Did afta formation Divert Korea’s Exports to asean countries? Yoon Heo* 1




Yüklə 100.94 Kb.
tarix23.04.2016
ölçüsü100.94 Kb.



Did AFTA Formation Divert Korea’s Exports to ASEAN Countries?


Did AFTA Formation Divert Korea’s Exports to ASEAN Countries?
Yoon Heo* 1

Abstract
This study aims to evaluate the sectoral impact of the AFTA formation on Korean exports to ASEAN countries. Because the bilateral trade flows between Korea and ASEAN were expected to change slowly as a result of the persistence of trade relationships as well as sunk costs, the SYS-GMM estimator was considered to be more appropriate for our model.

The empirical results indicate that the effects of the AFTA on trade flows between Korea and ASEAN countries differed widely across sectors. For 5 of 15 selected sectors, the AFTA had a negative effect on Korean exports to ASEAN countries, whereas for the remaining 9, the effect was unclear. Overall, Korea’s exports were diverted to ASEAN members between 1980 and 2006 as a result of the AFTA formation.


Keywords: AFTA, Korea, Trade Diversion, Sectoral Evidence, SYS-GMM



  1. Introduction

The ASEAN Free Trade Area (AFTA) was implemented in 1993 by ASEAN-6 countries (Brunei, Indonesia, Malaysia, the Philippines, Singapore, and Thailand) and is aimed primarily at integrating member countries into a single production base and creating a regional market of approximately 550 million people. To this end, member countries agreed to lower or eliminate tariffs and non-tariff barriers within 15 years of its implementation. The main instrument of the tariff reduction scheme has been the Common Effective Preferential Tariff (CEPT), which covers both manufactured and agricultural products. However, following the Asian financial crisis in 1997, the member countries decided at the sixth ASEAN summit in December 1998 to accelerate trade liberalization by revising the timetable to 2002. In the mid-1990s, four more countries (CLMV) joined ASEAN: Vietnam (1995), Myanmar, (1998), Laos (1998), and Cambodia (1999). These countries are also participating in the AFTA under the following deadlines: Vietnam in 2006, Myanmar and Laos in 2008, and Cambodia in 2010.

Korea is a major trading partner of ASEAN countries. ASEAN countries have proven to be important markets for Korea’s manufactured products, and Korea has relied heavily on raw materials and light manufactured products from ASEAN countries. Nevertheless, Korea’s exports to ASEAN countries have declined steadily in recent years; the exports, which accounted for 5.2% of Korea’s total exports in 1988, rose to 15.7% in 1996 and then declined steadily to 9.6% in 2005 (KITA, 2007). From the Korean perspective, trade diversion is likely because of the preferential treatment granted by ASEAN countries to their members. As discussed in Section II, the intensity of bilateral trade between Korea and ASEAN has decreased, and the degree of the regional trade orientation of both Korea and ASEAN to their respective market has weakened in recent years. Therefore, it is important to determine the extent to which trade diversion from the AFTA has affected Korean exports to AFTA members. The present paper is guided by the following research questions:





  • First, what are the effects of the AFTA on Korean exports to ASEAN countries?

  • Second, what are its effects on Korean exports by industry?

  • Third, what are the key determinants of Korean exports to ASEAN countries?

  • Fourth, what are the characteristics of trade patterns between Korea and ASEAN countries?

This study contributes to the literature in several ways. First, this study estimates the effects of the AFTA on Korean trade flows by using sectoral data, not aggregate trade data, which allow the capture of sector-specific effects across industries, principally because the removal of trade barriers under the AFTA follows very different timetables depending on products. Indeed, many products are subject to exclusion from the Inclusion List under the CEPT. However, no study has employed sectoral data to assess the impact. Second, this study uses the SYS-GMM (system generalized method of moments), a key tool for estimating such effects because it can address the problems of heteroskedasticity and autocorrelation in panel data and the dynamic characteristics of such data. Third, instead of pooling data across various countries, this study focuses solely on the effects of the AFTA on Korean exports. Finally, this study provides an in-depth understanding of the dynamic patterns of bilateral trade relations between Korea and ASEAN over the past two decades.

