Skip to main content
SpringerLink
Log in

Analysis of Factors Affecting Persistent and Transient Inefficiency of Ethiopia’s Smallholder Cereal Farming

  • Chapter
  • First Online:
Efficiency, Equity and Well-Being in Selected African Countries

Abstract

This essay explains persistent and transient inefficiency effects among smallholder cereal farmers in Ethiopia using household-level panel dataset for 1999–2015. It uses a 4-component stochastic frontier model with determinants of inefficiency and uses a mixed efficiency analysis approach in two steps. First, it estimates persistent and transient inefficiency scores and simultaneously explains their differentials. Second, in a two-stage approach it explains the overall inefficiency effects. Inefficiency effects models reveal that most farmer-specific characteristics, adaptation strategies, agro-ecological and climatic factors influence farming efficiencies with different magnitudes. Transient efficiency is enhanced by gender, household size and number of plots, while it is negatively influenced by age, secondary schooling and temperature variations. Persistent inefficiency is negatively influenced by altitude and ecological factors while overall efficiency is enhanced by farm size, gender, household size and remittances; improved adaptation strategies; and weather and ecological factors. It is negatively influenced by credit use, age, territory, schooling, off/non-farm activities and extreme weather variations. The essay also shows that omission of weather factors from specification affects not only reduce the model’s precision, but also results in biased inefficiency scores and estimates of determinants. These findings are important and can be used to initiate policy options when planning climate change adaptation strategies and agricultural policies. It also discusses policies that advance input supply and sustain improved adaptation strategies and which are suitably designed to suit the needs of farmers and agro-ecological zones’ peculiarities to enhance short-term and long-term productive efficiencies of cereal farming in Ethiopia.

This chapter builds on the Ph.D. thesis of Omer Berisso available at http://etd.aau.edu.et/bitstream/handle/123456789/14274/Oumer%20Berisso.pdf?sequence=1&isAllowed=y

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • African Development Bank (AfDB). (2016). Federal Democratic Republic of Ethiopia: Country Strategy Paper-CSP, 2016-20.

    Google Scholar 

  • Aigner, D., Lovell, C. K., & Schmidt, P. (1977). Formulation and estimation of stochastic frontier production model. Journal of Econometrics, 6(1), 21–37.

    Article  Google Scholar 

  • Alemu, B., Nuppenau, E. A., & Boland, H. (2009). Technical efficiency of farming systems across agro ecological zones in Ethiopia: An application of Stochastic Frontier approach. Agricultural Journal of Econometrics, 4, 202–207.

    Google Scholar 

  • Banker, R. D., & Natarajan, R. (2008). Evaluating contextual variables affecting productivity using data envelopment analysis. Operations Research, 56, 48–58.

    Article  Google Scholar 

  • Barnwal, P., & Kotani, K. (2013). Climatic impacts across agricultural crop yield distributions: An application of quartile regression on rice crops in Andhra Pradesh, India. Ecological Economics, 87, 95–109.

    Article  Google Scholar 

  • Battese, G. E., & Coelli, T. J. (1992). Frontier production functions, technical efficiency and panel data: With application to paddy farmers in India. Journal of Productivity Analysis, 3, 153–169.

    Article  Google Scholar 

  • Battese, G. E., & Coelli, T. J. (1995). Models for technical inefficiency in a stochastic frontier production function for panel data. Empirical Economics, 20, 325–332.

    Article  Google Scholar 

  • Belotti, F., Daidone, S., Ilardi, G., & Atella, V. (2012). Stochastic frontier analysis using Stata. Stata Journal, 2, 1–39.

    Google Scholar 

  • Berisso, O. M. (2017). Impact of Weather variations on cereal productivity and influences of agro-ecological differences in Ethiopian cereal production. In A. Heshmati (Ed.), Economic transformation for poverty reduction in Africa (pp. 9–35). London: Routledge.

    Google Scholar 

  • Beyan, A., Jema, H., & Endrias, G. (2013). Analysis of Farm Households' technical efficiency in production of smallholder farmers: The Case of Girawa District, Ethiopia. American-Eurasian Journal of Agricultural and Environmental Science, 13(12), 1615–1621.

    Google Scholar 

  • Chou, C., Chen, C. A., Tan, P. H., & Chen, K. T. (2012). Mechanisms for global warming impacts on precipitation frequency and intensity. Journal of Climate, 25(9), 3291–3306.

    Article  Google Scholar 

  • Colombi, R., Kumbhakar, S. C., Martini, G., & Vittadini, G. (2014). Closed-skew normality in stochastic frontiers with individual effects and long/short-run efficiency. Journal of Productivity Analysis, 42, 123–136.

    Article  Google Scholar 

  • Farrell, M. J. (1957). Measurement of productive efficiency. Journal of the Royal Statistical Society, 120(3), 253–281.

    Article  Google Scholar 

  • Greene, W. (2005a). Reconsidering heterogeneity in panel data estimators of the stochastic frontier models. Journal of Econometrics, 126(2), 269–303.

    Article  Google Scholar 

  • Greene, W. (2005b). Fixed and random effects in stochastic frontier models. Journal of Productivity Analysis, 23, 7–32.

