Abstract
Power law distributions have previously been observed in data like city-size distributions (Zipf’s Law), income distributions, and financial asset prices. In this paper, we explore the distribution of real estate prices in Charleston County, South Carolina. We fit power law, lognormal and exponential distributions to the data and compare the goodness of fit among the distributions. We find that the best fit distribution lies somewhere between the lognormal and power law distributions. We estimate how the power law exponent changes over time and find a potential relationship between the shape of the power law distribution and the bursting of the real estate bubble in 2007.
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