A Copula-Based Stochastic Frontier Analysis of Thai Jasmine Rice Production in the Northeast of Thailand

Abstract

Thai jasmine rice holds immense economic significance both domestically and as a major export, making it a vital contributor to the Thai economy. Traditional and modern agricultural practices, centered around rice cultivation, play a pivotal role in the culture and economy of the Northeast region. However, concerns have arisen regarding rice production efficiency in recent times due to capital and labor availability challenges. Motivated by these concerns, this study employs a copula-based stochastic frontier modeling (copula-SFM) framework to investigate production efficiency empirically. The research is based on a sample of 384 farmers in the Northeast of Thailand. The Akaike Information Criterion (AIC) is utilized to select the most appropriate model. The results indicate that the Gaussian copula-SFM outperforms other copula models. Notably, the study identifies total area, capital, and labor as critical factors significantly contributing to the positive impact on jasmine rice production. Furthermore, the research ranks provinces based on average technical efficiency (TE) scores, revealing Khon Kaen Province, Yasothon Province, and Roi Et Province as the top-performing regions.