| Peer-Reviewed

Assessing the Effect of Agriculture Sub-sectors on the Gambia’s Economic Growth Using Time Series Econometric Models

Received: 1 July 2020    Accepted: 21 July 2020    Published: 19 August 2020
Views:       Downloads:
Abstract

The study aimed to assess the contribution of agriculture sub-sectors on the economic growth of The Gambia. The study used time series data obtained from The Gambia Bureau of Statistics for the period from 2004 to 2016. Variables included: Economic growth, Crops, Livestock, Fisheries and Forestry. Denton’s method of disaggregation was used to convert annual data into quarterly series. Auto Regressive Distributed Lag model of the co-integrating vector was re-parameterized into Error Correction Model and used to assess the effect of the study variables to the economic growth. The results reveal that crops and fisheries sub-sectors have strong positive effect on economic growth in the long-run while crops and livestock sub-sector have positive effect in the short run to economic growth in first lag. The study concludes that agriculture sub-sectors influence economic growth in The Gambia. Therefore, the study recommends that massive attention and investments be directed to the agriculture sector for more economic expansion.

Published in International Journal of Agricultural Economics (Volume 5, Issue 4)
DOI 10.11648/j.ijae.20200504.17
Page(s) 142-149
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

Auto Regressive Distributed Lag Model, Economic Growth, Agriculture Sub-sectors

References
[1] Kemisola, C. (2014). Government Expenditure on Agriculture and Economic Growth in Nigeria.
[2] Satyal, V. R. (2013). African agriculture, transformation and outlook. NEPAD (New Partnership for African Development) 11.
[3] World Bank (2011). Global Strategy to Improve Agricultural and Rural Statistics. Economic and sector work.
[4] OECD-FAO (2016). Agriculture in Sub-Saharan Africa: Prospects and challenges for the next decade. https://dx.doi.org/10.1787/agr_outlook-2016-5-en.
[5] FAO (2002). The Role of Agriculture in the Development of Least-developed Countries and their Integration into the World Economy. Fao.
[6] Awokuse, T. O. (2009). Does agriculture really matter for eonomic growth in developing countries? Am. Agric. Econ. Assoc. Annu. Meet. 26–28.
[7] World Bank (2016). World Development Indicators. https://databank.worldbank.org/source/world-development-indicators.
[8] The Gambia Bureau of Statistics (2019). Economic indicators. https://www.gbosdata.org/about-us.
[9] The Gambia Bureau of Statistics (2013). The Gambia 2013 Population and Housing Census Preliminary Results. Gambia Bur. Stat. 23.
[10] Gibba, A. & Molnar, J. A. (2016). Study on exports as a determinant of economic. Some Stud. Econ. Chang. ISBN 978-80-89691-27-2 237–244.
[11] Nkoro, E., & Uko, A. K. (2016). Autoregressive Distributed Lag (ARDL) Cointegration Technique: Application And Interpretation. J. Stat. Econom. Methods 5, 63–91.
[12] Al-Malkawi, H.-A. N., Marashdeh, H. a. & Abdullah, N. (2012). Financial Development and Economic Growth in the UAE: Empirical Assessment Using ARDL Approach to Co-integration. Int. J. Econ. Financ. 4, 105–115.
[13] Khim, V., & Liew, S. (2004). Which Lag Length Selection Criteria Should We Employ ? Univ. Putra Malaysia Econ. Bull. 3, 1–9.
[14] Tursoy, F. (2014). Causality between stock price and GDP in Turkey: An ARDL Bounds testing approach. Energy Econ. Lett. 9, 25–31.
[15] Engle, R. F. & Granger, C. W. J. (1987). Co-Integration and Error Correction: Representation, Estimation, and Testing. Econometrica 55, 251–276.
[16] Brown R. L, Durbin J & Evans J. M. (1975). Techniques for Testing the Constancy of Regression Relationships over Time Series B (Methodological). J. R. Stat. Soc. 37, 149–192.
[17] Chongela, J.(2015). Contribution of Agriculture Sector to the Tanzanian Economy. Am. J. Res. Commun. 3, 57–70.
[18] Shoka, I. H. (2015). Contribution of Agriculture To the Economic Growth of Zanzibar Contribution of Agriculture To the Economic. Masters Thesis, Mzumbe University.
[19] Raza S. A & Yasir A. F. M. (2010). Role of Agriculture in Economic Growth of Pakistan. Int. Res. J. Financ. Econ.
[20] Chandio, A. A., Yuansheng, J., & Magsi, H. (2016). Agricultural Sub-Sectors Performance: An Analysis of Sector-Wise Share in Agriculture GDP of Pakistan. International Journal of Economics and Finance, 8 (2), 156. https://doi.org/10.5539/ijef.v8n2p156
Cite This Article
  • APA Style

