Acta Univ. Agric. Silvic. Mendelianae Brun. 2017, 65(2), 679-688 | DOI: 10.11118/actaun201765020679

Asian Countries in the Global Rice Market

Vladimir Milovanovic, Luboš Smutka
Facultry of Economics and Management, Czech University of Life Sciences Prague, Kamycka 129, 165 21 Prague, Czech Republic

Rice is an important Asian commodity, a region with diverse production systems and consumption patterns. With an increasing population leading to an increase in demand, the main drivers which determine rice production need to be identified. The study thus attempts to identify and assess the key drivers of rice production and the future prospects in major rice producing countries within the region using simple and stepwise multiple linear regression. In most of the countries, rice production was found to be determined by indicators such as yield, country consumption and country population, each accounting for about 90 percent of variation in rice production. Among the mentioned indicators, country population should be given the most weight to as majority of rice is consumed by humans, thus validating the need to address the necessity to enhance rice production that commensurate with an increasing population.

Keywords: rice production, Asia, determinants of rice production
Grants and funding:

The project was realized with the support of the Internal Grant Agency of the Faculty of Economics and Management, Czech University of Life Sciences Prague (20171018 - Aging in rural India: Implications for agriculture and smallholder farmers).

Prepublished online: April 30, 2017; Published: May 1, 2017  Show citation

ACS AIP APA ASA Harvard Chicago IEEE ISO690 MLA NLM Turabian Vancouver
Milovanovic, V., & Smutka, L. (2017). Asian Countries in the Global Rice Market. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis65(2), 679-688. doi: 10.11118/actaun201765020679
Download citation

References

  1. BELIA, S., FIDLER, F., WILLIAMS, J. and CUMMING, G. 2005. Researchers misunderstand confidence intervals and standard error bars. Psychological Methods, 10(4): 389 - 396. DOI: 10.1037/1082-989X.10.4.389 Go to original source...
  2. BERRY, W. D. and FELDMAN, S. 1985. Multiple regression in practice. Thousand Oaks: SAGE Publications. Go to original source...
  3. CHATTERJEE, S. and SIMONOFF, J.S. 2013. Handbook of regression analysis. New Jersey: Wiley. Go to original source...
  4. CSU. 2015. Research methods: Multiple regression. [Online] Long Beach: California State University. Available at: http://web.csulb.edu/~msaintg/ppa696/696regmx.htm. [Accessed: 2016, September 09].
  5. FOOD AND AGRICULTURE ORGANIZATION OF UNITED NATIONS (FAO). 2000. Bridging the rice yield gap in the Asia-Pacific region. [Online] Rome: Food and Agriculture Organization of the United Nations. Available at: http://www.fao.org/docrep/003/x6905e/x6905e00.htm#Contents. [Accessed: 2016, May 17].
  6. FOOD AND AGRICULTURE ORGANIZATION OF UNITED NATIONS (FAO). 2016. Statistical database. [online] Rome: Food and Agriculture Organization of the United Nations. Available at: http://faostat3.fao.org/home/E. [Accessed 2016, August 24].
  7. ISSAR, A. and VARMA, P. 2016. Are Indian rice exporters able to price discriminate? Empirical evidence for basmati and non-basmati rice. Applied economics, 48(60): 5897 - 5908. DOI: 10.1080/00036846.2016.1186798 Go to original source...
  8. LI, X., LIU, N., YOU, L., KE, X., LIU, H., HUANG, M. and WADDINGTON, S. R. 2016. Patterns of cereal yield growth across China from 1980 to 2010 and their implications for food production and food security. PLOS ONE, 11(7): e0159061. DOI: 10.1371/journal.pone.0159061 Go to original source...
  9. MAITAH, M., REZBOVA, H., SMUTKA, L. and TOMSIK, K. European sugar production and its control in the world market. Sugar Tech, 18(3): 236 - 241. DOI: 10.1007/s12355-016-0439-9
  10. NCSS. 2015. Stepwise regression. [Online]. Available at: http://ncss.wpengine.netdna-cdn.com/wp-content/themes/ncss/pdf/Procedures/NCSS/Stepwise_Regression.pdf. [Accessed: 2016, August 25].
  11. RUTHERFORD, A. 2001. Introducing ANOVA and ANCOVA: A GLM approach. London: SAGE Publications.
  12. SHERMAN, R., DANIEL, M. D., SHAHNILA, I., NICOLA, C., BERNARDO, C., ARTHUR, G., GUY, H., ULRICH, K., KHONDOKER, M., SWAMIKANNU, N., RICHARD, D. R., MARK, W. R., GBEGBELEGBE, S., TIMOTHY, B. S. and KEITH, D. W. 2015. Climate change adaptation in agriculture: Ex ante analysis of promising and alternative crop technologies using DSSAT and IMPACT. IFPRI Discussion Paper 1469. [Online]. Washington, D.C.: International Food Policy Research Institute (IFPRI). Available at: http://ebrary.ifpri.org/cdm/ref/collection/p15738coll2/id/129694. [Accessed: 2016, July 07].
  13. STIGLER, S.M. 1989. Francis Galton's account of the invention of correlation. Statistical Science, 4(2): 73 - 79. DOI: 10.1214/ss/1177012580 Go to original source...
  14. THE WORLD BANK (WB). 2008. Myanmar: Capitalizing on rice export opportunities. [Online] Washington, D.C.: The World Bank. Available at: http://documents.worldbank.org/curated/en/570771468323340471/Myanmar-Capitalizing-on-rice-export-opportunities. [Accessed: 2016, September 28].
  15. UNITED NATIONS (UN). 2016. Member states. [Online]. New York: United Nations. Available at: http://www.un.org/en/member-states/index.html. [Accessed: 2016, July 20].

This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY NC ND 4.0), which permits non-comercial use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.