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Reexamining the relationships between stock prices and exchange rates in ASEAN-5 using panel Granger causality approach
Economic Modelling 32 (2013) 560–563
Contents lists available at SciVerse ScienceDirect
Economic Modelling journal homepage: www.elsevier.com/locate/ecmod
Reexamining the relationships between stock prices and exchange rates in ASEAN-5 using panel Granger causality approach Chin-Chia Liang a, Jeng-Bau Lin b,⁎, Hao-Cheng Hsu c a b c
Department of Finance, Dayeh University, Changhua 51591, Taiwan Department of Business Administration, National Chung Hsing University, Taichung, Taiwan Department of Finance, National Chung Hsing University, Taichung, Taiwan
a r t i c l e
i n f o
Article history: Accepted 1 March 2013 Keywords: ASEAN-5 Stock-oriented hypothesis Capital mobility Economic fundamentals Panel Granger-causality Dynamic ordinary least squares
a b s t r a c t We revisit the relationships between the equity market and currency market in ASEAN-5 using the panel Granger causality and panel DOLS methodologies. Our results support the “stock-oriented” hypothesis of exchange rates proposed by Branson (1983) and Frankel (1983), which states that exchange rates impact stock prices negatively via capital mobility. Meanwhile, on a per country and panel basis, the testing results using the DOLS approach match those of the short-run and long-run causal relations running from exchange rates to stock prices. These findings suggest that the monetary authorities for the ASEAN-5 should keep allowing their currency values of being determined by the economic fundamentals instead of interrupting them only in order to stimulate export growth unless a great deal of short-term speculative funds (hot money) flow into the currency markets. © 2013 Elsevier B.V. All rights reserved.
1. Introduction The 1997 Asian financial crisis has stimulated the monetary authorities of the ASEAN to undertake a crucial reform in the exchange rate regimes. The tremendous changes in exchange rates since then have raised a higher risk of international economic transaction. Meanwhile, the rapid integration of various international financial markets in this region has promoted interactive relations among macroeconomic factors (see Hatemi and Roca, 2005; Pan et al., 2007; Tai, 2007). Faced with the high integration of these financial markets, the investors of the ASEAN seemed to have more opportunities to diversify their investment portfolios internationally (see Doong et al., 2005; Lin, 2012; Tsai, 2012). In addition, such a rapid integration of capital and currency markets also has attracted much attention to academicians and practitioners since the late 1990s for these economies. However, as mentioned above, when international investors in capital markets are engaged in cross-border transactions, they are potentially exposed to foreign exchange risk. Hence, for researchers, there has been an increasing concern and interest in the dynamic relationships among the prices of financial assets. Recently, some academic studies on financial asset prices mainly focused on stock prices and exchange rates. Two theoretical models linking equity markets and currency markets can account for this relationship. First, the “flow-oriented model” states that exchange rates influence stock prices positively based on the hypothesis that
⁎ Corresponding author. E-mail address: [email protected] (J.-B. Lin). 0264-9993/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.econmod.2013.03.001
exchange rate changes influence real output and hence stock prices via international competitiveness and trade balance in general (see Dornbusch and Fischer, 1980). The empirical evidence supported the flow-oriented hypothesis of exchange rates (see Chiang et al., 2000; Fang, 2002; Phylaktis and Ravazzolo, 2005; Wongbangpo and Sharma, 2002; Wu, 2000). Second, the “stock-oriented model” states that stock prices impact exchange rates negatively, and vice versa, via (short-term) capital mobility in capital accounts (see Branson, 1983; Frankel, 1983). The empirical evidence favored the stock-oriented hypothesis of exchange rates (see Aggarwal, 1981; Gavin, 1989; Ibrahim and Aziz, 2003; Kwona and Shinb, 1999; Maysami and Koh, 2000; Soenen and Hennigar, 1988; Tai, 2007; Tsai, 2012). Furthermore, in the short-run causality test there were several previous studies surveying unusual and unexpected movements in the equity market and the currency market. So far, the empirical findings on the causal relationship between the two variables have been mixed. One group of researches supported the result that exchange rates Granger cause stock prices (see Abdalla and Murinde, 1997; Doong et al., 2005; Hatemi and Roca, 2005; Ibrahim, 2000; Pan et al., 2007). Other studies provided some evidence that stock prices Granger cause exchange rates (see Ajayi et al., 1998; Doong et al., 2005; Granger et al., 2000; Hatemi and Roca, 2005; Lin, 2012; Pan et al., 2007). As indicated in the above literature, however, there has been a proliferation of such studies using different techniques, time periods and sample of countries. 1 1 If the referenced papers are cited in this study, this represents that there exists a uni-directional or bi-directional causal relationship between exchange rates and stock prices.
