Measuring technical efficiency of dry-season rice farming using a stochastic frontier approach: evidence from Dilem Village, Malang, Indonesia
DOI:
https://doi.org/10.33474/jase.v6i2.24380Keywords:
dilem;, technical efficiency;, dry season;, Hapless;, RiceAbstract
Rice farming in Indonesia is strongly influenced by seasonal conditions, particularly the contrast between the rainy and dry seasons. Climate change has altered the timing and patterns of these seasons, with the dry season becoming shorter and more irregular, affecting input utilization and the technical efficiency of rice farming. This study aims to analyze the production factors influencing rice output, estimate technical efficiency levels, and identify the determinants of technical efficiency in dry-season rice farming. A quantitative approach was employed using a Stochastic Production Frontier (SPF) model to estimate technical efficiency, while a Tobit regression model was applied to examine factors influencing efficiency levels. The study used primary data collected from 93 rice farmers selected by random sampling. The empirical results indicate that land area, seed, and urea fertilizer have a positive and significant effect on rice production during the dry season. The estimated mean technical efficiency score of 0.792 suggests that rice farmers operate at a relatively efficient level, although there remains potential to improve efficiency through better input management further. Furthermore, farming experience and farmers’ participation in agricultural extension and training programs were found to positively and significantly influence technical efficiency. These findings imply that effective management of production inputs and human capital development are important for enhancing efficiency in dry-season rice farming. Therefore, strengthening agricultural extension services and promoting continuous learning and technology adoption among farmers are essential to improve the overall efficiency and productivity of rice farming systems under changing climatic conditions.
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