Jeffrey P. Cohen is an associate professor of Real Estate and Finance at UCONN’s Center for Real Estate, and Dean’s Ackerman Scholar, at the School of Business. Professor Cohen has longstanding collaborative research relationships with the Federal Reserve Bank of St. Louis, and has been a recent Visiting Scholar at the St. Louis Fed in May, 2017 , December, 2017, March 2018, and June 2019. His current research interests include the impact of airports and airport noise on commercial and residential property values; property taxation; land value estimation; housing price spillovers across jurisdictions; the impacts of storms on real estate values; and the geographical aspects of REITs. Among approximately 40 peer-reviewed journal publications, he has published his research in several top journals, including: Review of Economics and Statistics, Journal of Urban Economics, Journal of Regional Science, Regional Science and Urban Economics, Journal of Real Estate Finance and Economics, Real Estate Economics, Federal Reserve Bank of St. Louis Review, and others.
He has previous teaching experience at Tufts University, the University of Maryland at College Park, and the University of Hartford. Professor Cohen has also worked full-time at the U.S. Environmental Protection Agency as part of an award from the National Academies; and has been a Fellow with, and a seminar organizer for the Lincoln Institute of Land Policy. He also has previous full-time employment experience in the private sector as a Senior Economist at Standard and Poor’s. He has served on expert panels for the National Academies, the U.S. Environmental Protection Agency, and the Lincoln Institute of Land Policy. His other grants and consulting clients have included the U.S. Department of Energy, the U.S. Small Business Administration, Organization for Economic Cooperation and Development (OECD), the Vancouver Airport Authority in Canada, the Lincoln Institute of Land Policy, the Robert Wood Johnson Foundation, and the National Metropolitan Transportation Center (METRANS) at California State University-Long Beach.
Professor Cohen is currently the Principal Investigator on Phase 1 of a grant from the State of Connecticut Department of Transportation and the U.S. Department of Transportation/Federal Highway Administration, on how the new commuter rail line (called CTrail) connecting New Haven, Hartford, and Springfield MA, impacts real estate in neighborhoods near the stations.
Areas of Expertise (4)
Residential Real Estate
Applied Spatial Econometrics
Real Estate Economics and Finance
Transportation and Real Estate
University of Maryland at College Park: Ph.D., Economics 1998
University of Toronto: M.A., Economics 1993
Tufts University: B.S., Quantitative Economics 1992
Media Appearances (2)
How disasters — manmade or natural — affect the real estate market
Boston Globe online
Because the Federal Emergency Management Agency flood maps are available to the public, many buyers understand the risk they’re taking when they buy in a documented flood plain, said Jeffrey Cohen, a University of Connecticut professor of finance and real estate. However, as the climate warms and storms grow stronger and wetter, locations once considered safe are also getting hit — and when our expectations of risk change, home values can react in kind. Cohen is seeing that play out in his current research on New York City home prices before and after Superstorm Sandy ravaged the city in 2012.
Home Warranties Offer Buyers Protection. Just Don’t Forget the Inspection
Wall Street Journal print
However, in hot markets with low inventory, offering a home warranty may be a warning sign to potential buyers, says Jeffrey P. Cohen, a professor of finance and real estate at the University of Connecticut School of Business. "If you’re in a market like New York City I would see it as a red flag that something may come up." Even if a home warranty is included in the sale, buyers shouldn’t forgo a home inspection, Prof. Cohen says. Skipping an inspection might make your offer more competitive in a bidding war, "but you might be ignoring issues that may come up years from now. You may be hurting yourself down the road," he says.
2019 Using Lorenz-type curves, means tests, ordinary least squares, and locally weighted regressions (LWR), we examine the relative burdens of whites, blacks, and Hispanics in Georgia from road and air traffic noise. We find that whites bear less noise than either blacks or Hispanics and that blacks tend to experience more traffic noise than Hispanics. While every Metropolitan Statistical Area (MSA) showed that blacks experienced relatively more noise than average, such a result did not hold for Hispanics in roughly half of the MSAs.
2019 In this study, we develop and apply a new methodology for obtaining accurate and equitable property value assessments. This methodology adds a time dimension to the Geographically Weighted Regressions (GWR) framework, which we call Time-Geographically Weighted Regressions (TGWR). That is, when generating assessed values, we consider sales that are close in time and space to the designated unit.
2016 While an understanding of spatial spillovers and feedbacks in housing markets could provide valuable information for location decisions, little known research has examined this issue for the US Metropolitan Statistical Areas (MSAs). Also, it is unknown whether there can be differences in the spatial effects before and after a major housing “bust”. In this paper we examine spatial effects in house price dynamics.
2014 An important measure of the capital–land ratio in urban areas is the Floor Area Ratio (FAR), which gives a building's total floor area divided by the plot size. Variations in the FAR across cities remain an understudied measure of urban spatial structure. We examine how the FAR varies across the five boroughs of New York City. In particular, we focus on the FAR gradient over the 20th century.
2010 The importance of “broader” economic effects of transportation infrastructure has recently become apparent. “Broader” refers to impacts beyond the geographic boundaries within which the infrastructure investments are undertaken. Approaches to estimate “broader” impacts in production and cost function models are evaluated. A contribution of this paper is the empirical demonstration with a cross-section of US states’ manufacturing data that ignoring broader effects of a spatially lagged dependent variable can lead to mis-statements of the overall productive impacts of public infrastructure.