MSc

The present investigations, time series modeling and forecasting of the yield of cashew in kerala was undertaken with the following objectives.

1. To formulate a suitable model for the forecast of production of cashew crop in Kerala
2. To work out the major determinants of yield variations.


For this purpose, secondary data were collected from the Directorate of economics and statistics, Government of Kerala , Thiruvananthapuram for a period of thirtyseven years starting from the year 1956-57. The data on average, production , productivity price of raw cashew kernel and annual rainfall were collected. The stochastic models viz. Box -Jenkins model, distributed lad model, log normal diffusion model and markov chain model were tried on the time series.

Univariate ARIMA models of all the variables were considered separately, Diagnosis checking was done to ascertain the adequacy of the model. Then the fitted models were used to obtain the sample period and post sample period forecasts. To judge the forecasting ability of the model the Mean absolute percentage error (MAPE)was calculated. The results showed that the univariate ARIMA models offered a good technique for predicting the magnitude of all the variables. Cross correlation analysis of the series was done with yield as the dependent variable and area price and rainfall as the independent variables. But the results were not in favour of trying a transfer function model.

Distributed lag models of varying types involving selected exogeneous variables were developed. The area response models had lagged area, price risk, lagged price and lagged rainfall as the explanatory variables while yield response function. The result of the analysis clearly indicated that area was not responsive to prices. Cashew growers are least sensitive to price movements and they prefer to grow the crop in all types of soil due to its wide adaptability and ease of management. The coefficient of determination of all functions were relatively high indicating that the proposed models were satisfactory in describing yield and acreage fluctuations.

The log normal diffusion model was fitted to the data on production of cashew in Kerala. It was found that the model gave a satisfactory fit to the data. Yield forecasts for the period from 1997 to 1999 were obtained using the model .

A four state Markov chain model was used to represent the time series distribution of production. The four states of the model were identified based on the qualities of the series and a transition probability matrix was calculated. Equilibrium probabilities were estimated. It was found that the yields reached equilibrium position after twenty years. The steady state probabilities were estimated and used to forecast the production .