Volume 5, Issue 2, March 2020, Page: 43-48
A Bayesian Approach to Evaluating the Dynamics of Rice Production in Madagascar
Finaritra Solomampionona Maminirivo, Department of Agricultural Economics, Obihiro University of Agriculture and Veterinary Medicine, Obihiro-Hokkaido, Japan
Koki Kyo, Faculty of Management and Information Science, Niigata University of Management, Kamo-Niigata, Japan
Received: Feb. 25, 2020;       Accepted: Mar. 17, 2020;       Published: Apr. 28, 2020
DOI: 10.11648/j.ijae.20200502.12      View  204      Downloads  118
Abstract
In Madagascar, domestic rice production does not meet the local demand. Thus, increasing productivity is crucial for ensuring food security for a booming population. The last two decades have been marked by technological improvements in support of a vision of agricultural development. The main objective of the present study is to evaluate rice productivity in Madagascar based on changes in technology and the planted area during the period from 1961 to 2017. To conduct our analysis, we construct a set of statistical models involving time-varying parameters that capture the changes in productivity and progress in rice production technology. To estimate these time-varying parameters, we apply Bayesian methods based on the smoothness prior approach. The estimates for variances in system noise show that the proposed model is well fitted to the data. In addition, the results provide the interesting finding that technological change is estimated to be elastic, with values increasing from 1 to 8 during the six decades of the study period. However, the planted area estimates are inelastic, despite positive values fluctuating around 0.9–1. Thus, rice productivity in Madagascar is highly dependent on technology, although more time is required before a positive response is seen.
Keywords
Rice Productivity, Madagascar, Bayesian Statistical Modeling, State–space, Kalman Filter
To cite this article
Finaritra Solomampionona Maminirivo, Koki Kyo, A Bayesian Approach to Evaluating the Dynamics of Rice Production in Madagascar, International Journal of Agricultural Economics. Vol. 5, No. 2, 2020, pp. 43-48. doi: 10.11648/j.ijae.20200502.12
Copyright
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Reference
[1]
Chauvin N. D., Porto G., and Mulangu F., 2017. Agricultural Supply Chains, Growth and Poverty in Sub-Saharan Africa: Market Structure, Farm Constraints and Grass-root Institutions. Chapter 8: The case of Madagascar. Springer, Advances in African Economic, Social and Political Development. 195p, p 143-149. Doi: 10.1007/978-3-662-53858-6
[2]
Maret F., 2007. Distortions to Agricultural Incentives in Madagascar. George Washington University, Agricultural Distortions Working Paper 53. 50p.
[3]
MAEP (Ministère de l`Agriculture, de l`Elevage et de la Pêche à Madagascar), 2019. Système de production des statistiques sur les coûts de production agricole à Madagascar test sur le riz, le manioc, le café et la vanille. Global Strategy improving Agricultural and Rural Statistics, African Development Bank, European Union. 124p.
[4]
INSTAT (Institut National de Statistique Madagascar), 2019. Troisième Recensement General de la Population et de l`habitation (RGPH-3).
[5]
Hume D. W., 2009. Vary Gasy: Folk Models of Rice and Implications for Agricultural Development in Eastern Madagascar. Etudes Ocean Indien. Open Editions Journal 42-43. 12p. Doi: 10.4000/oceanindien.812
[6]
Balasubramanian V., Sie M., Hijmans R. J. and Otsuka K., 2007. Increasing rice production in Sub-Saharan Africa: Challenges and Opportunities. Elsevier, Advances in Agronomy 94, p 55-133. Doi: 10.1016/S0065-2113(06)94002-4
[7]
Saito K., Dieng I., Toure A. A., Somado E. A. and Wopereis M. C. S., 2015. Rice yield growth analysis for 24 African countries over 1960–2012. Elsevier, Global food security 5: p 62-69. Doi: 10.1016/j.gfs.2014.10.006
[8]
Varma P., 2017. Rice productivity and food security in India: A study of the Rice system Intensification. Springer. Centre for Management in Agriculture (CMA), N°250. Indian Institute of Management Ahmedabad (IIMA). Doi: 10.1007/978-981-10-3692-7
[9]
Bhagirath S. C., Khawar J., and Gulshan M., 2017. Rice Production Worldwide. Springer International Publishing. 561p. Doi: 10.1007/978-3-319-47516-5.
[10]
Ploch L. and Cook N., 2012. Madagascar`s political crisis: the impact of the political crisis on the economy. Congressional Research Service Report. P 14-16.
[11]
The World Bank, 2013. Madagascar: Measuring the Impact of the Political Crisis. https://www.worldbank.org/en/news/feature/2013/06/05/madagascar-measuring-the-impact-of-the-political-crisis.
[12]
Razafindrakoto M., Roubaud F., and Wachsberger J. M., 2018. The puzzle of Madagascar’s economic collapse through the lens of social sciences. La lettre d`information de DIAL, Developpement Institution et Mondialisation. 12p.
[13]
FEWSNET, 2018. Madagascar food security outlook, Poor harvests will result in a harder lean season in Southeastern Madagascar. USAID. 13p.
[14]
Jin H. and Jorgenson, 2010. Econometric modeling of technical change. Elsevier, Journal of Econometrics. P 205-209. Doi: 10.1016/j.jeconom.2009.12.002
[15]
Kyo K., Noda H., and Kitagawa G., 2013. Bayesian analysis of unemployment dynamics in Japan. Asian Journal of Management Science and Applications, Vol. 1, No. 1. P 4-25. Doi: 10.1504/AJMSA.2013.056005
[16]
Kitagawa G. and Gersh W., 1996. Smoothness Priors Analysis of Time Series. Springer, New York.
