IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v7y2020i1d10.1057_s41599-020-00576-x.html
   My bibliography  Save this article

Socioeconomic determinants of farm household land allocation for grass pea production in North Wollo Zone of Amhara region, Ethiopia

Author

Listed:
  • Shimeles Damene

    (Addis Ababa University)

  • Dawit Diriba Guta

    (Addis Ababa University)

  • Mohammed Assen

    (Addis Ababa University)

  • Poshendra Satyal

    (University of East Anglia)

Abstract

Grass pea (Lathyrus sativus) is widely cultivated and consumed in Ethiopia, where its overconsumption has caused cases of lathyrism. Despite this fact, there are limited empirical studies carried out in Ethiopia on the factors driving household decision to grow grass pea and intensity of land allocation to its production. Therefore, this study was focused on exploring the determinants of smallholder farmers’ land allocation to grass pea production in two districts of Ethiopian highlands. Household survey, focus group discussions and key informant interviews were used as data collection methods. These were followed by statistical analysis of quantitative data with SPSS and thematic analysis of qualitative data. The study used the Heckman selection model to investigate the determinants of household’s intensity of land use for grass pea production. The data revealed that farmers in the study area annually allocated about 26% of their farm plots size to grass pea production. Household’s landholding size, age of household head and the head’s primary school attendance have statistically significant and positive effect on the size of land allocation to grass pea production. Farmers also switched to grass pea production due to its tolerance to drought and waterlogged soils. These all encouraged grass pea production and consumption by humans, which has resulted in lathyrism in the study area. Household access to health and farm extension services had negative and statistically significant effect on land allocation to grass pea production. Based on the findings, it is concluded that better access to markets, educational opportunities, credit facilities, family planning and farm extension services are needed to increase household awareness on crop diversification and enhance technology uptake and financial capacity. Consequently, this can help local people reduce allocation of land to grass pea production and decrease its consumption, thereby preventing the risk of lathyrism incidence.

