Analyzing Time Series and Cross Section Rent Data : An Illustration Using US Retail Data

Real estate research has a long and extensive history of analyzing rent dynamics. Due to data constraints, the retail market has been the least researched segment and, more generally, regional panels of data have been rarely analyzed. In this paper, we analyze rent dynamics at the Metropolitan Statistical Area (MSA) level by applying an error correction model, covering almost three decades of retail rent data for the 13 largest MSAs of the United States. We feature the joint analysis of time series and cross section space market data. This version: 20 December 2009 Hendershott is Professor of Property Economics and Finance at the Centre for Property Research, University of Aberdeen Business School, UK. Jennen is Assistant Professor of Finance and Real Estate at RSM and Investment Analyst at ING Real Estate Investment Management. MacGregor is MacRobert Professor of Land Economy at the University of Aberdeen Business School. The authors gratefully acknowledge the generous data support that was offered by Torto Wheaton Research in this project. *Corresponding author

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