The rest of this paper proceeds as follows. Section II briefly summarizes the evolution of bilateral trade pattern between Korea and ASEAN countries and specifies the model, data, and estimation methods. Section III presents the empirical results, and Section IV concludes the research.



  1. Model

  1. Changes in Trade Pattern between Korea and ASEAN countries

The trade between ASEAN-6 and Korea has expanded considerably in recent years. The bilateral trade between ASEAN-6 and Korea increased more than sevenfold from less than $8 billion in 1989 to more than $56 billion in 2006. Although the trade volume declined between 1997 and 1998, when both parties were battered by the Asian financial
crisis, it recovered soon after 1999. The bilateral trade rebounded to nearly $25 billion by the end of 1999 and expanded to over $33 billion in 2001, rising above pre-crisis levels.

With regard to exports, ASEAN-6's exports to Korea increased more than 7.3 times, from $3.8 billion in 1989 to $27.5 billion in 2006. On the other hand, its imports from Korea increased more rapidly than its exports over the same period. As a consequence, Korea recorded a consistent trade surplus over this entire period (except for 2001-05).

The exports of Korea and ASEAN to their major trading partners worldwide. Korea’s exports to China increased sharply after the normalization of diplomatic relations between the two countries in 1992, but this came at the expense of exports to the U.S. and Japan. Korea’s exports to ASEAN in percentage, which increased considerably between the late 1980s and the early 1990s, have gradually declined since the mid-1990s. The share of ASEAN’s exports to the U.S. and Japan also declined. ASEAN’s exports to Japan (as a percentage of its total exports) witnessed the largest decline, from over 20% between 1985 and 1989 to less than 11% in 2006. ASEAN’s exports to the U.S. also decreased sharply. In addition, Three more important points should be highlighted in the export patterns of ASEAN countries during the past two decades. First, the intra-regional trade between ASEAN countries has increased over time but occurred only among original members (ASEAN-6). For new member countries (CLMV), intra-regional trade with ASEAN has actually declined since the mid-1990s, when most of those countries became members of the AFTA. Second, ASEAN’s exports to Korea have increased moderately in the past two decades, but these exports were only from ASEAN-6 countries. Third, the export patterns of CLMV countries differed from those of ASEAN-6 countries and Korea. CLMV’s exports to the U.S. and the EU increased dramatically, whereas those to China increased only moderately.

The trade patterns between Korea and ASEAN have changed substantially in the past two decades. The several important changes are as follows: First, intra-industry trade tended to be much higher for manufactured goods than for non-manufactured goods. The level of intra-industry trade between Korea and ASEAN increased over time, indicating


the importance of Korea’s trade links with ASEAN economies. Second, Korea enjoyed a comparative advantage in manufacturing industry groups, whereas ASEAN countries enjoyed the same in primary industry groups. Therefore, the results suggest that the structure of bilateral trade is consistent with the comparative advantage of respective countries. Finally, despite the considerable expansion of trade between Korea and ASEAN countries in recent years, the degree of bilateral trade between them has decreased in intensity, and the extent of the regional trade orientation of both Korea and ASEAN to their respective markets has weakened. This can be explained in part by an increase in trade intensity among ASEAN countries and by the emerging role of China in the Korean and ASEAN markets.

  1. Model Specification

To examine the effects of the AFTA on Korea’s sectoral exports to ASEAN countries, we specified our augmented gravity model as follows2:

LnEXhkjt= β0 + β1lnPCGDPjt + β2lnPOPjt + β3lnDISTkj + β4lnAREAj + β5lnXRjit β6lnPCGDP_DIFkjt + β7WTOjt + β8AFTAjt + β9lnEXhkjt-1 +  Yeart + ekj

where


  • EXhkjt and EXhkjt-1 are export volumes of Korea’s sector h to country j (ASEAN) at times t and t-1, respectively.

  • PCGDPjt is the per capita GDP of importing country j at time t.

  • POPjt is the population of importing country j at time t.

  • DISTkj is the geographical distance (measured as the crow flies) between the capital of Korea (country k) and that of country j.

  • AREAj is the total area (measured in nautical miles) of country j.






  • XRjit is the real exchange rate of country j’s currency against the Korean won in year t.

  • PCGDP_DIFkjt is the difference in per capita GDP between Korea and country j at time t (in absolute value).

