| Peer-Reviewed

Effect of Price Changes on Green Gram Yield in Tharaka South Sub-County, Tharaka Nithi County, Kenya

Received: 16 May 2023    Accepted: 2 June 2023    Published: 27 June 2023
Views:       Downloads:
Abstract

Kenyans in Arid and Semiarid Lands (ASALs), rely heavily on green gram as a source of nutrition, earnings, and soil improvement, but yield has not kept up with growth in demand. Due to this, the Kenyan government's declared goal of improving food access, diversity, and nutritional status has been hampered in these areas. In comparison to the worldwide and national averages of 0.73 mt/ha and 0.67 mt/ha, respectively, the yield in Tharaka South Sub-County is still too low at 0.56 mt/ha, considerably below the crop's estimated 1.5 mt/ha national potential. Green gram yield is mainly constrained by fluctuating producer prices and rational producers may only improve yields in response to a price increase. This study aimed at analysing the green gram yield responsiveness to the commodity’s price changes in Tharaka South Sub-County, Tharaka Nithi County, Kenya for the period 2002-2021. The study employed descriptive research design and used secondary data. The data on seasonal green gram price and yield was collected from Tharaka Nithi County Department of Agriculture and analysed using linear regression model and qualitative methods. It was observed that the trends of green gram yield and price have been fluctuating over the study period. The green gram yield obtained during the October November December (OND) season was higher than the yield obtained during the March April May season (MAM). As portrayed by the economic law of demand and supply, green gram price during OND season was lower than the price offered during MAM season. Further the findings of the model showed that price changes explained 25.3% of the variables affecting green gram yield. Additionally, the findings of the regression analysis revealed that yield has been increasing at a decreasing rate as price increases by 1%. A 1% increase in price was associated with 0.47% decrease in yield probably due to reuse of seed. The study concluded that increasing green gram yield requires a supportive price, but this is not a sufficient condition but other support to reduce production risks should be provided. Further, access to certified seed should be enhanced to reduce chances of seed recycling or reuse. The study recommends the setting up of a functional agricultural commodity market for structured marketing of green gram as well as supporting production for sustainable yield.

Published in International Journal of Agricultural Economics (Volume 8, Issue 3)
DOI 10.11648/j.ijae.20230803.15
Page(s) 108-115
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

