Share This Article:

Causalities between Price, Pond Area and Employment in Aquaculture Production

Abstract Full-Text HTML Download Download as PDF (Size:251KB) PP. 175-183
DOI: 10.4236/nr.2013.42023    3,303 Downloads   5,039 Views  


The role of aquaculture industry is becoming more prominent in order to supplement marine capture in meeting the food need for the growing Malaysian population. In an attempt to minimize depletion of marine fisheries, only traditional vessels are allowed to fish along the coastal area while bigger vessels are relegated to deep-sea fishing. During the 9th Malaysian Plan (2006-2010) aquaculture has been recognized as the engine of growth in the national food sector’s development strategy. Future fisheries policy is expected to focus more on aquaculture production, marketing and technological improvement as an alternative to marine capture. This paper investigates the causalities between the selected freshwater fish prices, aquaculture area and production. The study aspires to establish whether or not market price is a key contributor to a rise in the aquaculture area and production. Aquaculture firms comprising the individual culturists are generally motivated by the economic potential of the industry which is reflected in excess of price over cost of production. Our hypothesis is that government policy and initiation rather than prices had give rise to greater participation of culturists and hence augmented the level of employment. However, production increase has a negative implication on environment degradation. Thus there is a conflicting view as regards to the employment opportunity generated by aquaculture undertakings and the need for sustainable development arising from this growing industry. Multivariate time series analysis was used in this investigation.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

N. Mustapha, A. Aziz and N. Hashim, "Causalities between Price, Pond Area and Employment in Aquaculture Production," Natural Resources, Vol. 4 No. 2, 2013, pp. 175-183. doi: 10.4236/nr.2013.42023.


[1] Department of Fisheries Malaysia, “Annual Fisheries Statistics (1987-2007),” 2010.
[2] Government of Malaysia, “Rancangan Malaysia Kesembilan 2006-2010,” Unit Perancang Ekonomi Malaysia, 2010.
[3] EarthTrends AQUASTAT, “Information System on Water and Agriculture Country Profiles,” 2003.
[4] P. J. Pradeep, T. C. Srijaya, H. Anuar, S. Faizah and C. Anil, “The Aquatic Chicken Tilapia and its Future Prospects in Malaysia,” Institute of Tropical Aquaculture, University Malaysia Terengganu, Terengganu. Prospect, Malaysian Premier Higher Education Magazine Times Guides Sdn Bhd, Pelangi Damansara, 2010, pp. 52-56.
[5] W. Enders, “Applied Econometrics Time Series. New Jersey,” John Wiley & Sons Inc., Hoboken, 2003.
[6] M. H. Pesaran and B. Pesaran, “Working with Microfit 4.0 Interactive Econometric Analysis,” Oxford University Press, Oxford, 1997.
[7] R. F. Engle and W. J. Granger, “Cointegration and Error Correction: Representation, Estimation and Testing,” Econometrica, Vol. 55, No. 2, 1987, pp. 251-276. doi:10.2307/1913236
[8] S. Johansen and K. Juselius, “Testing Structural Hypotheses in a Multivariate Cointegration Analysis of the PPP and UIP for UK,” Journal of Econometrica, Vol. 53, No. 1-3, 1992, pp. 211-244. doi:10.1016/0304-4076(92)90086-7
[9] Osterwald-Lenum, “A Note with Quantiles of the Asymptotic Distribution of the Maximum Likelihood Cointegration Rank Test Statistics,” Oxford Bulletin of Economics and Statistics, Vol. 54, No. 3, 1992, pp. 461-472. doi:10.1111/j.1468-0084.1992.tb00013.x
[10] A. Rosilawati, A. H. Shaari, and I. Ismail, “Test on Dynamic Relationship between Financial Development and Growth in Malaysia,” Gadjah Mada International Journal of Business, Vol. 9, No. 1, 2007, pp. 1-17.
[11] C. W. Granger, “Developments in the Study of Cointegrated Variables,” Oxford Bulletin of Economics and Statistics, Vol. 48, No. 3, 1986, pp. 213-227. doi:10.1111/j.1468-0084.1986.mp48003002.x
[12] D. F. Hendry, “Econometric Modeling with Cointegrated variables: An Overview,” Oxford Bulletin of Economics and Statistics, Vol. 48, No. 3, 1986, pp. 201-212. doi:10.1111/j.1468-0084.1986.mp48003001.x
[13] S. Johansen and K. Juselius, “Maximum Likelihood Estimation and Inference on Cointegration with Application to the Demand for Money,” Oxford Bulletin of Economics and Statistics, Vol. 52, No. 2, 1990, pp. 169-210. doi:10.1111/j.1468-0084.1990.mp52002003.x
[14] C. W. Granger, “Investigating Causal Relationships by Econometric Models and Cross-Spectral Methods,” Econometrica, Vol. 37, No. 3, 1969, pp. 424-438. doi:10.2307/1912791

comments powered by Disqus

Copyright © 2018 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.