Abstract
Investments in biofuels are booming globally in response to increasing costs of fuels and growing concern over climate change. The high and often fluctuating fuel prices have frustrated development efforts in Ethiopia. This has prompted policymakers to review energy development strategies and search for mechanisms that minimize dependence on high cost imported fossil oils. An important mechanism identified in this area is substituting fossil fuels with domestically produced biofuels. Currently, investments in biofuels with the aim of producing ethanol and biodiesel are underway in the country. This study investigates the impact of biofuel investments on growth, poverty, and food security in Ethiopia using a dynamic computable general equilibrium (CGE) model linked to the microsimulation (MS) model. The CGE model uses the 2005–06 social accounting matrix (SAM) while the MS model uses the 2004–05 Household Income, Consumption and Expenditure (HICE) survey. The simulation results for the before and after shock periods were fed into the household model using distribution analysis (DAD) software that yielded the FGT poverty indices. The results suggest that biofuel investments provide a new opportunity for enhancing economic growth and reducing poverty. Our results also show the complementarities between ‘biofuels’ and ‘food’ production.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
REST—Relief Society of Tigrai and ORDA—Organization for Rehabilitation and Development in Amhara region.
- 2.
The five AEZs include the humid lowlands moisture reliable (AEZ1), moisture sufficient highlands (cereal-based) (AEZ2), moisture sufficient highlands (enset-based) (AEZ3), drought prone (Highlands) (AEZ4) and pastoralist (arid lowland plains) (AEZ5) (see EDRI 2009) for details on AEZs).
- 3.
For a detailed exposition of this type of a model, and for the implementation of the ‘standard’ model in the GAMS modeling language, see Lofgren et al. (2002).
- 4.
In the basic model version the consumer price index (CnPI) is fixed (exogenous variable) and functions as the numeraire, otherwise the producer price index (DPI) may be fixed. A numeraire is vital since the model is homogenous of degree zero in prices. Subsequently, a doubling of the value of the numeraire will double all prices but leave all real quantities/real resource allocation unchanged. As a remark, all simulated price and income changes should be interpreted as changes in relation to the numeraire price index (Lofgren et al. 2002).
- 5.
The DAD (distribution analysis/analyze distribution) software is ‘designed to facilitate the analysis and the comparisons of social welfare, inequality, poverty and equity across distributions of living standards’ (Duclos et al. 2010).
- 6.
If gi = Z − Y i , then g i represents income (consumption) shortfall of the ith individual (household) and this is assumed to be zero for those above the poverty line (Abebe 2005).
- 7.
α denotes the weight given to the poorest of the poor and so the higher the value of α, the more is the concern for the poorest (Abebe 2005).
- 8.
We assume a total 200,000 ha of sugarcane and jatropha each, 17, 414 of castor and 22,500 ha of palm will be utilized at the end of 2020 by current operational developers of biofuel crops. In the biofuels scenarios, we evenly distribute yet unutilized land over the 15 periods which implies no displacement of smallholders.
- 9.
Since the consumer is harmed prior to policy change by paying the price equivalent in income, negative EV changes represent welfare (utility) loss as a result of the policy shock. The concept of EV informs that price increases from P 1 to P 2 lead to welfare loss by as much as the loss of income equal to EV if the price remained at P 1.
- 10.
Though the number of rural households is less in the survey, one point of note is that the number of people each sample rural household represents (weights) is very large compared to urban households.
References
Abebe, S. (2005). Essays on poverty, risk and consumption dynamics in Ethiopia. Goteborg University: Economic Studies, School of Economics and Commercial Law.
Arndt, C., K. Pauw, and J. Thurlow. 2010. Biofuels and economic development in Tanzania, IFPRI Discussion Paper 00966. Washington, DC: IFPRI.