C.-C. Liang et al. / Economic Modelling 32 (2013) 560–563 Table 1 Panel heterogeneous unit root test results. Variables
SP EX
Table 2 Pedroni's heterogeneous panel cointegration test results.
IPS Level
First difference
1.5661 2.1636
−11.8393⁎⁎ −10.5291⁎⁎
⁎⁎ Denote significance at the 5% level.
The aim of this paper, therefore, is to reexamine the relationship between stock prices and exchange rates for the ASEAN-5 economies using panel methodology. Our paper differs from previous works in that we apply panel methods to test for unit roots, cointegration and short-run and long-run Granger causality relationships between the variables in this study. The group of novel methods has three advantages: (i) to increase the sample size and power of test, (ii) to allow for heterogeneity among countries, and (iii) to check for robustness of the empirical results by contrasting the panel short-run and long-run causality results with those from the individual estimation using a vector error correction model (VECM) for each country. The remainder of this study is structured as follows. Section 2 describes the data and methodology used in this study. Section 3 contains empirical results and interpretations. Finally, Section 4 concludes with policy implications. 2. Data and methodology The monthly data on the series of stock prices (SP) and exchange rates (EX) are sourced from DataStream covering the period 2008/8–2011/6 for the ASEAN-5. The ASEAN-5 countries include Indonesia, Malaysia, Philippines, Singapore and Thailand. The stock indices of the stock exchange of the ASEAN-5 are used for stock prices. The exchange rates are denominated in terms of the US dollar. The two variables surveyed here take a logarithm form. To re-investigate the causal relationships between stock prices and exchange rates for the ASEAN-5, we propose to conduct three tests such as the panel unit-root test, the panel cointegration test and the panel causality test, and the estimation of panel dynamic ordinary least squares (DOLS). In examining the causal relationships between the two variables, the long-run and short-run causality testing methods are employed in this study. 3. Empirical results First, this paper employs the Im, Persaran and Shin (IPS) (Im et al., 2003) panel unit-root test. 2 The results of these tests are reported in Table 1, indicating that the statistics significantly confirm that the level values of all series are non-stationary; that is, all variables are I(1). After the first differencing, all the variables are stationary at the 5% significance level. The next step is to test whether a long-run relationship exists between them. Here, the panel cointegration tests developed by Pedroni (2000, 2004) are conducted to test the long-run cointegrating relation of stock prices with exchange rates. The test allows for heterogeneity in the intercepts and slopes of the cointegration equation. Pedroni (2000, 2004) provides seven statistics for the test of the null of no cointegration in heterogeneous panels. Pedroni's seven statistics are based on the estimated residuals from the panel cointegration regression as follows: SP i;t ¼ α i þ δi t þ βi EX i;t þ νi;t 2
561
Within-dimension
Test statistic
Between-dimension
Test statistic
Panel Panel Panel Panel
1.2777⁎ −1.5164⁎ −1.8741⁎⁎ −2.2811⁎⁎
Group rho-statistic Group PP-statistic Group ADF-statistic
−0.4877 −1.5139⁎ −1.7082⁎⁎
v-statistic rho-statistic PP-statistic ADF-statistic
Note: The null hypothesis is that the variables are not cointegrated. Under the null tests, all variables are distributed normal (0, 1). ⁎ Indicate statistical significance at the 1% level. ⁎⁎ Indicate statistical significance at the 5% level.
