Hedonic Price

Hedonic pricing models aim to quantify the value of goods and services by decomposing their price into the value of their individual attributes. Recent research heavily emphasizes leveraging machine learning, particularly deep learning architectures like convolutional neural networks (CNNs) and transformers, to extract features from unstructured data such as images and text descriptions, significantly improving the accuracy of price estimations. This integration of AI techniques enhances the precision of hedonic price indices, with applications ranging from real estate valuation to inflation tracking and the creation of more accurate quality-adjusted price indices. The resulting improvements in predictive power have significant implications for economic analysis and market forecasting.