Border Trade and Regional Integration - Wiley Online Library

Review of Development Economics, 18(2), 300–312, 2014 DOI:10.1111/rode.12085

Border Trade and Regional Integration Ying Ge, Yin He, Yeheng Jiang, and Xiaopeng Yin*

Abstract Although it is an important building block of regional integration, very little research has investigated border trade between neighboring countries. This paper fills this gap by examining the patterns and determinants of China’s border trade with its neighboring countries. First, a disaggregated, firm-product level trade data is used to provide a detailed overview of border trade growth and dynamics. The paper shows that trade liberalization has significantly encouraged new firms to enter the export market, and new private firms account for the majority of the expansion in border exports and the shift toward more sophisticated products. Second, a gravity model is used to investigate the determinants of border trade. The results suggest that multilateral and regional integration, market size and institutional quality play important roles in promoting border trade.

1. Introduction Border trade is defined as the exchange of goods and services across international land borders within a reach of up to 30 km. Studies on border trade are very limited owing to the difficulty of recording border transactions and their relatively small scale. While border trade only accounts for a small proportion of total international trade, it has important effects on the economic development of border regions and plays a significant role in the regional integration of inland areas. China is a particularly interesting case in the study of border trade because it has experienced rapid economic growth combined with sharply increasing regional disparities. It is well recognized that international trade is one of the main engines of economic growth and access to international trade is a driving force behind the substantial gap between the development of coastal and inland areas (Gao, 2004; Fu, 2004; Kanbur and Zhang, 2005). Figure 1 shows the geographic distribution of the regions of China involved in border trade. China borders fourteen countries (Afghanistan, Bhutan, Burma, India, Kazakhstan, Kyrgyzstan, Laos, Mongolia, Nepal, North Korea, Pakistan, Russia, Tajikistan and Vietnam) and has an inland border of more than 22,000 km. Eight provinces are involved in border trade: Liaoning, Jilin, Heilongjiang, Inner Mongolia, Xinjiang, Tibet, Yunnan and Guangxi. Most of these provinces are located in inland areas far from the coastline. The regional income of these provinces is below the national average, with Yunnan, Tibet and Guangxi the least developed provinces in China.1 Border trade has benefited the local economies in these areas by promoting local production and service provision, and increasing local employment and household income. Border trade

* Yin: No. 10, Huixin Street East, School of International Trade and Economics, University of International Business and Economics, P.O. Box 119, Beijing, China, 100029. Tel: +86-10-6449-3689; Fax: +86-106449-3042; E-mail: [email protected]. Ge, He and Jiang: School of International Trade and Economics, University of International Business and Economics, Beijing, China. The authors would like to thank an anonymous referee for helpful comments. Funding from University of International Business and Economics is gratefully acknowledged.

© 2014 John Wiley & Sons Ltd

BORDER TRADE AND REGIONAL INTERGRATION

Russia Kazakhstan

301

Russia

Russia Heilongjiang Mongolia

Kyrgyzstan

Xinjiang Inner Mongolia

Tajikistan

Pakistan Afghanistan

Liaoning

Jilin

Russia North Korea

Tibet

Nepal India

Bhutan India Yunnan

Guangxi

Burma Laos

Vietnam

Figure 1. Border Regions in China Notes: Darker areas with labeled names are China’s border provinces. They are Liaoning Province, Jilin Province, Heilongjiang Province, the Inner Mongolia Autonomous Region, the Xinjiang Uygur Autonomous Region, Tibet/the Xizang Autonomous Region, Yunnan Province, and the Guangxi Zhuang Autonomous Region. The 12 neighboring countries that are included in our dataset are labeled in dark, bold font. They are North Korea, Russia, Mongolia, Kazakhstan, Kyrgyzstan, Tajikistan, Afghanistan, Pakistan, Nepal, Burma, Laos, and Vietnam.

