Beyond Labels: A Spatial Proximity Model for Detecting Misclassified Equipment Status on Residential Land

Land administration databases are central to property taxation, urban planning and development finance, yet the reliability of their records is rarely examined closely. This study analyses valuation inversion, a mismatch in which the land readiness categories recorded in the national transaction register contradict the expected price hierarchy, in the Ljubljana Urban Region, Slovenia. The analysis draws on 735 valid land transactions across four Market Analytical Areas of the Slovenian mass appraisal system. Under the recorded categories, parcels with a building permit, the highest readiness category, carried no significant price premium over partly equipped or non-equipped parcels and sold on average 12–17% below parcels recorded as equipped, even within the same municipality, while the recorded equipped category implied a premium of only 18–24%. A spatial proximity scoring model was developed to reclassify cadastral parcels based on measured distances to water supply, sewerage, electricity and road infrastructure. After reclassification, land within connectable distance of all four networks achieved on average 46.1% higher prices than partly or non-equipped land (unweighted mean of the four areas). In hedonic models controlling for location, plot size, slope and transaction year, the premium was 48–76%, and it remained significant under alternative scoring thresholds and distance bands and for the most recent sales. Once infrastructure is accounted for, the price gap between permit-labelled and equipped parcels is roughly halved and no longer significant. These findings indicate that valuation models relying solely on recorded readiness classifications may introduce systematic bias into mass appraisal systems. Spatial proximity scoring offers a scalable approach to screening the infrastructure component of land readiness records, with implications for automated valuation models, property tax equity and infrastructure investment planning.