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Effects of Small-Scale Agricultural Crop Commercialisation on Rural Household Welfare in Tanzania: A Case Study of Liwale District, Lindi Region

Received: 8 September 2018     Accepted: 26 September 2018     Published: 22 October 2018
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Abstract

This study aimed at examining the effect of crop commercialisation on rural households’ poverty in Tanzania. The household survey data was collected from a sample of 389 rural households. Commercialisation index was used to estimate the level of household crop commercialisation. The principal component analysis was used to develop a household welfare index which was then clustered to identify poor and non-poor households through cluster analysis, the method automatically guided the decision retaining two clusters by calculating the measure-of-fit that is Bayesian Information Criterion (BIC). To examine the factors affecting the household poverty status, a logistic model was employed. Results revealed that the majority (65.6%) of the households are poor. The level of crop commercialisation is averaged to 66% indicating a commercialised farming practice. The results further showed that crop commercialisation, women participation in crop income allocation, off-farm income, access to extension services and household size significantly reduce household poverty while household head’s age had an adverse effect. The study suggests that the small and medium agricultural processing units in rural areas should be given priorities and strengthened since they are crucial to promoting the level of commercialisation among rural households. Furthermore, in periods of sufficient and excess harvest, the crops trade restrictions with the neighbour countries should be eliminated to increase the level of commercialisation and earnings to the local rural farmers.

Published in International Journal of Agricultural Economics (Volume 3, Issue 5)
DOI 10.11648/j.ijae.20180305.12
Page(s) 103-111
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), 2018. Published by Science Publishing Group

Keywords

Agriculture, Commercialisation, Rural, Welfare

References
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[2] Nkonya, N., and J. Barreiro-Hurle. "Analysis of incentives and disincentives for cashew nuts in the United Republic of Tanzania." Technical notes series, MAFAP, FAO, Rome (2013).
[3] Alliance for a Green Revolution in Africa. Africa Agriculture Status Report 2016; Progress towards Agricultural Transformation in Africa, 2016.
[4] United Republic of Tanzania. Agriculture Sector Development Programme Phase Two (ASDP II) 2015/2016-2024/2025, Dar es Salaam, 2016.
[5] United Republic of Tanzania. 2015 Tanzania in Figures. National Bureau of Statistics, Dar es Salaam, 2016.
[6] United Republic Tanzania. National Five Year Development Plan 2016/17 – 2020/21, 2016.
[7] United Republic of Tanzania. National Agriculture Policy: The Ministry of Agriculture Food Security and Cooperatives, Dar es Salaam, 2013.
[8] Leavens, M. Kennedy. "Gender and agriculture in Tanzania." (2011).
[9] Muriithi, Beatrice W. "Smallholder horticultural commercialization: Gender roles and implications for household well-being in Kenya." international conference of agricultural economists, Milan, Italy. 2015.
[10] United Republic of Tanzania. Household Budget Survey 2011/2012. National Bureau of Statistics, Dar es Salaam, 2014.
[11] Strasberg, Paul J., et al. Effects of agricultural commercialization on food crop input use and productivity in Kenya. No. 11463. Michigan State University, Department of Agricultural, Food, and Resource Economics, 1999.
[12] Jaleta, Moti, Berhanu Gebremedhin, and Dirk Hoekstra. "Smallholder commercialization: Processes, determinants and impact." (2009).
[13] Mitiku, Amsalu. "Impact of smallholder farmers’ agricultural commercialization on rural households’ poverty." The International Journal of Applied Economics and Finance 8.2 (2014): 51-61.
[14] Eskola, Elina. Commercialisation and poverty in Tanzania: Household-level analysis. No. 05-27. 2005.
[15] Masanjala, Winford H. "Cash crop liberalization and poverty alleviation in Africa: evidence from Malawi." Agricultural Economics 35.2 (2006): 231-240.
[16] Wolter, Denise. "Tanzania: The challenge of moving from subsistence to profit." OECD Journal: General Papers 2009.2 (2009): 79-102.
[17] United Republic of Tanzania. Basic Demographic and Socio-Economic Profile. Statistical Tables Tanzania Mainland: National Bureau of Statistics; Ministry of Finance, Dar es Salaam, 2014.
[18] Gorbachev, Olga. "Did household consumption become more volatile?" American Economic Review 101.5 (2011): 2248-70.
[19] United Republic of Tanzania. Population and housing census: population distribution by administrative areas. National Bureau of Statistics: Ministry of Finance, Dar es Salaam, 2012.
[20] Wagstaff, A., O. O’Donnell, and E. van Doorslaer. "Quantitative techniques for health equity analysis." (2007).
[21] Hoque, S. F. "Asset-based poverty analysis in rural Bangladesh: A comparison of principal component analysis and fuzzy set theory." Sustainability Research Institute University of Leeds SRI Paper 59 (2014).
[22] Mooi, E., and M. Sarstedt. "Cluster analysis. A concise guide to market research." (2011): 237-84.
[23] Krishnan, Vijaya. "Constructing an area-based socioeconomic index: A principal components analysis approach." Edmonton, Alberta: Early Child Development Mapping Project (2010).
[24] Smits, Jeroen, and Roel Steendijk. "The international wealth index (IWI)." Social Indicators Research 122.1 (2015): 65-85.
[25] Kirui, Oliver K., and Georgina W. Njiraini. "Impact of Collective Action on the smallholder agricultural commercialization and incomes: Experiences from Kenya." Centre for Development research, Germany. Paper prepared for the 4th Conference of AAAE. Tunisia. 2013.
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  • APA Style