Arndt, Channing, Rui Benfica, Finn Tarp, James Thurlow, and Rafael Uaiene. 2009. Biofuels, poverty, and growth: A computable general equilibrium analysis of Mozambique, IFPRI Discussion Paper 00803. Washington, DC: IFPRI.
Baier, S.L, M. Clements, C.W. Griffiths, and J.E. Ihrig. 2009. Biofuels impact on crop and food prices: Using an interactive spreadsheet, FRB International Finance Discussion Paper No. 967. Available at SSRN: http://ssrn.com/abstract=137283
Benfica, R. (2006). An analysis of income poverty effects in cash cropping economies in rural Mozambique: Blending econometric and economy-wide models, PhD dissertation. Department of Agricultural Economics, Michigan State University, East Lansing.
Cockburn, J., and B. Decaluwé. 2006. Replacing representative with real households in dynamic CGE analysis of poverty: Challenges and opportunities. PEP: CIRPÉE and Université Laval.
Colombo, G. 2008. Linking CGE and microsimulation models: A comparison of different approaches, 08–054. Discussion Paper No: Centre for European Economic Research.
CSA (Central Statistical Agency). 2007. National population census. Addis Ababa.
CSA (Central Statistical Agency). 2008. Household income, consumption and expenditure survey 2004: HICE 2004/2005 Metadata. CSA, Addis Ababa.
Dejene, A., F. Belay, and W. Sindu. 2007. Trade liberalization, poverty and inequality in Ethiopia: A CGE microsimulation analysis. Paper presented at the 6th PEP Research Network General Meeting, 14–16 June 2007, Lima, Peru.
Dimaranan, B. (ed.). 2006. Global trade, assistance, and production: The GTAP 6 data base. Center for Global Trade Analysis. West Lafayette, IN, USA: Purdue University.
Dornbosch, R., and R. Steenblik. 2007. Biofuels: Is the cure worse than the disease? OECD, round table on sustainable development, 11–12 September 2007. Paris.
Duclos, J.Y., A. Araar, and C. Fortin. 2010. DAD: A software for distributive analysis (analyse distributive). MIMAP Programme: International Development Research Centre, Government of Canada and CRFA, Universite Laval.
EDRI (Ethiopian Development Research Institute). 2009. Ethiopia input output table and social accounting matrix (SAM) 2005/06. Addis Ababa: EDRI.
Ewing, M., and S. Msangi. 2009. Biofuels production in developing countries: Assessing tradeoffs in welfare and food security. Environmental Science & Policy 12(4): 520–528.
Foster, J., J. Greer, and E. Thorbecke. 1984. A class of decomposable poverty measures. Econometrica 52(3): 761–766.
Gebreegziabher Z., A. Mekonnen, T. Ferede, F. Guta, J. Levin, G. Köhlin, T. Alemu, and L. Bohlin. 2013. Distributive effect and food security implications of biofuel investment in Ethiopia: a CGE analysis. EfD DP 13-02. Washington, DC: Environment for development initiative and resources for the future (www.rff.org)
Hausmann, R. 2007. Biofuels can match oil production, Financial Times, 6 November.
Headey, D., and S. Fan. 2008. Anatomy of a crisis: the causes and consequences of surging food prices. Agricultural Economics 39: 375–391.
Huppi, M., and M. Ravallion. 1991. the sectoral structure of poverty during an adjustment period: Evidence for Indonesia in the mid-1980s. World Development 9(2): 1653–1678.
Lofgren, H., R.L. Harris, S. Robinson, M.El Said, and M. Thomas. 2002. A standard computable general equilibrium (CGE) model in GAMS’, microcomputers in policy research, 5. Washington, DC: International Food Policy Research Institute.
Mitchell, D. 2008. A note on rising food prices, The World Bank, Development Prospects Group, Policy Research Working Paper #4682.
MoFED (Ministry of Finance and Economic Development). 2010. The five year (2010/11–2014/15) growth and transformation plan. Addis Ababa: MoFED.
