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A Dynamic Study on Housing and Stock Market in Europe: Focused on Greece

East Asian Journal of Business Economics / East Asian Journal of Business Economics, (E)2288-2766
2020, v.8 no.1, pp.57-69
https://doi.org/10.20498/eajbe.2020.8.1.57
Jeong, Dong Bin
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Abstract

Purpose – This study examines what are the asset market fluctuations in Europe and how each economic variable affects major variables, and explore the dynamics of housing and stock market through Greece. The variables under consideration are balance on current account, index of stock, gross domestic product, housing price indices, M3, real tare of interest and household credits. We investigate the functional and causal relationships between housing and stock market. Research design, data, and methodology – Vector error correction model (VECM) is used to figure out the dynamic relationships among variables. This study also contains the augmented Dickey-Fuller unit root, cointegration test, Granger causality test, impulse response function and variance decomposition analysis by EViews 11.0. Results – The statistical tests show that all variables under consideration have one unit root and there is a long-term equilibrium relationship among variables for Greece. GDP, IR_REAL, M3, STOCK ana LOAN can be considered as causal factors to affect real estate market, while GDP, LOAN, M3, BCA and HOUSING can bring direct effects to stock market in Greece. Conclusions – It can be judged that the policy that affects the lending policy of financial institutions may be more effective than the indirect variable such as monetary interest rate.

keywords
Cointegration, Unit root test, Vector Error Correction model

Reference

1.

Bae, B.I. (2016). European fiscal crisis and economic integration: evolution of and the challenges to the European union. Journal of Contemporary European Studies, 34(4), 393-415.

2.

Cho, D. (2006). Introductory Financial Econometrics. Seoul, Korea: Cheongram Academy.

3.

Dickey, D.A. & Fuller, W.A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(1), 427–431.

4.

Engle, R.F. & Granger, C.W.J. (1987). Co-integration and error correction: representation, estimation and testing. Econometrica, 55(2), 251–276.

5.

Gourinchas. P. O., & Obsfeld, M. (2012). Stories of the twentieth century for the twenty-first. American Economic Journal: Macroeconomics. 4(1), 226-265.

6.

Granger, C. W. J. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37(3), 424–438.

7.

Granger, C.W.J. (1980). Testing for causality: a personal viewpoint. Journal of Economic Dynamics and Control, 2(1), 329–352.

8.

Granger, C.W. J. (2004). Time series analysis, cointegration, and applications. American Economic Review, 94(3), 421–425.

9.

Hatemi-J, A. (2014). Asymmetric generalized impulse responses with an application in finance. Economic Modelling, 36(1), 18–22.

10.

Koo, C. K. (2015). Formation of Euro capitalism and restructuring of German model. Korean and World Politics, 32(4), 107-145.

11.

Lütkepohl, H. (2007). New Introduction to Multiple Time Series Analysis. Berlin: Springer-Verlag.

12.

Park, H. M. & Yi, C. D. (2014). A VECM analysis of monetary and fiscal policies for the EU. Journal of Contemporary European Studies, 32(1), 331-372.

13.

Reinhart, C. M., & Rogoff, K. S. R. (2009). The aftermath of financial crises. American Economic Review, 99(2), 466-472.

14.

Said, S. E. & Dickey, D. A. (1984). Testing for Unit Roots in Autoregressive-Moving Average Models of Unknown Order. Biometrika, 71(3), 599–607.

15.

Schularick, M., & Taylor, A. M. (2012). Credit booms gone bust: monetary policy, leverage cycles, and financial crises, 1870-2008. American Economic Review, 102(2), 1029-61.

16.

Sims, C. A. (1980). Macroeconomics and reality. Econometrica, 48(1), 1-48.

East Asian Journal of Business Economics