Conference Agenda

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

Please note that all times are shown in the time zone of the conference. The current conference time is: 13th Aug 2022, 09:39:53am IST

Session Overview
Poster Session at Welcome Reception
Wednesday, 06/July/2022:
6:30pm - 8:00pm

Location: Exam Hall

Front Square, Trinity College

External Resource:
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A Text Convolution Network-Based Policy Uncertainty Index: An Application for China

Fu, Yuqi; Yang, Zan; Ding, Liqun; Quan, Rongxi

Tsinghua University, China, People's Republic of;

Newspaper text has become one of the critical data sources for measuring economic policy uncertainty. In some cases, newspaper discussions of policy uncertainty are expressed in subtle and implied ways. It is necessary to mimic market practitioners to process and identify perceived, concept-based uncertainties. In this study, we use the text convolution network to develop an index of EPU for China’s real estate market. The index effectively captures the characteristics of policy uncertainty in the market under media censorship and conservative cultural context. We highlight that the approach can also be widely applied to other concept-based text analyses.

Agglomeration In the Flexible Working Era: The Micro-location Choices of Co-working Offices

Lavoratori, Katiuscia1; Wu, Yi2; Zhang, Melanie {Fangchen}3

1International Business and Strategy, Henley Business School, University of Reading; 2Real Estate and Planning, Henley Business School, University of Reading; 3Dept of Architecture and Built Environment, Northumbria University, United Kingdom;

The emerging co-working space phenomenon provides a unique case for the knowledge spillover under the hybrid working style. We investigate the micro-location choices of co-working offices at the postcode district level. With the co-working space locations from 12 co-working operators in central London during 2009-2020, results from the conditional logit model show that, the co-working offices tend to choose the districts with higher industry diversity, a higher proportion of Culture and Creative Industry (CCI) business, or where the local industries contain more “teleworkable” job types. Meanwhile, co-working spaces tend to locate at those where start-up firms concentrated, echoing that the influences of knowledge spillover differ among firms’ life cycles. The results are robust when controlling the business strategies of co-working office providers, as well as the infrastructure, connectivity, and urban density at the local level. The findings cast light on the discussion of spatial clustering and micro-location choices with the case of sharing economy. It also shares substantial policy implications on the strategy design of boosting agglomeration benefits and productivity returns with co-working space.

Applying the Game Theoretic Dynamic of a Mixed Stackelberg Oligopoly to the Provision of New Build Social and Private Housing in the Greater Dublin Area

Lyons, Michael Flannan

Technological University Dublin, Ireland;

The increasing influence of REITs, private equity funds and PLCs on the Irish housing market, accompanied by planning and design standard legislation has created conditions that are conducive to oligopoly. This research analyses the market concentration of the new build housing market in the Greater Dublin Area and provides a theoretical framework that showcases the potential evolution of the market to an oligopoly. Although the industry is not definitively an oligopoly, it is on a trajectory of increased concentration, whilst conforming to the theoretical indicators of this market structure. The game theoretic dynamic of a mixed Stackelberg oligopoly is provided as a remedy to the current housing situation. By publicly purchasing a privately owned company to provide social housing, a position of tacit influence can be observed on the private market with a negligible crowd out effect, providing the opportunity to rectify social inequality through the housing market. Taking into account the overwhelming need for further housing supply, this framework can provide a new home for the lower income percentiles whilst simultaneously facilitating a prosperous free market in the private sector and in turn creating a Nash equilibrium.

Combining hedonics, GEKS and state space models to construct CPPIs

Ishaak, Farley1,2; Ouwehand, Pim2

1University of Delft; 2Statistics Netherlands;

Constructing price indices for commercial real estate is challenging due to heterogeneous and limited observations. Common price index models often result in volatile series. State space models can be applied afterwards to (smoothen the series and) reduce volatility, but this leads to failure in practical and methodological requirements. In this study, a combination of hedonic imputation, GEKS and state space methods is explored with the aim to maintain the requirements of limited revision, time reversibility, circularity and identity and at the same time reduce the volatility of the final price index. Commercial real estate transactions in the Netherlands were used to asses various compilation scenario’s. The preliminary results show that the introduction of a multilevel method, such as GEKS, can help in maintaining at least some of the requirements. GEKS by itself does not meet the requirement of limited revision, but splicing methods can be used to resolve this. The result is a method that balances user requirements and properties that are desirable from a theoretical perspective.

Do macroeconomic factors matter in housing markets?

Lin, Pin-Te

University of Reading, United Kingdom;

This research examines whether most variation in house price changes is mainly driven by local or national factors. Employing a novel data containing both capital appreciation and income component in the U.S. Metropolitan Statistical Areas, results show that macroeconomic factors, absorbed by time fixed effects, account for 43% of the variation in capital gains and 2% of the variation in rental yields. Overall, the findings empirically support the prior literature assuming that the nature of housing markets is mainly local. The findings suggest a greater role of local factors for understanding cross-sectional income returns in housing markets.