where SP and EX are the natural logarithms of stock prices and exchange rates, respectively, and αi and δi are the country and time fixed effects, respectively. νi,t is an error term. 3 Table 2 summarizes the results of Pedroni's heterogeneous panel test. The cointegration tests of Pedroni indicate a significant cointegration relationship between the variables. At the 1% or 5% significance level, except for the panel group rho-statistic the other six statistics strongly reject the null hypothesis of no cointegration. Thus, we conclude that a long-run relationship exists between the stock price and the exchange rate for the ASEAN-5. Since the two variables are cointegrated, we proceed to estimate the long-run cointegration coefficients using the panel DOLS approach (see Kao and Chiang, 2000). As shown at the bottom of Table 3, the panel parameter is − 3.9555 for exchange rates. Because the cointegration coefficient is statistically significantly negative at the 5% level, this means that a 1% increase in exchange rates raises stock prices by around − 3.96%. On a per country basis, exchange rates all have significantly negative impacts on stock prices at the 5% level. Our negative finding is able to support the “stock-oriented” hypothesis of exchange rates proposed by Branson (1983) and Frankel (1983), which states that exchange rates influence stock prices negatively via capital mobility in the capital accounts. More importantly, the long-run equilibrium negativity result implies that the appreciating (depreciating) currencies of the ASEAN-5 encouraged international funds searching for investment opportunity and portfolio management to flow into (out of) these economies. Therefore, the capital mobility based on portfolio balance would be really one of the crucial determinants influencing the performance and stability of the equity markets in the ASEAN-5, which is consistent with Doong et al. (2005), Lin (2012) and Tsai (2012). 4 A two-step procedure to estimate a panel-based error correction model is employed based on Engle and Granger (1987) for the short-run and long-run relationships between the variables: ΔSP it ¼ ϕ1i þ
p X L¼1
ΔEX it ¼ ϕ2i þ
p X L¼1
p X ϕ11L ΔSP it−L þ ϕ12L ΔEX it−L þ κ 1 ect it−1 þε1it
ð2Þ
L¼1 p X ϕ21L ΔEX it−L þ ϕ22L ΔSP it−L þκ 2 ect it−1 þ ε2it
ð3Þ
L¼1
where Δ denotes first difference and L is the optimal lag length determined by the Schwarz Bayesian Criterion (SBC), ϕji(i = 1, 2; j = 1, 2) represents the fixed country effect, ectit − 1 is the error term, κj is the adjustment coefficient, and εj is the disturbance term. First, in the short-run analysis, the exchange rate does not Granger cause the
ð1Þ
IPS test allows for heterogeneity in these dynamics. Furthermore, slope heterogeneity is more reasonable in the case where cross country data are used. In this study, heterogeneity arises because of differences in economic conditions and degree of development in each country.
3 Following Gavin (1989), Kwona and Shinb (1999) and Maysami and Koh (2000), the stock price served as the dependent variable. The estimation result is not significant and hence not shown here if we regress EX on SP using the panel DOLS method. 4 The scales of trading volume in equity shares in the ASEAN-5 are small relative to those in the developed economies.
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C.-C. Liang et al. / Economic Modelling 32 (2013) 560–563
Table 3 Panel dynamic OLS estimates (the dependent variable is SP). Country
Individual DOLS results Indonesia Malaysia Philippines Singapore Thailand Panel DOLS results
Table 4 Panel causality test results (2008:08–2011:06).
EX
Source of causation (independent variable)
Coefficient
t-Statistic
−3.7176⁎⁎ −2.4158⁎⁎ −5.6682⁎⁎ −2.7860⁎⁎ −5.1901⁎⁎
−13.7102 −8.7329 −6.3949 −3.7349 −13.2661
−3.9555⁎⁎
−20.4999
Note: Asymptotic distribution of t-statistic is standard normal as T and N go to infinity. ⁎⁎ Denote significance at the 5% level.
stock price if and only if all the coefficients of ϕ12L are equal to zero in Eq. (2). In the reverse case, the stock price does not Granger cause the exchange rate if and only if all the coefficients of ϕ22L are equal to zero in Eq. (3). Second, we implement a joint test of ectit − 1 and the respective interactive terms to check for the long-run causality in Eqs. (2) and (3).5 With a cointegrating relation between the two variables, we perform a panel-based error correction model to examine the short-run and the long-run causality between them. Table 4 shows the F-test results of the panel short-run and long-run causality tests for Eqs. (2) and (3). The empirical results indicate that there are both short-run and long-run uni-directional causalities between the variables, respectively. In the panel short-run causality analysis, this means that only changes in exchange rates lead to changes in stock prices. Similarly, the result of the panel long-run causality test shows that only changes in exchange rates lead to changes in stock prices, which completely is in conformity with the result obtained above using the panel DOLS approach. It is worthwhile noting that, our panel short-run causality results seem to be in line with Abdalla and Murinde (1997), Doong et al. (2005), Hatemi and Roca (2005), Ibrahim (2000), and Pan et al. (2007).