    Nelson Ochieng, Aloyce Hepelwa. (2018). Effects of Small-Scale Agricultural Crop Commercialisation on Rural Household Welfare in Tanzania: A Case Study of Liwale District, Lindi Region. International Journal of Agricultural Economics, 3(5), 103-111. https://doi.org/10.11648/j.ijae.20180305.12

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    ACS Style

    Nelson Ochieng; Aloyce Hepelwa. Effects of Small-Scale Agricultural Crop Commercialisation on Rural Household Welfare in Tanzania: A Case Study of Liwale District, Lindi Region. Int. J. Agric. Econ. 2018, 3(5), 103-111. doi: 10.11648/j.ijae.20180305.12

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    AMA Style

    Nelson Ochieng, Aloyce Hepelwa. Effects of Small-Scale Agricultural Crop Commercialisation on Rural Household Welfare in Tanzania: A Case Study of Liwale District, Lindi Region. Int J Agric Econ. 2018;3(5):103-111. doi: 10.11648/j.ijae.20180305.12

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  • @article{10.11648/j.ijae.20180305.12,
      author = {Nelson Ochieng and Aloyce Hepelwa},
      title = {Effects of Small-Scale Agricultural Crop Commercialisation on Rural Household Welfare in Tanzania: A Case Study of Liwale District, Lindi Region},
      journal = {International Journal of Agricultural Economics},
      volume = {3},
      number = {5},
      pages = {103-111},
      doi = {10.11648/j.ijae.20180305.12},
      url = {https://doi.org/10.11648/j.ijae.20180305.12},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijae.20180305.12},
      abstract = {This study aimed at examining the effect of crop commercialisation on rural households’ poverty in Tanzania. The household survey data was collected from a sample of 389 rural households. Commercialisation index was used to estimate the level of household crop commercialisation. The principal component analysis was used to develop a household welfare index which was then clustered to identify poor and non-poor households through cluster analysis, the method automatically guided the decision retaining two clusters by calculating the measure-of-fit that is Bayesian Information Criterion (BIC). To examine the factors affecting the household poverty status, a logistic model was employed. Results revealed that the majority (65.6%) of the households are poor. The level of crop commercialisation is averaged to 66% indicating a commercialised farming practice. The results further showed that crop commercialisation, women participation in crop income allocation, off-farm income, access to extension services and household size significantly reduce household poverty while household head’s age had an adverse effect. The study suggests that the small and medium agricultural processing units in rural areas should be given priorities and strengthened since they are crucial to promoting the level of commercialisation among rural households. Furthermore, in periods of sufficient and excess harvest, the crops trade restrictions with the neighbour countries should be eliminated to increase the level of commercialisation and earnings to the local rural farmers.},
     year = {2018}
    }
    

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    T1  - Effects of Small-Scale Agricultural Crop Commercialisation on Rural Household Welfare in Tanzania: A Case Study of Liwale District, Lindi Region
    AU  - Nelson Ochieng
    AU  - Aloyce Hepelwa
    Y1  - 2018/10/22
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    DO  - 10.11648/j.ijae.20180305.12
    T2  - International Journal of Agricultural Economics
    JF  - International Journal of Agricultural Economics
    JO  - International Journal of Agricultural Economics
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    EP  - 111
    PB  - Science Publishing Group
    SN  - 2575-3843
    UR  - https://doi.org/10.11648/j.ijae.20180305.12
    AB  - This study aimed at examining the effect of crop commercialisation on rural households’ poverty in Tanzania. The household survey data was collected from a sample of 389 rural households. Commercialisation index was used to estimate the level of household crop commercialisation. The principal component analysis was used to develop a household welfare index which was then clustered to identify poor and non-poor households through cluster analysis, the method automatically guided the decision retaining two clusters by calculating the measure-of-fit that is Bayesian Information Criterion (BIC). To examine the factors affecting the household poverty status, a logistic model was employed. Results revealed that the majority (65.6%) of the households are poor. The level of crop commercialisation is averaged to 66% indicating a commercialised farming practice. The results further showed that crop commercialisation, women participation in crop income allocation, off-farm income, access to extension services and household size significantly reduce household poverty while household head’s age had an adverse effect. The study suggests that the small and medium agricultural processing units in rural areas should be given priorities and strengthened since they are crucial to promoting the level of commercialisation among rural households. Furthermore, in periods of sufficient and excess harvest, the crops trade restrictions with the neighbour countries should be eliminated to increase the level of commercialisation and earnings to the local rural farmers.
    VL  - 3
    IS  - 5
    ER  - 

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Author Information
  • Department of Economics and Social Studies, School of Spatial Planning and Social Sciences, Ardhi University, Dar es Salaam, Tanzania

  • Department of Agricultural Economics and Business, College of Agricultural Sciences and Fisheries Technology, University of Dar es Salaam, Dar es Salaam, Tanzania

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