MSc

The research entitled “Time Series modelling for comparative performance and influencing factors of production on paddy and coconut in South India” was conducted with the objective of developing statistical models on trend in area, production and productivity of paddy and coconut across Kerala, Karnataka and Tamil Nadu and to develop different statistical models for analysing the price movement of these crops across the states overtime and to develop models for analysing the influencing factors of production. Secondary data regarding area, production, productivity and rainfall were collected for a period of past 25 years from Directorate of Economics and Statistics (Govt. of Karnataka), Department of Economics and Statistics (Govt. of Kerala and Tamil Nadu) and Coconut Development Board. Secondary data on price was collected for major markets of paddy (Thanjavur and Raichur) and copra (Kochi, Kangayam and Tumkur) from indiastat and Agmarknet.
Trend analysis was used to understand the trends in area, production and productivity using different linear and nonlinear growth models. Compound Annual Growth Rate (CAGR) was estimated using exponential model to compare the performance in area, production and productivity of paddy and coconut in South India. Johansen’s co-integration technique was used to understand the price movement in the markets across the states for price of paddy and copra. Panel data regression analysis was done to identify the climatic variables that influence the production of paddy and coconut.
From trend analysis, the best model was selected based on adj. R2, criteria of randomness, normality and Root Mean Square Error (RMSE). In paddy, quadratic model was found to be the best fitted model for area and production in Karnataka, production and productivity in Kerala and area in Tamil Nadu. Cubic model was found to be the best model for area in Kerala, productivity in Tamil Nadu and power model for productivity in Karnataka and compound model for production in Tamil Nadu. In case of coconut, quadratic model was found to be the best fitted model for area, production and productivity in Karnataka and area and productivity in Tamil Nadu. Cubic model was found to be the best model for area, production and productivity in Kerala and production in Tamil Nadu.
Comparative performance of paddy and coconut in Southern states was compared based on CAGR for a period from 1987-2017. CAGR revealed that production (1.1%) and productivity (1.0%) of paddy in Karnataka and productivity (1.5%) in Kerala was found to be positive and significant. Area (-4.5%) and production (-3.0%) of paddy in Kerala and area (-0.7%) in Tamil Nadu was found to be negative and significant. In case of coconut, positive and significant CAGR was noticed for area, production and productivity in Karnataka and Tamil Nadu and production (1.4%) and productivity (2.0%) in Kerala where as a declining trend in area (-0.6%) was noticed in Kerala.
Stationarity is the prime requirement for co-integration analysis of price of paddy and coconut in various markets and it was tested using Augmented Dickey Fuller test (ADF). The results of ADF test indicated that price of paddy in Thanjavur (TN) and Raichur (Karnataka) markets and price of copra in Kochi (Kerala), Kangayam (TN) and Tumkur (Karnataka) markets were stationary after taking the first difference which suggested that all the price series were integrated of order one I(1). The result of Johansen’s co-integration test revealed that monthly wholesale price of paddy in Thanjavur and Raichur markets were co-integrated. Similarly price of copra in Kochi (Kerala), Kangayam (TN) and Tumkur (Karnataka) markets was also co-integrated which means that price in different markets are moving together. Granger Causality test was applied to find the direction of causality from one market to another and it revealed that there was a bidirectional influence in Thanjavur and Raichur market price of paddy. In case of copra, there was a bidirectional influence between Kochi and Kangayam market price and unidirectional influence on prices of Kochi and Tumkur.

The effect of climatic factors on production was analysed using panel data regression with fixed effect model suggests that average rainfall during Q3 (July - September) and Q4 (October - December) had a positive and significant effect on production of paddy. In case of coconut, previous year average rainfall during Q1t-1 (January - March) and Q4t-1 (October - December) had a positive and significant influence on production of coconut.
Trend in area, production and productivity was well explained by cubic and quadratic model for paddy and coconut with high adj R2 and least RMSE. CAGR of productivity of paddy in three South Indian states has shown a positive trend but there was a declining trend in area under paddy in Kerala and Tamil Nadu. There was a significant positive growth rate in area, production and productivity of coconut in Karnataka and Tamil Nadu and production and productivity in Kerala. However, the productivity in Tamil Nadu (14251 nuts ha-1) and Karnataka (13181 nuts ha-1) was far ahead as compared to that of Kerala (9664 nuts ha-1). The monthly wholesale price of paddy in Thanjavur and Raichur markets and price of copra in Kochi, Kangayam and Tumkur markets were co-integrated which indicates that any price change in one market influence the price in other markets. Production of paddy was influenced by Q3 (July - September) and Q4 (October - December) rainfall, in case of coconut, production was influenced by previous year average rainfall during Q1t-1 (January - March) and Q4t-1 (October - December).