Markov Chain Analysis- A Discrete Assessment on Livestock Sector Trade in India and Allied Countries

Abstract

Objective/Methods: The research was to analyze the export and import of livestock products (India) to Oman, Afghanistan, Liberia, Maldives, Algeria, Bangladesh, Kuwait, Vietnam, Philippines, Jordon and Saudi Arabia and U.A.E countries through Markov-chain analysis, and to identify the important factors responsible for livestock production. The Markov chain Analysis was employed to analyse the dynamic nature of trade pattern specially the structural changes in any system whose progress through time can be measured in the term of single outcome variable. To accomplish the objective under study the period taken for all livestock products export was 2006-2007 to 2017-2018.
 Findings/Applications: The study on import and export of agricultural commodities revealed a significant benchmark based on Markov chain analysis. The Markov Chain analysis revealed that, India has an edge to export milk products to Algeria, Bangladesh and U.A.E, as indicated by the highest retention probability. In case of egg, export to Oman, Afghanistan, Liberia, Maldives indicated by the highest retention capacity. In case of buffalo meat, export to Vietnam, Philippines, Jordon and Saudi Arabia as indicated by the highest retention probability. In case of sheep meat, export to Saudi Arabia, Oman and Kuwait had the highest retention probability. The multiple linear regression analysis indicated that the factors for milk production (number of buffaloes, Area under permanent Pasture and Grazing land and institutional credit), for meat production (number of animals slaughtered, population of poultry, buffalo, sheep and goat, number of veterinary institutes) and for egg production (Number of layers and number of veterinary institutes) were highly significant to increase the livestock product production.