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Real Exchange Rate Volatility and International Trade: ASEAN Experience towards ASEAN Economic Community1 Angelina Ika Rahutami2 Abstract Currently, ASEAN economies are going to initiate the ASEAN Economic Community (AEC) in 2015 for a better and more extensive economic integration. The diversity within ASEAN (including the exchange rate volatility) and new initiative of economic integration namely AEC, are the interesting condition to analyze. The purposes of this paper are to describe the economic condition of the ASEAN Member States (AMSs) and to contribute to the empirical discussion on the impacts of exchange rate volatility on trade of ten AMSs during 2001‐ 2011. Panel regression method is used in this article. At present the progress towards the ASEAN Community is progressing to be better and more converged one. The result provides evidence that the exchange rate volatility has no statistically significant on the export and import of AMSs. The estimation results also show that the increasing of term of trade will induce the export value. The home income also has a positively significant effect on import value, but the real exchange rate has a negative significant effect. Key words: AEC, Real Exchange Rate Volatility, International Trade
Introduction During the last two decades, we have seen the acceleration of the process of globalization. One of the impacts of globalization is trade liberalization. It stimulates economic cooperation between and among countries, regional, bilateral or multilateral cooperation. Nowadays, ASEAN (Association of South East Asia Nation) establishes the new integration process after the AFTA trading agreement is not sufficient enough to face up the globalization. It makes market and produces a better welfare. ASEAN economies are going to initiate the ASEAN Economic Community (AEC) in 2015 for a better and more extensive economic integration. The AEC scope is broader than the AFTA arrangement and it becomes a very significant development milestone in ASEAN. One of the AEC blue print targets is related with trade. Based on the theory, beside the principles of competitive and comparative advantage, there are various factors that affect trade, such as gross domestic product, exchange rate, term of trade, and price,. However, trade flows might be improved or distorted not only by government interventions, but also by exchange rate fluctuations. After the financial crisis in 1997, some of ASEAN member States (AMSs) have changed their exchange rate system, from fixed to floating exchange rate system. This exchange rate system changing made the exchange rate more volatile because government minimized its intervention. The fluctuations of exchange rate
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This article is proposed for the seminar and discussion series of Nijmegen School of Management Radboud University 2 Lecturer of Faculty of Economic and Business, Soegijapranata Catholic University, Indonesia
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can be measured by exchange volatility. The exchange rate volatility has a different definition regarding with the exchange rate fluctuation and depreciation or appreciation. The exchange rate volatility is measured by the exchange rate standard deviation or variance, whilst the exchange rate fluctuation is measured by the difference of actual and trend value
, but the exchange rate deprecation or
appreciation is measured by deviation of actual value and the previous one
.
The exchange rate volatility is the source of exchange rate risk and it has a certain implication on international trade. The literatures offer various explanations for the effect of exchange rate volatility on trade. The previous research results are ambiguous. Some of them explained that exchange rate volatility had a positive impact (De Grauwe and Skudelny, 2000; Bacchetta and van Wincoop, 2000; Langley et al., 2000), but some of the researches were about the negative impact (Arize, Osang, & Slottje, 2000; Chowdhurry, 1993; Dell’Ariccia, 1999; Kim and Lee, 1996; Peree and Steinherr, 1989; Bahmani, 2002; Doganlar, 2002; Cho, G., Sheldon, & McCorriston, 2002). There were also the results that showed the insignificant effect on trade (Goeltom, 1997; Susilo, 2001; Rahutami and Kusumastuti, 2007; Baum and Caglayan, 2010; Tenreyro, 2007; Eicher and Henn, 2009; Baum and Caglayan, 2010). The diversity within ASEAN (including the exchange rate volatility) and new initiative of economic integration namely AEC, are the interesting condition to analyze. The purposes of this paper are to describe the economic condition of the AMSs and to contribute to the empirical discussion on the impacts of exchange rate volatility on trade of ten AMSs, namely Brunei Darussalam, Cambodia, Indonesia, Lao, Malaysia, Myanmar, Philippines, Singapore, Thailand and Vietnam, over the annual period of 2001 – 2011. The rest of the paper is organized as follows: the next section describes