||Although the hedonic framework can be said to vary substantially from the traditional sales comparison approach used in real estate appraisal in that the former rests on much stronger conceptual grounds than the latter while benefitting from large transaction samples that enable statistical inference, both are derived from a similar paradigm with respect to how prices, hence market values, are determined. While the hedonic approach is much more explicit about the determinants of property values and can provide reliable estimates of individual attributes’ marginal contribution, it may – unlike the sales comparison approach underestimate the prominent influence that surrounding properties exert on any given nearby housing unit and sale price. In this paper, a simple method for reconciling the two approaches is developed within a rigorous conceptual and methodological framework. It is based on peer effect models, an analytical device developed, and mainly used, by labour economists, which we adapt to the hedonic price equation so as to incorporate nearby properties’ influences, thereby controlling for non observable neighbourhood effects. The ensuing model accounts for four types of effects, namely endogenous interactions effects (comparable sales influences), exogenous, or neighbourhood, effects, fixed location effects and, finally, spatial autocorrelation effects. This research relies on a database provided by the former Quebec Urban Community (CUQ) Assessment Division on some 15,700 sales of single-family detached houses that took place on the former CUQ territory between January 1990 and December 1996, with prices ranging from $50,000 (Can.) to $250,000. Preliminary findings suggest that integrating peer effects in the hedonic equation allows bringing out the combined impacts of endogenous, exogenous and spatially correlated effects in the house price determination process, with spatial autocorrelation of model residuals being significantly reduced without resorting to a spatial autoregressive procedure. Further investigation is still needed though in order to find out which sub-market delineation should be used to obtain optimal model performances.