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References

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Appendix I. Summary Statistics

(Obtained from the Sample Used in the Benchmark GDP Growth Regression)

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Appendix IIA. Coefficient Estimates of the Benchmark GDP Growth Regressions Using Output-Weighted Indices

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Notes: The dependent variable is 5-year average of real GDP growth. The North and Emerging South GDP refer to the 5-year averages of the output-weighted GDP growth indices of the respective groups. Coefficient estimates regarding standard growth variables are not reported but available from the authors upon request. Heteroscedasticity consistent robust standard errors from the pooled OLS regression are reported in parenthesis. The symbols *, ** and *** indicate statistical significance at the 10 percent, 5 percent, and 1 percent levels respectively.
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Notes: The dependent variable is 5-year average of real GDP growth. The North and Emerging South GDP refers to the 5-year averages of the output-weighted growth indices of the respective groups. Each of the North and Emerging South countries has a respective country-specific output-weighted group-wide GDP index calculated by adjusting the PPP weights for the rest of the corresponding group. Coefficient estimates regarding standard growth variables are not reported but available from the authors upon request. Heteroscedasticity consistent robust standard errors from the pooled OLS regression are reported in parenthesis. The symbols *, ** and *** indicate statistical significance at the 10 percent, 5 percent, and 1 percent levels respectively.

Appendix IIB. Coefficient Estimates of the Benchmark Sectoral Growth Regressions

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Notes: The dependent variables are 5-year averages of annual industry, services and agriculture value-added growth at constant local currency. Coefficient estimates regarding standard growth variables are not reported but available from the authors upon request. The North and Emerging South sectoral activity refer to the 5-year average growth of the country specific trade-weighted indices of the respective groups. Heteroscedasticity consistent robust standard errors from the pooled OLS regressions are reported in parenthesis. The symbols *, ** and *** indicate statistical significance at the 10 percent, 5 percent, and 1 percent levels respectively.

Appendix III. Coefficient Estimates of the Full Model for the GDP Growth Regressions

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Notes: The dependent variable is 5-year average of real GDP growth. Heteroscedasticity consistent robust standard errors from the pooled OLS regression are reported in parenthesis. Coefficient estimates from the standard growth variables are not reported but available from the authors upon request. The North and Emerging South GDP refer to the 5-year averages of the country specific trade-weighted GDP growth indices of the respective regions. The symbols *, ** and *** indicate statistical significance at the 10 percent, 5 percent, and 1 percent levels respectively.

Appendix IVA. Regional Extensions of the Benchmark and Full Regression Models

(GDP and Industry Growth)

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Notes: The dependent variables are 5-year averages of real GDP and industry value-added growth. Heteroscedasticity consistent robust standard errors from the pooled OLS regression are reported in parenthesis. The symbols *, ** and *** indicate statistical significance at the 10 percent, 5 percent, and 1 percent levels respectively. The Asia-Pacific and Latin America and the Caribbean samples are obtained by including all the Emerging South and Developing South economies in each geographical region. The first column of the tables refers to the standard benchmark growth regressions. Columns 2 and 3 refer to the full growth model with the 5-year averages of the de-jure trade openness, FDI-Portfolio liabilities to GDP ratio and oil price change added to the benchmark specification. The North and Emerging South GDP and industry activity refer to 5-year average growth of the country specific trade-weighted indices of the respective groups. Coefficient estimates regarding export structure, openness and common shock variables as well as the globalization and the pre-globalization impact of the North and Emerging South growth are reported. Coefficient estimates from other standard growth variables are not reported but they are available from the authors upon request.

Appendix IVB.

Figure IVa.
Figure IVa.

Growth Impact of the North

(Coefficient Estiamates from the Benchmark Regressions)

Citation: IMF Working Papers 2007, 280; 10.5089/9781451868432.001.A999

Notes: The benchmark pooled OLS coefficient estimates showing the globalization and pre-globalization effects of the North and Emerging South GDP growth on the Asia Pacific and Latin America and the Caribbean regions are taken from the first column of the tables in Appendix IVA and the corresponding regressions using sectoral growth rates.
Figure IVb.
Figure IVb.

Growth Impact of the Emerging South

(Coefficient Estiamates from the Benchmark Regressions)

Citation: IMF Working Papers 2007, 280; 10.5089/9781451868432.001.A999

Notes: See figure IVa.

