American Journal of Theoretical and Applied Statistics

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An Assessment of Farmers Livelihood in the Coffee Certification Schemes in Tanzania

Received: 14 September 2015    Accepted: 26 September 2015    Published: 12 October 2015
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Abstract

This study was undertaken to assess the impacts of adoption of various types of coffee certifications on the livelihoods of smallholder farmers. The main objective of this study was to compare the livelihood of farmers under the different producer groups with respect to their income and food security situation. It begins with an introduction to impact assessment and a description of the methodology and its challenges with an outline of the method used for handling outliers and comparing the certified and non-certified farmers and the producer groups. Secondary data from coffee survey data collected by COSA and partners for analyzing the impact of sustainability standards forms the basis of this study. Multi stage cluster sampling was used to sample farmers that were interviewed. In the first stage, the coffee growing areas in Tanzania and the active certification programs were identified. Then second level producer groups that had obtained certification were used to obtained the sampling frame of the first level producer groups. Random sampling was then used to select the first level producer groups and also randomly select villages with farmer in the producer groups. Non parametric methods have been used to compare the producer groups because one sample does not follow a normal distribution and most of them are highly skewed. Error bars plots have been used to compare the significance difference in the producer groups. Aggregate income from the different forms in which coffee was sold has been computed and used for comparison. It also evaluates the food security situation last production year of the farmers across the different producer groups. The key indicators used, showed that generally, adoption of the various coffee certifications programs have positive impacts on income and food security. In the course of this study, the areas of further research that emerged are; an evaluation of the farmers livelihood before intervention is done to ascertain whether their livelihood has changed due to adoption of certification or due to other factors and the development of a stepwise procedure for an outlier identification and ascertaining their validity. The methods that were used for outlier detection were subjective.

DOI 10.11648/j.ajtas.20150406.15
Published in American Journal of Theoretical and Applied Statistics (Volume 4, Issue 6, November 2015)
Page(s) 446-463
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Coffee Certifications, Smallholder Farmers, Livelihoods Assessment, Outlier Detection

References
[1] Andrews, D. and Pregibon, D. (1978), “Finding the outliers that matter”, Journal of the Royal Statistical Society. Series B (Methodological), 85-93.
[2] Bacon, C. (2005), “Confronting the coffee crisis: can fair trade, organic, and specialty coffees reduce small-scale farmer vulnerability in northern Nicaragua?” World Development, 33, 497-511.
[3] Bacon, C., Méndez, V., and Gliessman, S. (2008), Confronting the coffee crisis: fair trade, sustainable livelihoods and ecosystems in Mexico and Central America, The MIT Press.
[4] Bania, N., Leete, L., and Wisconsin-Madison (2007), Institute for Research on Poverty, U. Income Volatility and Food Insufficiency in US Low-Income Households, 1992-2003, Institute for Research on Poverty.
[5] Bulmer, M. (1979), Principles of statistics, Dover Pubns.
[6] Carney, D. (1998), “Implementing the sustainable rural livelihoods approach,” Sustainable rural livelihoods: What contribution can we make, 3-23.
[7] Dasgupta, S. (1989). Diffusion of agricultural innovations in village India, Wiley Eastern Limited, New Delhi.
[8] Davies, L. and Gather, U. (1993), “The identification of multiple outliers”, Journal of the American Statistical Association, 782-792.
[9] Ellis, F. (2000), Rural livelihoods and diversity in developing countries, Oxford University Press, USA.
[10] Giovannucci, D., Byers, A., and Liu, P. (2008), “Adding value: Certified coffee trade in North America”
[11] Hadi, A. (1992), “Identifying multiple outliers in multivariate data”, Journal of the Royal Statistical Society. Series B (Methodological), 54, 761-771
[12] Hawkins, D. (1980), Identification of outliers, Chapman & Hall.
[13] Hulme, D. (1997). Impact assessment methodologies for microfinance: A review, AIMS, USAID.
[14] Iglewicz, B. and Hoaglin, D. (1993), “How to Detect and Handle Outliers (ASQC Basic References in Quality Control, Vol. 16),”Milwaukee, WI: American Society for Quality Control.
[15] Johnson, R. and Wichern, D. (2002). Applied multivariate statistical analysis, vol. 5, Prentice Hall Upper Saddle River, NJ.
[16] Kumar, R. (2010), Research methodology: A step-by-step guide for beginners, Sage Publications Ltd.
[17] Leedy, P. and Ormrod, J. (2005), “Qualitative research methodologies” Practical research planning and design, 8, 133-160.
[18] Lewis, J. (2005), “Strategies for survival: Migration and fair trade-organic coffee production in Oaxaca, Mexico,”The Center for Comparative Immigration Studies, Working Paper.
[19] Martincic, F. and Schwiebert, L. (2006), “Distributed event detection in sensor networks”, in Systems and Networks Communications, 2006. ICSNC'06. International Conference on, IEEE, pp. 43-43.
[20] Mayne, R., Tola, A., and Kebede, G. (2002), “Crisis in the birth place of coffee”, Oxfam International research paper, Oxfam International.
[21] Pena, D. and Yohai, V. (1995). “The detection of influential subsets in linear regression by using an influence matrix”, Journal of the Royal Statistical Society. Series B (Methodological), 145-156.
[22] Ponte, S. (2004a), “The politics of ownership: Tanzanian coffee policy in the age of liberal reformism”, African Affairs, 103, 615.
[23] Ponte, S. (2004b), “Standards and sustainability in the coffee sector”, International Institute for Sustainable Development. Available at http://www. iisd. org.
[24] Ravallion, M. (2003), “Assessing the poverty impact of an assigned program”, The impact of economic policies on poverty and income distribution: evaluation techniques and tools, 103-22.
[25] Raynolds, L. (2002), Poverty alleviation through participation in Fair Trade coffee networks: existing research and critical issues, Ford Foundation.
[26] Read, R. (1999), “Detecting outliers in non-redundant diffraction data”, Acta Crystallographica Section D: Biological Crystallography, 55, 1759-1764.
[27] Wollni, M. and Zeller, M. (2007). “Do farmers bene_t from participating in specialty markets and cooperatives? The case of coffee marketing in Costa Rica1”, Agricultural Economics, 37, 243-248.
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    Charles Kipkorir Masson. (2015). An Assessment of Farmers Livelihood in the Coffee Certification Schemes in Tanzania. American Journal of Theoretical and Applied Statistics, 4(6), 446-463. https://doi.org/10.11648/j.ajtas.20150406.15