MOME (Ministry of Mines and Energy). 2007. The biofuel development and utilization strategy of Ethiopia. Addis Ababa: MoME.
MOWE (Ministry of Mines and Energy). 2013. The biofuel development and utilization strategy of Ethiopia. Addis Ababa: MOWE.
NBE (National Bank of Ethiopia). 2010/2011. Annual report 2008/2009. Addis Ababa: NBE.
Negash, M. 2012. Biofuels and Food Security: Micro-evidence from Ethiopia. Poster prepared for presentation at the International Association of Agricultural Economists (IAAE) Triennial Conference, Foz do Iguaçu, Brazil. August 18–24, 2012.
OECD. 2008. Biofuel support policies: An economic assessment.
Pratt, Nin A., and B. Bingxin Yu. 2008. An updated look at the recovery of agricultural productivity in Sub-Saharan Africa, IFPRI Discussion Paper 00787. Washington, DC: Development Strategy and Governance Division.
Ravallion, M. 2004. Pro-poor growth: A primer, Policy Research Working Paper 3242. Washington, DC: The World Bank.
Savard, L. 2003. Poverty and income distribution in a CGE—household micro simulation model. Top-Down/ Bottom UP Approach, International Development Research Centre; CIRPEE, Working Paper 03–43.
Savard, L. 2005. Poverty and inequality analysis within a CGE framework: A comparative analysis of the representative agent and microsimulation approaches, Development Policy Review 23(3): 313–332.
The World Bank. 2005. Introduction to poverty analysis. Poverty manual.
The World Bank. 2009/2010. Annual report, 2009 and 2010.
Thurlow, J. 2004. A Dynamic computable general equilibrium (CGE) model for South Africa: Extending the static IFPRI model, Working Paper 1-2004.
Uaiene, R. 2008. Determinants of agricultural technical efficiency and technology adoption in Mozambique, PhD dissertation. Purdue University, W. Lafayette, IN.
UNEP (United Nations Environment Program). 2009. Towards sustainable production and use of resources: Assessing biofuels. Nairobi: UNEP.
Acknowledgments
We are grateful to the International Food Policy Research Institute (IFPRI) and the Ethiopian Development Research Institute (EDRI) for supporting us financially and the Environmental Economics Policy Forum for Ethiopia (EEPFE) which gave us permission to use the modified Social Accounting Matrix (SAM).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Appendices
Appendices
1.1 Appendix 1
Share in total biofuel crop land by biofuel crop type (%). Source MOWE (2013)
1.2 Appendix 2
Land allocation per biofuel crop to operational developers
No. | Biofuel crops | Land under cultivation (ha) | Potential land (ha) | Total land (ha) | AEZs |
|---|---|---|---|---|---|
1 | Sugarcane | 47,500 | 333,500 | 381,000 | 1, 2, 4, 5 |
2 | Jatropha | 106,983 | 107,617 | 214,600 | 3, 4 |
3 | Castor bean | 8529 | 8885 | 17,414 | 4, 5 |
4 | Palm | 800 | 21,700 | 22,500 | 1 |
5 | Pongamia | 7 | 49,993 | 50,000 | 4 |
6 | Curton and candlenet | 500 | 1500 | 2000 | 4 |
Total | 164,319 | 523,195 | 687,514 |
1.3 Appendix 3
Impact on prices of cereals. Source CGE results
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Debela, G.M., Tamiru, S. (2016). Biofuels, Poverty, Food Security and Growth in Ethiopia: A Computable General Equilibrium Microsimulation Analysis. In: Heshmati, A. (eds) Poverty and Well-Being in East Africa. Economic Studies in Inequality, Social Exclusion and Well-Being. Springer, Cham. https://doi.org/10.1007/978-3-319-30981-1_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-30981-1_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-30980-4
Online ISBN: 978-3-319-30981-1
eBook Packages: Economics and FinanceEconomics and Finance (R0)