Price Volatility of Agricultural Products: Evidence From Producer Fruits Price in Batu Municipality, Indonesia

This paper attempts to investigate the price volatility of fruits with higher economic values, which are avocado, apple, guava, banana, and jackfruit, and analyzes the long-term and short-term period relationship between production and prices of these fruits. The data used are the quarterly productions and prices of avocado, apple, guava, banana, and jackfruit on the producer level for 2012 to 2020 obtained from Agriculture office of Batu Municipality. The volatility evaluation was using the ARCH/GARCH. The long-term relationship was analyzed using the Johansen cointegration test, and the short-term relationship used the Error Corection Mechanism (ECM). The results of the volatility analysis confirmed that every fruit studied had a low volatility rate. In addition, the productions and prices of the commodities studied had been cointegrated in the long-run; however only avocado, guava, and apple have a short-run relationship. The government is suggested to provide price and production information systems to ensure farmers' market access. Keywords: price volatility, fruits, ARCH/GARCH, cointegration, EC

Information criteria for non-normalized models

Many statistical models are given in the form of non-normalized densities with an intractable normalization constant. Since maximum likelihood estimation is computationally intensive for these models, several estimation methods have been developed which do not require explicit computation of the normalization constant, such as noise contrastive estimation (NCE) and score matching. However, model selection methods for general non normalized models have not been proposed so far. In this study, we develop information criteria for non-normalized models estimated by NCE or score matching. They are approximately unbiased estimators of discrepancy measures for non-normalized models. Simulation results and applications to real data demonstrate that the proposed criteria enable selection of the appropriate non-normalized model in a data-driven manner.Peer reviewe