Intra-Regional Trade and Business Cycles in Southeast Asia

By

John Thornton and Alessandro Goglio

I. Introduction

I n southeast Asia, the high and growing share of intra-regional trade in total trade is likely to have important implications for business cycle behavior in the region.t Krugman (1993) points out that in-

creased trade integration means that countries are able to specialize more in their production, making them more sensitive to industry-specific shocks so that the correlation of business cycles between countries would tend to be reduced. In contrast, Frankel and Rose (1997) argue that if economic integration mainly occurs through intra-industry trade, business cycles may become more similar across countries. Frankel and Rose stress that the ambiguity of economic theory in this area makes resolving the issue essentially an empirical question; they demonstrate a positive cross-country relationship between the degree of trade inte- gration and the correlation of business cycles for 21 industrialized coun- tries for the period 1959-1993 and conclude that this is evidence of trade integration mainly reflecting intra-industry trade. 2

One feature of the Frankel and Rose study is the limited diversity of income levels and industrial structures in the sample of countries they use: all countries in the sample were industrialized throughout the period and intra-industry trade is a dominant feature of their bilateral trade. Greenaway and Milner (1986) suggest several reasons why intra- industry trade might be less important in trade between developed coun-

Remark: The views expressed in this paper should be attributed to the authors and not the organizations with which they are affiliated. I For example, the share of intra-regional trade in total trade for the ten southeast Asian economies that form the sample of this study increased from around 30 percent in 1975 to 36 percent in 1985 and further to 49 percent in 1996. 2 Recent results reported by Fat~is (1997) of regional and national business cycle sym- metries in the European Union also are consistent with the view that trade integration takes the form of increased intra-industry trade; the results show that cross-regional cor- relation has been increasing over time across countries and decreasing within countries, suggesting that trade integration has created more cross-border links.

ThomtorttGoglio: Intra-Regional Trade and Business Cycles 167

tries or between developed and developing economies, including dif- ferences in incomes and economic structure, the greater availability of primary products which are less capable of differentiation, and income constraints in developing economies which limit the demand for dif- ferentiated goods. Thus, the Frankel and Rose result would be more convincing if it was robust to a country sample with more diversity in the level of country development and industrial structures. In this note we report preliminary results from such a test using a sample of ten southeast Asian economies. 3

II. Data, Specification and Empirical Results

We use data for real GDP, bilateral exports and imports, and total trade from the OECD data tape. As a first step we compared the corre- lation of GDP growth rates of the ten southeast Asian economies with that of the aggregate for the group as a whole for the periods 1976-1985 and 1986-1996 to see what happened to the degree of business cycle synchronization from one period to the next. The results, reported in Table 1, suggest that while the correlation coefficients generally remain very low (and even negative in three cases), synchronization was high- er in seven out of the ten cases in the later period,

Table 1 - Southeast Asia GDP Growth Correlations with Region Average

Japan Korea China, mainland Hong Kong China Taiwan Province of China Indonesia Malaysia Philippines Singapore Thailand

1976-t985 1986-1996

0.78 0.95 0.24 0.64 0.64 -0.41

-0.O3 O.28 0.41 0.39 0.27 -0.19

-0.14 -0.06 -0.25 0.42 -0,06 0.16

0,3 t O.59

Note: Data are correlation coefficients of each economy's annual average GDP growth rate with that of the GDP weighted annual average for all economies.

3 More accurately, the sample comprises eight southeast Asian countries (Japan, Korea, mainland China, Indonesia, Malaysia, the Philippines, Singapore and Thailand) and two Chinese "provinces" (Taiwan Province of China and Hong Kong China).

168 Weltwirtschaftliches Archiv 1999, Vol. 135(1)

We then tested for the impact of increased trade integration on GDP growth correlations by estimating the following equation from Frankel and Rose (1997):

Corr(y)ijr = ot + fl Trade( ~)ijr + eij.c,

where Corr(y)ijr denotes the correlation of the annual real GDP growth between southeast Asian country i and country j over time span ~'; Trade (~)ijr denotes the natural logarithm of a trade intensity variable

- in this case, the ratio of bilateral trade (exports plus imports) between country i and country j to the sum of i and j ' s total trade; a and fl are the regression coefficients estimated and e is the error term. The sign on the coefficient fl indicates whether trade specialization or intra- industry trade effects dominate - a negative sign being consistent with the specialization effect being dominant and a positive sign indicating the dominance of intra-industry trade. Data are annual and we ran the regression over the two subperiods 1976-85 and 1986-96.

Frankel and Rose (1997) point out that as countries often manage their exchange rates in relation to those of their major trading partners, an observed positive association between trade integration and business cycles might be the result of countries pursuing similar monetary poli- cies rather than having similar economic structures. While southeast Asian economies do not appear to manage their exchange rates against each other, Frankel (1994) and Frankel and Wei (1994) show that the US dollar has a large weight in the exchange rate policies of several of them, which should lead them to pursue broadly similar monetary pol- icies. Accordingly, we report results using instrumental variables (IV) as well as OLS. The instruments in the former case were the log of the distance between countries and a zero/one common language dummy variable. 4 The estimates of fl and the respective t-statistics are report- ed in Table 2. There was not a significant relation between trade inte- gration between two southeast Asian economies and the degree of cor- relation of economic activity over 1976-1985; however, as integration increased over 1986-1996 there was a positive and statistically signif- icant relation, although the size of the coefficient on fl was relatively small (0.17 and 0.44 for the OLS and IV estimates, respectively).

4 The instruments are standard variables in the gravity model of bilateral trade.

Thornton/Goglio: Intra-Regional Trade and Business Cycles 169

T a b l e 2 - Est imates o f the Ef fec t o f Sou theas t As ian Trade In tens i ty on G D P : Growth Correlations, 1 9 7 6 - 1 9 9 6

(a) 1976-1985

Trade coefficient (fl)

(b) 1986-1996

Trade coefficient (fl)

Note: Estimates from:

Corr(y)~j~ = ct + fl Trade(t~)O T + eiO~.

OLS estimates IV estimates

0.105 0.222 (1.396) (1.936)

0.171 0.436 (2.080) (2.116)

See text for description of variables. Instrumental variables are the log of the dis- tance between pairs of economies and a dummy variable if economies share a com- mon language, t-statistics are in parentheses below the estimated coefficients.

III. Conclusion

In this note we considered the relationship between trade integra- tion and the cross-country correlation of business cycle activity in south- east Asia. We found a positive and significant relationship between the degree of bilateral trade intensity and the cross-country bilateral corre- lation of business activity over the period 1986-1996, a period when trade integration was proceeding rapidly. Thus, the Frankel and Rose (1997) finding that more trade integration between industrialized coun- tries tends to result in more highly synchronized business cycles, ap- pears to be robust to a sample of countries which have diverse income levels and economic structures and are likely to have less bilateral intra- industry trade.

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