In the real estate market, multi-parametric valuation methods are particularly useful to understand and define all the factors that contribute to the formation of market prices, involving both intrinsic and extrinsic factors. Location is arguably one of the most important (if not the most important) feature the market value of a property depends on. However, other buildings feature also influence the price formation mechanism. In the field of property valuation, this study aims to discuss the contribution of intrinsic versus extrinsic features of the buildings in the assessment of properties' prices. The scope of the study is to examine how, and to what extent, fixed effects determine the best estimate of the market value of a building, especially in comparison to construction characteristics, by means of a multi-parametric econometric analysis. An econometric market value assessment application, in fact, is able to determine the relationship that relates some features describing the property (the independent variables) and its market value (the dependent variable). The marginal appreciation of buildings' characteristics is explored by means of a Random Forest feature selection process and a Multiple Regression analysis. The results of this research also reflect the changes in the real estate market that have occurred in response to anomalous events in recent years, including the COVID-19 pandemic, the War in Ukraine, and the increase in the costs of construction. The analysis is applied for an exemplary case study in Northern Italy.