計畫編號：NSC91-2416-H032-015研究期間：200208~200307研究經費：381,000[[sponsorship]]行政院國家科學委員

聶建中

計畫編號：NSC91-2416-H032-015研究期間：200208~200307研究經費：381,000行政院國家科學委員

Tamkang University Institutional Repository

????????????????  ????   ??????????????????????????????   ?????????? ?????NSC91-2416-H-032-015- ?????91?08?01??92?07?31? ??????????????     ?????????      ?????????  ?????????????     ? ? ? ? 92?10?31?  1???????????????????? ???????????????????-?????????? The Reality of the CPI and the Efficiency of the Asset Investment - Evidence from Taiwan's Real Estate and Stock Markets   ????: NSC 91-2416-H-032-015 ????:  91 ? 8? 1? ? 92? 7? 31? ???: ? ? ?  ????:  ???? TEL: 886-2-2621-5656 ext.2591.  E-Mail: niehcc@mail.tku.edu.tw Abstract     This research attempts to judge the reality of the price index without incorporating the prices of stock and real estate and to analyze the efficiency of the diversification when investing in both assets of stock and real estate over the period of 1986Q1 to 2002Q3 in Taiwan by employing various multivariate VAR models. The empirical results first indicate that diversification by investing in both assets of stock and real estate is fruitless since the market is efficient. Granger causality tests provide us perceptual information that the price index without incorporating the prices of stock and real estate is spurious. Nonetheless, the formulating of a STECM is not necessary since the linear functional form is not violated in our examination. Key Words: Stock price, Real Estate Price, Consumer Price Index, ARDL, STECM  I. Introduction Without considering the asset prices of stock and real estate, the consumer price index (CPI) in Taiwan seems not appropriate one to reflect the real price level.  There is probably another type of inflation latent if the asset prices of stock and real estate are incorporated into the price index.  Moreover, the interrelationships between real estate price and stock price are generally acknowledged strong (see e.g., Gyourko and Keim, 1992, Goldstein and Nelling, 1999, and Fu and Ng, 2001).  The up-and-down of the stock trend drives the fluctuation of a country's economy, which in turn causes a strong impact on the price of the real estate market. Testing for the causal relation between stock and real estate markets can be found in Liu et al. (1990), Eichholtz(1997), Okunev and Wilson(1997), and He(2000). Therefore, this study tries to employ various time-series methodologies, using Taiwan as the sample base, to investigate the long-run equilibrium and the short-run dynamic relationship among CPI, stock price and real estate price. The findings of this study are used to (1) judge the reality of the price index without incorporating the prices of stock and real estate and (2) analyze the efficiency of the diversification when investors decide to invest in both assets of stock and real estate.   II. Data The data sets used here consist of quarterly time series on stock price index, real estate price index and consumer price index covering the period of 1986Q1 to  22002Q3.  Stock price index and consumer price index were obtained from the AREMOS database of the Ministry of Education of Taiwan.  Real estate price index was collected and constructed by Hsin-Yi Real Estate Inc.  Examination of the individual data series makes it clear that the logarithmic transformations were required to achieve stationarity in variance; therefore, all the data series were transformed to logarithmic form.  III. Methodologies and Empirical Results A. Unit Root Tests In this study we apply several conventional unit root tests, such as ADF, PP, KPSS, DF-GLS, ERS, and NP.  Empirical results indicate that CPI is integrated of order one, I(1), whereas mixed results of I(0) and I(1) are come out for both series of stock price index and real estate price index.   B. ARDL Bounding Test Since the cointegrating vector incorporates both I(0) and I(1) series, the ARDL-UECM bounding test developed by Pesaran et al. (2001)  is thus an appropriate method to examine the long-run relationship between the three variables considered in this paper. ( ARDL have been widely employed since then, e.g., Abbot, Darnell and Evans (2001, exchange rate for the UK), Bentzen and Engsted (2001, energy for Denmark), Ghatak and Siddiki (2001, exchange rate for India), Atkins and Coe (2002, Fisher effect for the US and Canada), Bahmani-Oskooee and Ng (2002, money demand for HK), Fedderke and Liu (2002, capital flow for South Africa), Tang and Nair (2002, import demand for Malaysia), Vita and Abbott (2002, saving and investment for the US), and Bahmani-Oskooee and Goswami(2003, J curve for Taiwan)).  