  • WTOjt is a dummy variable that equals 1 if country j is a member of the WTO and 0 otherwise at time t.

  • ­AFTAjt is a dummy variable that equals 1 if country j belongs to the AFTA and 0 otherwise at time t.

  • Yeart is a set of binary variables that is unity in the specific year t.

  • ekj represents the error terms.

To date, most of the previous empirical studies have used aggregate bilateral trade as the dependent variable (Rose, 2004). As mentioned by Dhar and Panagariya (1999) and others, total trade should not be used as a dependent variable because this approach imposes the equality of coefficients on imports and exports, which may not be tenable. Previous empirical studies have demonstrated that the gravity equation can be successfully applied to commodity trade (Bergstrand, 1989; Martínez-Zarzoso & Nowak-Lehmann, 2004; Jayasinghe & Sarker 2007). When countries negotiate an FTA, because of the domestic resistance of influential interest groups, countries frequently exclude sensitive products from tariff reduction schemes under the FTA. This is particularly the case for the AFTA; a number of sensitive products were excluded from the CEPT scheme. Thus, the use of sectoral panel data has been recommended for evaluating the impact of an FTA on trade flows by using the gravity equation.

Following Harris and Mátyás (1998), Badinger and Breuss (2004), and De Benedictis and Vicarelli (2005), we estimated the gravity equation by using a dynamic estimator (using a lagged dependent variable as one of the regressors), which allowed us to evaluate the short- and long-run dynamics more precisely. Repeated interactions between business partners, as well as sunk costs associated with distribution and service networks, warrant a dynamic relationship of the model (De Nardis and Vacarelli, 2005). Therefore, it is appropriate to hypothesize that past exports can exert a substantial impact on current exports.


C. Data and the Estimation Method

The presence of a lagged dependent variable as one of the regressors can lead to biased and inconsistent estimated coefficients of OLS and fixed-effects estimators (Nickell, 1981; Sevestre and Trognon, 1985; Baltagi, 2001; Harris and Mátyás, 2004). As Nickell (1981) demonstrated, fixed-effects estimators yield a downward bias, whereas OLS estimators generate an upward bias (Hsiao, 1986). Arellano and Bond (1991) developed the first-differenced GMM (DIF-GMM) to correct these problems. However, Blundell and Bond (1998) and Bond et al. (2001) demonstrated that the DIF-GMM may be subject to a large downward finite-sample bias, particularly in cases in which the number of available time periods is small. It has been shown that the SYS-GMM estimator brings about a noticeable improvement in the small-sample bias and precision relative to the DIF-GMM estimator, particularly when the dependent variable is highly persistent (De Mello-Sampayo, 2009). Because the bilateral trade flows between Korea and ASEAN were expected to change slowly as a result of the persistence of trade relationships as well as sunk costs, the SYS-GMM estimator was considered to be more appropriate for our model than the DIF-GMM estimator.



This study used export data at the two-digit level of the SITC (Rev.1); the data spanned from 1980 to 2006.3 The data on exports of Korea and ASEAN-10 at the two-digit level of the SITC were drawn from the UN COMTRADE database. In terms of the explanatory variables, the data on per capita GDP (in 2000 U.S. dollars), the population, and the area (in square km) were drawn from the World Bank’s World Development Indicators CD-ROM. The data on the geographical distance between the capital of Korea and those of ASEAN countries were drawn from the website of the Centre d’Etudes Prospectives et d’Informations Internationales (CEPII).


  1. Empirical Results

As shown in Table 1. Compared with the lagged dependent variable’s coefficient from the SYS-GMM estimator (0.69), the OLS estimator’s coefficient had an upward bias of 0.90, and the fixed-effects estimator’s coefficient had a downward bias of 0.53.
[ TABLE 1 ] Regression Results for Aggregate Data

Independent Variables

OLS

Fixed Effects

SYS – GMM

Coef.

t-statistic

Coef.

t-statistic

Coef.

t-statistic

Lagged Exports

0.90a

189.61

0.53a

57.03

0.69a

3.31

PCGDPj

0.11a

5.04

0.15c

1.71

0.59a

4.17

POPj

0.14a

7.09

0.67a

3.68

1.05a

8.07

AREAj

-0.01

-1.11

-0.82

-0.52

-0.28a

-2.83

Exchange rateij

0.00

-0.19

-0.03

-1.16

-0.04

-0.76

DISTij

-0.09

-1.32

N/a

N/a

-0.07

-0.12

DIF-PCGDPij

0.11b

2.51

0.69a

11.75

-0.29

-1.28

WTO

-0.09

-1.58

0.57a

6.86

-0.59c

-1.79

AFTA

-0.12a

-3.12

-0.001

-0.02

-0.09

-0.81

Constant

-1.52c

-1.91

-2.76

-0.15

-3.27

-0.66

No. of obs.