4. Conclusion We reexamine the relationships between the equity market and currency market in the ASEAN-5 using the panel Granger causality and panel DOLS methodologies over 2008/8 to 2011/6. Our results support the “stock-oriented” hypothesis of exchange rates proposed by Branson (1983) and Frankel (1983), which states that exchange rates influence stock prices negatively via portfolio balance. In addition, the long-run estimated panel parameter result indicates that a 1% appreciation (depreciation) in the currencies on panel basis raises (reduces) stock prices by approximately − 3.96%. The results of the panel short-run and long-run Granger causality tests find that the uni-directional causality from exchange rates to stock prices for the emerging economies of the ASEAN-5. These findings suggest that, as has been well done by these countries since the Asian financial crisis, the monetary authorities for the ASEAN-5 countries should keep allowing their currency values of being determined by the economic fundamentals instead of interrupting them only in order to stimulate export growth unless tremendous 5 More clearly, we check whether the two sources of causation are jointly significant, in order to test for Granger causality. This can be done by testing the joint hypotheses H0 : k1 = 0 and ϕ12L = 0 for all i in Eq. (2) or H0 : k2 = 0 and ϕ22L = 0 for all i in Eq. (3). Following a shock to the system, the joint test indicates which variable(s) bear the burden of short-run adjustment to re-establish long-run equilibrium. See AsafuAdjaye (2000).
Short-run
ΔSP ΔEX
Joint/short-run and long-run
ΔSP
ΔEX
ΔSP; ect
ΔEX; ect
– 1.421
9.082⁎⁎ –
– 2.758
5.06⁎⁎ –
Notes: All are F-statistics. ect indicates the estimated error-correction terms. The optimal lag chosen is one using the SBC. ⁎⁎ Indicates that the parameters are significant ate the 5% level.
short-term speculative funds (hot money) flow into the currency markets. References Abdalla, I., Murinde, V., 1997. Exchange rate and stock price interactions in emerging financial markets: evidence on India, Korea, Pakistan and the Philippines. Applied Financial Economics 7, 25–35. Aggarwal, R., 1981. Exchange rates and stock prices: a study of thee US capital markets under floating exchange rates. Akron Business and Economics Review 12, 7–12. Ajayi, R.A., Friedman, J., Mehdian, S.M., 1998. On the relationship between stock returns and exchange rates: tests of Granger causality. Global Finance Journal 9, 241–251. Asafu-Adjaye, J., 2000. The relationship between energy consumption, energy prices and economic growth: time series evidence from Asian developing countries. Energy Economics 22, 615–625. Branson, W.H., 1983. Macroeconomic determinants of real exchange risk. In: Herring, R.J. (Ed.), Managing Foreign Exchange Rate Risk. Cambridge University Press, Cambridge. Chiang, T.C., Yang, S.Y., Wang, T.S., 2000. Stock return and exchange rate risk: evidence from Asian stock markets based on a bivariate GARCH model. International Journal of Business 2, 97–117. Doong, S.C., Yang, S.Y., Wang, A.T., 2005. The dynamic relationship and pricing of stocks and exchange rates: empirical evidence from Asian emerging markets. Journal of American Academy of Business 7, 118–123. Dornbusch, R., Fischer, S., 1980. Exchange rates and current account. American Economic Review 70, 960–971. Engle, R.F., Granger, C.W.J., 1987. Co-integration and error correction: representation, estimation, and testing. Econometrica 55, 251–276. Fang, W.S., 2002. The effects of currency depreciation on stock returns: evidence from five East Asian economies. Applied Economics Letters 9, 195–199. Frankel, J.A., 1983. Monetary and portfolio-balance models of exchange rate determination. In: Bhandari, J.S., Putnam, B.H. (Eds.), Economic Interdependence and Flexible Exchange Rates. MIT Press, Cambridge. Gavin, M., 1989. The stock market and exchange rate dynamics. Journal of International Money and Finance 8, 181–200. Granger, C.W.J., Huang, B.N., Yang, C.W., 2000. A bivariate causality between stock prices and exchange rates: evidence from recent Asian flu. The Quarterly Review of Economics and Finance 40, 337–354. Hatemi, J.A., Roca, E., 2005. Exchange rates and stock prices: interaction during good and bad times: evidence