The uni-equation of the ARDL-UECM model in our study is expressed as the following form: ttrtstpnj jtrjdnj jtsjcnj jtpjbtp εφφφ +−+−+−+∑=−∆∑=+−∆∑=+−∆=∆ 131211302011  where p, s, and r represent CPI, stock price, and real estate price, respectively. All these variables are taken into a logarithm form.  Since the appropriate lag length is crucial for the credibility of the VAR’s result, we adopted the MAIC suggested by Ng and Perron (2001) to select the lag length and found that lags of 2, 8, and 7 (n1, n2, and n3) for CPI, stock price, and real estate price, respectively, are most appropriate for our model. That is, an ARDL-UECM-MAIC(2, 8, 7) model is constructed.    The result of ARDL bounding test shows that the F-statistic is larger than the critical value of the upper bound, boundary for I(1), which indicates that there exists a long-run level relationship among these three variables. This long-run relationship in turn connotes the existence of a efficiency market hypothesis (EMH). Thus, diversification by investing in both assets of stock and real estate is fruitless. C. Granger Causality Test Nonetheless, Granger causality test is applied for the lead-lag examination among our three variables. The results based on multivariate VAR model significantly indicate that there exists unidirectional causal relation running from each of the real estate price index and the stock price index to consumer price index.  This empirical finding provides us perceptual  3information that the price index constituted without incorporating the prices of stock and real estate might be spurious. This ‘spurious price index’ contains an important policy implication in constructing consumer price index in Taiwan.  D. Variance Decomposition and General Impulsive Function Though VDC gives us similar result to those found in Granger causality test, however, G-IRF give us different result.  We find no interaction among these three variables. E. Stability Test Based on the CUSUM and CUSUMSQ plots, we find that our estimated model is stable. F. Nonlinear Test This paper further employs smooth transition error correction model (STECM) proposed by Granger and Teräsvirta(1993) and Teräsvirta(1994) to examine the linear vs. nonlinear adjustment of the ECM by looking at different non-linear functional forms of the disequilibrium error. Van Dijk and Teräsvirta(2000) has a good survey for the recent developments of smooth transition autogressive (STAR) models and several good applications of STECM can be found in Huang, Lin and Cheng(2001) and Milas and Otero(2002), among others. The STECM is formulated as following form: tdtttt crzFWWy µθθππ ++++=∆ − ),;()( /10/10where ///11 ),...,,,...,,( pttptttt XXyyZW −−−− ∆∆∆∆= and ),0(~ 2σµ NIDt . The coefficient vector 1π  has a dimension of 1×m  and )1)(1( ++= kpm . The function ),;( crzF dt−  is a continuous transition function with the transition variable dtz −  and parameter (r, c) that provides a variety of nonlinear models, e.g., logistic, exponential or quadratic logistic functions.  In this paper, residlp(-1) is used as a transition variable, d is selected to be 4 since the p-value of H0 reaches the lowest one (0.238) when d=4 and the logistic function is adopted for our STECM because of that H03 has the lowest p-value of 0.0328 comparing with H02 and H01 (0.763 and 0.777) under d=4. Though we construct a nonlinear form for our examination, the result shows that the linear functional form is not mis-specified, which indicates that no nonlinear effect exists in the model.   IV. Conclusion Employing various multivariate VAR models over the period of 1986Q1 to 2002Q3, this research attempts to (1) judge the reality of the price index without incorporating the prices of stock and real estate and (2) analyze the efficiency of the diversification when investing in both assets of stock and real estate, by investigating, linearly and nonlinearly, the long-run and short-run interrelation among consumer price index, stock price and real estate in Taiwan. Our empirical results indicate that there exists a long-rung level relation among these variables. Diversification by investing in both assets of stock and real estate is thus fruitless since the market is efficient. Granger causality tests show a unidirectional causality relation running from each of the stock price index and the real estate price index to  4consumer price index. This empirical finding provides us perceptual information that the price index without incorporating the prices of stock and real estate might be spurious. This ‘spurious price index’ contains an important policy implication in constructing consumer price index in Taiwan. Nonetheless, both the stability test and the linearity test show that the formulating of a STECM is not necessary since our estimated model is stable and the linear functional form is not violated in our examination.   [References] 1. Abbot, A., A. Darnell and L. Evans (2001), “The influence of exchange rate variability on UK exports,” Applied Economics Letters, 8, 47-49. 2. Atkins, F. J. and P. J. Coe (2002), “An ARDL bounds test of the long-run Fisher effect in the United States and Canada”, Journal of Macroeconomics, 24(2), 255-266. 3. Bahmani-Oskooee, M. and G. G. Goswami (2003), “A disaggregated approach to test the J-curve phenomenon: Taiwan versus her major trading partners,” Journal of economics and finance, 27, 1, 102-113. 4. Bahmani-Oskooee, M. and R. Ng, (2002), “Long-run demand for money in Hong Kong: An application of the ARDL model,” International Journal of Business and Economics, 1(2) 147-155. 5. Bentzen, J. and T. Engsted (2001), “A revival of the autoregressive distributed lag model in estimating energy demand relationships,” Energy, 26, 45-55. 6. Eichholtz, M. A. Piet, (1997), “Real Estate Securities and Common Stocks: A First International Look.” Real Estate Finance, 14, 70-74. 7. Fedderke, J.W. and W. Liu (2002), “Modelling the determinants of capital flows and capital flight:  with an application to South African data from 1960 to 1995,” Economic modeling, 19, 419-444. 8. Fu, Yuming and Lilian K Ng, (2001), “Market efficiency and return statistics: Evidence from real-estate and stock markets using a present-value approach,” Real Estate Economics, 29(2). 227-250  9. Goldfajn, I., and P. Gupta (2001), “Overshootings and Reversals: The Role of Monetary Policy”, Central Bank of Chile Working Paper, No. 126, 279-302. 10. Goldstein, A. Michael and Edward F. Nelling (1999), “REIT Return Behavior in Advancing and Declining Stock Markets.” Real Estate Finance, 15, 68-77.  11. Granger, C.W.J., and T. Terasvirta (1993), Modelling Nonlinear Economic Relationships, Oxford University Press, Oxford. 12. Gyourko, J. and D. Keim, “What Does the Stack Market Tell Us About Real Returns.” Journal of the American Real Estate and Urban Economics Association, (1992), 20, pp.457-486. 13. He, Ling T.,  "Causal relationships between apartment REIT stock returns and unsecuritized residential real estate," Journal of Real Estate Portfolio Management, 2000, 6(4), 365-372 14. Huang, Cliff J., Chien-Fu Jeff Lin and Jen-Chi Cheng, (2001), “Evidence on nonlinear error correction in money demand: the case of Taiwan,” Applied Economics, 33, 1727-1736 15. Liu, C.H., D. Hartzell, D.W. Grei,o and T.V. Crissom, “The Integration of the Real Estate Market and the Stock Market: Some Preliminary Evidence.” Journal of the American Real Estate  5and Urban Economics Association, (1990), 3, pp.261-282. 16. Milas, Costas and Jesus Otero, (2002), “Modelling Official and Parallel Exchange Rates in Colombia under Alternative Regimes: A Non-linear Approach,” Economic Modelling, 20, 165-179 17. Pesaran, M. H., Y. Shin, and R. J. Smith (2001), “Bounds Testing Approaches to the Analysis of Long-Run Relationship”, Journal of Applied Econometrics, 16, 289-326 18. Okunev, John and Patrick J. Wilson. (1997), “Using Nonlinear Test to Examine Integration Between Real Estate and Stock Markets,” Real Estate Economics, 25, 487-503.  19. Tang, T. C. and M. Nair (2002), “A Cointegration Analysis of Malaysian Import Demand Function: Reassessment from the Bounds Test”, Applied Economics Letters, 9(5), 293-296. 20. Terasvirta, T. (1994), “Specification, Estimation and Evaluation of Smooth Transition Autoregressive Models,” Journal of American Statistic Association, 89, 208-218. 21. Van Dijk, D., T. Terasvirta and P.H. Franses (2002), “Smooth Transition Autoregressive Models -- A Survey of Recent Developments,” Econometric Reviews, 21(1), 1–47 22. Vita, G. D. and A. Abbott (2002), ”Are Saving and Investment Cointegratd? An ARDL Bounds Testing Approach”, Economics Letters, 2002, 77(2), 293-299                                              1?????????????????????? ?????????????????????????     ?                                              ? ? The Reality of the CPI and the Efficiency of the Asset Investment   ? ?      -- Evidence from Taiwan's Real Estate and Stock Markets  ? ?                       ??????????????????????????  ?????;?????  ?????? ?????NSC  91-2416-H-032-015 ?????91? 8? 1?? 92? 7? 31?  ?????? ? ? ? ?????? ???????         ???????????????? ??????????????? ????????????????? ?????????????????????? ??????????????????    ????? ??????????   ? ? ? ? 92?  7 ? 31 ? 

The Reality of the CPI and the Efficiency of the Asset Investment - Evidence from Taiwan$s Real Estate and Stock Markets-

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