Annual Private Capital Conference 2019 Private Real Estate Returns and Procyclical Risk Taking by Spencer J. Couts Discussion by Andri Rabetanety Glion Institute of Higher Education, University of Cergy Pontoise Annual Private Capital Conference 2019 June 28, 2019

DiPasquale-Wheaton (1992) - Integrated model of real estate markets Motivation (1/2) DiPasquale-Wheaton (1992) - Integrated model of real estate markets The DiPasquale-Wheaton (1992) model graphically determines rental price, asset price, newly constructed stock, and total stock in a real estate market Supports the hypothesis of a procyclical development exposure to real estate capital and letting market Procyclical nature development exposure

Motivation (2/2) No specific term Open Ended Real Estate (OPRE) Fund Closed Ended Real Estate Fund No specific term Continuous periodic subscriptions and redemptions Investment in stabilized real estate assets A stated termination date Pre-determined subscription period and no redemption options Variety of real estate assets (stabilized, non stabilized) P We compare the open ended and close ended private real estate funds along the key characteristics: maturity, fundraising, strategy An existing investor who wants to exit must sell on the open market to another investor who wants to put money in When net new money comes in, the manager invests in extra underlying assets If investors don’t like the portfolio they could go. While exiting investors sell units back to the fund manager, who disposes of underlying investments to meet net redemptions To manage redemption OPRE fund managers invest in liquid assets the steady income stream makes such funds particularly attractive to certain institutional investors Relationship between the investor queue and real estate strategy Effect of the development exposure on OPRE market risk exposure

Main contributions Procyclical development exposure by OPRE funds OPRE fund flow pressure reduces the development exposure Lagged development exposure increases OPRE fund’s market risk exposure (accounting for the effect of leverage) Relationship between variation of development exposure and both capex ratio and conversion

Methodology Model Fund level data 34 funds from 2004 to 2015 NCREIF Fund Index – Open End Equity, NCREIF Property Index Capital flow data Townsend group Quarterly reports Department working directly with OPRE funds Model

General Comments (1/3) 1) Open-ended funds have low development allocation (7% in average based on papers’ data). Correlation with NCREIF Property Index (NPI). What is the repartition within the development classification (Conversion, development, expansion, pre-development vs renovation, initial leasing) ? Analysis within the subset (conversion, development, expansion, pre-development) Liquidity holdings are not (and can not be) extracted from fund performance with the given data. In this regard, it must be acknowledged that retail funds by nature are induced to carry more liquidity.

General Comments (2/3) 2) NCREIF does not calculate individual fund returns of the NCREIF OE Index. The managers submit their fund returns (as reported to the funds’ investors) to NCREIF Reporting bias ? 3) Adjust for different liquidity holdings between funds 4) Development activities create values for fund investors. Paper shows that development acquisitions positively drives funds’ net return. Have the funds build and hold strategies ? Do funds develop properties from the ground up and convert them into stabilized assets ? Or do those funds have a more opportunistic approach of build and sell strategies ? Liquidity holdings are not (and can not be) extracted from fund performance with the given data. In this regard, it must be acknowledged that retail funds by nature are induced to carry more liquidity.

General Comments (3/3) 5) Paper argues alternative explanation for time varying development exposure: NPV pricing and reaching for yield. To test the time varying development pricing and reaching for yield assumption, the model accounts for fund and time fixed effects. Fund/Time fixed effect can be explained by other fund characteristics Could there be a better proxy for development pricing? To test the reaching for yield assumption, the author verifies that the regression coefficients for capital commitment and development acquisition should be positive. Table 6 capital commitment and development acquisition are not defined in the regression equations Is there a separate table ?

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