skip to main content
10.1145/3453187.3453321acmotherconferencesArticle/Chapter ViewAbstractPublication PagesebimcsConference Proceedingsconference-collections
research-article

Factors Influencing Housing Prices: An Empirical Analysis From New York City

Published:24 March 2021Publication History

ABSTRACT

This paper studies the determinants of housing price dynam- ics in the New York City. This model is used to study the effect of house factors on the house prices appreciate rate. Using the records of real estate transactions between 2003 and 2017 in the New York City (short referred to as NYC), this paper found that the influencing factors of the property itself have different effects on the house prices appreciate rate. After removing the factor of real estate location, for the average house price appreciate rate, the number of real estate transactions has the greatest impact on house prices; in the case of different house price levels, the land area of the house has the greatest influence on house price growth dur- ing the boom and the depression of housing prices, while the structure and land area of the real estate does the greatest during the recovery period of housing prices

References

  1. C. Burnside, M. Eichenbaum, and S. Rebelo. Understanding booms and busts in housing markets. Journal of Political Economy, 124(4):1088--1147, 2016.Google ScholarGoogle ScholarCross RefCross Ref
  2. J. Favilukis, S. C. Ludvigson, and S. Van Nieuwerburgh. The macroeconomic effects of housing wealth, housing finance, and limited risk sharing in general equilibrium. Journal of Political Economy, 125(1):140--223, 2017.Google ScholarGoogle ScholarCross RefCross Ref
  3. E. L. Glaeser, J. Gyourko, and R. E. Saks. Why have housing prices gone up? American Economic Review, 95(2):329--333, 2005.Google ScholarGoogle ScholarCross RefCross Ref
  4. A. Justiniano, G. E. Primiceri, and A. Tambalotti. Credit supply and the housing boom. Technical report, National Bureau of Economic Research, 2015.Google ScholarGoogle Scholar
  5. K. A. Kiel and J. E. Zabel. Location, location, location: The 3l approach to house price determination. Journal of Housing Economics, 17(2):175--190, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  6. N. Kiyotaki, A. Michaelides, and K. Nikolov. Winners and losers in housing markets. Journal of Money, Credit and Banking, 43(2-3):255--296, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  7. T. Landvoigt, M. Piazzesi, and M. Schneider. The housing market (s) of san diego. American Economic Review, 105(4):1371--1407, 2015.Google ScholarGoogle ScholarCross RefCross Ref
  8. T. Piskorski and A. Tchistyi. Stochastic house appreciation and optimal mortgage lending. The Review of Financial Studies, 24(5):1407--1446, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  9. J.-V. Rios-Rull and V. Sanchez-Marcos. An aggregate economy with different size houses. Journal of the European Economic Association, 6(2-3):705--714, 2008.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Factors Influencing Housing Prices: An Empirical Analysis From New York City

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Other conferences
      EBIMCS '20: Proceedings of the 2020 3rd International Conference on E-Business, Information Management and Computer Science
      December 2020
      718 pages
      ISBN:9781450389099
      DOI:10.1145/3453187

      Copyright © 2020 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 24 March 2021

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article
      • Research
      • Refereed limited

      Acceptance Rates

      EBIMCS '20 Paper Acceptance Rate112of566submissions,20%Overall Acceptance Rate143of708submissions,20%
    • Article Metrics

      • Downloads (Last 12 months)43
      • Downloads (Last 6 weeks)4

      Other Metrics

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader