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Testing for the relationship between turnover ratio and price in Taiwan ’ s real estate market

Testing for the relationship between turnover ratio and price in Taiwan ’ s real estate market. Chou, Mei-Ling. Assistant Professor Nanya Institute of Technology. ERES Conference 2010, Milano, Italy. Background. Object. Data. Application. Conclusion.

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Testing for the relationship between turnover ratio and price in Taiwan ’ s real estate market

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  1. Testing for the relationship between turnover ratio and price in Taiwan’s real estate market Chou, Mei-Ling Assistant Professor Nanya Institute of Technology ERES Conference 2010, Milano, Italy

  2. Background Object Data Application Conclusion • Turnover ratio=housing flow divided by housing stock • The same housing flow not means the same supply. • I use the turnover ratio in place the transaction volume (housing flow).

  3. Background Object Data Application Conclusion Summer 2007 U.S. subprime mortgage crisis 2009.5.20 R.O.C. Presidential election SARS 2009.9 Global financial crisis

  4. Background Object Data Application Conclusion • To test the stationary of the turnover ratio by unit root test . • To built the VAR (Vector Autoregression) model to evaluate how the turnover ratio influence the housing price. • We use the VAR Granger Causality Tests to test the lead and lag relations of turnover ratio and housing price.

  5. Background Object Data Application Conclusion

  6. Background Object Data Application Conclusion the variables are stationary after 1st difference

  7. Background Object Data Application Conclusion • the Johansen(1991) test with a structural break in short-run dynamics is used to examine the number of common trends in the series. • the turnover ratio and log unit price in Taiwan and in Taipei all have cointegration relation. • The results examine the stability of long-run parameters under unstable short-run parameters.

  8. Background Object Data Application Conclusion + Log unit price(t-1) Log unit price(t) Taiwan Turnover ratio(t-1) Turnover ratio(t) — + Log unit price(t-1) Log unit price(t) Taipei Turnover ratio(t-1) Turnover ratio(t) + • the error correction model(ECM) is estimated and Granger causality for cross-relationship is defined in the context of the error correction model. Positive effect Negative effect

  9. Background Object Data Application Conclusion • Taiwan: the lead and lag relation of TRATIO and DTPPRICE in Taiwan is not significant. • Taipei: the turnover ratio leads the log unit price two period.

  10. Background Object Data Application Conclusion • The impulse response functions of these spreads and their standard errors are derived to inspect the speed of the market adjustment to a shock. • There has a jump response of log unit price to one S.D innovation of turnover ratio. • The response of turnover ratio to one S.D. innovation of log unit price is short-run, and the response is larger in Taipei.

  11. Background Object Data Application Conclusion • The variance of TRATIOt-1 (or DTPPRICEt-1) can explained by itself above 98%. • To have the data of TRATIOt-1 can explain the variance of unit price 31% in 4th period.

  12. Background Object Data Application Conclusion • The variance of TCRATIOt-1 (or DTCPPRICEt-1) can explained by itself above 95%. • To have the data of TREATIOt-1 only can explain the variance of unit price 3% in 3rd period.

  13. Background Object Data Application Conclusion • Unit root test: • The turnover ratio and unit price would be stable after a long period. • Johansen Cointegration test: • The turnover ratio and log unit price in Taiwan and in Taipei were stability of long-run parameters under unstable short-run parameters. • Impulse response function: • When a unexpected shock of turnover ratio, the variance of unit price is long-run. • If there has a unexpected shock of unit price variance, the effect on turnover ratio is large and short-run. • To have more information of turnover ratio would be helpful to explain the unit price variance.

  14. The End Thanks for your listening!

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