How important are inter-city spillovers for FDI? Evidence from Chinese Cities (work-in-progress)

1. How important are inter-city spillovers for FDI? Evidence from Chinese Cities(work-in-progress) Chang Liu Sailesh Gunessee Presentation at School of Economics, Zhejiang University, 23rd December 2010

2. Research Background & Motivation Wide array of contributions to the literature on FDI in China. While we’ve learnt a lot yet we identify some issues: • Spatial relationship quite rare in FDI studies in general (Coughlin and Segev, 2000; Hong et al., 2008; Chen, 2009) • omission of spatial interdependence of FDI > may lead to biased estimates > fail to capture third-country effects (see Yeaple , 2003; Ekholm et al., 2007; Blonigen, et al. 2007). Thus, neighbourhood effects & spillovers neglected in most previous studies. • Inter-city spillovers understudied • Most work have used provincial data or combination of ‘firm-provincial data’. • Spatial studies focus on ‘inter-provincial’ spillovers + Spillovers better captured in smaller areas • Two notable studies using city-level data (He, 2002) and firm-city (Head and Ries, 1996): both ignore spatial elements • Regional differences: limited consideration given due to use of provincial data. 04/10/2014 2

3. Our work & Research Objectives • 1) How important are inter-city spillovers for FDI? {Is FDI in one city promoted by FDI/Market Potential in surrounding cities or at the expense?}; • 2) Is the influence the same for - i) the Hinterland and the Eastern regions. • Use city-level data to examine relationship between FDI and neighbouring market potential & the spatial lag of FDI (two major sources identified by literature). {These may also be important to tell us about FDI motives (see Blonigen et al. 2007; Ledyaeva, 2009).}

4. Our work & Insights • Potential insights from this work? • uncover insights into the importance of inter-city spillovers. • Since 2000 regional policy, to reduce regional disparity, has banked on ‘cheap labour costs’ and an ‘even spread of resources’ under the Great Western Development Strategy (GWDS) and Central China Rising Strategy (CCRS) to prop up the Hinterland. However, these policies are now deemed to be failures. The focus now has shifted towards developing ‘key cities’ to form ‘city clusters’. Our results may tell us about importance of spillovers in the hinterland and can be seen as relevant to the recent policy change.

5. Methodology & Data • Step 1: City level analysis • Data: 200 Chinese cities for 9 years (1999-2007) [Hinterland Cities: 105 + Eastern: 95] • Selection of cities based on Head and Ries (1995) of choosing cities that attracted minimum no. of FDI • China City Statistical Yearbook (various issues) • Ad Hoc solution for endogeneity used lagged explanatory variables • Spatial weights (W) constructed similar to Madariaga and Poncet (2007) • Carried spatial diagnostic tests: spatial lag model supported; spatial dependence for surrounding market potential and spatial FDI • Estimated using: OLS; Spatial OLS; Spatial 2SLS; Spatial ML

6. Hypotheses + - + + +/- + + +/-

7. Estimation results of the whole China (Whole Sample)

8. Estimation results of the eastern cities(Eastern)

9. Estimation results of the hinterland cities (Hinterland)

10. Initial findings, Discussion and Future Directions: • How important are inter-city spillovers for FDI? • Important to an extent but differences across regions & macro/micro view • City-results only: SMP weak and –ve; Spatial FDI +ve sig. (elements regional differences) • Firm-City results: SMP +ve (Overall & East) and insig.(Hinterland); Spatial FDI +ve (Overall & Hinterland) and -ve (East) • Explanations: 1) Datasets/Methods; 2) FDI motives • Future Directions: • Dynamic Spatial Panel Data for city-level analysis: ‘FDI in Space and Time’ • Explore further disaggregated location choice of MNEs • Firm-level analysis pursued with larger sample and other multinomial logit techniques • Paths: New Economic Geography + Spatial Agglomeration and Fiscal Competition + Environmental Spillovers

11. Appendix: FDI motives Work by Blonigen et al. (2007) and (later adapted by) Ledyaeva (2009) and Hong et al. (2008) have used the following classification: 04/10/2014 11

12. Appendix: Figure 1: Regional Disparity of FDI inflows in China *data of the first half year is used in 2009

13. Appendix: Figure 2: Spatial Disparity of FDI inflows in China

14. Appendix: Average Wages and Unit labour costs Figure 3: Spatial Disparity of Labour Costs in China 04/10/2014 14

15. Spatial Weights Appendix: • We follow Madariaga and Poncet (2007) in the construction of our spatial weights: • We choose a spatial weighting matrix W that depends exclusively on the geographical distance dijbetween cities i and j since the exogeneity of distance is unambiguous. • Distance-based weights are defined as follows: • dijis the distance in kilometres between cities i and j. The distance 1,624 km is the cut-off parameter above which interactions are assumed to be negligible. • This distance is chosen such that each city interacts with at least one other Chinese city. This cut-off parameter is important since there must be a limit to the range of spatial dependence allowed by the spatial weights matrix (Abreu et al., 2005) 04/10/2014 15

16. Hoover Coefficient of Specialisation Appendix: employment for sector j in China Total employment in city i Total employment in China Employment Data for 10 sectors: Manufacturing, Real Estate, Primary, Utilities, Construction, Transportation, Wholesale & Retail, Education & Health, Finance & Business Services, Other employment for sector j in city i 04/10/2014 16

17. References: • Abreu, M., De Groot, H. L. F., and Florax, R. J. G. M. (2005), Space and Growth: A Survey of Empirical Evidence and Methods. Région et Développement 21, 13-44. • Blonigen, B.A., Davies, R.B., Waddell, G.R., and Naughton, H.T. (2007) FDI in space: Spatial Autoregressive Relationship in Foreign Direct Investment. European Economic Review 51 (2007) 1303-1325. • Chen, Y-J. (2009) Agglomeration and Location of Foreign Direct Investment: The Case of China. China Economic Review 20 (2009), 549-557. • Coughlin, C. and Segev, E. (2000) Foreign Direct Investment in China: A spatial Econometric Study. The World Economy 23 (1), 1-23. • Crozet, M., Mayer, T. and Muchielli et al. (2004) How do firms agglomerate? A study of FDI in France. Regional Science and Urban Economics vol. 34, 27-54 • Ekholm, K., Forslid, R., Markusen, J.R. (2007) Export-Platform Foreign Direct Investment. Journal of European Economic Association, Vol. 5, No. 4, 776-795 • He, C. (2002) Information costs, agglomeration economies and the location of foreign direct investment in China. Regional Studies 36, 1029-1036

18. References: • Head, K. and Ries, J. (1996) Inter-City Competition for Foreign Investment: Static and Dynamic Effects of China’s Incentive Areas. Journal of Urban Economics 40, 38-60. • Hong, E., Sun, L-X., and Li, T. (2008) Location of Foreign Direct Investment in China: A Spatial Dynamic Panel Data Analysis by Country of Origin. Discussion Paper 86, The Centre for Financial & Management Studies, University of London. • Ledyaeva, S. (2009) Spatial Econometric Analysis of Foreign Direct Investment Determinants in Russian Regions. The World Economy, Vol.32, Issue 4, 643-666. • Madariaga, N. and Poncet, S. (2007) FDI in Chinese Cities: Spillovers and Impact on Growth. The World Economy, Vol.30, Issue 5, 837-862. • Yeaple, S.R. (2003) The Complex Integration Strategies of Multinationals and Cross Country Dependencies in the Structure of Foreign Direct Investment. Journal of International Economics 60 (2), 293-314.