Critical issues and advances in applying the sales comparison approach for real estate appraisal

The article examines the methodological foundations, opportunities, and limitations of the Sales Comparison Approach (SCA) within contemporary real estate valuation. While the SCA is widely regarded as the most market-oriented and theoretically consistent method for estimating market value, its practical application raises significant issues related to data quality, comparability, and the subjectivity of price adjustments.The study adopts a mixed conceptual and empirical approach. First, it develops a critical analysis of the SCA grounded in appraisal theory and international valuation standards, with particular attention to its epistemological consistency and operational requirements. Second, it presents an illustrative case study based on a residential property in Rome, applying the SCA to a set of comparable transactions selected within the year preceding the valuation date. This empirical application demonstrates the operational logic of the method and highlights key sources of uncertainty in real-world contexts.The results show that, despite its strong theoretical consistency with the definition of market value, the SCA is highly sensitive to data availability, market transparency, and methodological choices made by the valuer. In particular, the empirical application reveals the significant impact of adjustment assumptions—kept within a controlled range—and comparable selection on final value estimates, confirming the presence of an irreducible degree of subjectivity. At the same time, the convergence of adjusted prices within a limited range suggests that careful calibration of parameters can enhance the internal coherence of the procedure. The article contributes to the literature by proposing a non-dogmatic interpretation of the SCA as a structured yet flexible framework, rather than an inherently objective method. It also highlights the specific challenges associated with its application in information-constrained markets, such as the Italian context, and emphasises the need for greater integration with quantitative tools, improved data transparency, and more standardised adjustment criteria.