Gianluca Marcato
Professor of Finance and Real Estate
Head of Department, Real Estate and Planning
Director, Certificate in Government Property Leadership
Director, INREV / Henley Certificate in Non-Listed Real Estate Investment
Pricing and Indexes
Property Management Technology Adoption in the Short-Term Housing Rental Market (with S. Göppinger and J. Luque) - Real Estate Economics, Forthcoming
Mortgage Default Risk Amplifies the Effect of Systemic Risk on Risk Premium (With A. Almeida, M. Faias and J. Luque) - Working Paper
Investors Behaviour and Price Discovery: A Tale from Smoothing Dynamics of Commercial Real Estate Returns (with V. Mushi)
Publications
Supply Constraints and Search Equilibrium in Office Markets (with M. Tong)
Journal of Real Estate Finance and Economics, 2023
Abstract: We present a new conceptual framework to estimate office supply elasticity, where net business survival, physical and economic mismatch are used to identify frictional and structural vacancy. Alongside regulatory and geographical constraints, we also find an unobserved feature of supply elasticity linked to natural vacancy. Our results confirm that US Metropolitan Statistical Areas are generally supply inelastic and the search and matching process plays a key role in supply dynamics. In the least inelastic markets, investors tend to be more flexible to respond to negative demand shocks. As a result, we observe a reduction in structural vacancy and a subsequent increase in cyclical vacancy given the slow short-term movement in absorption. These findings also shed light upon office market dynamics during the COVID-19 period.
Supply Constraints and Search Equilibrium in Office Markets (with M. Tong)
Real Estate Economics, 2024
Abstract: We show evidence of the impact on pricing of a new technology providing information on market conditions (supply growth, demand patterns, pricing trends and competitor rates) in the short term rental market. Using a sample of 2,196 housing units over 18 months available on Airbnb in Madrid (Spain), we observe the adoption of this technology by property managers at different points in time for 16\% of our observations. Our Propensity Score Matching (PSM) estimates support the evidence of a greater market transparency obtained through the adoption of this technology, with a significant increase in revenues obtained through a reduced average daily price and increased occupancy. Overall, our results are robust to several model selections dealing with a potential endogeneity issue. We also show some preliminary evidence of property managers increasingly engaging in dynamic pricing after the adoption of this technology. Particularly, revenue growth seems to be generated through a small price drop leading to a rise in occupancy at the top end of the price distribution, rather than at the bottom end, where a significant and much higher price drop is not able to generate the necessary occupancy growth to obtain an overall increase in revenues.
Commercial Real Estate Returns: An Anatomy of Smoothing in Asset and Index Returns (with S. Bond and S. Hwang)
Real Estate Economics, 2012
Abstract: In this article, we investigate the commonly used autoregressive filter method of adjusting appraisal‐based real estate returns to correct for the perceived biases induced in the appraisal process. Many articles have been written on appraisal smoothing but remarkably few have considered the relationship between smoothing at the individual property level and the amount of persistence in the aggregate appraisal‐based index. To investigate this issue we analyze a large sample of appraisal data at the individual property level from the Investment Property Databank. We find that commonly used unsmoothing estimates at the index level overstate the extent of smoothing that takes place at the individual property level. There is also strong support for an ARFIMA representation of appraisal returns at the index level and an ARMA model at the individual property level.
Style Analysis in Real Estate Markets: Beyond the Sectors and Regions Dichotomy (with F. Fuerst)
Journal of Portfolio Management, 2009
Abstract: We evaluate a number of real estate sentiment indices to ascertain current and forward-looking information content that may be useful for forecasting demand and supply activities. Analyzing the dynamic relationships within a Vector Auto-Regression (VAR) framework and using the quarterly US data over 1988-2010, we test the efficacy of several sentiment measures by comparing them with other coincident economic indicators. Overall, our analysis suggests that the sentiment in real estate convey valuable information that can help predict changes in real estate returns. These findings have important implications for investment decisions, from consumers’ as well as institutional investors’ perspectives.
Smoothing and Implication for Asset Allocation Choices (with T. Key)
Journal of Portfolio Management, 2007
Abstract: Despite the strong evidence of persistence in direct real estate returns at the segment level, the effectiveness of such strategies for property investors has not been thoroughly investigated. This paper presents results of simulated momentum and contrarian (buy winner or buy loser) investment strategies in UK property, using annual and monthly returns series. We find strong potential gains from momentum strategies based on preceding returns over a six to twelve month period. Contrarian strategies, by contrast, perform poorly. Whether these gains are attainable to real world investors depends on assumptions on transactions costs, but we find some momentum strategies still produce excess returns when net returns are used. These results also have implications for the pricing and performance of index-based property derivatives.
The Measurement and Modelling of Commercial Real Estate Performance (with P. Booth)
British Actuarial Journal, 2004
Abstract: In this paper we discuss methods of developing real estate indices, the availability of real estate data, the problems of using published real estate data and how real estate data can be used for stochastic investment modelling for actuarial purposes. In recent years there have been many developments in the collection, presentation and analysis of real estate data that have not found their way into the actuarial literature. We review those developments and suggest and develop ways in which raw real estate investment data can be used for actuarial purposes. We then review the Wilkie real estate stochastic investment model and use the research of real estate finance academics to inform a critique and development of that model. In developing the models, different data sets are used, including data from valuation-based and de-smoothed indices in order to find appropriate parameter estimates. The significance (or otherwise) of the parameter estimates is tested for each of the fitted models and the differences between the fitted models are examined. By reviewing research in the real estate finance field, making use of the latest research and developing original work, the main aim of this paper is to ensure thatactuaries have the means to collect, understand and manipulate real estate data for performance
measurement and investment modelling purposes.
Style Analysis in Real Estate Markets and the Construction of Value and Growth Indices
Journal of Real Estate Portfolio Management, 2004
Abstract: Style analysis in equity markets is becoming more appealing to real estate investors. However, the literature in this sector generally uses either equity indexes (United States), or regional and sector ones (United Kingdom) to explain performances of real estate vehicles. This is a problem, mostly due to the lack of “proper” real estate style indexes. This paper suggests a quantitative model to decide the best criterion to breakdown a sample in order to create style indexes in real estate markets. The empirical analysis uses the Jones Lang LaSalle valuation database (4,004 properties) and ranks properties by their own equivalent yield. The findings indicate “median” as the most appropriate method to split the sample.
The Dependency Between Returns from Direct Real Estate and Returns from Real Estate Shares (with P. Booth)
Journal of Property Investment and Finance, 2004
Abstract: Despite improvements in certain countries in recent years, the provision of performance information on the direct real estate market still suffers from a lack of timeliness and reliability. The latter problem is particularly an issue for higher‐frequency data provision. This paper investigates whether there is information from the indirect market that might be useful in helping us understand better the direct real estate market. Direct real estate indices do not measure the performance of underlying transactions prices properly because they are based on valuations – and therefore may be subject to valuation smoothing. Indirect real estate indices do not properly measure the value investors put on the underlying assets of real estate companies because real estate companies are geared. Compares appropriately adjusted indices, and shows that there is information in indirect index returns that can usefully help us understand the performance of the direct market and an index is produced of de‐geared monthly real estate share returns for the UK.