Appendix V. List of Countries

North (23)

East Asia and Pacific

Australia, Japan, New Zealand

North America

Canada, United States

Europe

Austria, Belgium, Switzerland, Denmark, Spain, Finland, France, United Kingdom, Germany, Greece, Ireland, Iceland, Italy, Luxembourg*, Netherlands, Norway, Portugal, Sweden

Emerging South (23)

Latin America and the Caribbean

Argentina, Brazil, Chile, Colombia, Mexico, Peru, Venezuela.

South Asia, East Asia and the Pacific

China, Hong Kong SAR, India, Indonesia, Korea, Malaysia, Pakistan, Philippines, Singapore, Thailand

Europe

Turkey

Middle East and North Africa

Egypt, Israel, Jordan, Morocco*

Sub-Saharan Africa

South Africa

Developing South (60)

Middle East and North Africa

Algeria, Tunisia, Syrian Arab Republic

South Asia, East Asia and the Pacific

Bangladesh, Nepal, Sri Lanka, Papua New Guinea

Latin America and the Caribbean

Barbados, Bolivia, Ecuador, El Salvador, Guatemala, Paraguay, Costa Rica, Dominican Republic, Guyana, Haiti, Honduras, Jamaica, Nicaragua, Panama, Trinidad and Tobago**, Uruguay

Sub-Saharan Africa

Benin, Botswana, Burkina Faso*, Burundi*, Cameroon, Cape Verde*, Central African Republic, Chad*, Comoros*, Congo, Dem. Rep., Congo, Rep., Cote d’Ivoire*, Equatorial Guinea*, Ethiopia*, Gabon*, Gambia, Ghana, Guinea*, Guinea-Bissau, Kenya, Lesotho, Madagascar*, Malawi, Mali, Mauritania, Mauritius, Mozambique, Niger, Nigeria*, Rwanda, Senegal, Seychelles**, Tanzania, Togo, Uganda, Zambia, Zimbabwe.

Notes: * and ** indicate the countries that are not included in the benchmark and the full model regressions due to incomplete data.

Appendix VI. Data Sources and Descriptions

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1

Çiğdem Akın is with George Washington University. We would like to thank Michael Plummer and two anonymous referees for useful suggestions. We are grateful to Peter Berezin, Stijn Claessens, Selim Elekdağ, Thomas Helbling, Hideaki Hirata, Rolf Langhammer, Jong-Wha Lee, Eswar Prasad, Tara Sinclair, Nikola Spatafora, Marco Terrones, Kamil Yılmaz, and Kei-Mu Yi for helpful comments. A slightly shorter version of this paper will soon be published in the Journal of Asian Economics. Dionysios Kaltis provided able research assistance.

2

These changes have been the subject of several articles in the media, as the quote at the top of this page and following examples show: “The new prominence of emerging markets represent a sharp departure from the flurry of financial crises that tore through Mexico, Asia, and Russia in the 1990s…” (USA Today, February 8, 2007); and “the idea that the world economy was being pushed along in an American supermarket trolley was always an exaggeration… The difference now is that the rest of the world is doing more of the carrying…” (The Economist, February 24, 2007). In addition, these changes have recently been at the center of an intensive debate about whether emerging market economies can decouple from the slowing of the U.S. economy (see Helbling and others, 2007, and Dées and Vansteenkiste, 2007).

3

The globalization period also coincides with a prolonged decline in the volatility of output in a number of countries in the North (see Kose, Otrok and Whiteman, 2007). In addition, the beginning of the globalization period marks the start of the Uruguay Round negotiations which substantially accelerated the process of unilateral trade liberalizations in many developing countries.

4

Their methodology closely follows the one in Kose, Otrok, and Whiteman (2003) who decompose the volatility in output, consumption, and investment into the world, region, country, and idiosyncratic components using a sixty-country sample over the 1960–90 period.

5

Several other researchers find relatively stronger business cycle co-movement among developed economies using factor models (see Kose, Otrok, and Whiteman, 2007 and Canova, Ciccarelli, and Ortega, 2007) or simple correlations (see Kose, Prasad, and Terrones, 2003).

6

Similarly, Calderon, Loayza, and Schmidt-Hebbel (2005) show the importance of the growth rate of trade partners in explaining domestic growth using a sample of 76 countries during 1970–2000. Ahmed and Loungani (2000) employ a vector-error correction model for the period of 1973–96 to estimate the impact of export weighted aggregate GDP of the largest trading partners on domestic output of several emerging market economies in Asia and Latin America. They report that the impact of foreign output shocks is roughly one-for-one after controlling for other shocks. Hsiao, Hsiao and Yamashita (2003) analyze the extent of interdependence between the United States and the Asia-Pacific region using VAR models.

