Working Paper Series

The Center for Real Estate periodically publishes the Working Paper Series which provides a vehicle for faculty, research associates, fellows, and visiting scholars to highlight their research.

The series is also available on SSRN, and will include the very latest academic articles produced by MIT/CRE researchers. If you would like to receive updates from SSRN when new papers are released, you can subscribe to the eJournal at no cost by clicking “Subscribe” above.


Below is a library of select working papers from the series: 

Retail Carbon Footprints: Measuring Impacts from Real Estate and Technology

Dr. Andrea Chegut, MIT Center for Real Estate, REI Lab Director
Diego Fernandez, MSRED, REI Lab Research Analyst
James Scott, REI Lab, Technology Scouting Lead
Juncheng Yang, REI Lab, Computational Urban Designer
Erin Glennon, REI Lab Manager

Over the last quarter of a century, no asset class in real estate has seen more transformation than the retail sector, due to advances in technology, innovations in the supply chain and ever-advancing changes in consumer behavior. Where once consumers flocked to suburban shopping malls and the brick-and-mortar stores of city streets, ecommerce – combined with next-day delivery capability – has completely altered how we purchase all forms of goods. Coinciding with this transformation, climate change across the globe has now reached a point where it is unquestionably impacting our environment, economy and resiliency as a society. The question we must now ask is which of these forms of consumer behavior leads to lower carbon emissions, and is better for the world in which we live. This analytical study aims to investigate and measure consumers’ Greenhouse Gas (GhG) emissions while engaging in either ecommerce purchasing or the more traditional purchasing from brick-and-mortar stores. 


The Evolution of the Warehouse: Trends in Technology, Design, Development and Delivery

Steve Weikal, CRE Tech lead, MIT Real Estate Innovation Lab
James Robert Scott, Lead Researcher, MIT Real Estate Innovation Lab

Advancements in technology and the adoption of new applications for data analytics, ubiquitous sensors, artificial intelligence, and autonomous vehicles are improving productivity and allowing for more efficient use of space, according to the report. Warehouse and distribution properties will benefit considerably from these changes.  


Dr. R. Kelly Cameron, MIT Center for Real Estate
Renee McCall, Boston Public Schools

Recently published in Voices in Urban Education (VUE), a peer-reviewed journal published by NYU’s Metro Center for Research on Equity and the Transformation of Schools. 


Which Malls Close | July 2020

William C. Wheaton, Dept. of Economics and Center for Real Estate at MIT
Morgan Fleischman, MIT Center for Real Estate

The retail services industry amounts to well over five trillion dollars annually with at least 1 million retail establishments across the United States. Since 2010, sales have increased by nearly 4 percent annually. Although the industry is undergoing an enormous change driven by technology, evolving consumer behavior, and innovation, it still plays an important role in shaping the economic, cultural, and social viability of communities across the country.  This working paper utilizes rigorous empirical research focusing on just mall closures in the United States, using hundreds of property-level data points. Second, we compute the distances for each mall relative to each other to estimate the amount of spatial competition each mall faces. Finally, we develop a predictive model to identify the centers at risk of going under today.


Doubts about Density: Covid-19 across Cities and Towns

William C. Wheaton, Dept. of Economics and Center for Real Estate at MIT
Anne Kinsella Thompson, MIT Center for Real Estate

It has been 85 days since the first case of Covid-19 was detected in the US. Until most recently information on the spread of the disease was not available by geographic areas smaller than counties. In an earlier piece, we found a significant positive impact of county density on the daily progress of the disease in a dynamic model. Since then, static data on disease incidence at the municipal level (as of 4/15/20) has become available in a few states. We use Massachusetts data since it is a fully incorporated state. We find that municipalities with greater density and with a greater share of land use in commercial-industrial categories have a significantly higher per capita incidence of the disease. The quantitative impact of density is particularly large.


The Geography of Covid-19 growth in the US: Counties and Metropolitan Areas

William C. Wheaton, Dept. of Economics and Center for Real Estate at MIT
Anne Kinsella Thompson, MIT Center for Real Estate

It has been 70 days since the first case of Covid-19 was detected in the US. Since then it has spread and grown in all but 2 of 376 MSAs and all but 45 of the 636 counties that are contained in these MSA. In this paper we examine the determinants of how rapidly the virus grows once it has been seeded within a MSA or county. We find virus cases can be well predicted by area population, as well as days-since-onset. In the data, virus cases scale almost proportionately with population, and excluding population significantly changes the impact of days-since-onset. Growth is also related to residential density and per capita income, particularly at the county level. There are weaker relationships to MSA average household size, per capita income, and the fraction of the population that is over 65. These results come from parameterizing a simple power function model of cumulative infections since onset. This is shifted proportionately by the various MSA/County covariates. We also experiment with restricting the sample of areas so as to have a minimum number of cases – equal to .01% of the area’s population. This effectively focuses on the more advanced part of the virus growth curve. Here we find a significant further decrease in the coefficient of days-since-onset. This is preliminary evidence that the virus growth is tapering. We intend to repeat our analysis as time progresses.