    Fatou Jobarteh, Majige Selemani. (2020). Assessing the Effect of Agriculture Sub-sectors on the Gambia’s Economic Growth Using Time Series Econometric Models. International Journal of Agricultural Economics, 5(4), 142-149. https://doi.org/10.11648/j.ijae.20200504.17

    Copy | Download

    ACS Style

    Fatou Jobarteh; Majige Selemani. Assessing the Effect of Agriculture Sub-sectors on the Gambia’s Economic Growth Using Time Series Econometric Models. Int. J. Agric. Econ. 2020, 5(4), 142-149. doi: 10.11648/j.ijae.20200504.17

    Copy | Download

    AMA Style

    Fatou Jobarteh, Majige Selemani. Assessing the Effect of Agriculture Sub-sectors on the Gambia’s Economic Growth Using Time Series Econometric Models. Int J Agric Econ. 2020;5(4):142-149. doi: 10.11648/j.ijae.20200504.17

    Copy | Download

  • @article{10.11648/j.ijae.20200504.17,
      author = {Fatou Jobarteh and Majige Selemani},
      title = {Assessing the Effect of Agriculture Sub-sectors on the Gambia’s Economic Growth Using Time Series Econometric Models},
      journal = {International Journal of Agricultural Economics},
      volume = {5},
      number = {4},
      pages = {142-149},
      doi = {10.11648/j.ijae.20200504.17},
      url = {https://doi.org/10.11648/j.ijae.20200504.17},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijae.20200504.17},
      abstract = {The study aimed to assess the contribution of agriculture sub-sectors on the economic growth of The Gambia. The study used time series data obtained from The Gambia Bureau of Statistics for the period from 2004 to 2016. Variables included: Economic growth, Crops, Livestock, Fisheries and Forestry. Denton’s method of disaggregation was used to convert annual data into quarterly series. Auto Regressive Distributed Lag model of the co-integrating vector was re-parameterized into Error Correction Model and used to assess the effect of the study variables to the economic growth. The results reveal that crops and fisheries sub-sectors have strong positive effect on economic growth in the long-run while crops and livestock sub-sector have positive effect in the short run to economic growth in first lag. The study concludes that agriculture sub-sectors influence economic growth in The Gambia. Therefore, the study recommends that massive attention and investments be directed to the agriculture sector for more economic expansion.},
     year = {2020}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Assessing the Effect of Agriculture Sub-sectors on the Gambia’s Economic Growth Using Time Series Econometric Models
    AU  - Fatou Jobarteh
    AU  - Majige Selemani
    Y1  - 2020/08/19
    PY  - 2020
    N1  - https://doi.org/10.11648/j.ijae.20200504.17
    DO  - 10.11648/j.ijae.20200504.17
    T2  - International Journal of Agricultural Economics
    JF  - International Journal of Agricultural Economics
    JO  - International Journal of Agricultural Economics
    SP  - 142
    EP  - 149
    PB  - Science Publishing Group
    SN  - 2575-3843
    UR  - https://doi.org/10.11648/j.ijae.20200504.17
    AB  - The study aimed to assess the contribution of agriculture sub-sectors on the economic growth of The Gambia. The study used time series data obtained from The Gambia Bureau of Statistics for the period from 2004 to 2016. Variables included: Economic growth, Crops, Livestock, Fisheries and Forestry. Denton’s method of disaggregation was used to convert annual data into quarterly series. Auto Regressive Distributed Lag model of the co-integrating vector was re-parameterized into Error Correction Model and used to assess the effect of the study variables to the economic growth. The results reveal that crops and fisheries sub-sectors have strong positive effect on economic growth in the long-run while crops and livestock sub-sector have positive effect in the short run to economic growth in first lag. The study concludes that agriculture sub-sectors influence economic growth in The Gambia. Therefore, the study recommends that massive attention and investments be directed to the agriculture sector for more economic expansion.
    VL  - 5
    IS  - 4
    ER  - 

    Copy | Download

Author Information
  • The Gambia National Bureau of Statistics, Kanifing Institutional Layout, Greater Banjul, The Gambia

  • Department of Research, Bank of Tanzania, Dar es Salaam, Tanzania

  • Sections