Abstract

PurposeThis paper aims to analyze the heuristics and cognitive biases described by behavioral finance in the investment decision-making process of Portugal’s housing market.Design/methodology/approachIn a first step, the authors applied an exploratory factor analysis (EFA) to assess the impact of heuristics and cognitive biases on investors’ decision-making. In a second step, the authors run a structural equation model (SEM) diagram path to assess if the sociodemographic characteristics of housing market investors determine the identified heuristics and if the heuristics condition the investors’ investment criteria.FindingsHerd behavior and the heuristics of representativeness, availability and anchoring influence the housing market’s investors’ behavior in their decision-making process. Investors with above-average income show higher levels of overconfidence. Investors showing higher levels of overconfidence also tend to be more sensitive to the house price under analysis for investment. Women tend to show higher levels of the availability and anchoring heuristic. In turn, housing market investors showing higher levels of availability and anchoring heuristic tend to be more sensitive to the price and location of the house under analysis for investment.Research limitations/implicationsThe explained variance of the EFA is below 50%, and the root mean square of approximation of the SEM is above the threshold of 0.05. These indicators are evidence of the models’ fragility.Practical implicationsGovernments and regulators can better prevent real estate bubbles if they monitor behavioral biases and heuristics of housing investors together with quantitative indicators. Realtors can profit from adapting their marketing strategy and commercial communication to investors of sociodemographic groups more prone to a specific type of heuristics.Originality/valueTo the best of the authors’ knowledge, this is the first study that combines the contributions of behavioral finance with Portugal’s housing investment market and the first study connecting heuristics to investment criteria.

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