The growing empirical literature testing informational efficiency of real estate markets uses data from various contexts and at different levels of aggregation. The results of these studies are mixed. We use a distinctive meta-analysis to examine whether some of these study characteristics and contexts lead to a significantly higher chance for identification of an efficient real estate market. The results generated through meta-regression suggest that use of stock market data and individual level data, rather than aggregate data, significantly improves the probability of a study concluding efficiency. Additionally, the findings neither provide support for the suspicion that the view of market efficiency has significantly changed over the years nor do they indicate a publication bias resulting from such a view. The statistical insignificance of other study characteristics suggests that the outcome concerning efficiency is a context-specific random manifestation for the most part.