[17]
Kitagawa G., 2010. Introduction to time series modeling. CRC Press, New York
[18]
Inglesi-Lotz R., 2011. The evolution of price elasticity of electricity demand in South Africa: A Kalman filter application. Elsevier, Energy Policy. Doi: 10.1016/j.enpol.2011.03.078
[19]
Tesfahun Berhane, Nurilign Shibabaw, Aemiro Shibabaw, Molagin Adam, and Abera A. Muhamed, 2018. Forecasting the Ethiopian Coffee Price Using Kalman Filtering Algorithm. Journal of ressources ecology, 9 (3): 302–305. Doi: 10.5814/j.issn.1674-764x.2018.03.010
[20]
Chansu L., 2019. Estimating residential and industrial city gas demand function in the Republic of Korea – A Kalman Filter application. MDPI, Sustainability. 12p. Doi: 10.3390/su11051363.
[21]
Fernando V. G., Tomas M. M., and Juan M. L., 2015. Dynamical approach for real-time monitoring of Agricultural Crops. IEE Geosience and Remote sensing. Doi: 10.1109/TGRS.2014237.
[22]
Afsharia, Gadsdenb, and Habibia, 2017. Gaussian filters for parameter and state estimation: A general review of theory and recent trends. Elsevier Signal Processing 135, p 218–238. doi: 10.1016/j.sigpro.2017.01.001.
[23]
Katzfuss M., Stroudb J. R., and Wikle C. K., 2016. Understanding the Ensemble Kalman Filter. The American Statistician. Taylor and Francis Group. Volume 70, p 350-357.
[24]
Kalman R. E., 1960. A New Approach to Linear Filtering and Prediction Problems. Transactions of the ASME–Journal of Basic Engineering, 82 (Series D), p 35–45.
[25]
Kyo K., and Noda H., 2016. Correspondence between Turning Points in Trend of Oil Price and Business Cycles in Japan, Proceedings of 2nd International Conference on Sustainable Development. Atlantis Press, Advances in Engineering Research, volume 94. P 388-396.
[26]
Hoeffler H., 2011. The Political Economy of Agricultural Policies in Africa: History, Analytical Concepts and Implications for Development Cooperation. Quarterly Journal of International Agriculture 50. P 29-53.
[27]
Ssozi J., Asongu S. A., and Amavilah V., 2018. The Effectiveness of Development Aid for Agriculture in Sub-Saharan Africa. African Governance and Development Institute. Munich Personal RePEc Archive Paper No. 88530. P 48.
[28]
Barrett, 1994. Understanding Uneven Agricultural Liberalisation in Madagascar. Cambridge University Press, the journal of modern African studies n°32, p 449-476.
[29]
Randrianarisoa J. C., and Minten B., 2001. Agricultural Production, Agricultural Land and Rural Poverty in Madagascar. Ilo Program, Cornell University. 46p.
[30]
Penot E., Dabat M. H., Rakotoarimanana A., and Grandjean P., 2014. L’évolution des pratiques agricoles au lac Alaotra à Madagascar. Une approche par les temporalités. Biotechnology Agronomy Social Environnemental Journal. V8 (3), p 329-338.
[31]
Liu P., Koroma S., Arias P., and Hallam D., 2013. Trends and impacts of foreign investment in developing country agriculture: evidence from case studies. Food and Agriculture Organization of the United Nations. 382p.
[32]
Moser C., and Barrett, 2006. The complex dynamics of smallholder technology adoption: the case of SRI in Madagascar. IAAE, Agricultural Economics n°35, p 373-388. Doi: 10.1111/j.1574-0862.2006.00169.x
[33]
Dabat M., Jenn-Treyer O., Grandjean P., Vallois P., Du Portal D., and Chalvin A.; 2008. Innovation technique et réduction de la pauvreté à Madagascar: débat revisité sur la pertinence du système de riziculture intensive. MAEP Madagascar, Agence Française pour le Développement. Document de travail BV lac n° 6. 29p.
[34]
Serpentie G., 2017. Le système de riziculture intensive ou « SRI » à Madagascar. Entre légende urbaine et innovation rurale. Anthropologie et Développement. Open Editions Journal n°16-17, p 67-99. Doi: 10.4000/anthropodev.588
[35]
Minten B. and Barrett C., 2008. Agricultural Technology, Productivity, and Poverty in Madagascar. Elsevier, World Development Vol. 36, No. 5, p. 797–822. Doi: 10.1016/j.worlddev.2007.05.004
[36]
Harvey C. A., Rakotobe Z. L., Rao N. S., Dave R., Razafimahatratra H., Rabarijohn R. H., Rajaofara H., and MacKinnon J. L., 2014. Extreme vulnerability of smallholder farmers to agricultural risks and climate change in Madagascar. Philosophical Transactions of the Royal Society. B369: 20130089. 12p. Doi: 10.1098/rstb.2013.0089
[37]
Minten B., Dorosh P., Dabat M. H., Jenn-Treyer O., and Magnay J., Razafintsalama Z., 2006. Rice markets in Madagascar in disarray: Policy options for increased efficiency and price stabilization. Washington, World Bank. Africa Region Working Paper Series No. 101, cirad-00773025f. 77p.
[38]
FAO, 2016. More effective and sustainable investments in water for poverty reduction. Water for the rural poor, Agricultural Water Management Investment Project. http://www.fao.org/in-action/water-for-poverty-in-africa/countries/madagascar
Browse journals by subject