has also strengthened community ties across borders and facilitated regional integration with neighboring countries. There are few studies on China’s border trade and they mainly focus on the economic and political relationship between China and a specific trade partner. For example, Womack (1994) studied the border trade between China and Vietnam and found that this trade had significantly improved regional integration between Vietnam and the southwestern regions of China. He also found that policy changes played an important role in border trade. Roper (2000) examined the effects of SinoVietnamese political ties on the economic development of Vietnamese border regions. Quynh Cao and Wang (2011) showed that the China–Vietnam border trade structure reflected comparative advantage, with China exporting technology-intensive manufacturing products to Vietnam. They also found that infrastructure investments in border regions significantly promoted border trade. Kim (1994) suggested that China has become the largest trading partner of the Russian Far East since the collapse of the Soviet Union, mostly as a result of border trade. Wu and Chen (2004) examined Sino-Central Asian economic integration and found that border trade liberalization has had a large effect on the economic development of border regions. Raballand and Andresy (2007) also emphasized the important role of Sino-Central Asian border trade as part of China’s Go West policy, and suggested that Central Asian countries should further develop trade ties with China through border trade. All of these previous studies focused on a specific trade partner and used aggregate data on bilateral trade flows. There has been no systematic analysis of China’s border © 2014 John Wiley & Sons Ltd

302 Ying Ge et al. trade based on disaggregated trade data. In this paper, we fill this gap by providing an integrated perspective on China’s border trade with its twelve neighboring countries. We use a disaggregated customs trade dataset that covers all exporters and importers involved in border trade during the period from 2000 to 2006. These micro-level trade data provide a unique opportunity to examine the patterns and determinants of China’s border trade. First, we provide a detailed overview of border trade growth and dynamics at the national level, firm level and product level. The results suggest that trade liberalization has significantly encouraged new firms, and in particular private traders, to enter the export market. New private firms account for the majority of the sixfold export expansion, and the shift toward the export of more sophisticated products. In contrast, China’s border imports are growing at a much slower rate and are dominated by less sophisticated products, such as crude materials and mineral fuels. Second, we use a gravity model to investigate the determinants of border trade. We find that multilateral, regional and bilateral integration and collaborations play important roles in promoting border trade. Increasing market size and economic growth in neighboring countries are positively related to China’s border exports while the institutional quality of importing countries is negatively related to the level of border trade. The remainder of the paper is organized as follows. Section 2 describes the patterns of border trade at the national, firm, and product levels. Section 3 examines the determinants of China’s border trade and section 4 concludes the paper.

2. The Patterns of China’s Border Trade Data We use disaggregated trade transaction data, at the eight-digit harmonized system (HS) level, from Chinese Customs. This dataset covers monthly imports and exports for the period from 2000 to 2006. We aggregate the dataset to establish an annual frequency. The variables in this dataset include trade regime, value, quantity, and ownership and contact information of the firm (e.g. company name, telephone, zip code, contact person). These statistics are summarized in the Chinese Customs Statistical Yearbooks. Our sample covers all trade transactions with a trade regime classified as border trade and includes about 200,000 product-firm level trade transactions with 12 neighboring countries.2 General Patterns of Border Trade During the sample period, China’s border trade grew slower than its total value of international trade. The total commodity trade in China increased by a factor of 2.7, from US$474.3 billion in 2000 to US$1,421.9 billion in 2006. During this period, border trade has increased by a factor of 2.5, from US$4.6 billion in 2000 to US$16.1 billion in 2006. Figure 2 shows the overall trend of border trade growth. The growth of border trade was quite unbalanced; border exports increased more than sixfold while imports grew by only 92%. Another interesting feature of border trade is that China continued to run a trade deficit until 2005, despite an increasing trade surplus in total trade during the sample period. Figure 3 shows the industry composition of border trade. Manufacturing products accounted for more than 85% of border exports during the period from 2000 to 2006. © 2014 John Wiley & Sons Ltd

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0

2

Volume 4 6

8

10


2000

2001

2002

2003 year

Exports

2004

2005

2006

Imports

Figure 2. Trends in Border Trade Growth (US$ billion)

Exports

Imports

2.0%

8.2% 2.2% 2.4%

22.3%

15.8% 50.0% 62.1%

7.9%

17.8% 7.1%

Food & live animals

Beverages & tobacco

Crude materials, except fuels

Mineral fuels

Animal & vegetable oils

Chemicals & related products

Leather, rubber, wood, paper, etc.