Green Gram, Price, Changes, Yield

References
[1] Lal, G. M., Lavanya, G. R., & Udayasri, S. (2022). Estimation of Variability and Genetic Divergence in Greengram [Vigna radiata (L.) Wilczek] for Yield Characters. International Journal of Plant & Soil Science, 49-56.
[2] Krishna, A. G., & Kumar, A. (2022). Efficacy of insecticides and neem oil against spotted pod borer [Maruca vitrata (Geyer)], on greengram [Vigna radiata (L.)]. The Pharma Innovation Journal, 425-428.
[3] Marwein, Y., & Ray, L. I. (2019). Performance of rajma (Phaseolus vulgaris) cultivars under organic mulches in Meghalayan Plateau of North Eastern India. Legume Research-an international journal, 42 (1), 114-118.
[4] Nair, R., & Schreinemachers, P. (2020). Global status and economic importance of mungbean. The mungbean genome, 1-8.
[5] Government of Kenya (GoK), (2020). Can Green Gram Enhance Food and Nutrition Security in Kenya? Evidence from top eight Green Gram Producing Counties in Kenya: The National Treasury and Planning.
[6] Muchomba, M. K., Muindi, E. M., & Mulinge, J. M. (2023). Overview of Green Gram (Vigna radiata L.) Crop, Its Economic Importance, Ecological Requirements and Production Constraints in Kenya. Journal of Agriculture and Ecology Research International, 24 (2), 1-11.
[7] Assouto, A. B., Houensou, D. A., & Semedo, G. (2020). Price risk and farmers’ decisions: A case study from Benin. Scientific African, 8, e00311.
[8] Shoko, R. R., Chaminuka, P., & Belete, A. (2016). Estimating the supply response of maize in South Africa: A Nerlovian Partial Adjustment Model Approach. Agrekon, 55 (3), 237–253.
[9] Narain, D. (1965). Impact of price movements on areas under selected crops in India, 1900-1939. CUP Archive.
[10] Abodi, M., Obare, G., & Kariuki, I. (2021). Supply and demand responsiveness to maize price changes in Kenya: An application of error correction autoregressive distributed lag approach. Cogent Food & Agriculture, 7 (1), 1957318.
[11] Huong, N. V., & Yorobe, J. M. (2017). Maize supply response in Vietnam. Asian Journal of Agriculture and Development, 14 (1362-2017-855), 89-105.
[12] Prager, D., Burns, C., Tulman, S., & MacDonald, J. (2020). Farm use of futures, options, and marketing contracts (No. 1473-2020-854).
[13] Salifou, C. K., Erbao, C., Ousseini, A. M., & Metuge Mekongcho, T. (2019). Cocoa Production Output Response to Smallholder Price Speculation: Case Study of Cote d’Ivoire and Nigeria. International Economic Journal, 33 (2), 350-364.
[14] Haile, M. G., Kalkuhl, M., & von Braun, J. (2016). Worldwide acreage and yield response to international price change and volatility: a dynamic panel data analysis for wheat, rice, corn, and soybeans. American Journal of Agricultural Economics, 98 (1), 172-190.
[15] Jongeneel, R., & Gonzalez-Martinez, A. R. (2020). Estimating crop yield supply responses to be used for market outlook models: Application to major developed and developing countries. NJAS-Wageningen Journal of Life Sciences, 92, 100327.
[16] Rashid, S. (2018). Food Price Stabilization Policies in a Globalizing World (6-8). Case Studies in Food Policy for Developing Countries: Domestic Policies for Markets, Production, and Environment, 2, 95.
[17] Shahzad, M., Jan, A. U., Ali, S., & Ullah, R. (2018). Supply response analysis of tobacco growers in Khyber Pakhtunkhwa: An ARDL approach. Field Crops Research, 218, 195-200.
[18] Yu, T., Mahe, L., Li, Y., Wei, X., Deng, X., & Zhang, D. (2022). Benefits of crop rotation on climate resilience and its prospects in China. Agronomy, 12 (2), 436.
[19] Magrini, E., Balié, J., & Morales‐Opazo, C. (2017). Cereal price shocks and volatility in sub‐Saharan Africa: what really matters for farmers’ welfare? Agricultural Economics, 48 (6), 719-729.
[20] Onono, P. A. (2018). Response of sorghum production in Kenya to prices and public investments. Sustainable Agriculture Research, 7 (2), 19–29.
[21] Bor, O., & Bayaner, A. (2009). How Responsive is the Crop Yield to producer prices? A panel data approach for the case of Turkey. New Medit, 8 (4), 28-33.
