The increase in farmland prices in many parts of the world over the past decade has sparked discussions about whether non-farmers pay higher prices for farmland. This study uses a causal machine learning approach with a rich data set of land transactions in Germany to quantify the potential price premium paid by non-farmers. By applying the causal forest method, we uncover the heterogeneity of price premiums and reveal moderating effects of covariates. We find that the average positive price premium by non-farmers decreases with parcel size and distance to a highway exit.

中文翻译：

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非农民比农民花更多的土地费用吗？


过去十年来，世界许多地方的农地价格上涨引发了关于非农民是否为农田支付更高价格的讨论。本研究使用因果机器学习方法和丰富的德国土地交易数据集来量化非农民支付的潜在价格溢价。通过应用因果森林法，我们揭示了价格溢价的异质性并揭示了协变量的调节作用。我们发现，非农民的平均正价格溢价随着地块大小和到高速公路出口的距离而降低。