Additional Evidence Regarding Las Cruces Housing Price Dynamics
Steven Fullerton and
Thomas Fullerton ()
Asian Journal of Economic Modelling, 2022, vol. 10, issue 1, 17-26
Abstract:
To examine housing price dynamics for Las Cruces, New Mexico, a theoretical model is developed that takes into account the supply and demand sides. The employed ARDL estimation methodology allows for more realistic modeling of market dynamics than prior studies of this residential real estate market, the second largest in New Mexico. A slightly larger sample size is also utilized. The results obtained corroborate evidence reported in several previous housing studies. Some unexpected outcomes also indicate that consistently reliable interlinkages between housing prices and explanatory variables may be elusive. Among the latter, an inverse relationship between apartment rents and single-family housing prices is most surprising but may be a consequence of the large university and college student population in Las Cruces. As post-secondary enrollments increase, so too do faculty numbers, allowing both housing prices and apartment rents to increase simultaneously. That implies that apartments and single-unit houses may be complements rather than substitutes in college towns like Las Cruces. Additional research using data for other small- and medium-sized urban economies would be helpful.
Keywords: Housing economics; Urban economics; Las Cruces. (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:
Downloads: (external link)
https://archive.aessweb.com/index.php/5009/article/view/4418/6829 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:asi:ajemod:v:10:y:2022:i:1:p:17-26:id:4418
Access Statistics for this article
More articles in Asian Journal of Economic Modelling from Asian Economic and Social Society
Bibliographic data for series maintained by Robert Allen ().