8059

8059

8059

R-Square

0.85

0.48




AB (2) test







0.13

Sargan test (P-value)







0.89

Note: 1. The dependent variable is Ln (Exports).

2. All variables except dummies (WTO and AFTA) are expressed in natural logarithms.

3. Subscripts a, b, and c indicate statistical significance at the 1%, 5%, and 10% levels, respectively.

4. Coefficients of time dummies are not reported.



The results obtained using the SYS-GMM estimator indicate that the gravity model provided a good fit with the aggregate data, explaining a large portion of the variation in bilateral trade flows. The key estimated coefficients were statistically significant at a
high level of significance. Compared with the OLS and fixed effects estimators, the SYS-GMM estimator resulted in an improvement in the explanatory power of the per capita GDP and population variables. In addition, the lagged dependent variable (lagged exports) was found to be an important explanatory variable for all model specifications. This suggests a need for considering the role of a lagged dependent variable in the gravity model. In the SYS-GMM, the per capita GDP variable had a significant positive effect on exports. The positive sign of per capita GDP suggests that an increase in individual income can increase purchasing power, which in turn can stimulate import demand. Specifically, all other things being equal, every 10% increase in the per capita GDP of ASEAN countries produced a 6.9% increase in their demand for Korean exports. The estimated coefficient of the importing country’s population was positive and highly statistically significant, suggesting that country size is related directly to trade. Larger countries have a greater capacity to absorb imports than smaller countries. In fact, it is worth noting that the population coefficient was found to be the most important variable influencing the direction of Korea’s exports to ASEAN countries. The dummy variable for ASEAN countries being WTO members showed a statistically significant negative effect on Korean exports. This suggests that ASEAN countries tend to divert their imports from Korea to more efficient countries when they become WTO members. This result supports Rose’s (2004) study, in which he determined the negative impact of the WTO dummy on bilateral trade flows.
As noted earlier, our primary interest is in the impact of the AFTA on Korean exports to ASEAN countries. The regression results of the SYS-GMM estimator demonstrate that the formation of the AFTA had a significant negative relationship with Korean exports to ASEAN countries. This implies that the formation of the AFTA did not have a substantial effect on Korean exports to ASEAN countries. This result is also consistent with the findings of Lee and Park (2005) and Calvo-Pardo, Freund, and Ornelas (2009) on the impact of the AFTA on non-member countries. The present study, using aggregate data, found no evidence that the AFTA harms non-members by diverting AFTA members’ imports from non-member countries to AFTA’s members. This implies that the AFTA can be a “building block” to free trade. Moreover, Lee, Koo, and Park (2008)
found that trade creation is observed in Korea’s exports to the AFTA bloc. However, we need to note that the tariff reduction and elimination process under the AFTA has been implemented differently across sectors. In addition, sectoral heterogeneous effects can be cancelled out at the aggregate level, resulting in

aggregation bias in trade diversion effects.

For the abovementioned reasons, we estimated the gravity equation for 15 major sectors based on their export share in Korea’s total exports. Table 2 presents the estimated coefficients. Overall, the gravity model worked well and yielded consistent outcomes across sectors. The estimated coefficients for the AFTA varied across sectors. The estimated coefficients that were negative and statistically significant included 5 sectors: medicinal and pharmaceutical products (54); plastic materials (58); rubber manufactures (62); non-metallic mineral manufactures (66); and scientific/control instruments and photographs (86). This implies that the formation of the AFTA has diverted Korea’s exports to ASEAN members for these specific sectors. In real terms, Korea’s exports of these products to ASEAN countries had declined or increased only minimally in value between 1995 and 2005.4 Moreover, the intra-regional trade among ASEAN countries increased considerably for most of these products.5

On the other hand, the estimated coefficient for the petroleum and petroleum (33) was positive and statistically significant. This positive coefficient can be explained by the special characteristics of the sector’s products, which are important inputs for the industrialization of ASEAN countries. In fact, Korea and ASEAN countries have demonstrated a complementary relationship in terms of producing and refining petroleum products; ASEAN countries are endowed with abundant crude oil, whereas Korea has advanced oil refinery technology. In monetary terms, Korea’s exports of


petroleum and petroleum products to ASEAN countries increased dramatically from $53.8 million in 1990 to $3.5 billion in 2005.
In terms of the remaining 9 sectors, the coefficients for the AFTA were either positive or negative, but they were statistically insignificant. Overall, the estimated results for the 15 sectors indicate that trade diversion effects dominated trade creation effects in Korea-ASEAN trade flows under the AFTA. The results of the comparison between aggregate and sectoral approaches confirm that the latter provides more robust and clear-cut results than the former.

One of the most salient points in Table 2 is the marked consistency in the behavior of estimated coefficients for the lagged exports across all the sectors regardless of sector characteristics. The coefficients were positive and highly significant (mostly at the 1% level) for all the sectors. This result reflects the fact that there are repeated interactions between exporters and importers as well as sunk costs related with distribution and service networks. Therefore, the exclusion of a lagged dependent variable in the gravity equation may lead to serious bias in the estimated results.

The estimated coefficients for importers’ per capita GDP were positive and statistically significant for 13 of the 15 sectors at the SITC 2-digit level between 1980 and 2006. This suggests that these products tend to be income elastic. In fact, the demand for electrical machinery (72), transport equipment (73), medicinal and pharmaceutical products (54), and scientific and control instruments (86) has increased dramatically in recent years. The estimated coefficients for the population of ASEAN countries were all positive and statistically significant across all the sectors. This demonstrates that the demand of more populous countries can better absorb imports than that of less populous ones. In addition, as expected, the estimated coefficients for the area of trading partners were negative and largely statistically insignificant.

The estimated coefficients for the real exchange rate of currencies of ASEAN countries against the Korean won were negative and statistically significant for chemical elements and compounds (51), iron and steel (67), electrical machinery, apparatus and


appliances (72), and scientific and control instruments (86), indicating that the depreciation of ASEAN currencies can discourage imports from Korea. In reality, these sectors are all quite sensitive to changes in prices. For another 10 sectors, the estimated coefficients for the real exchange rate were negative but statistically insignificant.
The estimated coefficients for the difference in per capita GDP support the Linder hypothesis for 6 sectors: textile fibers (26); plastic materials (58); rubber manufactures (62); machinery (71); transport equipment (73); and scientific/control instruments and photographs (86). These negative effects of differences in per capita GDPI indicate that countries with similar per capita incomes levels tend to have similar demand patterns and produce similar but differentiated products, making them more likely to trade with each other. On the other hand, the estimated coefficient for chemical elements and compounds (51) was both positive and significant. The positive sign of this coefficient indicates that the Hechscher-Ohlin effect dominated the Linder effect.





Note:

1. Sector: (by SITC-2 digit level, Rev1)

26: Textile fibers, not manufactured;

33: Petroleum and petroleum products;

51: Chemical elements and compounds;

54: Medicinal and pharmaceutical products;

58: Plastic materials, etc.;

61: Leather, leather manufures (n.e.s.) & dresses;

62: Rubber manufactures, n.e.s.;

66: Non-metallic mineral manufactures;

67: Iron and steel;

69: Manufactures of metal, n.e.s.;

71: Machinery, other than electric;

72: Electrical machinery, apparatus & appliances;

73: Transport equipment;

86: Scientific & control instruments, photographs;

89: Miscellaneous manufactured articles.

