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Regional Housing Prices in the USA: An Empirical Investigation of Nonlinearity

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  • Sei-Wan Kim

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  • Radha Bhattacharya

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Abstract

Existing literature on housing prices is predominantly in a linear framework, and an important question that has not been addressed is whether housing prices exhibit nonlinearity. We examine Smooth Transition Autoregressive (STAR) model based nonlinear properties of housing prices over the 1969–2004 period for the entire US and the four regions. Our main findings are (1) housing price for the entire US and all regions except for the Midwest show non-linearity, (2) the dynamic properties implied by the nonlinear estimation explain the typical patterns that have characterized each housing market, and (3) results of Granger causality tests look more plausible in the nonlinear framework where we find stronger evidence of Granger causality from housing price to employment and also from mortgage rates to housing price. Copyright Springer Science+Business Media, LLC 2009

Suggested Citation

  • Sei-Wan Kim & Radha Bhattacharya, 2009. "Regional Housing Prices in the USA: An Empirical Investigation of Nonlinearity," The Journal of Real Estate Finance and Economics, Springer, vol. 38(4), pages 443-460, May.
  • Handle: RePEc:kap:jrefec:v:38:y:2009:i:4:p:443-460
    DOI: 10.1007/s11146-007-9094-y
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Petra Posedel & Maruška Vizek, 2011. "Are House Prices Characterized by Threshold Effects? Evidence from Developed and Post-Transition Countries," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(6), pages 584-600, December.
    2. Tsangyao Chang & Tsung-Pao Wu & Rangan Gupta, 2015. "Are house prices in South Africa really nonstationary? Evidence from SPSM-based panel KSS test with a Fourier function," Applied Economics, Taylor & Francis Journals, vol. 47(1), pages 32-53, January.
    3. Tsai, I-Chun & Peng, Chien-Wen, 2016. "Linear and nonlinear dynamic relationships between housing prices and trading volumes," The North American Journal of Economics and Finance, Elsevier, vol. 38(C), pages 172-184.
    4. Rangan Gupta, 2012. "Forecasting House Prices for the Four Census Regions and the Aggregate US Economy: The Role of a Data-Rich Environment," Working Papers 201214, University of Pretoria, Department of Economics.
    5. Natalia Bailey & Sean Holly & M. Hashem Pesaran, 2016. "A Two‐Stage Approach to Spatio‐Temporal Analysis with Strong and Weak Cross‐Sectional Dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 249-280, January.
    6. repec:ire:issued:v:20:n:02:2017:p:127-165 is not listed on IDEAS
    7. Barros, Carlos Pestana & Gil-Alana, Luis A. & Payne, James E., 2012. "Comovements among U.S. state housing prices: Evidence from fractional cointegration," Economic Modelling, Elsevier, vol. 29(3), pages 936-942.
    8. Amina Ahec Šonje & Anita Ceh Casni & Maruška Vizek, 2012. "Does housing wealth affect private consumption in European post-transition countries? Evidence from linear and threshold models," Post-Communist Economies, Taylor & Francis Journals, vol. 24(1), pages 73-85, June.
    9. Zhang, Wei-Bin, 2016. "Economic Globalization and Interregional Agglomeration in a Multi-Country and Multi-Regional Neoclassical Growth Model," INVESTIGACIONES REGIONALES - Journal of REGIONAL RESEARCH, Asociación Española de Ciencia Regional, issue 34, pages 95-121.
    10. Balcilar, Mehmet & Gupta, Rangan & Shah, Zahra B., 2011. "An in-sample and out-of-sample empirical investigation of the nonlinearity in house prices of South Africa," Economic Modelling, Elsevier, vol. 28(3), pages 891-899, May.
    11. Tsangyao Chang & Wen-Chi Liu & Goodness C. Aye & Rangan Gupta, 2016. "Are there housing bubbles in South Africa? Evidence from SPSM-based panel KSS test with a Fourier function," Global Business and Economics Review, Inderscience Enterprises Ltd, vol. 18(5), pages 517-532.
    12. Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2012. "The Out-of-Sample Forecasting Performance of Non-Linear Models of Regional Housing Prices in the US," Working Papers 1209, University of Nevada, Las Vegas , Department of Economics.
    13. Torben Klarl, 2016. "The nexus between housing and GDP re-visited: A wavelet coherence view on housing and GDP for the U.S," Economics Bulletin, AccessEcon, vol. 36(2), pages 704-720.
    14. Christophe Andre & Rangan Gupta & John W. Muteba Mwamba, 2016. "Are Housing Price Cycles Asymmetric? Evidence from the US States and Metropolitan Areas," Working Papers 201635, University of Pretoria, Department of Economics.
    15. Nissan, Edward & Payne, James E., 2013. "A Simple Test of σ-Convergence in U.S. Housing Prices across BEA Regions," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 43(2).
    16. Katrakilidis, Constantinos & Trachanas, Emmanouil, 2012. "What drives housing price dynamics in Greece: New evidence from asymmetric ARDL cointegration," Economic Modelling, Elsevier, vol. 29(4), pages 1064-1069.
    17. MeiChi Huang, 2014. "Monetary policy implications of housing shift-contagion across regional markets," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 38(4), pages 589-608, October.
    18. Canepa, Alessandra & Chini, Emilio Zanetti, 2016. "Dynamic asymmetries in house price cycles: A generalized smooth transition model," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 91-103.

    More about this item

    Keywords

    Housing market; STAR; Granger causality; Dynamic property; R10; R21; C12; C13; C32; G10;

    JEL classification:

    • R10 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - General
    • R21 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Housing Demand
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: 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
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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