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A Dynamic Relationship Between Internet Search Activity, Housing Price, and Trading Volume

±è´ë¿ø(Kim, Dai Won) , À¯Á¤¼®(Yu, Jung Suk) Àú

pp.125~140 (16pages)

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In the housing market, the internet searching activity trail means collective thinking and represents purchase intent. Therefore, if we can capture the meaningful relationship between the internet searching activity, the housing price, and the housing trading volume, it would mean we can predict the future using the internet searching activity data as a index for the housing market. In this context, we conducted the empirical research to examine the dynamic relationship between the internet searching activity and the housing price and trading volume.
Using the ¡°NAVER Trend data as a proxy for the internet searching activity, the apartment sale price index as a proxy for the housing price, and the apartment trading volume index as a proxy for the housing trading volume, we set up the panel data of 23 autonomous districts in Seoul form Jan. 2007 to Feb. 2014.
In results from the Arellano-Bond dynamic panel model, we found that the internet searching activity had an positive(+) effect on the housing price and trading volume with some time lags. From the results of IRFs and FEVDs derived from the panel VAR model analysis, we also found that the internet searching activity had the strongest effect on housing market at the first order lag and influences much more on the housing price rather than the trading volume. In addition, panel Granger causality test results showed that the internet searching activity and the housing price, the housing price and trading volume had mutual cyclic causalities each other.

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