Outlines: 1. Introduction 2 Empirical Analysis Framework and Data 2.1 Basic Specification

1. FDI Spillovers Effect, Environmental Pollution and Total Factor ProductivityGuoqing ZHAO1 and Zhongyuan ZHANG21.School of Economics, Renmin University of China, Beijing, 100872 ,China2. Institute of Asia-Pacific Studies, Chinese Academy of Social Sciences, Beijing, 100007,China2012-6

2. Outlines: 1. Introduction 2 Empirical Analysis Framework and Data 2.1 Basic Specification 2.2 Data and definitions of key variables 2.3 Measuring Forward and Backward FDI spillover 3 Estimation results 3.1 The Effects of FDI Spillover and Environmental Pollution on Productivity 4 The FDI Spillover Effect and Environment Pollution 5 Conclusions

3. 1. Introduction • Some empirical studies confirm positive productivity spillovers from FDI. Blomstrom and Sjoholm(1999) Sadik and Bolbol(2001) • But others find negative or no spillovers. Aitken and Harrison(1999) Veugelers and Cassiman (2004)

4. The mixed evidence intuitively implies that there is no universal relationship between FDI and domestic firms’ productivity. • Javorcik(2004) argues that researchers have been looking for FDI spillovers in the wrong place since multinationals have an incentive to prevent information leakage that would enhance the performance of their local competitors.

5. the presence of FDI creates negative externalities within industries and positive externalities between industries through vertical linkages Bwalya(2006) finds no intra-industry productivity spillovers from FDI but significant inter-industry knowledge spillovers occurring through linkages in Zambia’s firm. Jordaan(2008) finds negative externalities within industries but positive externalities between industries that in several Mexican regions in the early 1990s.

6. Using a large panel of Chinese manufacturing firms, Liu(2008) finds that spillovers through backward and forward linkages between industries Lin et. al. (2009) find strong and robust vertical spillover effects on both state-owned firms and non-state firms in China’s manufacturing firms (above a minimum scale) from 1998 to 2005.

7. In this paper we also investigate the relationship between FDI and the environmental performance of industries the pollution haven hypothesis (PHH), which states that FDI will be attracted to those countries with less stringent environmental regulations thus inducing a regulatory “race to the bottom” in order to attract higher FDI inflows from dirty sectors to the detriment of the host country’s environment Esty and Geradin, 1997; Mani and Wheeler, 1998.

8. In contrast, the pollution halo hypothesis argues that the presence of foreign-owned firms may yield substantial environmental benefits to developing countries since FDI has been known to directly encourage the dissemination of environmental related knowledge and technologies Albornoz et al., 2009.

9. Empirical Analysis Framework and Data 2.1 Basic Specification To examine the correlation between industry productivity and FDI in the same sector (intra-industry) and inter-industry, the empirical framework can be described as following:

11. 2.2 Data and definitions of key variables The datum were obtained from the China Statistical Yearbook (NBSC, 2000–2009) which cover 28 industries from 1999 to 2008(2004 was the year for which the data was unavailable). Table 1 presents definitions of the key variables used in the empirical estimations.

13. Table 2 Descriptive statistics(omitted) Panel A Summary statistics Panel B Correlation matrix

14. 2.3 Measuring Forward and Backward FDI spillover

16. 3 Estimation results 3.1 The Effects of FDI Spillover and Environmental Pollution on Productivity

18. Table 3 presents the estimations of equation (2). • use the Hausman test for our regression model to select the proper specification between fixed-effect and random-effect approach. • first entry FH and FW, FH and BW (excluding environment pollution variables) into the equation alternatively.

19. Focusing our attention to the spillover effects of FDI firstly, we do not find any statistically significant effects of horizontal FDI spillover on industry productivity since the coefficients on FH, though positive, are insignificant.

20. In contrast, we find strong positive effects of backward FDI spillover on industry’s productivity for the coefficients on BW are significant positive, suggesting effectively backward linkages across industries. • we also find uneven positive spillovers from forward FDI spillover, which is positive significant in column (1) and loss its power in column (3) when we include BW variable, • Overall, when we explicitly separate horizontal spillovers, backward linkages and forward linkages, our results support that FDI spillovers are more likely existing the backward linkages across industries.

21. There are four environment pollution indices : industry wasted water discharge per revenue from principal business (WA), total volume of industrial sulphur dioxide emission per revenue from principal business (SO2), total volume of industrial soot emission per revenue from principal business (SMO) and total volume of industrial dust emission per revenue from principal business (DI), Table 3 presents the estimations of the full specification of equation (2).

