IDEAS home Printed from https://ideas.repec.org/a/sek/jijobm/v10y2022i1p30-58.html
   My bibliography  Save this article

Analysis of Red Pepper Production Risk Adjusted Technical Efficiency: The Case Of Lanfuro District In Siltie Zone, Southern Ethiopia

Author

Listed:
  • Muktar Geleto

    (Muktar Geleto)

  • Mohammed Essa

    (Werabe University)

Abstract

This study objective was to add the additional empirical findings on the works of literature, that explain the possible causes of red pepper yield fluctuations in the study area. The output gap that exists between observed and the potential output indicates an opportunity for further output growth. To estimate the production risk and technical inefficiency effects the study was employed a cross-sectional data that collected from 320 sampled red pepper farmers in the study area. The results of the study confirmed that the translog (transcendental logarithmic ) production model specification was the best-fitted model. To estimate the level of technical efficiencies, this study was employed the stochastic frontier model with flexible risk properties that able to considered production risk. Hence, the output fluctuation is evaluated from both production risk and technical inefficiency sources. The estimations results of the mean output, production risk and technical inefficiency models provided by using a one-step maximum likelihood in the sfcross command with STATA16 software. The study justifies the presence of technical inefficiency and production risk in the red pepper production process. The input variable fertilizer, seed, another cost of agrochemicals and labour positively affect the red pepper output. The study also shows that the red pepper production technologies exhibit increasing returns to scale in the study area. Fertilizer, seed, costs of agrochemicals reduce output risk whilst labour increase output risk but its effect was insignificant. This study finding demonstrates that the causes of technical efficiency differentials among sampled red pepper farmers in the study area. The average technical efficiency scores of red pepper farmers are 62.5 per cent in the study area. There is a significant difference between the estimations of the production risk-adjusted and not adjusted averages technical efficiencies. The market information, extension contact, and gender being head household positively related to technical efficiency. The age of household head, the prevalence of diseases, family size and education at college and above level negatively related to technical efficiency. This study recommends that inputs for red pepper production should be made readily available, affordable and accessible to farmers so that more may be employed to further increase output.

Suggested Citation

  • Muktar Geleto & Mohammed Essa, 2022. "Analysis of Red Pepper Production Risk Adjusted Technical Efficiency: The Case Of Lanfuro District In Siltie Zone, Southern Ethiopia," International Journal of Business and Management, International Institute of Social and Economic Sciences, vol. 10(1), pages 30-58, May.
    • Handle: RePEc:sek:jijobm:v:10:y:2022:i:1:p:30-58
    as