Machinery & transport equipment

Miscellaneous manufactured articles

Figure 3. Industrial Composition of Border Trade

In contrast, the primary border imports were crude materials and mineral fuels, with manufactured products only accounting for a small portion of border imports. We use the definition and methodology from Rodrik (2006) to calculate the sophistication of China’s border trade as the follows: © 2014 John Wiley & Sons Ltd

9.2

9.25

Sophistication 9.3 9.35 9.4

9.45

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2000

2001

2002

2003 Year

Exports

2004

2005

2006

Imports

Sophitication is in logarithm

Figure 4. Export and Import Sophistication

Sopht = ∑ θ it hi ,

(1)

i

where θit is the export (or import) share of the HS six-digit product i in year t and hi is the sophistication of product i. Figure 4 illustrates the change in the sophistication of border trade between 2000 and 2006 and suggests that the sophistication of border exports significantly increased. This upgrade in border export structure is consistent with previous findings that China’s export basket has become more sophisticated and increasingly overlapped with that of more developed countries (Rodrik, 2006; Schott, 2005). Figure 4 also shows an opposite trend in import sophistication, which is because crude materials and mineral fuels play a dominant role in China’s border imports.

Firm-level Dynamics of Border Trade We use firm-level trade data to examine the patterns of both exports and imports. In 2000, there were only 874 exporters and 1,030 importers involved in border trade. This is consistent with previous finding that only a small number of firms are involved in international trade (Bernard et al., 2005). However, the number of traders increased significantly over the period of study. By 2006, the number of exporters had increased to 1,694 and the number of importers had increased to 1,595. We decompose the growth of border trade into extensive and intensive margins. The growth in the extensive margin represents the increase in trade value due to new products or the entry of new firms. The growth in the intensive margin refers to the increase in trade value that is due to existing products or firms. Following Amiti and Freund (2010), we use the following decomposition equation:

TVt − TVt − 1 SVt − SVt − 1 DVt − 1 NVt = − + , TV TV TV TVt 1 1 t− 1 −1 t − t − growth


intensive

extensive

(2)


305

Table 1. Trade Growth in Extensive and Intensive Firm Margins (%) Exports Period 2000–2001 2001–2002 2002–2003 2003–2004 2004–2005 2005–2006 2000–2006

Imports

Intensive

Extensive

Growth

Intensive

Extensive

Growth

–37 84 26 0 43 18 45

0 33 64 27 22 18 600

–37 117 90 27 65 36 645

–10 18 –8 16 9 4 5

12 0 19 1 4 4 86

2 18 11 17 13 8 91

where TV is the total trade value; SV is the trade value of the survival firms (or products) that continued to trade; DV is the trade value of firms (or products) that existed in the previous year but exited during the period; and NV is the trade value of new firms (or products) that entered the trading market during this period. Table 1 shows the border trade growth in the extensive and intensive margins. The results suggest that most of the growth in China’s border trade was due to the extensive margin. During the period from 2000 to 2006, border exports expanded more than sixfold, mainly owing to the contributions of new exporters. Border imports almost doubled during this period, with new importers accounting for 86% of this growth. Figure 5 reports the ownership composition of the traders. The patterns of border exports and imports are similar. In 2000, state-owned enterprises (SOEs) dominated border trade and privately owned enterprises (POEs) only accounted for about 5% of border exports and about 10% of border imports. The ownership structure of border trade significantly changed during the period of trade liberalization, marked by China’s access to the World Trade Organization (WTO). By 2006, the share of POEs in both border exports and imports had increased to more than 70%, while the share of SOEs had shrunk significantly. To examine the dynamics of border trade, we report the Kaplan–Meier survival rate of the trading firms in Figure 6. These results suggest that the border trade market is quite dynamic. Only 10% of traders survived in the export market throughout the sample period. About 29% of the firms exited the export market after the first year and the median time length of a firm exporting to a specific neighboring country is two years. SOEs have the highest survival rate, at about 20%. The survival rate of collectively owned enterprises (COEs) is about 12% and that of POEs is only 3%. The median length of survival for border importers is two years. The survival rate of firms after the first year in the import market is 79%, which is slightly higher than the survival rate in the export market. The survival rate of SOEs, COEs and POEs throughout the whole period is 26%, 20% and 3%, respectively.