about the evolution of cooperation towards AEC, after that the section presents the literature survey on exchange rate volatility and trade. The next section describes the methodology employed and the sources of data collected, and then the following section reports the empirical results. The last section is the conclusion. Evolution of Cooperation towards ASEAN Economic Community (AEC) The ASEAN Community rests on three pillars: the AEC, The ASEAN Socio‐Cultural Community (ASCC), and ASEAN political and Security Community (APSC) (ASEAN Brief, 2012). The AEC will be a gear to realize the ASEAN regional economic. The ASEAN Leaders had originally intended to create the AEC by 2020, but in early 2007 they advanced the deadline to 2015 (AEC Blueprint, www.aseansec.org). The AEC is the realization of the final goal of economic integration as promoted in the Vision 2020. It is based on a convergence of interests of AMSs to deepen and broaden regional economic integration. The AEC scope is broader than the AFTA arrangement because it covers goods, services, investments and production factors liberalization. The AEC blueprint (www.aseansec.org) – consistent with the goals set out in the 2007 ‐ targets four objectives, that are (i) establishing ASEAN as a single market and production base; (ii) making ASEAN more dynamic and competitive with new mechanisms; (iii) inducing the equitable economic development across countries; and (iv) accelerating regional integration in the priority sectors. 2
Currently the trade within ASEAN has been going stronger and the overall price variance across the region decreased. This trend is consistent with ASEAN markets which become more integrated. Table 1 Progress towards the ASEAN Community ‐ Selected indicators Outcome indicators Value of total trade in goods Intra‐ASEAN total (USD billion) Intra‐ASEAN share (%) Average price level (PPP conversion factors) GDP basket commodities ASEAN6:CLMV ratio ASEAN coefficient of variation Consumer basket of commodities ASEAN6:CLMV ratio ASEAN coefficient of variation
Benchmark Latest data Status Year Value Year Value 2004 260.9 2011 598.2 Increasing 2004 24.3 2011 25.0 Increasing 2000 1.57 2011 1.56 Converging 2000 0.327 2011 0.251 Converging 2000 1.57 2011 1.42 Converging 2000 0.387 2011 0.279 Converging
Source: ASEAN Secretariat Notes: ASEAN coefficient of variation is defined as the standard deviation across ASEAN Member States normalized by the average
Table 1 shows that the progress towards the ASEAN Community is progressing to be better and more converged one. The intra ASEAN trade in goods is increasing and the average price level is converging. The value of goods traded within ASEAN and between ASEAN and the rest of the world increased significantly (by 129 and 121 per cent respectively) between 2004 and 2011. During that period intra‐ ASEAN trade grew from around US$261 billion in 2004 to US$598 billion in 2011. Price variance across the region in terms of a GDP and consumer basket commodities decreased. This condition differs with the previous condition that volatility of ASEAN countries domestic currency against US$ tended to be high (Rahutami, 2007). It gave a high cost in transaction even after the ASEAN integration. Cost incurred will reduce the benefits of trade integration. This last data in table 1 is consistent with more integrated ASEAN markets. Review of Related Literature Exchange rate volatility There are two regimes of exchange rate system namely fixed exchange rate system and floating exchange rate system. The fixed exchange rate system needs government intervention to stabilize the exchange rate and it also needs the good condition of foreign exchange reserves. The collapse of Breton Woods in 1973 led to a significant fluctuation in the exchange rate. The data also showed that adoption of floating exchange rate system in many countries tended to increase the exchange rate uncertainty. The most prominent nature of exchange rate is the exchange rate movements which are very sensitive to the politic and economic changing. Barkouas et al. (2002), and Hviding, Nowak, and Ricci (2004) showed that the exchange rate volatility could arise from three components:
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1. Changes in economic fundamental factors such as purchasing power of consumers 2. Changes in the microstructure aspect of foreign exchange market as though bubbles and rumors, noise traders, speculation and portfolio shifts. 3. The noisy signal of potential future policy changes like inflation, interest rate, money supply and output growth. 4. The exchange rate regime. As mentioned before, one of the exchange rate measurements is volatility. There are various approches to measure exchange rate volatility that are: 1. Standard deviation of level or change of the exchange rate (Bahmani & Ltaifa, 1992; Chowdury, 1993; and Stokman, 1995) 2. Moving average standard deviation (MASD), as in Koray and Lastrapes (1989) and Chowdhury (1993). The short run volatility (V) is measured using the following formula: m Vt 1 / m et i 1 et i 2 i 1