from the ASEAN-4 countries. Applied Financial Economics 15, 539–546. Ibrahim, M., 2000. Cointegration and Granger causality tests of stock price and exchange rate interactions in Malaysia. ASEAN Economic Bulletin 17, 36–47. Ibrahim, H., Aziz, H., 2003. Macroeconomic variables and the Malaysian equity market: a view through rolling sub-samples. Journal of Economic Studies 30, 6–27. Im, K.S., Pesaran, M.H., Shin, Y., 2003. Testing for unit roots in heterogeneous panels. Journal of Econometrics 115, 53–74. Kao, C., Chiang, M.H., 2000. On the estimation and inference of a cointegrated regression in panel data. Advances in Econometrics 15, 7–51. Kwona, C.S., Shinb, T.S., 1999. Cointegration and causality between macroeconomic variables and stock market returns. Global Finance Journal 10, 71–81. Lin, C.H., 2012. The comovement between exchange rates and stock prices in the Asian emerging markets. International Review of Economics and Finance 22, 161–172. Maysami, R.C., Koh, T.S., 2000. A vector error correction model of the Singapore stock market. International Review of Economics and Finance 9, 79–96. Pan, M.S., Fok, C.W., Liu, Y., 2007. Dynamic linkages between exchange rates and stock prices: evidence from East Asian markets. International Review of Economics and Finance 16, 503–520. Pedroni, P., 2000. Critical values for cointegration tests in heterogeneous cointegrated panels. Advances in Econometrics 61, 653–670. Pedroni, P., 2004. Panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis: new results. Econometric Theory 20, 597–627. Phylaktis, K., Ravazzolo, F., 2005. Stock prices and exchange rate dynamics. Journal of International Money and Finance 24, 1031–1053.
C.-C. Liang et al. / Economic Modelling 32 (2013) 560–563 Soenen, L., Hennigar, E., 1988. An analysis of exchange rates and stock prices — the US experience between 1980 and 1986. Akron Business and Economic Review 19, 7–16. Tai, C.S., 2007. Market integration and contagion: evidence from Asian emerging stock and foreign exchange markets. Emerging Markets Review 8, 264–283. Tsai, I.C., 2012. The relationship between stock price index and exchange rate in Asian markets: a quantile regression approach. Journal of International Financial Markets, Institutions and Money 22, 609–621.
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Wongbangpo, P., Sharma, S.C., 2002. Stock market and macroeconomic fundamental dynamic interactions: ASEAN-5 countries. Journal of Asian Economics 13, 27–51. Wu, Y., 2000. Stock prices and exchange rates in a VEC model-the case of Singapore in the 1990s. Journal of Economics and Finance 24, 260–274.
Contents lists available at SciVerse ScienceDirect
Economic Modelling journal homepage: www.elsevier.com/locate/ecmod
Reexamining the relationships between stock prices and exchange rates in ASEAN-5 using panel Granger causality approach Chin-Chia Liang a, Jeng-Bau Lin b,⁎, Hao-Cheng Hsu c a b c
Department of Finance, Dayeh University, Changhua 51591, Taiwan Department of Business Administration, National Chung Hsing University, Taichung, Taiwan Department of Finance, National Chung Hsing University, Taichung, Taiwan
a r t i c l e
i n f o
Article history: Accepted 1 March 2013 Keywords: ASEAN-5 Stock-oriented hypothesis Capital mobility Economic fundamentals Panel Granger-causality Dynamic ordinary least squares
a b s t r a c t We revisit the relationships between the equity market and currency market in ASEAN-5 using the panel Granger causality and panel DOLS methodologies. Our results support the “stock-oriented” hypothesis of exchange rates proposed by Branson (1983) and Frankel (1983), which states that exchange rates impact stock prices negatively via capital mobility. Meanwhile, on a per country and panel basis, the testing results using the DOLS approach match those of the short-run and long-run causal relations running from exchange rates to stock prices. These findings suggest that the monetary authorities for the ASEAN-5 should keep allowing their currency values of being determined by the economic fundamentals instead of interrupting them only in order to stimulate export growth unless a great deal of short-term speculative funds (hot money) flow into the currency markets. © 2013 Elsevier B.V. All rights reserved.
