A strategy for incorporating higher-frequency determinants of inefficiency into the stochastic frontier models with production function indicators compiled at lower frequencies is proposed. Furthermore, the problem with positive skewness in stochastic frontier models is resolved by postulating a logistic function for the inefficiency equation and refraining from assuming a more complicated distribution of the inefficiency term. High frequency determinants are incorporated into the inefficiency equation in a nonparametric function. The model is estimated with hybrid methods in a backfitting algorithm instead of maximum likelihood estimation (MLE), which typically struggles with convergence issues and is vulnerable to distributional assumptions. The model is then used to characterize the linkage between firm efficiency and extreme weather events using data from electric cooperatives in the Philippines. This provides an approach to assess micro level sustainability issues from extreme weather arising events from climate change.

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