The Financial Impacts of Coworking: Rental Prices and Market Dynamics in the Commercial Office Market

Andrea Chegut, Massachusetts Institute of Technology
Mike Langen, Maastricht University – Department of Finance

Coworking providers, like WeWork, have shifted the competitive landscape for office tenants through differentiating office amenities, leasing fully-equipped desks or offices over flexible time periods. However, even though coworking providers are a tenant type in consumer demand, little is known about the strategic interaction of this growing tenant with landlords in the real estate sector. In this paper, we assess landlord-coworking provider interaction through lease contract valuation, assessing if landlords see coworking providers as a substitute, benefit or risk, compared to other tenants. Using lease contracts from six US cities between 2008 to 2018, we compare rent conditions between coworking providers and tenants within the same building. We document that landlords treat coworking providers as substitutes not differentiating in effective rent compared to other tenants. Coworking providers take systematically longer lease durations, resulting in higher tenant incentives, such as free rent periods and tenant improvement concessions. Controlling for lease duration, coworking providers receive significantly more tenant concessions. We do not find value-increasing external effects of coworking providers, concluding that landlords are indifferent towards coworking tenants.


Tokenized Security & Commercial Real Estate

Julie Smith, Manasi Vora, CFA, Dr. Hugo Benedetti, Kenta Yoshida, Zev Vogel, CFA

Prof. David Geltner and Steve Weikal contributed expertise on real estate tokenization to a recently published working paper from the Sloan School of Management and the MIT Digital Currency Initiative.


Bricks or Clicks? The Efficiency of Alternative Retail Channels

William C. Wheaton, Dept. of Economics and Center for Real Estate at MIT
Edward Tung, Carmel Partners, MSRED ’18

There is widespread recognition that the retail sector is undergoing a significant transformation [Hortascu and Syverson, 2015]. Rather than have stores act as the intermediary between consumers and producers, Web-based platforms together with efficient destination-based delivery services are providing a viable and thriving alternative. The latter model has been hailed as giving consumers far greater shopping choice and also creating more transparent and competitive prices. In this paper we examine an additional possible advantage of “etailing” over “retailing” – that of operational efficiency. We study the annual financial (10k) reports of 122 firms that represent this full range of alternatives between pure-play internet delivery (Amazon, Land’s End, 1-800Flowers), to traditional pure Brick and Mortar stores (Dollar Stores, Auto Zone) to mixed formats that use both models (Best Buy, J. Crew). We obtain the Gross Profit of each enterprise (Sales Revenue minus Cost-of-Goods) as well as factor inputs (employment, store and distribution space). The question posed is how the various components of a firm’s operating expenses are impacted by the share of its sales that are derived through stores, as opposed to the internet. If internet based “e-tailing” can operate more efficiently, then in addition to providing a broader range of goods, sooner or later it will also provide those goods at lower prices. In this case the winner in the war between bricks and click will be obvious [Bedetti, 2017].  


Will Coworking Work?

William C. Wheaton, Dept. of Economics and Center for Real Estate at MIT
Alex Krasikov, Economist, CBRE Econometric Advisors


Robots, Automation and the Demand for Industrial Space

William C. Wheaton, Dept. of Economics and Center for Real Estate at MIT
Jing Ren, Economist, CBRE Econometric Advisors

We utilize the data set developed by Acemoglu & Restrepro (2017) depicting the likely adoption rate of robots by firms in each US MSA. Our focus is on the impact of this automation metric on the market for industrial real estate (factories and warehouses). We get similar results to their negative impacts of automation on local labor markets. Over the 1993-2007, MSA with an industry mix that that more rapidly automating are associated with significantly less construction of new industrial space, less growth in overall occupied space, and lower increases in industrial space rents. The use of industry mix based “estimated” robot adoption, and a wide range of applied control variables, suggests that this relationship is causal.


