Block pricing is widespread among electricity and water utilities to protect lowincome households and to encourage energy conservation through higher marginal prices. However, whether a block pricing system achieves those objectives is controversial. In this article, we analyze the impact of alternative electricity pricing systems on the welfare of consumers for the case of residential electricity block pricing in Korea. To do this, we first develop a theoretical model to compute each household's welfare change under alternative pricing systems. Then, we estimate the residential electricity demand function and compute every household's electricity consumption and expenses under alternative pricing systems. Finally, we compute each household's welfare change and social welfare to draw policy implications.

This study contributes to guidance for understanding farmland purchase and rent decisions in Korea via an analysis using a machine learning tool, Random Forests: A Supervised Machine Learning Algorithm. Farm Household Economy Survey is employed to predict the relationship between farmland acquisition and farm household economic characteristics. Our main findings are two folds. First, a farmland purchase decision is positively related to transfer incomes, the value of inventory & fixed assets, and the value of farmland that farmers owned. Second, a farmland rent decision is also positively associated with a rent paid in a prior year, revenue from field crops, inventory and agricultural assets, and transfer incomes.

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