A Predictive Model for Farmland Purchase/Rent Using Random Forests

초록

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.

키워드

Random ForestsFarmland acquisitionFarm household economic characteristicsdata-driven variable selection
제목
A Predictive Model for Farmland Purchase/Rent Using Random Forests
저자
정호연김영준임소영
DOI
10.24997/kjae.2022.63.3.153
발행일
2022-09
유형
Y
저널명
농업경제연구
63
3
페이지
153 ~ 168