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    Charles Kipkorir Masson. An Assessment of Farmers Livelihood in the Coffee Certification Schemes in Tanzania. Am. J. Theor. Appl. Stat. 2015, 4(6), 446-463. doi: 10.11648/j.ajtas.20150406.15

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    AMA Style

    Charles Kipkorir Masson. An Assessment of Farmers Livelihood in the Coffee Certification Schemes in Tanzania. Am J Theor Appl Stat. 2015;4(6):446-463. doi: 10.11648/j.ajtas.20150406.15

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  • @article{10.11648/j.ajtas.20150406.15,
      author = {Charles Kipkorir Masson},
      title = {An Assessment of Farmers Livelihood in the Coffee Certification Schemes in Tanzania},
      journal = {American Journal of Theoretical and Applied Statistics},
      volume = {4},
      number = {6},
      pages = {446-463},
      doi = {10.11648/j.ajtas.20150406.15},
      url = {https://doi.org/10.11648/j.ajtas.20150406.15},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20150406.15},
      abstract = {This study was undertaken to assess the impacts of adoption of various types of coffee certifications on the livelihoods of smallholder farmers. The main objective of this study was to compare the livelihood of farmers under the different producer groups with respect to their income and food security situation. It begins with an introduction to impact assessment and a description of the methodology and its challenges with an outline of the method used for handling outliers and comparing the certified and non-certified farmers and the producer groups. Secondary data from coffee survey data collected by COSA and partners for analyzing the impact of sustainability standards forms the basis of this study. Multi stage cluster sampling was used to sample farmers that were interviewed. In the first stage, the coffee growing areas in Tanzania and the active certification programs were identified. Then second level producer groups that had obtained certification were used to obtained the sampling frame of the first level producer groups. Random sampling was then used to select the first level producer groups and also randomly select villages with farmer in the producer groups. Non parametric methods have been used to compare the producer groups because one sample does not follow a normal distribution and most of them are highly skewed. Error bars plots have been used to compare the significance difference in the producer groups. Aggregate income from the different forms in which coffee was sold has been computed and used for comparison. It also evaluates the food security situation last production year of the farmers across the different producer groups. The key indicators used, showed that generally, adoption of the various coffee certifications programs have positive impacts on income and food security. In the course of this study, the areas of further research that emerged are; an evaluation of the farmers livelihood before intervention is done to ascertain whether their livelihood has changed due to adoption of certification or due to other factors and the development of a stepwise procedure for an outlier identification and ascertaining their validity. The methods that were used for outlier detection were subjective.},
     year = {2015}
    }
    

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    AB  - This study was undertaken to assess the impacts of adoption of various types of coffee certifications on the livelihoods of smallholder farmers. The main objective of this study was to compare the livelihood of farmers under the different producer groups with respect to their income and food security situation. It begins with an introduction to impact assessment and a description of the methodology and its challenges with an outline of the method used for handling outliers and comparing the certified and non-certified farmers and the producer groups. Secondary data from coffee survey data collected by COSA and partners for analyzing the impact of sustainability standards forms the basis of this study. Multi stage cluster sampling was used to sample farmers that were interviewed. In the first stage, the coffee growing areas in Tanzania and the active certification programs were identified. Then second level producer groups that had obtained certification were used to obtained the sampling frame of the first level producer groups. Random sampling was then used to select the first level producer groups and also randomly select villages with farmer in the producer groups. Non parametric methods have been used to compare the producer groups because one sample does not follow a normal distribution and most of them are highly skewed. Error bars plots have been used to compare the significance difference in the producer groups. Aggregate income from the different forms in which coffee was sold has been computed and used for comparison. It also evaluates the food security situation last production year of the farmers across the different producer groups. The key indicators used, showed that generally, adoption of the various coffee certifications programs have positive impacts on income and food security. In the course of this study, the areas of further research that emerged are; an evaluation of the farmers livelihood before intervention is done to ascertain whether their livelihood has changed due to adoption of certification or due to other factors and the development of a stepwise procedure for an outlier identification and ascertaining their validity. The methods that were used for outlier detection were subjective.
    VL  - 4
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Author Information
  • Department of Statistics and Computer Science, Moi University, Eldoret, Kenya

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