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An Empirical Analysis on the Relationship between Stock Price, Interest Rate, Price Index and Housing Price using VAR Model

The Journal of Distribution Science / The Journal of Distribution Science, (P)1738-3110; (E)2093-7717
2013, v.11 no.10, pp.63-72
https://doi.org/https://doi.org/10.13106/jds.2013.vol11.no10.63.
Kim, Jae-Gyeong
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Abstract

Purpose - This study analyzes the relationship and dynamic interactions between stock price index, interest rate, price index, and housing price indices using Korean monthly data from 2000 to 2013, based on a VAR model. This study also examines Granger causal relationships among these variables in order to determine whether the time series of one is useful in forecasting another, or to infer certain types of causal dependency between stochastic variables. Research design, data, and methodology - We used Korean monthly data for all variables from 2000: M1 to 2013: M3. First, we checked the correlations among different variables. Second, we conducted the Augmented Dickey-Fuller (ADF) test and the co-integration test using the VAR model. Third, we employed Granger Causality tests to quantify the causal effect from time series observations. Fourth, we used the impulse response function and variance decomposition based on the VAR model to examine the dynamic relationships among the variables. Results - First, stock price Granger affects interest rate and all housing price indices. Price index Granger, in turn, affects the stock price and six metropolitan housing price indices. However, none of the Granger variables affect the price index. Therefore, it is the stock markets (and not the housing market) that affects the housing prices. Second, the impulse response tests show that maximum influence on stock price is its own, and though it is influenced a little by interest rate, price index affects it negatively. One standard deviation (S.D.) shock to stock price increases the housing price by 0.08 units after two months, whereas an impulse shock to the interest rate negatively impacts the housing price. Third, the variance decomposition results report that the shock to the stock price accounts for 96% of the variation in the stock price, and the shock to the price index accounts for 2.8% after two periods. In contrast, the shock to the interest rate accounts for 80% of the variation in the interest rate after ten periods; the shock to the stock price accounts for 19% of the variation; however, shock to the price index does not affect the interest rate. The housing price index in 10 periods is explained up to 96.7% by itself, 2.62% by stock price, 0.68% by price index, and 0.04% by interest rate. Therefore, the housing market is explained most by its own variation, whereas the interest rate has little impact on housing price. Conclusions - The results of the study elucidate the relationship and dynamic interactions among stock price index, interest rate, price index, and housing price indices using VAR model. This study could help form the basis for more appropriate economic policies in the future. As the housing market is very important in Korean economy, any changes in house price affect the other markets, thereby resulting in a shock to the entire economy. Therefore, the analysis on the dynamic relationships between the housing market and economic variables will help with the decision making regarding the housing market policy.

keywords
VAR, Stock Price, Price Index, Interest Rate, Housing Price Index

Reference

1.

Chang, Young Gil, & Lee, Chun Seob (2010). A Study on the Relation of Commercial Real Estate Market and Macroeconomic Factors. Korea Real Estate Review, 20(1), 87-113.

2.

Engle, F. A., & Granger, C. W. J. (1987). Cointegration and Error Correction: Representation, Estimation and Testing. Econometrica, 55(2), 251-276.

3.

Fama, E. (1981). Stock Returns, Real Activity, Inflation and Money. American Economic Review, 71, 545-565.

4.

Fama E., & Schwert, William (1979). Asset Returns and Inflation. Journal of Financial Economics, 5, 115-146.

5.

Goswami, G., & Jung, S.C. (1997). Stock Market and Economic Forces: Evidence from Korea. IMF Working Paper. From<http://papers. ssrn.com/so13/Delivery.cfm? abstractid=1937914>(Retrieved on April 6, 2012).

6.

Granger, C.W.J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(7), 424-438.

7.

Ji, Ho Jun (2001). The relationship between Housing Price and Chonsei Price. Housing Finance, 225, 1-26.

8.

Johansen, S. (1988). Statistical Analysis of Cointegration Vectors. Journal of Economic Dynamics and Control, 12, 231-254.

9.

Johansen, S., & Juselius, K. (1992). Testing Structural Hypotheses in a Multivariate Cointegration Analysis for the PPP and the UIP for U.K. Journal of Econometrics, 53, 211-244.

10.

Kim, Min Gyu, & Jang, Woo Jin (2010). Analysis of Foreign Investment on Bond Futures using VAR and VECM. Proceedings of 2010 Autumn Conference of The Korean Institute of Industrial Engineers (pp. 1-8). Seoul, Korea.

11.

Kim, Tae Ho (2008). Testing for the Statistical Interrelationship between the Real Estate and the Stock Markets. The Korean Journal of Applied Statistics, 21(3), 497-508.

12.

Kim, Yun-Yeong, & Park, Joon Yong (2009). Foreign Impulse Analysis for Korea in a Global Structural VAR Model. Kyong Je Hak Yon Gu, 57(2), 5-37.

13.

Lee, Jong Won, & Lee, Sang Don (1995). Econometric Analysis using Rats. Seoul, Korea: Parkyoungsa Publishing, 1038-1050.

14.

Lee, Jung-Wan (2012). The Impact of Foreign Exchange Rates on International Travel: The Case of South Korea. Journal of Distribution Science, 10(9), 5-11.

15.

Lee, Keun-Yeong (2002). An Analysis of Causality between Exchange Rates and Stock Prices. Kyong Je Hak Yon Gu, 50(4), 231-266.

16.

Lee, Keun Yeong (2006). Causal Relationships between Stock Returns and Inflation: The Case of Korea. Kyong Je Hak Yon Gu, 54(4), 189-222.

17.

Lee, Rae Yeong (2006). Real Estate Investment. Seoul, Korea: Samyoungsa Publishing, 161-162.

18.

Lee, Youngsoo (2012). Dynamics of Housing Price and Inflation in Korea. Journal of the Korea Real Estate Analysis Association, 18(4), 55-72.

19.

Lim, Jae Man (2002). The Integration with Real Estate Market and Financial Market. Journal of the Korea Real Estate Analysts Association, 8(1), 13-24.

20.

Moon, Kwon-Soon (1997). A understanding of Vector Autoregressive Model. Statistical Analysis Review, 2(1), 23-56.

21.

Park, Heon Soo, & An, Ji A (2009). The Sources of Regional Real Estate Price Fluctuations. Korea Real Estate Review, 19(1), 27-49.

22.

Ryu, Hyunwook, & Koh, Sungsoo (2012). An Empirical Study on the Relationship between Price Change and Trading Volume: Evidence from Seoul Housing Market. Journal of the Korea Real Estate Analysis Association, 18(3), 23-36.

23.

Sim, Sung-Hoon (2006). House Price and Macroeconomic Cycles: A Comparative Analysis of Pre- and Post Economic Crisis Periods. Journal of the Korea Real Estate Analysts Association, 12(1), 147-163.

24.

Son, Jong Chil (2010). Dynamic Analysis of Correlations among Monetary Policy, Real and Financial Variables and Housing Prices. Korea Real Estate Review, 58(2), 179-219.

25.

Song, Joonhyuk (2012). Analysis on Housing Rental and Sales Markets with Structural Breaks. Applied Economics, 14(1), 151-185.

26.

Yim, Byung-Jin, & Han, Sung Yun (2009). A Study on the Relationship between Return on Real Estate and Korea Composite Stock Price Index. Korean Industrial Economics Association, 22(4), 2065-2083.

27.

Yoo, Ji Soo (2007). A Study of Determination of Housing Prices and Housing Occupancy Choice. Applied Economics, 9(1), 199-217.

The Journal of Distribution Science