Journal of Geographical Sciences

, Volume 25, Issue 10, pp 1247–1263 | Cite as

Estimating inter-regional trade flows in China: A sector-specific statistical model

  • Weidong LiuEmail author
  • Xin Li
  • Hongguang Liu
  • Zhipeng Tang
  • Dabo Guan


China has huge differences among its regions in terms of socio-economic development, industrial structure, natural resource endowments, and technological advancement. These differences have created complicated linkages between regions in China. In this study, building upon gravity model and location quotient techniques, we develop a sector-specific model to estimate inter-provincial trade flows, which is the base for making a multi-regional input-output table. In the model, we distinguish sectors with less intra-sector input from those with larger intra-sector input, and assume that the former sectors tend to compete among regions while the latter tend to cooperate among regions. Then we apply this new method of inter-regional trade estimation to three sectors: food and tobacco, metal smelting and processing, and electrical equipment. The results show that selection of bandwidth has a significant impact on the assessment of inter-regional trade. Trade flows are more scattered with the increase of bandwidths. As a result, bandwidth reflects the spatial concentration of geographical activities, which should be distinguishable for different industries. We conclude that the sector-specific spatial model can increase the credibility of estimates of inter-regional trade flows.


multi-regional input-output analysis trade flows sector-specific statistical model China 


