Copula Modeling to Identify the Dependency Structure of Agricultural Production and Its Environment Indicators in Indonesia

Abstract

Agriculture is a very potential field developed in agrarian countries such as Indonesia. The country has abundant natural wealth as a food source for plants. In addition, the natural condition also has an important role on the quality and quantity of agricultural products. This study aims to model dependency structure of rice production and its environment indicators, in this case, includes temperature change, CO₂ emission, and rainfall precipitation, in Indonesia using copula model. We identify the linearity of correlation between variables by comparing Pearson correlation with normality assumption and dependency structure modeled by copula function with any marginal distribution. We analyze and discuss how copula model shows the dependency between variables which cannot be identified by linear correlation.