서강대학교

초록/요약

This study used the number of newspaper articles as a proxy variable to analyze the correlation between information arrival, house prices and trade volume. Prior studies have uncovered the relationship between two variables, such as price and trade volume or price and information arrival, but the simultaneous relationship between all three variables has largely been untouched. The number of newspaper articles was processed into data by selecting a keyword that appropriately reflects market change via online search engines. Monthly data from the Seoul and Kangnam area(Which includes Kangnam, Sucho and Songpa Gu districts) residential housing market from 1999 to 2005 provided core information for house prices and trading volume. Considering the synchronism of all three variables, simultaneous structural regression equation estimate and Vector Auto-Regression analysis(VAR) were used to analyze the data. An empirical analysis on simultaneous relationship revealed that indirect effects, in which an increase of newspaper articles causes panic buying and this in turn causes prices and trading volume to rise, and direct effects, in which news itself directly effects trading volume, exist simultaneously all over Seoul. In the case of Kangnam, news was found to directly effect trading volume. And a dynamic causal relationship analysis indicated that news affected price levels in both Kangnam and the whole of Seoul, and this in turn had an effect on trading volume. In the two analyses it also turned out that news had a larger impact in Kangnam, where the housing market is over-heated, than entire Seoul.