    Download full text from publisher

    File URL: https://iises.net/international-journal-of-business-management/publication-detail-116973
    Download Restriction: no
    File URL: https://iises.net/international-journal-of-business-management/publication-detail-116973?download=2
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Coelli, Tim J. & Battese, George E., 1996. "Identification Of Factors Which Influence The Technical Inefficiency Of Indian Farmers," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 40(2), pages 1-26, August.
    2. Hung‐Hao Chang & Fang‐I Wen, 2011. "Off‐farm work, technical efficiency, and rice production risk in Taiwan," Agricultural Economics, International Association of Agricultural Economists, vol. 42(2), pages 269-278, March.
    3. Asche, Frank & Guttormsen, Atle G. & Roll, Kristin H., 2006. "Modelling Production Risk in Small Scale Subsistence Agriculture," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25574, International Association of Agricultural Economists.
    4. Just, Richard E. & Pope, Rulon D., 1978. "Stochastic specification of production functions and economic implications," Journal of Econometrics, Elsevier, vol. 7(1), pages 67-86, February.
    5. Mekdes Dessie & Teshale Woldeamanuel & Getachew Mekonnen, 2017. "Value Chain Analysis of Red Pepper: The Case of Abeshge District, Guragie Zone, South Ethiopia," International Journal of Environmental Sciences & Natural Resources, Juniper Publishers Inc., vol. 2(3), pages 94-101, June.
    6. Subal C. Kumbhakar, 2002. "Specification and Estimation of Production Risk, Risk Preferences and Technical Efficiency," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(1), pages 8-22.
    7. Azanaw Abebe & Merkuz Abera, 2019. "Pepper Disease Assessment and Identification in Major Growing Districts of West Gojam Zone in Northwestern Ethiopia," International Journal of Sustainable Agricultural Research, Conscientia Beam, vol. 6(1), pages 8-20.
    8. Anbes Tenaye, 2020. "Technical Efficiency of Smallholder Agriculture in Developing Countries: The Case of Ethiopia," Economies, MDPI, vol. 8(2), pages 1-27, April.
    9. Kumbhakar,Subal C. & Wang,Hung-Jen & Horncastle,Alan P., 2015. "A Practitioner's Guide to Stochastic Frontier Analysis Using Stata," Cambridge Books, Cambridge University Press, number 9781107029514.
    10. Antle, John M, 1983. "Testing the Stochastic Structure of Production: A Flexible Moment-based Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(3), pages 192-201, July.
    11. Hung-Jen Wang, 2002. "Heteroscedasticity and Non-Monotonic Efficiency Effects of a Stochastic Frontier Model," Journal of Productivity Analysis, Springer, vol. 18(3), pages 241-253, November.
    12. Kumbhakar, Sabul C., 1993. "Production risk, technical efficiency, and panel data," Economics Letters, Elsevier, vol. 41(1), pages 11-16.
    13. Reifschneider, David & Stevenson, Rodney, 1991. "Systematic Departures from the Frontier: A Framework for the Analysis of Firm Inefficiency," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 32(3), pages 715-723, August.
    14. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    15. Mette Wik & Tewodros Aragie Kebede & Olvar Bergland & Stein Holden, 2004. "On the measurement of risk aversion from experimental data," Applied Economics, Taylor & Francis Journals, vol. 36(21), pages 2443-2451.
    16. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    17. Kumbhakar,Subal C. & Wang,Hung-Jen & Horncastle,Alan P., 2015. "A Practitioner's Guide to Stochastic Frontier Analysis Using Stata," Cambridge Books, Cambridge University Press, number 9781107609464.
    18. Tadie Mirie Abate & Abebe Birara Dessie & Taye Melese Mekie, 2019. "Technical efficiency of smallholder farmers in red pepper production in North Gondar zone Amhara regional state, Ethiopia," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 8(1), pages 1-18, December.
    19. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Antti Saastamoinen, 2015. "Heteroscedasticity Or Production Risk? A Synthetic View," Journal of Economic Surveys, Wiley Blackwell, vol. 29(3), pages 459-478, July.
    2. Orea, Luis, 2019. "The Econometric Measurement of Firms’ Efficiency," Efficiency Series Papers 2019/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    3. Markose Chekol Zewdie & Michele Moretti & Daregot Berihun Tenessa & Zemen Ayalew Ayele & Jan Nyssen & Enyew Adgo Tsegaye & Amare Sewnet Minale & Steven Van Passel, 2021. "Agricultural Technical Efficiency of Smallholder Farmers in Ethiopia: A Stochastic Frontier Approach," Land, MDPI, vol. 10(3), pages 1-17, March.