Product-level Dynamics of Border Trade To investigate the product-level dynamics of border trade, we decompose the trade growth into intensive and extensive product margins and report the results in Table 2. There were a total of 5,828 HS 8-digit products included in the border export data. © 2014 John Wiley & Sons Ltd

100 80 60

Imports shares

0

20

40

60 40 0

20

Exports shares

80

100

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2000 2001 2002 2003 2004 2005 2006 POE COE

2000 2001 2002 2003 2004 2005 2006

SOE

POE COE

SOE

Figure 5. Ownership Composition of Traders Table 2. Trade Growth in Extensive and Intensive Product Margins (%) Exports Period 2000–2001 2001–2002 2002–2003 2003–2004 2004–2005 2005–2006 2000–2006

Imports

Intensive

Extensive

Growth

Intensive

Extensive

Growth

–36 105 87 25 62 36 574

–1 13 3 1 3 0 71

–37 118 90 26 65 36 645

–1 19 9 17 16 9 12

3 –1 2 0 –3 –1 79

2 18 11 17 13 8 91

Among these, 1,654 products were continuously exported from 2000 to 2006, and those products accounted for 75% of the total value of border exports. The intensive margin dominated the growth in border exports, with a growth rate of 574% during the sample period; in contrast, the growth rate of the extensive margin was only 71%. The pattern is slightly different in the border import market. Although border imports have grown much more slowly than exports, with a total growth rate of 91% over seven years, most of the growth came from the extensive margin (about 79%). There were 697 HS 8-digit products imported by China in 2000 and the number of imported products increased to 779 in 2006. There were only 224 products that were © 2014 John Wiley & Sons Ltd


0.75 0.50 0.25 0.00

0.50 0.25 0.00

Survival rate

0.75

1.00

Imports

1.00

Exports

307

2000 2001 2002 2003 2004 2005 2006 Year COE SOE

POE

2000 2001 2002 2003 2004 2005 2006 Year COE SOE

POE

Figure 6. Firm-Importer–Exporter Kaplan–Meier Survival Rate

consistently imported throughout the whole period and the share of these products as a percentage of total imports shrank from 59% in 2000 to 37% in 2006. Figure 7 shows the Kaplan–Meier survival rate of trading products. The median survival time of trading products was two years. About 40% of products traded with a specific neighboring country disappeared after the first year. Only 14% of exporting relationships and 18% of importing relationships survived throughout the seven-year study period. This pattern is similar to trade durations in the USA (Besedes and Prusa, 2006a,b) and the EU (Hess and Persson, 2011). The median time length of a product-importer–exporter relationship in the USA is 2–4 years and the trade duration is even shorter in the EU. In summary, both firm-level and product-level analysis suggests that China’s border trade is quite dynamic. Trade liberalization has significantly encouraged new firms and particularly private traders to enter the export market. New private firms accounted for the majority of the sixfold export expansion and the shift toward the export of more sophisticated products. In contrast, China’s border imports grew at a much slower rate and were dominated by less sophisticated products, such as crude materials and mineral fuels.

3. Determinants of China’s Border Trade In this section, we use the gravity model to identify the important determinants of China’s border exports. The specific feature of border trade in the gravity equation is that the geographical distance between the trading countries is zero. We use © 2014 John Wiley & Sons Ltd

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0.25 0.00

0.50

0.25

0.50

0.75

1.00

Imports

0.00

Survival rate

0.75

1.00

Exports

2000 2001 2002 2003 2004 2005 2006 Year

2000 2001 2002 2003 2004 2005 2006 Year

Figure 7. Product-Importer-Exporter Kaplan-Meier Survival Rate

disaggregated firm-product level trade data to examine the determinants of border trade.3 We focus not only on export value but also on the unit price and quantity of products, adopting the following gravity equation.

ln X fjht = β1 ln GDPjt + β 2Growthjt + β 3WTOjt + β 4 SCOjt + β 5 Pact jt + β6 Institution jt + β 7 POE f + δ h + λt + γ j + ε fhjt