7

The countries in this group roughly correspond to those included in the MSCI Emerging Markets Index. The main differences are that we drop the transition economies because of limited data availability and add Hong Kong SAR, Singapore and Venezuela.

8

Using PPP exchange rates is generally thought to provide a more balanced estimate of the relative importance of the rich and the poor countries since they adjust for the price distortions between traded and non-traded goods (see Callen, 2007). Developing countries constitute a much smaller share of the world economy when measured with weights in constant 2000 US dollars (see Helbling and others, 2007).

9

Implications of increased trade and financial flows for economic growth in the Emerging and Developing South economies have been the subject of numerous papers (see Kose and others, 2006; and Winters, 2004).

10

The rapid growth of Emerging South economies and their future growth potential have been a central theme in recent research. In particular, the growth potential of Brazil, Russia, India, and China (the BRIC economies) has been widely studied (see Coleman, 2007; Prasad, 2004; Tseng and Cowen, 2005; Aziz, Dunaway and Prasad, 2006; and Wilson and Purushothaman, 2003).

11

Developing countries undertook the majority of unilateral trade liberalizations reported to the GATT following the beginning of the Uruguay Round negotiations in 1986 (see Qureshi, 1996).

12

Due to data limitations, the Grubel-Lloyd indices are available only bilaterally. In order to compute the intra-industry trade intensity, the index values of different countries in the Emerging South group are averaged. Similarly, the average index values of the G-7 countries are used as a proxy for the North.

13

Most of these structural changes that can be classified as “pull factors” have taken place in the Emerging South economies. Privatization of state-owned enterprises, removal of restrictions on the acquisition of assets by foreigners, liberalization of domestic banking systems and stock markets, as well as gradual establishment of liberal capital account regimes have attracted the international capital flows towards the developing countries. As for the “push factors”, demographic changes in the North countries have resulted in a search for higher returns (see Prasad and others, 2003 for details). For a detailed discussion of the evolution of foreign assets and liabilities around the world, see Lane and Milesi-Ferretti (2006).

14

See Burgstaller and Saavedra-Rivano (1984) for an extension of the Findlay model with mobile capital flows. The model implies an inverse relationship between changes in the world capital stock and the South terms of trade. Beenstock (1988) shows that demand spillovers for the South exports through trade and a subsequent increase in the real commodity prices and terms of trade provide the main mechanism for the cyclical fluctuations and growth in the South economies. Chui and others (2002) provide a survey of the theoretical North-South models that combine the theory of trade with growth theory. For an excellent exposition of the insights from the earlier development literature analyzing the North-South linkages, see Lewis (1979).

15

Zebregs (2004b) shows that trade flows in Asia have become more China-centric overtime as the Chinese market accounted for 17 percent of the Asian exports in 2002. Gaulier, Lemonie and Unal-Kesenci (2007) document the increase in the volume of vertical trade flows within Asia. For a detailed discussion of the changing nature of China’s trade structure, see Cui and Syed (2007). IMF (2007) provides a brief discussion of the contribution of individual countries to global growth in recent years.

16

For example, China absorbed more than 8 percent of total raw material exports of the Developing South group making it the third largest market after the EU with 34 percent and the United States with 23 percent in 2002 (see Yang, 2003).

17

See Burstein, Kurz, and Tesar (2007) and Kose and Yi (2001, 2006) for models explaining the impact of vertical trade integration on the synchronization of business cycles.

18

We use the annual growth rates of constant local currency values of GDP, industry, services and agriculture value added. Detailed information about the list of countries and data series is provided in Appendices V-VI.

19

When the annual growth rate of GDP or sectoral aggregate is multiplied with the lagged weight for each country, the nominator of the weight term and the denominator of the growth term will cancel out each other and the sum of the product over the sample will be equal to the aggregate growth of each group. Output weights are used both in the calculations of GDP and sectoral output indices.

20

Since the quality of bilateral trade data for the Developing South countries is quite low, the trade weighted indices for this group are not constructed.

21

Since China belongs to the Emerging South group, the rest of Emerging South group is used to calculate the total trade of China with this group. The major trading hubs, including Hong Kong and Singapore, are excluded from the Emerging South group due to their disproportionately large shares of trade.