1. Introduction The 1997 Asian financial crisis has stimulated the monetary authorities of the ASEAN to undertake a crucial reform in the exchange rate regimes. The tremendous changes in exchange rates since then have raised a higher risk of international economic transaction. Meanwhile, the rapid integration of various international financial markets in this region has promoted interactive relations among macroeconomic factors (see Hatemi and Roca, 2005; Pan et al., 2007; Tai, 2007). Faced with the high integration of these financial markets, the investors of the ASEAN seemed to have more opportunities to diversify their investment portfolios internationally (see Doong et al., 2005; Lin, 2012; Tsai, 2012). In addition, such a rapid integration of capital and currency markets also has attracted much attention to academicians and practitioners since the late 1990s for these economies. However, as mentioned above, when international investors in capital markets are engaged in cross-border transactions, they are potentially exposed to foreign exchange risk. Hence, for researchers, there has been an increasing concern and interest in the dynamic relationships among the prices of financial assets. Recently, some academic studies on financial asset prices mainly focused on stock prices and exchange rates. Two theoretical models linking equity markets and currency markets can account for this relationship. First, the “flow-oriented model” states that exchange rates influence stock prices positively based on the hypothesis that
⁎ Corresponding author. E-mail address: [email protected] (J.-B. Lin). 0264-9993/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.econmod.2013.03.001
exchange rate changes influence real output and hence stock prices via international competitiveness and trade balance in general (see Dornbusch and Fischer, 1980). The empirical evidence supported the flow-oriented hypothesis of exchange rates (see Chiang et al., 2000; Fang, 2002; Phylaktis and Ravazzolo, 2005; Wongbangpo and Sharma, 2002; Wu, 2000). Second, the “stock-oriented model” states that stock prices impact exchange rates negatively, and vice versa, via (short-term) capital mobility in capital accounts (see Branson, 1983; Frankel, 1983). The empirical evidence favored the stock-oriented hypothesis of exchange rates (see Aggarwal, 1981; Gavin, 1989; Ibrahim and Aziz, 2003; Kwona and Shinb, 1999; Maysami and Koh, 2000; Soenen and Hennigar, 1988; Tai, 2007; Tsai, 2012). Furthermore, in the short-run causality test there were several previous studies surveying unusual and unexpected movements in the equity market and the currency market. So far, the empirical findings on the causal relationship between the two variables have been mixed. One group of researches supported the result that exchange rates Granger cause stock prices (see Abdalla and Murinde, 1997; Doong et al., 2005; Hatemi and Roca, 2005; Ibrahim, 2000; Pan et al., 2007). Other studies provided some evidence that stock prices Granger cause exchange rates (see Ajayi et al., 1998; Doong et al., 2005; Granger et al., 2000; Hatemi and Roca, 2005; Lin, 2012; Pan et al., 2007). As indicated in the above literature, however, there has been a proliferation of such studies using different techniques, time periods and sample of countries. 1 1 If the referenced papers are cited in this study, this represents that there exists a uni-directional or bi-directional causal relationship between exchange rates and stock prices.
C.-C. Liang et al. / Economic Modelling 32 (2013) 560–563 Table 1 Panel heterogeneous unit root test results. Variables
SP EX
Table 2 Pedroni's heterogeneous panel cointegration test results.
IPS Level
First difference
1.5661 2.1636
−11.8393⁎⁎ −10.5291⁎⁎
⁎⁎ Denote significance at the 5% level.