[22] Abu, O., Olaide, A. R., & Okwoche, V. A. O. (2015). Acreage response of soybeans to price in Nigeria. European Journal of Physical and Agricultural Sciences Vol, 3 (1).
[23] Paul Jr, M., Molua, E. L., Nzie, J. R. M., & Fuh, G. L. (2020). Production and supply of tomato in Cameroon: Examination of the comparative effect of price and non-price factors. Scientific African, 10, e00574.
[24] Fisher, B. S. (1982). Rational expectations in agricultural economics research and policy analysis. American Journal of Agricultural Economics, 64 (2), 260-265.
[25] Hidayat, N. K. N., Glasbergen, P., and Offermans, A. (2015). Sustainability certification and palm oil smallholders' livelihood: a comparison between scheme smallholders and independent smallholders in Indonesia. Int. Food 18, 25–48.
[26] Hodgson, G. M. (2012). On the limits of rational choice theory. Economic Thought, 1 (1, 2012).
[27] County Government of Kenya (CGoK) (2018). County integrated development plan 2018–2022. Kenya: County Government of Tharaka Nithi.
[28] Kenya National Bureau of Statistics (KNBS), (2019). Kenya population and housing census. Population by county and sub-county. Nairobi: Government Printer.
[29] Mugenda, A. G. (2008). Social Science Research: Theory and Principles. Nairobi: Applied Research & Training Services (ARTS) Press.
[30] Mahmood, Z., Basharat, M., & Bashir, Z. (2012). Review of classical management theories. International Journal of Social Sciences and Education, 2 (1), 512-522.
[31] Thornton, P. K., Aggarwal, P., & Parsons, D. (2017). Prioritising climate-smart agricultural interventions at different scales. Agric. Syst. 151, 149–152.
[32] Bairagi, S., Mishra, A. K., & Mottaleb, K. A. (2022). Impacts of the COVID-19 pandemic on food prices: Evidence from storable and perishable commodities in India. PLoS One, 17 (3), e0264355.
[33] Kimani, P. N., Kumar, S. N., & Panjwani, S. (2022). Impact of climate change on kidney bean (Phaseolus vulgaris L.) in India and Kenya.
[34] Demissie, T., Bolt, J., Duku, C., Groot, A., & Recha, J. (2019). Green gram Kenya: Climate change risks and opportunities. CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS); Wageningen Environmental Research, The Netherlands.
[35] Mugo, J. W., Opijah, F. J., Ngaina, J., Karanja, F., & Mburu, M. (2020). Suitability of Green Gram Production in Kenya under Present and Future Climate Scenarios Using Bias-Corrected Cordex RCA4 Models. Agricultural Sciences, 11, 882-896.
[36] Mumo, L., Yu, J., & Fang, K. (2018). Assessing impacts of seasonal climate variability on maize yield in Kenya. International Journal of Plant Production, 12 (4), 297-307.
[37] Mkonda, M. Y., & He, X. (2018). Climate variability and crop yields synergies in Tanzania’s semiarid agroecological zone. Ecosystem Health and Sustainability, 4 (3), 59-72.
[38] Koimbori, J. K., Shisanya, C. A., Murimi, S. K., & Petterson, R. (2019). Impacts of Climate Variability on Maize Yields in Bahati Sub-County, Kenya. Environmental Sciences, 7 (2), 45-55.
[39] Vijayasarathy, K., & Ashok, K. R. (2015). Climate adaptation in agriculture through technological option: determinants and impact on efficiency of production. Agricultural Economics Research Review, 28 (1), 103-116.
[40] Boutesteijn C. (2018). The Effects of Prices on Acreages and Yields of Biofuel Feedstock in the European Union Wageningen Economic Research (2018) Master Thesis.
[41] Nahar, M. A. (2016). The Impact of Climate Change in Bangladesh on the Rice Market and farm households. theses and dissertations.
[42] Miao, R., Khanna, M., & Huang, H. (2015). Responsiveness of crop yield and acreage to prices and climate. American Journal of Agricultural Economics, 98 (1), 191-211.
[43] Nasir, M. A., Wardhono, A., & Qori’ah, C. G. (2023). Determinants of tobacco supply in Indonesia: Generalized method of moment approach. In AIP Conference Proceedings (Vol. 2583, No. 1, p. 110002). AIP Publishing LLC.
[44] Le, T. T. (2016). Effects of climate change on rice yield and rice market in Vietnam. Journal of Agricultural and Applied Economics, 48 (4), 366-382.
Cite This Article
  • APA Style

