This paper uses a unique dataset to empirically test the implications of limited transparency in decentralized markets. We capture differences in the transparency level as a linkage mechanism among international commercial real estate markets. This connectivity arises from learning externalities of international investors. Our identification strategy exploits the specific feature of spatial econometrics to analyze the transmission of these externalities across opaque markets. We find empirical evidence of cross-sectional dependence and co-movements among global property market excess returns. Furthermore, local shocks are amplified via spillovers and feedback loops, which provide a source of instability in international property markets.

 

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