    4. Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances I," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370, Springer.
    5. Villano, Renato A. & O'Donnell, Christopher J. & Battese, George E., 2005. "An Investigation of Production Risk, Risk Preferences and Technical Efficiency: Evidence From Rainfed Lowland Rice Farms in the Philippines," Working Papers 12953, University of New England, School of Economics.
    6. McFadden, Jonathan R., 2017. "Yield Maps, Soil Maps, and Technical Efficiency: Evidence from U.S. Corn Fields," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258120, Agricultural and Applied Economics Association.
    7. Ali M. Oumer & Amin Mugera & Michael Burton & Atakelty Hailu, 2022. "Technical efficiency and firm heterogeneity in stochastic frontier models: application to smallholder maize farms in Ethiopia," Journal of Productivity Analysis, Springer, vol. 57(2), pages 213-241, April.
    8. Ajayi, Victor & Weyman-Jones, Tom, 2021. "State-level electricity generation efficiency: Do restructuring and regulatory institutions matter in the US?," Energy Economics, Elsevier, vol. 104(C).
    9. Abebayehu Girma Geffersa & Frank Wogbe Agbola & Amir Mahmood, 2022. "Modelling technical efficiency and technology gap in smallholder maize sector in Ethiopia: accounting for farm heterogeneity," Applied Economics, Taylor & Francis Journals, vol. 54(5), pages 506-521, January.
    10. Sabrina Auci & Laura Castellucci & Manuela Coromaldi, 2021. "How does public spending affect technical efficiency? Some evidence from 15 European countries," Bulletin of Economic Research, Wiley Blackwell, vol. 73(1), pages 108-130, January.
    11. Muhammad Rizwan & Ping Qing & Abdul Saboor & Muhammad Amjed Iqbal & Adnan Nazir, 2020. "Production Risk and Competency among Categorized Rice Peasants: Cross-Sectional Evidence from an Emerging Country," Sustainability, MDPI, vol. 12(9), pages 1-15, May.
    12. Muhamad Zahid Muhamad & Mad Nasir Shamsudin & Nitty Hirawaty Kamarulzaman & Nolila Mohd Nawi & Jamaliah Laham, 2022. "Investigating Yield Variability and Technical Efficiency of Smallholders Pineapple Production in Johor," Sustainability, MDPI, vol. 14(22), pages 1-18, November.
    13. Zhihai Yang & Amin W. Mugera & Fan Zhang, 2016. "Investigating Yield Variability and Inefficiency in Rice Production: A Case Study in Central China," Sustainability, MDPI, vol. 8(8), pages 1-11, August.
    14. MAIMOUNA DIAKITE & Jean-François BRUN, 2016. "Tax Potential and Tax Effort: An Empirical Estimation for Non-Resource Tax Revenue and VAT’s Revenue," EcoMod2016 9537, EcoMod.
    15. Ali D. Cagdas & Scott R. Jeffrey & Elwin G. Smith & Peter C. Boxall, 2016. "Environmental Stewardship and Technical Efficiency in Canadian Prairie Canola Production," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(3), pages 455-477, September.
    16. Keller, Michael, 2020. "Wasted windfalls: Inefficiencies in health care spending in oil rich countries," Resources Policy, Elsevier, vol. 66(C).
    17. Mark Andor & Christopher Parmeter, 2017. "Pseudolikelihood estimation of the stochastic frontier model," Applied Economics, Taylor & Francis Journals, vol. 49(55), pages 5651-5661, November.
    18. Danuse Nerudova & Marian Dobranschi, 2019. "Alternative method to measure the VAT gap in the EU: Stochastic tax frontier model approach," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-38, January.
    19. Nguyen, Hoa-Thi-Minh & Do, Huong & Kompas, Tom, 2021. "Economic efficiency versus social equity: The productivity challenge for rice production in a ‘greying’ rural Vietnam," World Development, Elsevier, vol. 148(C).
    20. Gralka, Sabine, 2018. "Stochastic frontier analysis in higher education: A systematic review," CEPIE Working Papers 05/18, Technische Universität Dresden, Center of Public and International Economics (CEPIE).

    More about this item

    Keywords

    Red Pepper; Flexible Stochastic Frontier Model; Production Risk-adjusted Technical Efficiency; Cobb-Douglas Production Function;
    All these keywords.

    JEL classification:

    • F00 - International Economics - - General - - - General
    • A19 - General Economics and Teaching - - General Economics - - - Other
    • B50 - Schools of Economic Thought and Methodology - - Current Heterodox Approaches - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sek:jijobm:v:10:y:2022:i:1:p:30-58. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Klara Cermakova (email available below). General contact details of provider: https://ijobm.iises.net/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.