1/ 2
(1)
3. The spot and forward of exchange rate (Hooper and Kohlagen, 1978). This measurement also indicates the uncertainty of exchange rate. 4. The maximum and minimum values of the exchange rate within the time interval (Peree and Steinherr, 1989; and Cho, Sheldon, & McCorriston, 2002). This measurement shows the long‐run volatility of exchange rate between any two trading countries. The long‐run volatility (V) is measured using the following formula:
(2)
where max and min e, respectively represent the maximum and minimum values of the exchange rate within a time interval t and k, and ep is the equilibrium exchange rate. 5. ARCH and GARCH model (Arize, 1995; Pozo, 1992). Therefore, ARCH exchange rate volatility is,
(3)
(4)
The advantage of ARCH and GARCH is using a parametric model of time‐varying variance to eliminate the independent of exchange rate changes and covering the stochastic processes of exchange rate (Caporale, and Doroodian, 1994). The exchange rate volatility shows the tendency of exchange rate changing and it is believed to be one of high cost economic driver. The volatility also indicates the international trade risk and barrier. 4
The Effect of Exchange Rate Volatility on Trade The exchange rate volatility has an important relationship with the trade balance directly through the cost of uncertainty and adjustment of business cycle (Barkoulas, Baum, & Caglaya, 2002) and indirectly via the output structure, investment and government policy (Agolli, 2002). The correlation between exchange rate volatility and international rate becomes more important in open economy. Hau (2002) stated that trade integration and real exchange rate volatility are structurally correlated. The more open economy is the more flexible aggregate price. This condition will decrease the unanticipated shocks of money Karemeraa et al. (2011) explained that the trade flows are generally affected by comparative advantage, government intervention and also the exchange rate fluctuations. Theoretically, the possibility relationship between volatility and export is both positive and negative (De Grauwe, 1988), but also no relationship (Baccheta and Wincoop, 2000). The different possibilities effect depends on the risk behavior of producers (De Grauwe, 1998). If producers are risk averse, an increase in exchange rate volatility is expected to decrease their export because they will move their sales from foreign markets to domestic markets. However, if producers are adequately risk averse, a volatility increase will stimulate producers to increase their export volume. The empirical findings of impact of exchange rate volatility on trade have remained inconclusive at best. In fact, numerous studies, theoretically and empirically, have attempted to find the nature of the relationship between exchange rate volatility and exports and reported both positive and negative relationships, but some have reported no significant relationship3. The empirical results of De Grauwe and Skudelny (2000) and Bacchetta & van Wincoop (2000) suggest that under certain regularity conditions, the exchange rate volatility lead to increase trade flows. The same finding also comes from Langley et al. (2000). It shows that exchange rate variability positively affects poultry exports to Thailand. The negative effect of volatility is showed by Arize, Osang, & Slottje (2000), Chowdhurry (1993), Dell’Ariccia (1999), Kim and Lee (1996), Peree and Steinherr (1989), Bahmani (2002) and Doganlar (2002). Cho, Sheldon & McCorriston (2002) that used the sectored analysis, and Coric and Pugh (2010) also reported the negative relationship on average. Baaka, Mahmoodb and Vixathepc (2007) used the Japanese export data indicated a negative and significant long‐run relationship between exports and exchange rate volatility in South Korea, Singapore and Thailand, and a positive but insignificant long‐run relationship. In Indonesian cases, Goeltom (1997), Susilo (2001) and Rahutami and Kusumastuti (2007) found that volatility had the significant effect on trade only in the long run, but not in the short run, and it only appeared in some Indonesian trade partners. Aristotelous (2001),Gagnon (1993) dan Bailey, Tavlas, & Ulan (1986) showed that there is no evidence that volatility had a significant impact on trade volume. Boug and Fagereng (2010) also found no "evidence suggesting that export performance (of Norwegian firms) has been significantly affected by exchange rate uncertainty". Tenreyro (2007) who used a simultaneous estimation approach found no significant impact of nominal exchange rate volatility on 3
According to Cote (1994) ambiguous results of research on the effect of exchange rate volatility on trade due to differences in measuring instruments and methods of volatility measurement as well as the rapid advancement of the financial sector. The rapid development of financial sector causes the the possibility of hedging, so the risk of bias can be reduced.
