Crude oil futures to manage the price risk of natural rubber: Empirical evidence from India | Kepulaje Abhaya Kumar, Prakash Pinto, Iqbal Thonse Hawaldar, Cristi Spulbar, Ramona Birau | Agricultural Journals

This study aims at developing econometric models to manage the price risk of Dry and Wet Cocoa beans with the help of ARIMA (Autoregressive Integrated Moving Average) and VAR (Vector Auto Regressive). The monthly price of Cocoa beans is collected for the period starting from April 2009 to March 2020 from the office of CAMPCO Limited, Mangalore, and the ICE Cocoa futures price from the website of investing.com. The augmented dickey fuller test is used to test the stationarity of the series. The ACF and PACF correlograms are used to identify the tentative ARIMA model. Akaike information criterion (AIC) and Schwarz criterion (SBIC), Sigma square, and adjusted R² are used to decide on the optional AR and MA terms for the models. Durbin–Watson statistics and correlograms of the residuals are used to decide on the model’s goodness of fit. Identified optimal models were ARIMA (1, 1, 0) for the Dry Cocoa beans price series and ARIMA (1, 1, 2) for the Wet Cocoa beans price series. The multivariate VAR (1) model found that the US and London Cocoa futures prices traded on the ICE platform will influence the price of Dry Cocoa in India. This study will be helpful to forecast the price of Cocoa beans to manage the price risk, precisely for Cocoa traders, Chocolate manufacturers, Cocoa growers, and the government for planning and decision-making purposes.

Many studies have stated that the usage of traditional cooking fuels like firewood, dung, and coal has caused many unfortunate deaths in India. The alternative fuel sources like LPG and electricity are in scarce and. Today, researches in the area of biofuel or bioenergy are of prime interest to many researchers to contribute to sustainable energy sources. Bioenergy from cattle dung is one such area, particularly for a country like India where dairy farms is a major supplier of feedstock. In this study, using logistic regression methodology, we have analysed the socio-economic factors influencing the adoption of biogas digesters among dairy farmers in Karnataka, India. The study revealed that the number of cattle and family size are the key factors for biogas adoption and poor knowledge of the family size and cattle ratio is the key hurdle. Using cross-tabulation and some basic mathematical analysis, we concluded that the optimal number of cattle for one adult in a family is 1. Keywords: Sustainable energy source, Biogas, Cattle dung, Dairy farmers, Socioeconomic factors, India JEL Classifications: Q4, P28 DOI: https://doi.org/10.32479/ijeep.10135