22

According to the trade-weighted index, for example, the African economies that trade heavily with France will have larger weights for France in the calculation of the North group-wide index in comparison to the Latin American economies that trade relatively less with France. Similarly, the Asian economies will have greater weights for the Japanese growth in their North indices because of their stronger trade linkages with Japan.

23

We focus on the differences between the Bretton Woods and globalization periods since we would like to isolate the impact of common shocks from that of globalization on the evolution of international growth spillovers over time (see Kose, Otrok and Whiteman, 2007).

24

We also compute the 10-year rolling window correlations of output and sectoral aggregates and find broadly consistent results with those reported in these tables.

25

The use of 5-year panels allows us to analyze the growth spillovers in the medium-term dampening the potential impact of transitory and volatile idiosyncratic shocks in shorter horizons. The panel regressions could also help explain some medium-term trends rather than year-to-year changes which are more apparent in the cross-correlations reported in the previous section. We tested the poolability of our specifications against the fixed or the random effects estimations but the existence of individual effects is rejected for the majority of the specifications.

26

The results with the output-weighted indices are broadly consistent with the results using trade-weighted indices (see Appendix IIA). Results with 1991 as the starting year of the globalization period are also similar.

27

As we discuss earlier, there are no significant changes in the nature of North-South trade and financial linkages in the pre-globalization period. In the previous section, we separate the common shock period to account for the impact of oil shocks in the 1970s and the contractionary monetary policies in the early 1980s. When we combine the two periods and compare the contemporaneous correlations of GDP and sectoral growth of the groups, we still observe the divergence of the cross-group activity in the globalization period.

28

Investment is significant in all specifications; the convergence variable is significant for the North and Emerging South groups; human capital development is significant for the GDP growth of the Emerging South group; population growth is significant for all the groups except the Emerging South; and inflation is significant for all the groups except the North.

29

The results by Arora and Vamvakidis (2006) partially support our findings about the importance of the North GDP growth for the rest of the world. Their study looks at the growth spillovers from the United States during the period of 1980–98 for a large sample of developed and developing countries and finds that a one percentage point increase in the growth of the U.S. GDP generates a one percentage point increase in the growth of rest of the world.

30

However, as we discuss later, this change is significant in the case of Asia Pacific countries.

31

Detailed results of the regressions associated with the sectoral growth spillovers are presented in Appendix IIB.

32

In addition, we check the impact of outliers employing two methods. First, we run our robust regressions using the iteratively re-weighted least squares. Second, we apply an alternative methodology by excluding the observations that are two standard deviations above or below the mean growth rate of the samples. Both methods lead to broadly similar coefficient estimates with those of the benchmark regressions. The results of these regressions are available from the authors upon request.

33

Manufacturing exports have a significant impact on GDP and sectoral growth of the whole sample and the Emerging South GDP. We find that trade openness has a positive impact on the GDP, industry and services growth of the Developing South group, and the GDP and services growth of the North group. Financial openness has a positive impact on the North. In contrast, the impact on the Emerging South is either statistically insignificant for the growth rates of GDP and services or negative for the industry growth. Finally, oil price changes positively affect the Developing South growth.

34

Note that these two regions include countries from both the Emerging and Developing South groups.

35

For additional information about the decoupling debate in the context of Asia, see He, Cheung and Chang (2007) and Asian Development Bank (2007).

36

For recent surveys on international policy coordination, see Meyer and others (2004) and Canzoneri, Cumby, and Diba (2005).

37

In his Nobel Prize lecture, Lewis (1979) notes that “…For the past hundred years the rate of growth of output in the developing world has depended on the rate of growth of output in the developed world. When the developed world grow fast the developing world grow fast, when the developed slow down, the developing slow down. Is this linkage inevitable?…” The results reported in this paper suggest that the nature of linkages between the developed world and the developing world has been changing, and, at least for the group of Emerging South countries of the developing world, the linkage Lewis identified appears to be evitable.

38

For an early discussion of these issues, see Currie and Vines (1988). Chui and others (2002) provide a survey of theoretical North-South models focusing on trade and growth. For some recent modeling efforts analyzing the implications of the changing nature of international trade linkages for the growth of world trade and transmission of business cycles, see Kehoe and Ruhl (2003), Yi (2003), Kose and Yi (2006), and Burstein, Kurz, and Tesar (2007).

Changing Nature of North-South Linkages: Stylized Facts and Explanations
Author: Miss Cigdem Akin and Mr. Ayhan Kose