of India were analyzed by time-series methods. Autocorrelation and partial autocorrelation functions were calculated for the data. The Box Jenkins ARIMA methodology has been used for forecasting. The diagnostic checking has shown that ARIMA (1, 1, 1) is appropriate. The forecasts from 2015-2016 to 2024-2025 were calculated based on the selected model. The forecasting power of autoregressive integrated moving average model was used to forecast tur production for ten leading years. These forecasts would be helpful for the policy makers to foresee ahead of time the future requirements of tur seed, import and/or export and adopt appropriate measures in this regard.

of India were analyzed by time-series methods. Autocorrelation and partial autocorrelation functions were calculated for the data. The Box Jenkins ARIMA methodology has been used for forecasting. The diagnostic checking has shown that ARIMA (1, 1, 1) is appropriate. The forecasts from 2015-2016 to 2019-2020 are calculated based on the selected model. The forecasting power of autoregressive integrated moving average model was used to forecast tobacco production for five leading years. These forecasts would be helpful for the policy makers to foresee ahead of time the future requirements of tobacco production, import and/or export and adopt appropriate measures in this regard.

: This paper has examined the market integration of wheat in Madhya Pradesh. Both market arrivals and prices of wheat have depicted increasing trends in almost all the selected markets of Madhya Pradesh. The present study aimed to study price movement of Wheat i.e. seasonal variation, price volatility and co-integration among the major wheat markets in Madhya Pradesh. For study purpose the data related to monthly average prices and arrivals of Wheat were collected from major markets from different markets in States viz., Bhopal, Gwalior, Indore, and Ujjain for the period 2005-2016. Moving average method used to study seasonal variation. The econometric tools like ADF test, Johansen's multiple co-integration test, Granger Causality Test and ARCH-GARCH model were used to arrive at conclusion. The results of study showed that the prices of wheat were higher in the months from March to August in all selected markets. The cyclical variation observed in the prices of Wheat in the selected markets. For all selected markets the prices series are free from the consequences of unit root and were stationary at first difference. The selected markets show long run equilibrium relationship and co-integration between them. Most of the markets showed bidirectional influence on Wheat prices of each other. Bhopal, Gwalior, Indore and Ujjain recorded low price volatility in wheat prices.

:Soybean is the leading oilseed produced globally. Huge fluctuations in prices of farm produce are observed during past few years. The present study aimed to study price movement of soybean i.e. seasonal variation, price volatility and co-integration among the major soybean markets in Madhya Pradesh. For study purpose the data related to monthly average prices and arrivals of soybean were collected from major markets from different markets in States viz., Betul, Dewas, Dhar and Indore for the period 2005-2016. Moving average method used to study seasonal variation. The econometric tools like ADF test, Johansen's Multiple Co-integration test, Granger Causality Test and ARCH-GARCH model were used to arrive at conclusion. The results of study showed that the prices of soybean were higher in the months from June to August in all selected markets. The cyclical variation observed in the prices of soybean in the selected markets. For all selected markets the prices series are free from the consequences of unit root and were stationary at first difference. The selected markets show long run equilibrium relationship and co-integration between them. Most of the markets showed bidirectional influence on soybean prices of each other. Betul, Dewas, Dhar, and Indore, recorded low price volatility in soybean prices.