Estimating Unobserved Long-run Trend and Cycles of House Price to Income Ratio in Ireland

Yao, Fang

Central Bank of Ireland, Ireland;

This paper estimates the unobserved trend cycles of the house price to income ratio (HPI)

in Ireland. I use a multivariate state-space model to decompose HPI into trend and cycle

components. Under this approach, the HPI trend is driven by exogenous driving forces,

such as demographics changes and neutral interest rates, while the cyclical component of

HPI is identified by using cyclical indicators. This approach allows explicit modelling of

trend and cycles in a uniformed framework and both are driven by data. At the end of the

paper, the use of this trend-cycle decomposition for calibrating Loan-to-income ratio policy

is demonstrated.


Burinskas, Arunas; Cohen, Viktorija

Vilnius University, Lithuania; ,

Real Estate Investment Trusts (REITs) is a widely used financial instrument in global listed real estate securities and proved to be remarkably effective in diversification, market accessibility, transaction cost cuts, inflation-hedging tool. In the literature, there is no argument that REITs are strongly driven by macroeconomic factors and correlate with securities markets. However, the mainstream focuses on few macroeconomic determinants only: inflation, GDP (Gross Domestic Product), unemployment rate, interest rate.

This article sheds some light on traditional indicators for REITs performance by arguing that there are several other reliable macroeconomic indicators that have not been receiving enough attention in academia. Our empirical observations suggest broadening approach in this respect.

Our findings prove that including economic indicators from the regular economic calendar might improve forecasting abilities (in terms of accuracy) of regression and ARDL models that usually are used establishing relations between REITs and their determinants.

Housing Purchase Restrictions and Entrepreneurship

Ma, Chao

Xiamen University, China, People's Republic of;

Using the entire universe of firm registration data from the Bureau of Industry and Commerce, we study how entrepreneurship is affected by the housing purchase restriction (HPR) policy, an austere housing-market cooling intervention in China. While the original purpose of HPR was only to slow house price growth, we find that HPR also increased firm creation. The explanation is that, when HPR is adopted, potential entrepreneurs whose housing purchase eligibilities are affected will no longer be distracted by housing investments from starting new businesses.

How Irrational Biases Affect Real Estate Supply Dynamics

Tong, Lok Man Michelle

CAIA,LSE & Reading Alumni;

We present an innovative approach to measure overconfidence bias and disposition effects based on real estate rental decisions to avoid market frictions. The effects of irrationality on real estate usable supply are explored at the first attempt. We develop a new conceptual model to describe this issue by defining economic and physical mismatch and introducing a behavioral supply elasticity which is driven by irrational bias. The empirical findings confirm that investor bias is the main cause of inelastic supply alongside regulatory and geographical constraints. Overconfidence bias is less frequent to occur comparing with disposition effect. To raise supply responsiveness, policymakers may offer incentives specific in the cities with the largest exposure in disposition effect for reducing mismatch.

Is Green Lending Subject to Home Bias? Comparing Mortgages by Banks and Nonbanks

Connolly, Michael1; Echeverry, David Felipe2

1Colgate University; 2Universidad de Navarra, Spain;

We document a distance effect in the production of green assets by banks relative to nonbanks, using data from multifamily mortgages bought by Fannie Mae after 2016. While the latter take an arms-length approach to their green issuance, the former concentrate their green portfolio close to headquarters. However, nonbank green loans perform better over time than the ones issued by banks. There is no significant difference in interest rates, suggesting that the relatively lower loan quality is not priced ex ante. This suggests that the local concentration of banks' green portfolio is driven by home bias rather than soft information.

Who Owns Climate Risk in the U.S. Real Estate Market?

Woodwell, Jamie; Fratantoni, Mike; Seiler, Edward

Mortgage Bankers Association, United States of America;

Physical, economic, and social changes associated with a changing climate will directly affect real estate markets in the U.S. Because market participants keenly focus on the identification, assessment, mitigation, underwriting, insurance, and pricing of risk, they create a unique case study for understanding the ways in which climate-related risks are likely to impact individual actors and the market ecosystem as a whole. Modeling the “ownership” of risks illuminates under which circumstances homeowners, insurance providers, lenders, investors, and others do and do not take on physical, transition and other risks, and the level of risk “owned” by each. We find that owners bear the burden of paying for the risks, in some circumstances through explicit or implicit insurance, but that the ways in which responsibility for climate risk is distributed among the various market players is heavily dependent on whether the property owner does or does not have a mortgage in place and whether that mortgage is held in a lender’s portfolio or sold into the secondary market. The results have broad implications for where risk management and regulation can have the most significant impacts.

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