Time series modeling for forecasting the adoption behaviour of shrimp farmers

Abstract

Commercial shrimp culture has emerged as a prominent sector of the coastal economy of India by virtue of the foreign exchange returns, rural employment it generates, and the economic viability of the enterprise and high market demand for the produce. The present study was conducted in Nellore and Nagapattinam districts a/India 10 forecast the adoption a/scientific technologies for a period of 17 years from 2004-2020, by the shrimp farmers using time series statistical modeling. The background data collected from 1997 to 2003 on the adoption behaviour of the farmers formed the database for predicting the adoption behaviour of the technologies. The study revealed that of the two statistical methods employed, namely Holt linear model and Holt exponential smoothing model, the goodness of fit generated by the Holt linear model with an R2 value 0/0.97 exhibited a higher degree of model adequacy over the Holt exponential smoothing model which revealed that in the years 2019 and 2020, the overall extent of adoption exceeded 100 percent which implies the development of new technologies by the research system and its subsequent adoption by the farmers. Besides factors such as changes in demography, demands in the export and local markets would motivate the shrimp fanners in future to adopt more of the improved technologies for getting higher yields.