Energy Performance and Capital Expenditures in Manufacturing Industries

Jasper Brinkerink, Free University of Bozen-Bolzano, Faculty of Economics and Management, Centre for Family Business Management
Andrea Chegut, MIT Center for Real Estate
Wilko Letterie, Maastricht University, School of Business and Economics, Department of Organization and Strategy

Little is known about how firms change energy consumption over time. Yet to meet global climatechange targets understanding how changes in firm investment impact environmental performanceis important for policy makers and firms alike. To investigate the environmental performance offirms we measure the energy consumption and efficiency of firms in the Netherlands’manufacturing industries before and after large capital expenditures over the 2000 to 2008 period.Unique to this data set, is that firm investment is decomposed into three streams: investment inbuildings only, in equipment only or a simultaneous investment in both buildings and equipment.We find firms increase energy consumption when experiencing a simultaneous investment.However, after large capital expenditures energy efficiency increases. Further decomposition byfirm types suggests that the building capital investments of firms active in high tech industries,energy intensive and low labor intensive industries does not concide with energy efficiencyimprovements, while energy efficiency does increase with capital expenditures in equipment.Hence, from a policy perspective targeted agreements that understand the production process offirms will require a differentiated strategy. In this case, voluntary agreements with firms, like thosewith equipment, may not shift energy consumption due to production demands. Third party verification to enhance transparency, subsidies or R&D tax credits may potentially yield better results. 


Brief Thoughts on Housing Supply and Policy*

Albert Saiz, MIT Center for Real Estate

* This working paper is the companion of a homonymous presentation in the conference 
about housing markets organized by the Nederlandsche Bank in Amsterdam on May 24-25, 2018.
A revised version of this document is expected to be published in the volume: “Hot
Property – The Housing Market in Major Cities.” Lohuis, Melanie; Nijskens, Rob; Hilbers,
Paul; and Heeringa, Willem (Editors). Willey, Amsterdam (forthcoming).


Is Innovation Really in a Place? Accelerator Program Impacts on Firm Performance

Sheharyar Bokhari, MIT Center for Real Estate

Andrea Chegut, MIT Center for Real Estate

Dennis Frenchman, MIT Dept. of Urban Studies and Planning

Isabel Tausendschoen, Real Estate Innovation Lab


2.  Urban Big Data: City Management and Real Estate Markets

Richard Barkham (CBRE)

Sheharyar Bokhari, MIT Center for Real Estate

Albert Saiz, MIT Center for Real Estate


3.   Real Trends: The Future of Real Estate in the United States

Albert Saiz, MIT Center for Real Estate

Arianna Salazar, MIT Dept. of Urban Studies and Planning


5.   Commercial Building Capital Consumption in the US

David Geltner, MIT Center for Real Estate

Sheharyar Bokhari, MIT Center for Real Estate


5.   Commercial Buildings Capital Consumption and the United States National Accounts

Sheharyar Bokhari, MIT Center for Real Estate

David Geltner, MIT Center for Real


6.   Energy Efficiency and Economic Value in Affordable Housing

Andrea Chegut, MIT Center for Real Estate

Piet Eichholtz, Maastricht University

Rogier Holtermans, Maastricht University


7.   Error Correction Models of MSA Housing “Supply” Elasticities: Implications for Price Recovery

William Wheaton, MIT Center for Real Estate, Department of Economics

Serguei Chervachidze, CBRE Econometric Advisers

Gleb Nechayev, CBRE Econometric Advisers


8.   Simultaneous and Solitary Spikes: Investment in Equipment and Buildings

Jasper Brinkerink, Maastricht University, School of Business & Economics

Andrea Chegut, MIT Center for Real Estate

Wilko Letterie, Maastricht University, School of Business & Economics


9.   The Price of Innovation: An Analysis of the Marginal Cost of Green Buildings

Andrea Chegut, MIT Center for Real Estate

Piet Eichholtz, Maastricht University School of Business & Economics

Nils Kok, Maastricht University School of Business & Economics


10.   The Mistakes People Make: Financial Decision Making when Buying and Owning a Home

Sumit Agarwal, National University of Singapore

Crocker Liu, Cornell University

Walter Torous, Massachusetts Institute of Technology

Vincent Yao, Fannie Mae


11.   The Income Tax Penalty on Rental vs Owner-Occupied Housing: An Argument for Apartment Rent Tax Exemption

David Geltner, MIT Center for Real Estate


12.   System Dynamics Modeling of Chinese Urban Housing Markets for Pedagogical and Policy Analysis Purposes

David Geltner, MIT Center for Real Estate

Richard de Neufville, MIT Engineering Systems Division

Xin Zhang, MIT Engineering Systems Division


13.   Characteristics of Depreciation in Commercial and Multi-Family Property: An Investment Perspective

Sheharyar Bokhari, MIT Center for Real Estate,

David Geltner, MIT Center for Real Estate