    Article  Google Scholar 

  • Harris, I., Jones, P. D., Osborn, T. J., & Lister, D. H. (2014). Updated high-resolution grids of monthly climatic observations–the CRU TS3, 10 Dataset. International Journal of Climatology, 34(3), 623–642.

    Article  Google Scholar 

  • Heshmati, A., Kumbhakar, S. C., & Hjalmarsson, L. (1995). Efficiency of Swedish pork industry: A farm level study using rotating panel data 1976-1988. European Journal of operational Research, 80, 519–533.

    Article  Google Scholar 

  • Hoff, A. (2007). Second stage DEA: Comparison of approaches for modeling the DEA scores. European Journal of Operational Research, 181, 425–435.

    Article  Google Scholar 

  • Huang, C. J., & Liu, J. T. (1994). Estimation of a non-neutral stochastic frontier production function. Journal of Productivity Analysis, 5, 171–180.

    Article  Google Scholar 

  • Jondrow, J., Lovell, C. A. K., Materov, I. S., & Schmidt, P. (1982). On the estimation of technical inefficiency in stochastic frontier production model. Journal of Econometrics, 19, 233–238.

    Article  Google Scholar 

  • Kumbhakar, S. C., & Heshmati, A. (1995). Efficiency measurement in Swedish dairy farms: An application of rotating panel data. American Journal of Agricultural Economics, 77, 660–674.

    Article  Google Scholar 

  • Kumbhakar, S. C., Ghosh, S., & McGuckin, J. T. (1991). A generalized production frontier approach for estimating determinants of inefficiency in US dairy farms. Journal of Business and Economic Statistics, 9, 279–286.

    Google Scholar 

  • Kumbhakar, S. C., Lien, G., & Hardaker, J. B. (2014). Technical efficiency in competing panel data models: A study of Norwegian grain farming. Journal of Productivity Analysis, 41(2), 321–337.

    Article  Google Scholar 

  • Kumbhakar, S. C., Wang, H. J., & Horncastle, A. P. (2015). A practitioner’s guide to Stochastic Frontier analysis using stata. New York: Cambridge University Press.

    Book  Google Scholar 

  • Lai, H. P., & Kumbhakar, S. C. (2016). Panel data Stochastic Frontier model with determinants of persistent and transient inefficiency, economics seminars papers, New York.

    Google Scholar 

  • Madau, F. A. (2011). Parametric estimation of technical and scale efficiencies in Italian Citrus Farming. Agricultural Economics Review, 12(1), 91–112.

    Google Scholar 

  • Ogada, M., Muchai, J., Mwabu, D., & Mathenge, M. (2014). Technical efficiency of Kenya’s smallholder food crop farmers: Do Environmental Factors Matter? Environment Development and Sustainability, 16(5), 1065–1076.

    Article  Google Scholar 

  • Parikh, A., & Shah, K. (1994). Measurement of technical efficiency in the North-West Frontier Province of Pakistan. Journal of Agricultural Economics, 45, 132–138.

    Article  Google Scholar 

  • Reinhard, S., Lovell, C. A. K., & Thijssen, G. J. (2002). Analysis of environmental efficiency variation. American Journal of Agricultural Economics, 84, 1054–1065.

    Article  Google Scholar 

  • Schmidt, P., & Sickles, R. C. (1984). Production frontier and panel data. Journal of Business and Economic Statistics, 2(4), 367–374.

    Google Scholar 

  • Schultz, T.W. (1964). Transforming traditional agriculture. New Haven: Yale University Press.

    Google Scholar 

  • Sherlund, S. M., Barrett, C. B., & Adesina, A. A. (2002). Smallholder technical efficiency controlling for environmental conditions. Journal of Development Economics, 69, 85–101.

    Article  Google Scholar 

  • Simar, L., & Wilson, P. (2007). Estimation and inference in two-stage, semi-parametric models of production processes. Journal of Econometrics, 136, 31–64.

    Article  Google Scholar 

  • The World Bank. (2010). The World Bank annual report 2010. Washington, DC: The World Bank Group.

    Book  Google Scholar 

  • Wooldridge, J. M. (2002). Econometric analysis of cross-section and panel data. Cambridge, MA: The MIT Press.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Economics, College of Business and Economics, Addis Ababa University, Addis Ababa, Ethiopia

    Oumer Berisso

Authors
  1. Oumer Berisso
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Jönköping International Business School (JIBS), Jönköping University, Jönköping, Sweden

    Pia Nilsson

  2. Jönköping International Business School (JIBS), Jönköping University, Jönköping, Sweden

    Almas Heshmati

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Berisso, O. (2019). Analysis of Factors Affecting Persistent and Transient Inefficiency of Ethiopia’s Smallholder Cereal Farming. In: Nilsson, P., Heshmati, A. (eds) Efficiency, Equity and Well-Being in Selected African Countries. Economic Studies in Inequality, Social Exclusion and Well-Being. Springer, Cham. https://doi.org/10.1007/978-3-030-11419-0_10

Download citation

Publish with us

Policies and ethics

Search

Navigation