IDEAS home Printed from https://ideas.repec.org/a/mve/journl/v35y2009i2p61-79.html
   My bibliography  Save this article

Trends and Cycles of Tech-Pole Housing Prices

Author

Listed:
  • Wensheng Kang

    (Kent State University-Tuscarawa)

Abstract

This paper examines the transmission mechanism of tech-pole housing prices and investigates the economic forces behind it. For this purpose, the work develops an MCMC algorithm to extract the latent common trend and cycle of the integrating prices and conduct Bayesian stochastic search for restriction selection of the panel data model. The evidence shows that the transmission magnitude and persistence depend importantly on the degree of IT-industry intensity between two metropolitan areas. While the common stochastic trend behind the price dynamics is primarily determined by normal income, the monetary policy is responsible for the common boom and bust of tech-pole housing cycles. The policy implication for the real asset pricing and risk hedging strategies are also discussed.

Suggested Citation

  • Wensheng Kang, 2009. "Trends and Cycles of Tech-Pole Housing Prices," Journal of Economic Insight, Missouri Valley Economic Association, vol. 35(2), pages 61-79.
    • Handle: RePEc:mve:journl:v:35:y:2009:i:2:p:61-79
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item

    JEL classification:

    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:mve:journl:v:35:y:2009:i:2:p:61-79. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Cullen Goenner (email available below). General contact details of provider: https://edirc.repec.org/data/mveaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.