2. The dependent variable is Ln(Exports).

3. All variables except dummies (WTO and AFTA) are expressed in natural logarithms.

4. Subscripts a, b, and c indicate statistical significance at the 1%, 5%, and 10% levels, respectively.

5. Coefficients of time dummies are not reported.


  1. Conclusion

The empirical results indicate that the effects of the AFTA on trade flows between Korea and ASEAN countries differed widely across sectors. For 5 of 15 selected sectors, the AFTA had a negative effect on Korean exports to ASEAN countries, whereas for the remaining 9, the effect was unclear. Overall, Korea’s exports were diverted to ASEAN members between 1980 and 2006 as a result of the AFTA formation. To provide an in-depth understanding of this diversion, we also examined the unique characteristics of trade patterns between Korea and ASEAN countries. Our findings report several important structural changes. First, the level of intra-industry trade between Korea and ASEAN increased over time, demonstrating the importance of Korea’s complementary links with ASEAN economies. Second, Korea enjoyed a comparative advantage in manufacturing industry groups, whereas ASEAN evidenced the same in primary industry groups. This suggests that the structure of bilateral trade between Korea and ASEAN is consistent with their comparative advantage. Finally, despite the dramatic expansion of trade between Korea and ASEAN countries in recent years, the degree of bilateral trade between them was less intense, and the extent of the regional trade orientation of both Korea and ASEAN to their respective markets has weakened.


*The author would like to thank Dr. Tran N. Kien for his excellent and constructive comments, research assistance, and efforts for the paper.

< References >
Arellano, M. and S. Bond (1991), ‘Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations’, The Review of Economic Studies, 58, 2, 277-97.

Anderson, J. E. and E. van Wincoop (2003), ‘Gravity with Gravitas: A Solution to the Border Puzzle’, American Economic Review, 93, 1, 170–92.

Baier, S. L. and J. H. Bergstrand (2007), ‘Do Free Trade Agreements Actually Increase Members' International Trade?’, Journal of International Economics, 71, 1, 72-95.

Braga, P., R. Sadafi and A. Yeats (1994) ‘Regional Integration in the Americas: Déjà Vu All Over Again?’, The World Economy, 17, 4, 577-601.

Bond, S. R., J. Temple and A. Hoeffler (2001), ‘GMM Estimation of Empirical Growth Models’, CEPR Discussion Papers 3048, London: Centre for Economic Policy Research.

Baltagi, B. H. (2001), Econometric Analysis of Panel Data (New York: Chichester).

Badinger, H. and F. Breuss (2004), ‘What has Determined the Rapid Post-war Growth of Intra-EU Trade?’, Review of World Economics, 140, 1, 31-51.

Bergstrand, J. H. (1989), ‘The Generalized Gravity Equation, Monopolistic Competition, and the Factor-Proportions Theory in International Trade’, The Review of Economics and Statistics, 71, 1, 143-53.

Blundell, R. and S. Bond (1998), ‘Initial Conditions and Moment Restrictions in Dynamic Panel Data Models’, Journal of Econometrics, 87, 1, 115–43.

Brülhart, M. (1994), ‘Marginal Intra-Industry Trade: Measurement and Relevance for the Pattern of Industrial Adjustment’, Weltwirtschaftliches Archiv, 130, 600–13.

Calvo-Pardo, H., C. Freund and E. Ornelas (2009), ‘The ASEAN Free Trade Agreement Impact on Trade Flows and External Trade Barriers’, Policy Research Working Paper No. 2960, Washington D.C.: The World Bank.

De Benedictis, L. and C. Vicarelli (2005), ‘Trade Potentials in Gravity Panel Data Models’, Topics in Economic Analysis and Policy, 5, 1, Article 20.


De Mello-Sampayo F. (2009), ‘Competing-Destinations Gravity Model: An Application to the Geographic Distribution of FDI’, Applied Economics, 41, 2237-53.

Dhar, S. and A. Panagariya (1999), ‘Is East Asia Less Open Than North America and the EEC? No’, in Piggott, J. and A. Woodland (eds.), International Trade Policy and the Pacific Rim (London: Macmillan).

Greenaway, D. and C. Milner (2002), ‘Regionalism and Gravity’, Scottish Journal of Political Economy, 49, 5, 574-85.

Harris, M. N. and L. Mátyás (1998), ‘The Econometrics of Gravity Models’, Melbourne Institute Working Paper 5/98, Melbourne: Institute of Applied Economic and Social Research.

Hsiao, C. (1986), Analysis of Panel Data (Cambridge: Cambridge University Press).

International Monetary Fund (IMF) (2008), Direction of Trade Statistics CD-ROM, Washington D.C.: IMF.