(3)

where Xfjht represents the export value, unit price, or quantity of an HS eight-digit product h that is exported from China to neighboring country j at year t; GDPjt is the gross domestic product (GDP) of neighbor j at year t, which measures the market size of the importing country; Growthjt is the growth rate of GDP in country j; WTOjt is a dummy variable that is equal to one if both China and the importing country j were WTO members in year t, and zero otherwise. SCOjt measures the membership of the Shanghai Cooperation Organization (SCO), which takes the value of one if both China and neighbor j were in the SCO in year t and zero otherwise; Pactjt is the number of economic pacts signed between China and country j in year t, which measures how close the political and economic relationship is between the two countries. Institutionjt is the institutional quality of country j in year t. We use two indexes from the World Governance Index (WGI) of the World Bank (Law and Control of Corruption) to assess institutional quality. Both indexes take values between –2.5 and 2.5, with a larger value representing better governance. POEf is a dummy variable that is equal to one if the exporter f is a private firm, and zero otherwise. δh, λt and γj are, respectively, product, year and country fixed effects. εfjht is an error term. The estimation results of the gravity model are reported in Table 3. Columns (1) and (2) report the results for export value, columns (3) and (4) report the results for © 2014 John Wiley & Sons Ltd

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BORDER TRADE AND REGIONAL INTERGRATION Table 3. Determinants of Border Trade Export value

LnGDP GDP Growth WTO SCO PACT Law Control of Corruption POE

Quantity

Unit value

Export value

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

0.519*** (0.037) 2.704*** (0.430) 0.217*** (0.029) 0.817*** (0.038) 0.017*** (0.002) –0.688*** (0.051)

0.455*** (0.036) 1.781*** (0.425) 0.156*** (0.033) 0.669*** (0.037) 0.015*** (0.002)

0.245*** (0.037) 1.639*** (0.423) 0.209*** (0.030) 0.632*** (0.038) 0.010*** (0.002) –0.593*** (0.051)

0.199*** (0.036) 1.046** (0.418) 0.128*** (0.034) 0.499*** (0.037) 0.009*** (0.002)

0.273*** (0.018) 1.066*** (0.205) 0.008 (0.015) 0.185*** (0.019) 0.006*** (0.001) –0.094*** (0.024)

0.255*** (0.018) 0.735*** (0.200) 0.027 (0.017) 0.169*** (0.019) 0.006*** (0.001)

0.295*** (0.051) 3.802*** (0.495) 0.149*** (0.042) 0.615*** (0.053) 0.011*** (0.002) –0.860*** (0.061)

0.195*** (0.050) 2.852*** (0.492) 0.076* (0.045) 0.383*** (0.051) 0.008*** (0.002)

0.027** (0.011)

–0.369*** (0.045) 0.029** (0.011)

0.019* (0.011)

–0.401*** (0.045) 0.021* (0.011)

0.009 (0.005)

0.031 (0.022) 0.008 (0.005)

Sophistication Sophistication Squared Country fixed effect Yes Year fixed effect Yes Product fixed effect Yes Firm fixed effect No R-squared 0.379 Observations 156,080

Yes Yes Yes No 0.379 156,080

Yes Yes Yes No 0.734 156,080

Yes Yes Yes No 0.734 156,080

Yes Yes Yes No 0.900 156,080

Yes Yes Yes No 0.900 156,080

–0.470*** (0.053)

1.441*** (0.315) –0.114*** (0.017)

1.436*** (0.315) –0.113*** (0.017)

Yes Yes No Yes 0.301 156,080

Yes Yes No Yes 0.300 156,080

Notes: Robust standard errors are in parentheses, ***p < 0.01, **p < 0.05, *p < 0.1.