    Mathenge Beatrice Mugure, Dennis K. Muriithi, Gathungu Geofrey Kingori. (2023). Effect of Price Changes on Green Gram Yield in Tharaka South Sub-County, Tharaka Nithi County, Kenya. International Journal of Agricultural Economics, 8(3), 108-115. https://doi.org/10.11648/j.ijae.20230803.15

    Copy | Download

    ACS Style

    Mathenge Beatrice Mugure; Dennis K. Muriithi; Gathungu Geofrey Kingori. Effect of Price Changes on Green Gram Yield in Tharaka South Sub-County, Tharaka Nithi County, Kenya. Int. J. Agric. Econ. 2023, 8(3), 108-115. doi: 10.11648/j.ijae.20230803.15

    Copy | Download

    AMA Style

    Mathenge Beatrice Mugure, Dennis K. Muriithi, Gathungu Geofrey Kingori. Effect of Price Changes on Green Gram Yield in Tharaka South Sub-County, Tharaka Nithi County, Kenya. Int J Agric Econ. 2023;8(3):108-115. doi: 10.11648/j.ijae.20230803.15

    Copy | Download

  • @article{10.11648/j.ijae.20230803.15,
      author = {Mathenge Beatrice Mugure and Dennis K. Muriithi and Gathungu Geofrey Kingori},
      title = {Effect of Price Changes on Green Gram Yield in Tharaka South Sub-County, Tharaka Nithi County, Kenya},
      journal = {International Journal of Agricultural Economics},
      volume = {8},
      number = {3},
      pages = {108-115},
      doi = {10.11648/j.ijae.20230803.15},
      url = {https://doi.org/10.11648/j.ijae.20230803.15},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijae.20230803.15},
      abstract = {Kenyans in Arid and Semiarid Lands (ASALs), rely heavily on green gram as a source of nutrition, earnings, and soil improvement, but yield has not kept up with growth in demand. Due to this, the Kenyan government's declared goal of improving food access, diversity, and nutritional status has been hampered in these areas. In comparison to the worldwide and national averages of 0.73 mt/ha and 0.67 mt/ha, respectively, the yield in Tharaka South Sub-County is still too low at 0.56 mt/ha, considerably below the crop's estimated 1.5 mt/ha national potential. Green gram yield is mainly constrained by fluctuating producer prices and rational producers may only improve yields in response to a price increase. This study aimed at analysing the green gram yield responsiveness to the commodity’s price changes in Tharaka South Sub-County, Tharaka Nithi County, Kenya for the period 2002-2021. The study employed descriptive research design and used secondary data. The data on seasonal green gram price and yield was collected from Tharaka Nithi County Department of Agriculture and analysed using linear regression model and qualitative methods. It was observed that the trends of green gram yield and price have been fluctuating over the study period. The green gram yield obtained during the October November December (OND) season was higher than the yield obtained during the March April May season (MAM). As portrayed by the economic law of demand and supply, green gram price during OND season was lower than the price offered during MAM season. Further the findings of the model showed that price changes explained 25.3% of the variables affecting green gram yield. Additionally, the findings of the regression analysis revealed that yield has been increasing at a decreasing rate as price increases by 1%. A 1% increase in price was associated with 0.47% decrease in yield probably due to reuse of seed. The study concluded that increasing green gram yield requires a supportive price, but this is not a sufficient condition but other support to reduce production risks should be provided. Further, access to certified seed should be enhanced to reduce chances of seed recycling or reuse. The study recommends the setting up of a functional agricultural commodity market for structured marketing of green gram as well as supporting production for sustainable yield.},
     year = {2023}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Effect of Price Changes on Green Gram Yield in Tharaka South Sub-County, Tharaka Nithi County, Kenya
    AU  - Mathenge Beatrice Mugure
    AU  - Dennis K. Muriithi
    AU  - Gathungu Geofrey Kingori
    Y1  - 2023/06/27
    PY  - 2023
    N1  - https://doi.org/10.11648/j.ijae.20230803.15
    DO  - 10.11648/j.ijae.20230803.15
    T2  - International Journal of Agricultural Economics
    JF  - International Journal of Agricultural Economics
    JO  - International Journal of Agricultural Economics
    SP  - 108
    EP  - 115
    PB  - Science Publishing Group
    SN  - 2575-3843
    UR  - https://doi.org/10.11648/j.ijae.20230803.15
    AB  - Kenyans in Arid and Semiarid Lands (ASALs), rely heavily on green gram as a source of nutrition, earnings, and soil improvement, but yield has not kept up with growth in demand. Due to this, the Kenyan government's declared goal of improving food access, diversity, and nutritional status has been hampered in these areas. In comparison to the worldwide and national averages of 0.73 mt/ha and 0.67 mt/ha, respectively, the yield in Tharaka South Sub-County is still too low at 0.56 mt/ha, considerably below the crop's estimated 1.5 mt/ha national potential. Green gram yield is mainly constrained by fluctuating producer prices and rational producers may only improve yields in response to a price increase. This study aimed at analysing the green gram yield responsiveness to the commodity’s price changes in Tharaka South Sub-County, Tharaka Nithi County, Kenya for the period 2002-2021. The study employed descriptive research design and used secondary data. The data on seasonal green gram price and yield was collected from Tharaka Nithi County Department of Agriculture and analysed using linear regression model and qualitative methods. It was observed that the trends of green gram yield and price have been fluctuating over the study period. The green gram yield obtained during the October November December (OND) season was higher than the yield obtained during the March April May season (MAM). As portrayed by the economic law of demand and supply, green gram price during OND season was lower than the price offered during MAM season. Further the findings of the model showed that price changes explained 25.3% of the variables affecting green gram yield. Additionally, the findings of the regression analysis revealed that yield has been increasing at a decreasing rate as price increases by 1%. A 1% increase in price was associated with 0.47% decrease in yield probably due to reuse of seed. The study concluded that increasing green gram yield requires a supportive price, but this is not a sufficient condition but other support to reduce production risks should be provided. Further, access to certified seed should be enhanced to reduce chances of seed recycling or reuse. The study recommends the setting up of a functional agricultural commodity market for structured marketing of green gram as well as supporting production for sustainable yield.
    VL  - 8
    IS  - 3
    ER  - 

    Copy | Download

Author Information
  • Department of Agricultural Economics, Agribusiness Management and Agricultural Education, Chuka University, Chuka, Kenya

  • Department of Physical Sciences, Chuka University, Chuka, Kenya

  • Department of Plant Sciences, Chuka University, Chuka, Kenya

  • Sections