Jayasinghe, S. and R. Sarker (2007), ‘Effects of Regional Trade Agreements on Trade in Agrifood Products: Evidence from Gravity Modeling Using Disaggregated Data’, Review of Agricultural Economics, 30, 1, 61-81.

Korea International Trade Association (KITA) (2007) ‘Trade Statistics’, Website: www.kita.org.

Lee, J. W. and I. W. Park (2005), ‘Free Trade Areas in East Asia: Discriminatory or Non-discriminatory?’, The World Economy, 28, 1, 21-48.

Lee, H. H, C. M. Koo and E. J. Park (2008), ‘Are Exports of China, Japan and Korea Diverted in the Major Regional Trading Blocs?’, The World Economy, 31, 7, 841-60.

Martínez-Zarzoso, I. and F. D. Nowak-Lehmann (2004), ‘Economic and Geographical Distance: Explaining Mercosur Sectoral Exports to the EU’, Open Economics Review, 15, 3, 291-314.

Mátyás L. (1997), ‘Proper econometric specification of the gravity model’, The World Economy, 20, 2, 363-8.

Micco, A., E. Stein and G. Ordoñez (2003), ‘The Currency Union Effect on Trade: Early Evidence from EMU’, Economic Policy, 18, 37, 315-56.
Nickell, S. (1981), ‘Biases in Models with Fixed Effects’, Econometrica, 49, 1417-426.

Rose, A. K. (2004), ‘Do We Really Know that the WTO Increases Trade?’, American Economic Review, 94, 1, 98-114.

Sevestre, P. and A. Trognon (1985), ‘A Note on Autoregressive Error Component Models’, Journal of Econometrics, 28, 231-45.

United Nations Statistics Division (2008), ‘United Nations Commodity Trade Statistics Database (COMTRADE)’, http://comtrade.un.org/db/default.aspx (accessed December 22, 2008).



World Bank (2008), ‘World Development Indicators, CD-ROM’, Washington D.C.: World Bank.

1* Professor, Graduate School of International Studies, Sogang University, Seoul, 121-742, Korea. Tel:82-2-705-8948, Fax: 82-2-705-8755, E-mail: hury@sogang.ac.kr

2 For the background and recent application of the gravity model, see Braga, Safadi, and Yeats (1994), Mátyás (1997), Greenaway and Milner (2002), Anderson and van Wincoop (2003), and Baier and Bergstrand (2007). To capture the Linder effect, we employed absolute differences in the per capita GDP (PCGDP DIF) of any two countries. A negative sign of the per capita GDP difference variable would support the hypothesis, whereas a positive sign would support the Hechscher-Ohlin hypothesis. In addition, the role of the exchange rate in determining trade flows is well known (Bergstrand, 1989; Micco, Stein & Ordoñez, 2003). The population and per capita GDP replace GDP in the equation.

3 The Korea-ASEAN (except Thailand) FTA on the goods sector took effect in 2007. FTAs on the service and investment sectors became effective in 2009. Thus, we observe the sample period (1980 to 2006) during which only ASEAN members (excluding Korea) enjoyed the preferential treatment from each other.

4 Korea exported 42% less non-metallic mineral manufactures and 10% less rubber manufactures to ASEAN countries between 1995 and 2005. In plastic materials (58) and scientific/control instruments and photographs (86), Korea’s exports to ASEAN countries increased by 80% and 25%, respectively, during the same period, whereas those to China increased by 259% and 10,069%, respectively (UNSD, 2008). Both Korea and ASEAN countries have enjoyed sharp increases in trade with China since the early 1990s. Thus, the China factor may alter the manner of trade between Korea and ASEAN.

5 For example, the share of intra-regional trade in total trade in plastic materials (58) increased from 25% in 1992 to 32% in 2006; rubber manufactures (62), from 17% to 28%; non-metallic mineral manufactures (66), from 18% to 22%; and scientific/control instruments and photographs (86), from 15% to 24%. The share in medicinal and pharmaceutical products (54) declined slightly because ASEAN countries diverted its imports from Korea to other non-member sources such as China.



Verilənlər bazası müəlliflik hüququ ilə müdafiə olunur ©azrefs.org 2016
rəhbərliyinə müraciət

    Ana səhifə