The aim of this paper, therefore, is to reexamine the relationship between stock prices and exchange rates for the ASEAN-5 economies using panel methodology. Our paper differs from previous works in that we apply panel methods to test for unit roots, cointegration and short-run and long-run Granger causality relationships between the variables in this study. The group of novel methods has three advantages: (i) to increase the sample size and power of test, (ii) to allow for heterogeneity among countries, and (iii) to check for robustness of the empirical results by contrasting the panel short-run and long-run causality results with those from the individual estimation using a vector error correction model (VECM) for each country. The remainder of this study is structured as follows. Section 2 describes the data and methodology used in this study. Section 3 contains empirical results and interpretations. Finally, Section 4 concludes with policy implications. 2. Data and methodology The monthly data on the series of stock prices (SP) and exchange rates (EX) are sourced from DataStream covering the period 2008/8–2011/6 for the ASEAN-5. The ASEAN-5 countries include Indonesia, Malaysia, Philippines, Singapore and Thailand. The stock indices of the stock exchange of the ASEAN-5 are used for stock prices. The exchange rates are denominated in terms of the US dollar. The two variables surveyed here take a logarithm form. To re-investigate the causal relationships between stock prices and exchange rates for the ASEAN-5, we propose to conduct three tests such as the panel unit-root test, the panel cointegration test and the panel causality test, and the estimation of panel dynamic ordinary least squares (DOLS). In examining the causal relationships between the two variables, the long-run and short-run causality testing methods are employed in this study. 3. Empirical results First, this paper employs the Im, Persaran and Shin (IPS) (Im et al., 2003) panel unit-root test. 2 The results of these tests are reported in Table 1, indicating that the statistics significantly confirm that the level values of all series are non-stationary; that is, all variables are I(1). After the first differencing, all the variables are stationary at the 5% significance level. The next step is to test whether a long-run relationship exists between them. Here, the panel cointegration tests developed by Pedroni (2000, 2004) are conducted to test the long-run cointegrating relation of stock prices with exchange rates. The test allows for heterogeneity in the intercepts and slopes of the cointegration equation. Pedroni (2000, 2004) provides seven statistics for the test of the null of no cointegration in heterogeneous panels. Pedroni's seven statistics are based on the estimated residuals from the panel cointegration regression as follows: SP i;t ¼ α i þ δi t þ βi EX i;t þ νi;t 2
561
Within-dimension
Test statistic
Between-dimension
Test statistic
Panel Panel Panel Panel
1.2777⁎ −1.5164⁎ −1.8741⁎⁎ −2.2811⁎⁎
Group rho-statistic Group PP-statistic Group ADF-statistic
−0.4877 −1.5139⁎ −1.7082⁎⁎
v-statistic rho-statistic PP-statistic ADF-statistic
Note: The null hypothesis is that the variables are not cointegrated. Under the null tests, all variables are distributed normal (0, 1). ⁎ Indicate statistical significance at the 1% level. ⁎⁎ Indicate statistical significance at the 5% level.
where SP and EX are the natural logarithms of stock prices and exchange rates, respectively, and αi and δi are the country and time fixed effects, respectively. νi,t is an error term. 3 Table 2 summarizes the results of Pedroni's heterogeneous panel test. The cointegration tests of Pedroni indicate a significant cointegration relationship between the variables. At the 1% or 5% significance level, except for the panel group rho-statistic the other six statistics strongly reject the null hypothesis of no cointegration. Thus, we conclude that a long-run relationship exists between the stock price and the exchange rate for the ASEAN-5. Since the two variables are cointegrated, we proceed to estimate the long-run cointegration coefficients using the panel DOLS approach (see Kao and Chiang, 2000). As shown at the bottom of Table 3, the panel parameter is − 3.9555 for exchange rates. Because the cointegration coefficient is statistically significantly negative at the 5% level, this means that a 1% increase in exchange rates raises stock prices by around − 3.96%. On a per country basis, exchange rates all have significantly negative impacts on stock prices at the 5% level. Our negative finding is able to support the “stock-oriented” hypothesis of exchange rates proposed by Branson (1983) and Frankel (1983), which states that exchange rates influence stock prices negatively via capital mobility in the capital accounts. More importantly, the long-run equilibrium negativity result implies that the appreciating (depreciating) currencies of the ASEAN-5 encouraged international funds searching for investment opportunity and portfolio management to flow into (out of) these economies. Therefore, the capital mobility based on portfolio balance would be really one of the crucial determinants influencing the performance and stability of the equity markets in the ASEAN-5, which is consistent with Doong et al. (2005), Lin (2012) and Tsai (2012). 4 A two-step procedure to estimate a panel-based error correction model is employed based on Engle and Granger (1987) for the short-run and long-run relationships between the variables: ΔSP it ¼ ϕ1i þ
p X L¼1
ΔEX it ¼ ϕ2i þ
p X L¼1
p X ϕ11L ΔSP it−L þ ϕ12L ΔEX it−L þ κ 1 ect it−1 þε1it
ð2Þ
L¼1 p X ϕ21L ΔEX it−L þ ϕ22L ΔSP it−L þκ 2 ect it−1 þ ε2it
ð3Þ
L¼1
where Δ denotes first difference and L is the optimal lag length determined by the Schwarz Bayesian Criterion (SBC), ϕji(i = 1, 2; j = 1, 2) represents the fixed country effect, ectit − 1 is the error term, κj is the adjustment coefficient, and εj is the disturbance term. First, in the short-run analysis, the exchange rate does not Granger cause the
ð1Þ
IPS test allows for heterogeneity in these dynamics. Furthermore, slope heterogeneity is more reasonable in the case where cross country data are used. In this study, heterogeneity arises because of differences in economic conditions and degree of development in each country.
