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Scaling behavior in land markets

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  • Taisei Kaizoji

Abstract

In this paper we present an analysis of power law statistics on land markets. There have been no other studies that have analyzed power law statistics on land markets up to now. We analyzed a database of the assessed value of land, which is officially monitored and made available to the public by the Ministry of Land, Infrastructure, and Transport Government of Japan. This is the largest database of Japan's land prices, and consists of approximately 30,000 points for each year of a 6-year period (1995-2000). By analyzing the data on the assessed value of land, we were able to determine the power law distributions of the land prices and of the relative prices of the land. The data fits to a very good degree the approximation of power law distributions. We also found that the price fluctuations were amplified with the level of the price. These results hold for the data for each of the 6 annual intervals. Our empirical findings present the conditions that any empirically accurate theories of land market must satisfy.

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Bibliographic Info

Paper provided by arXiv.org in its series Papers with number cond-mat/0302470.

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Date of creation: Feb 2003
Date of revision: Mar 2006
Publication status: Published in Physica A326 (2003) 256-264
Handle: RePEc:arx:papers:cond-mat/0302470

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Web page: http://arxiv.org/

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  1. repec:fth:osakae:408 is not listed on IDEAS
  2. Ogawa, Kazuo & Suzuki, Kazuyuki, 1998. "Land Value and Corporate Investment: Evidence from Japanese Panel Data," Journal of the Japanese and International Economies, Elsevier, vol. 12(3), pages 232-249, September.
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Cited by:
  1. Claes Andersson & Koen Frenken & Alexander Hellervik, 2006. "A complex network approach to urban growth," Environment and Planning A, Pion Ltd, London, vol. 38(10), pages 1941-1964, October.
  2. Andersson, Claes & Hellervik, Alexander & Lindgren, Kristian, 2005. "A spatial network explanation for a hierarchy of urban power laws," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 345(1), pages 227-244.
  3. Morales, Raffaello & Di Matteo, T. & Gramatica, Ruggero & Aste, Tomaso, 2012. "Dynamical generalized Hurst exponent as a tool to monitor unstable periods in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3180-3189.
  4. Raffaello Morales & T. Di Matteo & Ruggero Gramatica & Tomaso Aste, 2011. "Dynamical Hurst exponent as a tool to monitor unstable periods in financial time series," Papers 1109.0465, arXiv.org.

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