1. EHL Real Estate/ Finance Seminar Series | January 21 2016 Session Learning Externalities in Opaque Asset Markets: Evidence from International Commercial Real Estate Roland Füss & Daniel Ruf Authors:Roland Füss & Daniel Ruf Discussion by Prashant Das, Ph.D. © Ecole hôtelière de Lausanne

2. 2 Premise Limited transparency across markets leads to price comovements and cross-sectional dependence Positive association between entry costs and transparency differentials across markets © Ecole hôtelière de Lausanne Method Application of pair-specific, distance-decaying transparency differentials to multiple estimation techniques Finding Markets are connected through transparency differential –Geographic lag is insignificant: Economic lag (several measures) is significant Local price shocks in one market transmits to other markets of similar transparency level

3. 3 Potential Contributions & Strengths Disentangling of price drivers from transmission of shocks across markets Methodology –Innovative application of Spatial Econometric Technique into a non- spatial context Strength –Due diligence: unit root, heteroskedasticity –Multiple estimators: OLS, 2SLS, GMM… –Imputation strategy for randomly missing endogenous data –Robust Findings © Ecole hôtelière de Lausanne

4. 4 Concerns | Theory ‘A Small transparency differential between two markets implies… less information acquisition cost’ Transparency difference between the home & another opaque market = d If d= 0; investor pays no opacity markup –Debatable.  Opaque markets will increase the information acquisition cost for all –Is the ‘information acquisition»’ argument relevant?  Is it about Systemic Risk (as associated with opacity)?  Is bargaining power directly associated with market opacity? © Ecole hôtelière de Lausanne

5. 5 Concerns | Method Weight Matrix based on transparency differential assumes: –All markets at a given transparency level, irrespective of their geographic location, impact each other similarly –Only the markets for which the transparency scores are available impact each other –Minor: US CMBS may not be a universal signal © Ecole hôtelière de Lausanne

6. 6 Suggestion Missing Information in the Weight Matrix –Bilateral trade? –Geographic distance? –Economic ties (NAFTA, EuroZone, SAARC, ASEAN?) © Ecole hôtelière de Lausanne

7. 7 Do big cities have more in common with each other than with the rest of their own countries? …They face many similar challenges, whether it is in transport, housing, security, jobs, migration or education… Good News? Anecdotal Support to the Hypothesis…

8. 8 © Ecole hôtelière de Lausanne Thank you