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  1. Bergstrand J, 1985. The gravity equation in international trade: Some microeconomic foundations and empirical evidence. The Review of Economcis and Statistics, 67: 474–481.CrossRefGoogle Scholar
  2. Brunsdon C, Fotheringham A S, Charlton M E, 1996. Geographically Weighted Regression: A method for exploring spatial nonstationarity. Geographical Analysis, 28: 281–298.CrossRefGoogle Scholar
  3. Casetti E, 1972. Generating models by the expansion method: Applications to geographical research. Geographical Analysis, 4: 81–91.CrossRefGoogle Scholar
  4. Charlton M E, Fotheringham A S, 2009. Geographically Weighted Regression: Whilte Paper. National Centre for Geocomputation, National University of Ireland Maynooth.Google Scholar
  5. Chenery H B, 1953. Regional analysis. In: Chenery H B, Clark P G, Pinna V C (eds.). The Structure and Growth of the Italian Economy. Rome: U.S. Mutual Security Agency.Google Scholar
  6. Fan C C, 1997. Uneven development and beyond: Regional development theory in post-Mao China. International Journal of Urban and Regional Research, 21: 620–639.CrossRefGoogle Scholar
  7. Foster S A, Gorr W L, 1986. An adaptive filter for estimating spatially-varying parameters: Application to modeling police hours spent in response to calls for service. Management Science, 32: 878–889.CrossRefGoogle Scholar
  8. Guan D, Hubacek K, 2007. Assessment of regional trade and virtual water flows in China. Ecological Economics, 61: 159–170.CrossRefGoogle Scholar
  9. Hayami H, Nakamura M, 2007. Greenhouse gas emissions in Canada and Japan: Sector-specific estimates and managerial and economic implications. Journal of Environmental Management, 85: 371–392.CrossRefGoogle Scholar
  10. He L, Duchin F, 2009. Regional development in China: interregional transportation infrastructure and regional comparative advantage. Economic Systems Research, 21: 3–22.CrossRefGoogle Scholar
  11. Idaha T, 2005. How to utilize interregional input-output analysis in China. In: Okamoto N, Idaha T (eds.). Spatial Structure and Regional Development in China. New York: Palgrave Macmillan.Google Scholar
  12. Krugman P, Maurice O, 1997. International Economics Theory and Policy. 4th ed. Reading: Mass Addison-Wesley.Google Scholar
  13. Lenzen M, Pade L L, Munksgaard J, 2004. CO2 multipliers in multi-region input output models. Economic Systems Research, 16: 391–412.CrossRefGoogle Scholar
  14. LeSage J P, 1999. The theory and practice of spatial econometrics. Department of Economics, University of Toledo.Google Scholar
  15. LeSage J P, Pace R K, 2008. Spatial econometric modeling of origin-destination flows. Journal of Regional Science, 48: 941–967.CrossRefGoogle Scholar
  16. Liang Q M, Fan Y, Wei Y M, 2007. Multi-regional input-output model for regional energy requirements and CO2 emissions in China. Energy Policy, 35: 1685–1700.CrossRefGoogle Scholar
  17. McGregor P G, Swales J K, Turner K, 2008. The CO2 'trade balance' between Scotland and the rest of the UK: Performing a multi-region environmental input-output analysis with limited data. Ecological Economics, 66: 662–673.CrossRefGoogle Scholar
  18. Miller R E, Blair P D, 2009. Input-Output Analysis: Foundations and Extensions. New York, Cambridge University Press.CrossRefGoogle Scholar
  19. Minx J, Baiocchi G, Wiedmann T et al., 2009. Understanding changes in UK CO2 emissions 1992–2004: A structural decomposition analysis. UK: Stockholm Environment Institute.Google Scholar
  20. Moses L N, 1955. The stability of interregional trading patterns and input-output analysis. The American Economic Review, 45: 803–822.Google Scholar
  21. Munksgaard J, Pedersen K A, 2001. CO2 accounts for open economies: Producer or consumer responsibility? Energy Policy, 29: 327–334.CrossRefGoogle Scholar
  22. Munksgaard J, Pedersen K A, Wien M, 2000. Impact of household consumption on CO2 emissions. Energy Economics, 22: 423–440.CrossRefGoogle Scholar
  23. National Bureau of Statistics (NBS), 2011. Chinese Regional Input-Output Tables. Beijing: China Statistics Press.Google Scholar
  24. National Bureau of Statistics (NBS), 2012. China Statistical Yearbook. Beijing: China Statistics Press.Google Scholar
  25. Norman J, Charpentier A D, MacLean H L, 2007. Economic input-output life-cycle assessment of trade between Canada and the United States. Environmental Science & Technology, 41: 1523–1532.CrossRefGoogle Scholar
  26. Pan J, Phillips J, Chen Y, 2008. China's balance of emissions embodied in trade: Approaches to measurement and allocating international responsibility. Oxford Review of Economic Policy, 24: 354–376.CrossRefGoogle Scholar
  27. Peters G P, Hertwich E G, 2006. Pollution embodied in trade: The Norwegian case. Global Environmental Change, 16: 379–387.CrossRefGoogle Scholar
  28. Polenske K R, 1980. The U.S. Multiregional Input-output Accounts and Model. Lexington, MA, Lexington Books.Google Scholar
  29. Sargento A L M, 2007. Empirical examination of the gravity model in two different contexts: Estimation and explanation. Jahrbuch für Regionalwissenschaft, 27: 103–127.CrossRefGoogle Scholar
  30. Sargento A L M, Ramos P N, Hewings G J D, 2012. Inter-regional trade flow estimation through non-survey models: An empirical assessment. Economic Systems Research, 24: 173–193.CrossRefGoogle Scholar
  31. Shimoda T, Watanabe T, Ye Z et al., 2008. An empirical study on interdependency of environmental load and international IO structure in the Asia-Pacific region. In: International Input-Output Meeting on Managing the Environment. Seville, Spain.Google Scholar
  32. Shui B, Harriss R C, 2006. The role of CO2 embodiment in US-China trade. Energy Policy, 34: 4063–4068.CrossRefGoogle Scholar
  33. Tobler W R. 1970. A computer movie simulating urban growth in the detroit region. Economic Geography, 46: 234–240.CrossRefGoogle Scholar
  34. Turner K, Lenzen M, Wiedmann T et al., 2007. Examining the global environmental impact of regional consumption activities (Part 1): A technical note on combining input-output and ecological footprint analysis. Ecological Economics, 62: 37–44.CrossRefGoogle Scholar
  35. Walter I, 1973. The pollution content of American trade. Western Economic Journal, XI: 61–70.Google Scholar
  36. Wang J, Li L, Ge Y, 2000. A theoretic framework for spatial analysis. Acta Geographica Sinica, 55: 92–103.Google Scholar
  37. Weber C L, 2008. Uncertainties in constructing environmental multiregional input-output models. In: International Input-Output Meeting on Managing the Environment. Seville, Spain.Google Scholar
  38. Weber C L, Peters G P, Guan D et al., 2008. The contribution of Chinese exports to climate change. Energy Policy, 36: 3572–3577.CrossRefGoogle Scholar
  39. Wiedmann T, 2009. A review of recent multi-region input-output models used for consumption-based emission and resource accounting. Ecological Economics, 69: 211–222.CrossRefGoogle Scholar
  40. Wiedmann T, Lenzen M, Turner K et al., 2007. Examining the global environmental impact of regional consumption activities (Part 2): Review of input-output models for the assessment of environmental impacts embodied in trade. Ecological Economics, 61: 15–26.CrossRefGoogle Scholar
  41. Wiedmann T, Wood R, Minx J et al., 2008. Emissions embedded in UK trade - UK-MRIO Model results and error estimate. In: International Input-Output Meeting on Managing the Environment. Seville, Spain.Google Scholar
  42. Wyckoff A W, Roop J M, 1994. The embodiment of carbon in imports of manufactured products: Implications for international agreements on greenhouse gas emissions. Energy Policy, 22: 187–194.CrossRefGoogle Scholar
  43. Yang Z, Cai J, 2010. Progress of spatial statistics and its application in economic geography. Progress in Geography, 29: 757–768.Google Scholar

Copyright information

© Institute of Geographic Science and Natural Resources Research (IGSNRR), Science China Press and Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Weidong Liu
    • 1
    Email author
  • Xin Li
    • 2
  • Hongguang Liu
    • 3
  • Zhipeng Tang
    • 1
  • Dabo Guan
    • 2
    • 4
  1. 1.Institute of Geographic Sciences and Natural Resources Research, CASBeijingChina
  2. 2.Sustainability Research Institute, School of Earth and EnvironmentUniversity of LeedsLeedsUK
  3. 3.College of Public AdministrationNanjing Agricultural UniversityNanjingChina
  4. 4.ST Edmund’s CollegeUniversity of CambridgeCambridgeUK

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