Suggested Citation

  • Shimeles Damene & Dawit Diriba Guta & Mohammed Assen & Poshendra Satyal, 2020. "Socioeconomic determinants of farm household land allocation for grass pea production in North Wollo Zone of Amhara region, Ethiopia," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-10, December.
    • Handle: RePEc:pal:palcom:v:7:y:2020:i:1:d:10.1057_s41599-020-00576-x
    DOI: 10.1057/s41599-020-00576-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-020-00576-x
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/s41599-020-00576-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Junjie Wu & B. Wade Brorsen, 1995. "The Impact of Government Programs and Land Characteristics on Cropping Patterns," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 43(1), pages 87-104, March.
    2. Ian Coxhead & Bayou Demeke, 2004. "Panel Data Evidence on Upland Agricultural Land Use in the Philippines: Can Economic Policy Reforms Reduce Environmental Damages?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(5), pages 1354-1360.
    3. Taffesse, Alemayehu Seyoum & Dorosh, Paul A. & Gemessa, Sinafikeh Asrat, 2012. "Crop production in Ethiopia: Regional patterns and trends," IFPRI book chapters, in: Dorosh, Paul A. & Rashid, Shahidur (ed.), Food and agriculture in Ethiopia: Progress and policy challenges, chapter 3, International Food Policy Research Institute (IFPRI).
    4. Chibwana, Christopher & Fisher, Monica & Shively, Gerald, 2012. "Cropland Allocation Effects of Agricultural Input Subsidies in Malawi," World Development, Elsevier, vol. 40(1), pages 124-133.
    5. Menale Kassie, 2011. "Economic and Environmental Benefits of Forage Legume Intercropping in the Mixed System: A Case Study in West Gojam, Ethiopia," Working Papers 005, Policy Studies Institute.
    6. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    7. Laura Greig, 2009. "An Analysis of the Key Factors Influencing Farmer’s Choice of Crop, Kibamba Ward, Tanzania," Journal of Agricultural Economics, Wiley Blackwell, vol. 60(3), pages 699-715, September.
    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. Fissha Asmare & Jūratė Jaraitė & Andrius Kažukauskas, 2022. "Climate change adaptation and productive efficiency of subsistence farming: A bias‐corrected panel data stochastic frontier approach," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(3), pages 739-760, September.
    2. Sibande, Lonester & Bailey, Alastair & Davidova, Sophia, 2017. "The impact of farm input subsidies on maize marketing in Malawi," Food Policy, Elsevier, vol. 69(C), pages 190-206.
    3. Porgo, Mohamed & Kuwornu, John K.M. & Zahonogo, Pam & Jatoe, John Baptist D. & Egyir, Irene S., 2018. "Credit constraints and cropland allocation decisions in rural Burkina Faso," Land Use Policy, Elsevier, vol. 70(C), pages 666-674.
    4. CARPENTIER, Alain & GOHIN, Alexandre & SCKOKAI, Paolo & THOMAS, Alban, 2015. "Economic modelling of agricultural production: past advances and new challenges," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement (RAEStud), Institut National de la Recherche Agronomique (INRA), vol. 96(1), March.
    5. Li, Ji Feng & Wang, Xin & Zhang, Ya Xiong & Kou, Qin, 2014. "The economic impact of carbon pricing with regulated electricity prices in China ‐ An application of a CGE approach," Conference papers 332548, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    6. Nordhagen, Stella & Pascual, Unai, 2013. "The Impact of Climate Shocks on Seed Purchase Decisions in Malawi: Implications for Climate Change Adaptation," World Development, Elsevier, vol. 43(C), pages 238-251.
    7. Darima Fotheringham & Michael A. Wiles, 2023. "The effect of implementing chatbot customer service on stock returns: an event study analysis," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 802-822, July.
    8. Song, Wei-Ling & Uzmanoglu, Cihan, 2016. "TARP announcement, bank health, and borrowers’ credit risk," Journal of Financial Stability, Elsevier, vol. 22(C), pages 22-32.
    9. Arnberg, Soren & Hansen, Lars Garn, 2007. "The Dynamics of Farm Land Allocation - Short and Long Run Reactions in Long Micro Panel," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon 9978, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    10. Raymundo M. Campos-Vázquez, 2013. "Efectos de los ingresos no reportados en el nivel y tendencia de la pobreza laboral en México," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 23-54, November.
    11. Jonathan Gruber & Aaron Yelowitz, 1999. "Public Health Insurance and Private Savings," Journal of Political Economy, University of Chicago Press, vol. 107(6), pages 1249-1274, December.
    12. Campbell, Randall C. & Nagel, Gregory L., 2016. "Private information and limitations of Heckman's estimator in banking and corporate finance research," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 186-195.
    13. Leye Li & Louise Yi Lu & Dongyue Wang, 2022. "External labour market competitions and stock price crash risk: evidence from exposures to competitor CEOs’ award‐winning events," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(S1), pages 1421-1460, April.
    14. Calcagno, R. & Renneboog, L.D.R., 2004. "Capital Structure and Managerial Compensation : The Effects of Renumeration Seniority," Discussion Paper 2004-120, Tilburg University, Center for Economic Research.
    15. Son K. Lam & Thomas E. DeCarlo & Ashish Sharma, 2019. "Salesperson ambidexterity in customer engagement: do customer base characteristics matter?," Journal of the Academy of Marketing Science, Springer, vol. 47(4), pages 659-680, July.
    16. McCausland, David & Pouliakas, Konstantinos & Theodossiou, Ioannis, 2005. "Some are Punished and Some are Rewarded: A Study of the Impact of Performance Pay on Job Satisfaction," MPRA Paper 14243, University Library of Munich, Germany.
    17. Gary F. Peters & Andrea M. Romi & Juan Manuel Sanchez, 2019. "The Influence of Corporate Sustainability Officers on Performance," Journal of Business Ethics, Springer, vol. 159(4), pages 1065-1087, November.
    18. Fossen, Frank M. & König, Johannes, 2015. "Public health insurance and entry into self-employment," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112934, Verein für Socialpolitik / German Economic Association.
    19. Li, Chunyu & Lou, Chenxin & Luo, Dan & Xing, Kai, 2021. "Chinese corporate distress prediction using LASSO: The role of earnings management," International Review of Financial Analysis, Elsevier, vol. 76(C).
    20. Fernando Rios-Avila & Gustavo Canavire-Bacarreza, 2018. "Standard-error correction in two-stage optimization models: A quasi–maximum likelihood estimation approach," Stata Journal, StataCorp LP, vol. 18(1), pages 206-222, March.

    More about this item

    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:pal:palcom:v:7:y:2020:i:1:d:10.1057_s41599-020-00576-x. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.nature.com/ .

    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.