimation Model on Principal Components Significant at 10%; ** Significant at 5%; *** Significant at 1%.

  16. OLS Estimation Model on PCs: Key Results • 1st PC associated to the private and more egoistic dimension of SWB • Number of women in the household appears to have a negative and significant effect on the 1st PC; • Households with more arable land appear to be more satisfied with the personal and egoistic component of life. • 2nd PC associated to social and interpersonal satisfaction • Large families, extensive plots and conservation measures’ adoption seem to have a negative and significant effect on the social and interpersonal component; • Own and neighbors’ consumption have negative and significant effects on the 2nd PC lower economic well-being may be compensated by social and interpersonal relations.

  17. Conclusions • Life satisfaction appears to be significantly related to income, size of the household and other “classical” explanatory variables. • Happiness multidimensional measures can be effectively summarized by an economic -individualistic and a social-altruistic component. • Green growth variables seem to be important in the Ethiopian context, but with different effects on the two principal components; harvest’s protection against environmental shocks, tree diversification, and soil conservation measures' adoption enhance farmers’ life satisfaction. • However, these variables seem to be enhancing the individualistic component of life satisfaction, while they affect negatively the social component.

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