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trade flows. Eicher and Henn (2009) who used the gravity equation also do not find a robust impact of exchange rate volatility. Baum and Caglayan (2010) also conclude the same thing. The following table shows the summary of the result of the previous researches. Table 2 Exchange rate volatility and trade: literature survey Study Akhtar and Hilton (1984) Gotur (1985) Bailey et al. (1986) Bailey et al. (1987) Brada and Mendez (1988) Pere and Steinherr (1989) Savvides (1992)` Chowdhury (1993) Mckenzie and Brooks (1997) Aristotelous (2001) Vergil (2002) Das (2003) Baak (2004) Kasman and Kasma (2005) Arize et al. (2005) Chit (2008) Hondroyoannis et al. (2008)
Sample period 1974‐1981Q 1974‐1982Q 1973‐1984Q 1962‐1985Q 1973‐1977A 1960‐1985A 1973‐1986A 1973‐1990Q 1969‐1995Q 1989‐1999A 1990‐2000Q 1980‐2001Q 1980‐2002A 1982‐2001Q 1973‐2004Q 1982‐2005Q 1977‐2003Q
Research method used OLS OLS OLS OLS Cross section OLS Cross section VAR ARCH Gravity model Standard deviation ADF, ECM, Cointegration OLS Cointegration, ECM Cointegration, ECM Panel cointegration Panel data estimation techniques
Main results Negative effect Little to no effect Not significant, mixed effect Little to no effect Positive effect Negative effect Negative effect Significant negative effect Generally positive effect No effect on export Negative effect on export Significant negative effect on export Significant negative effect on export Significant negative effect on export Significant negative effect on export Significant negative effect on export Significant negative effect on export
Note: A= annual, Q = quarterly, M = monthly Source: Oztruk (2006, p 88‐92) Methods of Estimation This paper examines the impact of real exchange rate volatility on export and import of ten ASEAN member states over the annual period from 2001 to 2011. The ten AMSs are Brunei Darussalam, Cambodia, Indonesia, Lao PDR, Malaysia, Myanmar, Philippines, Singapore, Thailand, and Vietnam. The panel dataset of 110 observations is used. The estimation model is,
(5)
(6)
Where αij and ij are the unobservable country‐specific‐effect. This unobservable effect captures the time invariant country specific effects, such as cultural, economic and institutional factors that are not explicitly represented in the model (Chit, Rizov and Willenbockel, 2010). Whilst the Xijt is real total export value of each AMSs; Mijt is real total import value of each AMSs; GDPFit is the real gross domestic product of the main trade partner of each AMSs; GDPit is the real gross domestic product of each AMSs; VRERit is exchange rate volatility (measured by standard deviation), RERit is real exchange rate (defined 6
as exchange rate (the price of foreign currency in domestic currency. This article used USD as foreign ; TOTit is term of trade (defined as relative price of
currency) of each AMSs increase with TOT
non tradable to tradable goods). TOT is measured by
. where CPI is the domestic country’s
consumer price index, and PPI is the trading partner’s producer or wholesale price index. The sources of data are Statistics from ASEAN Secretariat and Asian Development Bank. The main trade partner of each AMSs is the country that has the biggest percentage of trade. Based on data from 2005 to 2011 the main trade partner of each AMSs is followed. Table 3 Main Partners – Export Destination Country (average of 2005‐2011) Home Country
Country destination Japan
Percentage of total Export (average % from 2005 to 2011) 43.42
Cambodia
United State
31.47
Indonesia
Japan
16.57
Lao PDR
Australia
26.48
Malaysia
Japan
11.43
Myanmar
India
11.43
Philippines
Japan
18.46
Singapore
Hongkong
11.03
Thailand
Japan
10.81
Viet Nam
United State
17.43
Brunei Darussalam
Source : ASEAN Secretariat
Japan is the main country destination of export from Brunei Darussalam that covers 43.2% of total export. Japan is also the main export destination for Indonesia, Malaysia, Philippines and Thailand that has a proportion of total export respectively 16.57%; 11.43%; 18.46% and 10.81%. 17.43% and 31.47% of the total export of Vietnam and Cambodia is exported to USA. The other main destination countries are India, Australia and Hongkong. This paper used panel regression, mainly the fixed‐effects model. Fixed effect model is used because the time dimension (T) of panel is larger than cross‐sectional dimension (N) (Hsiao, 1999). In this case, the fixed‐effects coefficients are consistent and asymptotically efficient. However, a major limitation of fixed‐effects model eliminates all time‐invariant explanatory variables. Based on the previous research (Chit, Rizov and Willenbockel, 2010), this article also employed the random‐effects model to check the robustness of results and to control for the effects of the time‐invariant explanatory variables. Based on theory and previous empirical findings, the hypotheses of regression coefficients are: αij and 4 0; 1 > 0; 2 and 2 0 (it depends on risk behavior); 3 > 0; 4 > 0; 1 > 0; 3 0; 4 > 0; 1 > 0; 3