22. The most striking result from Table 3 is that, in all specifications (from column (4) to (7)), • the coefficients on horizontal FDI effect variable (FH) are insignificant positive and the coefficients on backward FDI spillover (BW) are significant positive which echo the results of no statistically significant effects of horizontal FDI spillover on industry productivity and FDI spillovers are more likely existing the backward linkages across industries. the coefficients on WA, SO2, SMO and DI are all significantly negative at conventional significant level, suggesting environment pollutions do have disadvantages on industry’ productivity progress.

23. 3.2 The Dynamic empirical model of FDI Spillover Effects and Environmental Pollution on Productivity

24. It is well known that OLS estimates are biased and inconsistent the generalized method of moments (GMM) techniques developed by Arellano and Bond (1991) Arellano and Bover (1995) and Blundell and Bond (1998),

27. the coefficients on backward FDI spillover variables (BW) are significant positive except column (2), suggesting FDI spillovers are more likely existing the backward linkages across industries. There are some differences of the coefficients on forward FDI spillover variables (FW), which are positive and significant in 3 columns now suggesting the possibility of spillover effect exists among the forward linkage. However, there are essential changes on the coefficients on horizontal FDI spillover variables (FH), which are all significant negative now, suggesting the competition effect is important which preponderates over horizontal FDI spillover effect.

28. As for environment pollution variables, the coefficients on WA and SO2 are significantly negative, suggests environment pollutions do have disadvantages on industry’ productivity progress. However, the coefficients on SMO is insignificantly negative, the coefficients on DI is significantly positive, are different from the results of Table 3.

29. 4 The FDI Spillover Effect and Environment Pollution 4.1 The FDI Spillover Effect on the Marginal Effect of Environment Pollution

30. (6)

34. Table 5 reports the regression results which include the interaction terms between environment pollution indices and FDI spillover effect variables. the coefficients on the interaction variable between FH and WA, SO2 are significantly positive, the coefficients on the interaction variable between FH and SMO, DI are insignificantly positive, which suggest horizontal FDI spillover effect mitigates the disadvantage effect of environment pollution on industry’ productivity progress.

35. The coefficients on the interaction variable between FW and WA, SO2, SMO, DI are all insignificantly negative, while the coefficients on the interaction variable between BW and WA, SO2, DI are all insignificantly positive, suggesting no significant evidence of vertical FDI spillover effect mitigates the disadvantage effect of environment pollution on industry’ productivity progress.

36. 4.2 The Level Effect of FDI Spillover on Environment Pollution • To test the level effect of FDI spillover on environment pollution, in this paper we introduce the multivariate linear regression model which is a natural generalization of a linear regression model. • That is, two or more possibly correlated dependent variables are simultaneously modeled as the linear functions of the same set of predictor variables.

39. Table 6 reports the regression results of equation which include the contemporaneous environment pollution indices and lag all the right hand side regressors by one period. • The coefficients on horizontal FDI spillover effect variable (FH) in Panel A and B are all significantly negative, suggesting horizontal FDI spillover decreases the emission of environment pollution. • However, the coefficients on backward FDI spillover effect variable (BW) in Panel A and B are significantly positive except in column (1), suggesting backward FDI spillover increases the emission of environment pollution. • The results of forward FDI spillover effect are mixed,

40. The consistently significant coefficient on horizontal FDI spillover effect variable indicates that foreign firms may adopt low-power consuming and low-environment-pollution-intensity technologies which low the emission of environment pollution. • However, it is not mean that they be willing to transfer environmental knowledge within the same industry because their generosity does not appear to extend to direct competitors.

41. Though we have strong evidences of the positive vertical FDI spillover effect (especially through backward linkages) that promotes industry’ productivity progress, • the backward FDI spillover increases the emission of environment pollution. This maybe due to the spillover of backward FDI linkages are high-power consuming and high-environment-pollution-intensity technologies.

42. 5 Conclusions • examines the effects of the foreign direct investment (FDI), which is distinguished as horizontal, forward linkage and backward linkage spillovers, and environmental pollution on total factor productivity (TFP). • the existence of positive spillovers from FDI taking place through backward linkages, but there are no significant evidences of spillovers occurring through either the horizontal or the forward linkage channel. • Environmental pollution has significant negative effect on TFP.

43. horizontal FDI spillover effect mitigates the disadvantage effect of environment pollution on industry’ productivity progress and decreases the emission of environment pollution • the vertical FDI spillover effect (especially through backward linkages) doesn’t mitigate the disadvantage effect of environment pollution on industry’ productivity progress and increases the emission of environment pollution.

44. Q&A

45. Thank You！