3 Following Gavin (1989), Kwona and Shinb (1999) and Maysami and Koh (2000), the stock price served as the dependent variable. The estimation result is not significant and hence not shown here if we regress EX on SP using the panel DOLS method. 4 The scales of trading volume in equity shares in the ASEAN-5 are small relative to those in the developed economies.
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C.-C. Liang et al. / Economic Modelling 32 (2013) 560–563
Table 3 Panel dynamic OLS estimates (the dependent variable is SP). Country
Individual DOLS results Indonesia Malaysia Philippines Singapore Thailand Panel DOLS results
Table 4 Panel causality test results (2008:08–2011:06).
EX
Source of causation (independent variable)
Coefficient
t-Statistic
−3.7176⁎⁎ −2.4158⁎⁎ −5.6682⁎⁎ −2.7860⁎⁎ −5.1901⁎⁎
−13.7102 −8.7329 −6.3949 −3.7349 −13.2661
−3.9555⁎⁎
−20.4999
Note: Asymptotic distribution of t-statistic is standard normal as T and N go to infinity. ⁎⁎ Denote significance at the 5% level.
stock price if and only if all the coefficients of ϕ12L are equal to zero in Eq. (2). In the reverse case, the stock price does not Granger cause the exchange rate if and only if all the coefficients of ϕ22L are equal to zero in Eq. (3). Second, we implement a joint test of ectit − 1 and the respective interactive terms to check for the long-run causality in Eqs. (2) and (3).5 With a cointegrating relation between the two variables, we perform a panel-based error correction model to examine the short-run and the long-run causality between them. Table 4 shows the F-test results of the panel short-run and long-run causality tests for Eqs. (2) and (3). The empirical results indicate that there are both short-run and long-run uni-directional causalities between the variables, respectively. In the panel short-run causality analysis, this means that only changes in exchange rates lead to changes in stock prices. Similarly, the result of the panel long-run causality test shows that only changes in exchange rates lead to changes in stock prices, which completely is in conformity with the result obtained above using the panel DOLS approach. It is worthwhile noting that, our panel short-run causality results seem to be in line with Abdalla and Murinde (1997), Doong et al. (2005), Hatemi and Roca (2005), Ibrahim (2000), and Pan et al. (2007).
4. Conclusion We reexamine the relationships between the equity market and currency market in the ASEAN-5 using the panel Granger causality and panel DOLS methodologies over 2008/8 to 2011/6. Our results support the “stock-oriented” hypothesis of exchange rates proposed by Branson (1983) and Frankel (1983), which states that exchange rates influence stock prices negatively via portfolio balance. In addition, the long-run estimated panel parameter result indicates that a 1% appreciation (depreciation) in the currencies on panel basis raises (reduces) stock prices by approximately − 3.96%. The results of the panel short-run and long-run Granger causality tests find that the uni-directional causality from exchange rates to stock prices for the emerging economies of the ASEAN-5. These findings suggest that, as has been well done by these countries since the Asian financial crisis, the monetary authorities for the ASEAN-5 countries should keep allowing their currency values of being determined by the economic fundamentals instead of interrupting them only in order to stimulate export growth unless tremendous 5 More clearly, we check whether the two sources of causation are jointly significant, in order to test for Granger causality. This can be done by testing the joint hypotheses H0 : k1 = 0 and ϕ12L = 0 for all i in Eq. (2) or H0 : k2 = 0 and ϕ22L = 0 for all i in Eq. (3). Following a shock to the system, the joint test indicates which variable(s) bear the burden of short-run adjustment to re-establish long-run equilibrium. See AsafuAdjaye (2000).
Short-run
ΔSP ΔEX
Joint/short-run and long-run
ΔSP
ΔEX
ΔSP; ect
ΔEX; ect
– 1.421
9.082⁎⁎ –
– 2.758
5.06⁎⁎ –
Notes: All are F-statistics. ect indicates the estimated error-correction terms. The optimal lag chosen is one using the SBC. ⁎⁎ Indicates that the parameters are significant ate the 5% level.
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