export quantity and columns (5) and (6) report the results for unit value. These results suggest that the GDP of the importing country has a significant and positive effect on export value. The growth rate of GDP, which represents the future market potential of importing countries, also has a significant effect in promoting border trade. The results show that income and the GDP growth rate of the destination countries are positively correlated with the unit value of border exports. This is consistent with recent studies on quality differentiation that find that firms charge higher prices in richer destinations (e.g. Schott, 2004; Hallak, 2006; Baldwin and Harrigan, 2011). The results in Table 3 show that multilateral, regional and bilateral integration and collaborations play important roles in promoting border trade. In previous study, there is some debate about the effects of multilateral and regional trade agreement on trade flow. Although WTO membership is usually expected to promote bilateral trade between member countries, Rose (2004) found that the General Agreement on Tariffs and Trade (GATT)/WTO did not play a strong role in encouraging trade. In contrast, our results show that the WTO has had a significant and positive effect on both the export value and the quantity of border trade. The effects of SCO membership on border trade are much larger than those of WTO membership, which suggests that regional economic and political cooperation plays a more significant role in promoting border trade. This is consistent with a previous study by the World Bank (2007), which found that Central Asia Regional Economic Cooperation facilitated © 2014 John Wiley & Sons Ltd

310 Ying Ge et al. border trade within member countries and that border trade buttressed prosperity in these countries.4 Bilateral economic collaboration, as measured by the number of bilateral economic pacts between China and her trading partners, also has a positive effect on both the quantity and quality of border trade. The institutional quality of importing countries is likely to play a significant role in border trade. There is a large amount of literature on the effects of institution quality on international trade, with most studies focusing on the “extortion effect” in which bad institutions and corruption in the importer’s country increase trade costs and thus deter international trade. For example, Anderson and Marcouiller (2002) show that when law enforcement institutions are ineffective, corrupt government officials and other predators are able to steal and to collect bribes from traders at the importer’s border. However, bad institutions may be trade enhancing due to the “evasion effect” in which rent-seeking, corrupt officials allow traders to evade tariff barriers. For example, Dutt and Traca (2010) found that the marginal effect of corruption is trade enhancing in high-tariff environments. Our results show similar patterns for both indexes of institution quality: Law and Control of Corruption. The institutional quality of the importing country is negatively correlated with border exports from China. As most of China’s border trade partners are less developed countries with low institutional qualities, our results suggest that the “evasion effect” dominates the “extortion effect” in border trade. The previous section on border trade patterns showed a significant trend of an increasing importance of private firms in the border trade market. Using a gravity model, we investigate the link between the ownership of firms and border exports. The results in Table 3 show that export value is positively correlated with private ownership, which is consistent with trade patterns. For a robustness check, we control firm-fixed effects instead of product-fixed effects to investigate the link between border trade and product attributes. We include product sophistication and its squared term in the gravity model. The sophistication index for HS 6-digit products is defined and calculated by Rodrik (2006). The results are reported in columns (7) and (8) of Table 3. The estimated coefficient of product sophistication is positive and significant, which is consistent with the findings of previous sections that China’s border exports are shifting toward more sophisticated products. However, the link between border exports and product sophistication is not linear. The coefficient of the quadratic term is negative, which suggests that border exports concentrate on manufacturing products with a medium level of sophistication.

4. Concluding Remarks We use disaggregated firm-product level trade data to examine the patterns and determinants of China’s border trade. We find that trade liberalization has significantly encouraged new firms, especially private traders, to enter the export market. New private firms account for the majority of the sixfold expansion in exports, and the shift toward the export of more sophisticated products. In contrast, China’s border imports are growing much more slowly and are dominated by less sophisticated products, such as crude materials and mineral fuels. The gravity equation analysis shows that multilateral, regional and bilateral integration and collaborations play important roles in promoting border trade. Increasing market size and economic growth in neighboring countries are also positively related © 2014 John Wiley & Sons Ltd


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with China’s border exports, while the institutional quality of importing countries is negatively related to border trade.

