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Dating the start of the US house price bubble: an application of statistical process control

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Abstract

An exact dating of the onset of financial crises is important to learn which factors have caused or contributed to the financial turmoil. While most economists agree that the recent worldwide financial crises evolved as a consequence of a bursting bubble on the US housing market, the related literature yet failed to deliver a consensus on the question when exactly the bubble started developing. The estimates in the literature range in between 1997 and 2002, while applications of market-based procedures deliver even later dates. In this paper, we employ the methods of statistical process control to date the likely beginning of the bubble. The results support the view that the bubble on the US housing market already emerged as early as 1996/1997.

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Notes

  1. The empirical analysis was conducted with R in combination with the mFilter package (Balcilar 2007).

  2. In Zeileis et al. (2005) either all data or a moving window with fixed size are used. Note that the CUSUM process of the structural change literature differs from the one in statistical process control. Both designs are also known in the SPC literature (repeated significance tests and moving average charts, respectively). However, since the CUSUM test in the structural change literature is dominated by the described CUSUM chart and the EWMA chart, it is rarely used in the SPC literature.

  3. Again, we used R for conducting our empirical analysis. In addition, we used the following R packages: spc (Knoth 2018), vars (Pfaff 2008a, b) and zoo (Zeileis and Grothendieck 2005).

  4. The unit-root tests were conducted using the R package “fUnitRoots” (Wuertz et al. 2017).

  5. For the corresponding EWMA series with \(\lambda =0.05\) and \(\lambda =0.20\), see Figures 10 and 11 in online appendix.

  6. The detailed CUSUM series can be found in Figures 12 and 13 in online appendix.

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Berlemann, M., Freese, J. & Knoth, S. Dating the start of the US house price bubble: an application of statistical process control. Empir Econ 58, 2287–2307 (2020). https://doi.org/10.1007/s00181-019-01648-x

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