Modeling Space Market Dynamics: An Illustration Using Panel Data for US Retail

Bryan Duncan MacGregor; Patric Henry Hendershott; Maarten Jennen

doi:10.1007/s11146-013-9426-z

Modeling Space Market Dynamics: An Illustration Using Panel Data for US Retail

Bryan Duncan MacGregor^* (Corresponding Author), Patric Henry Hendershott, Maarten Jennen

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

Abstract

Real estate research has a long and extensive history of analyzing space market dynamics. Nonetheless, two areas have been under researched. Regional panels of data have been rarely analyzed. Moreover, due to data constraints, the retail market has been studied much less than other market segments.
This paper addresses both of these topics through an analysis of Metropolitan Statistical Area (MSA) level panel data. Our study covers almost three decades of annual retail data for 11 of the largest MSAs of the United States. We estimate a long run rent model and use Error Correction Models for short run rent, vacancy and supply adjustments. We show that local markets behave in different ways in both the long run and in their short run adjustments to supply changes. We identify two groups of similar markets.

Original language	English
Pages (from-to)	659-687
Number of pages	29
Journal	The Journal of Real Estate Finance and Economics
Volume	47
Issue number	4
Early online date	8 Jun 2013
DOIs	https://doi.org/10.1007/s11146-013-9426-z
Publication status	Published - Nov 2013

Keywords

Retail space market
Panel data
Error correction model

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Cite this

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title = "Modeling Space Market Dynamics: An Illustration Using Panel Data for US Retail",

abstract = "Real estate research has a long and extensive history of analyzing space market dynamics. Nonetheless, two areas have been under researched. Regional panels of data have been rarely analyzed. Moreover, due to data constraints, the retail market has been studied much less than other market segments.This paper addresses both of these topics through an analysis of Metropolitan Statistical Area (MSA) level panel data. Our study covers almost three decades of annual retail data for 11 of the largest MSAs of the United States. We estimate a long run rent model and use Error Correction Models for short run rent, vacancy and supply adjustments. We show that local markets behave in different ways in both the long run and in their short run adjustments to supply changes. We identify two groups of similar markets.",

keywords = "Retail space market, Panel data, Error correction model",

author = "MacGregor, {Bryan Duncan} and Hendershott, {Patric Henry} and Maarten Jennen",

note = "The authors gratefully acknowledge the generous data support that was offered by CBRE Econometric Advisors (CBRE EA), formerly Torto Wheaton Research, in this project. An earlier version was presented at the Annual AREUEA 2010 Meetings.",

year = "2013",

month = nov,

doi = "10.1007/s11146-013-9426-z",

language = "English",

volume = "47",

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journal = "The Journal of Real Estate Finance and Economics",

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T2 - An Illustration Using Panel Data for US Retail

AU - MacGregor, Bryan Duncan

AU - Hendershott, Patric Henry

AU - Jennen, Maarten

N1 - The authors gratefully acknowledge the generous data support that was offered by CBRE Econometric Advisors (CBRE EA), formerly Torto Wheaton Research, in this project. An earlier version was presented at the Annual AREUEA 2010 Meetings.

PY - 2013/11

Y1 - 2013/11

N2 - Real estate research has a long and extensive history of analyzing space market dynamics. Nonetheless, two areas have been under researched. Regional panels of data have been rarely analyzed. Moreover, due to data constraints, the retail market has been studied much less than other market segments.This paper addresses both of these topics through an analysis of Metropolitan Statistical Area (MSA) level panel data. Our study covers almost three decades of annual retail data for 11 of the largest MSAs of the United States. We estimate a long run rent model and use Error Correction Models for short run rent, vacancy and supply adjustments. We show that local markets behave in different ways in both the long run and in their short run adjustments to supply changes. We identify two groups of similar markets.

AB - Real estate research has a long and extensive history of analyzing space market dynamics. Nonetheless, two areas have been under researched. Regional panels of data have been rarely analyzed. Moreover, due to data constraints, the retail market has been studied much less than other market segments.This paper addresses both of these topics through an analysis of Metropolitan Statistical Area (MSA) level panel data. Our study covers almost three decades of annual retail data for 11 of the largest MSAs of the United States. We estimate a long run rent model and use Error Correction Models for short run rent, vacancy and supply adjustments. We show that local markets behave in different ways in both the long run and in their short run adjustments to supply changes. We identify two groups of similar markets.

KW - Retail space market

KW - Panel data

KW - Error correction model

U2 - 10.1007/s11146-013-9426-z

DO - 10.1007/s11146-013-9426-z

M3 - Conference article

VL - 47

SP - 659

EP - 687

JO - The Journal of Real Estate Finance and Economics

JF - The Journal of Real Estate Finance and Economics

SN - 0895-5638

IS - 4

ER -

Modeling Space Market Dynamics: An Illustration Using Panel Data for US Retail

Abstract

Keywords

UN SDGs

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