References Amiti, M. and C. Freund, “The Anatomy of China’s Export Growth,” in N. R. Feenstra and S.-J. Wei (eds), China’s Growing Role in World Trade, Chicago, IL: University of Chicago Press (2010). Anderson, J. and D. Marcouiller, “Insecurity and the Pattern of Trade: An Empirical Investigation,” Review of Economics and Statistics 84 (2002):345–52. Baldwin, Richard and James Harrigan, “Zeros, Quality, and Space: Trade Theory and Trade Evidence,” American Economic Journal: Microeconomics 3 (2011):60–88. Bernard, A., B. Jensen, and P. Schott, “Importers, Exporters, and Multinationals: A Portrait of Firms in the U.S. that Trade Goods,” NBER working paper 11404 (2005). Besedes, T. and T. Prusa, “Ins, Outs, and the Duration of Trade,” Canadian Journal of Economics 39 (2006a):266–95. ———, “Product Differentiation Duration of US Import Trade,” Journal of International Economics 70 (2006b):266–95. Dutt, P. and D. Traca, “Corruption and Bilateral Trade Flows: Extortion or Evasion?” Review of Economics and Statistics 92 (2010):843–60. Fu, X., “Limited Linkages from Growth Engines and Regional Disparities in China,” Journal of Comparative Economics 32 (2004):148–64. Gao, T., “Regional Industrial Growth: Evidence from Chinese Industries,” Regional Science and Urban Economics 34 (2004):101–24. Hallak, J., “Product Quality and the Direction of Trade,” Journal of International Economics 68 (2006):238–65. Hess, W. and M. Persson, “Exploring the Duration of EU Imports,” Review of World Economics 147 (2011):665–92. Kanbur, R. and X. Zhang, “Fifty Years of Regional Inequality in China: A Journey through Central Planning, Reform and Openness,” Review of Development Economics 9 (2005):87– 106. Kim, W., “Sino-Russian Relations and Chinese Workers in the Russian Far East: A Porous Border,” Asian Survey 34 (1994):1064–76. Quynh Cao, T.N. and X. Wang, “Sino-Vietnamese Trade Relations—with a Focus on CrossBorder Trade,” University of Gothenburg, Master Degree Thesis No. 2011:5, Gothenburg, Sweden (2011). Raballand, G. and A. Andresy, “Why Should Trade between Central Asia and China Continue to Expand?” Europe-Asia 5 (2007):235–52. Rodrik, D., “What’s So Special about China’s Exports,” China and World Economy 14, no. 5 (2006):1–19. Roper, C., “Sino-Vietnamese Relations and the Economy of Vietnam’s Border Region,” Asian Survey 40 (2000):1019–41. Rose, Andrew K., “Do We Really Know that the WTO Increases Trade?” American Economic Review 94 (2004):98–114. Schott, P., “Across-product versus Within-product Specialization in International Trade,” Quarterly Journal of Economics 119 (2004):647–78. ———, “The Relative Sophistication of Chinese Export,” NBER working paper 12173 (2005). Womack, B., “Sino-Vietnamese Border Trade: The Edge of Normalization,” Asian Survey 34 (1994):495–512. World Bank, “Cross-border Trade within the Central Asia Regional Economic Cooperation,” CAREC Institute, World Bank Report, Washington, DC (2007). Wu, H. and C. Chen, “The Prospects for Regional Economic Integration between China and the Five Central Asian Countries,” Europe–Asia Studies 56 (2004):1059–80. © 2014 John Wiley & Sons Ltd

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Notes 1. In 2010, the GDP per capita of five of these provinces was below the national average level, with Yunnan, Tibet and Guangxi ranked at 30, 28 and 26, respectively. The per capita annual income levels of urban households in seven out of the eight border provinces were below the national average, with Heilongjiang, Jilin and Yunnan ranked 31, 29 and 27, respectively, among the 31 provinces and municipal cities in China. Similarly, the per capita net annual income levels of rural households in seven out of the eight border provinces was below the national average, with Heilongjiang, Xinjiang and Tibet ranked 30, 28 and 26, respectively. 2. The Chinese Customs dataset does not include trade with India or Bhutan. 3. A small proportion of the firms involved in border trade are not located in border regions. To examine the determinants of border trade more precisely, we only include traders located in border regions. For a robustness check, we also estimate the gravity model using the full sample and the results are very similar to our benchmark results presented in Table 3. The results of the gravity model based on the full dataset are available upon request. 4. The members of the Central Asia Regional Economic Cooperation included in this dataset are Afghanistan, Azerbaijan, China, Kazakhstan, Kyrgyzstan, Mongolia, Tajikistan and Uzbekistan.
