Chapter

6 Foreign Direct Investment and Output Growth

Author(s):
Wanda Tseng, and Markus Rodlauer
Published Date:
February 2003
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Harm Zebregs

High rates of GDP growth have been associated with large inflows of foreign direct investment (FDI) to China, especially during the 1990s. This chapter examines how and to what extent FDI has contributed to China’s growth performance.

The existence of a positive link between FDI and GDP growth in host countries has been widely documented in the literature (de Mello, 1997). Such a link has also been established in the case of China (Démurger, 2000; Mody and Wang, 1997; Wei, 1994; Zhang, 1999). In contrast with most other studies, however, the analysis in this chapter distinguishes between the direct and the indirect contributions of FDI to GDP. The direct contribution works through the formation of capital and leads to the augmentation of the total capital stock. The indirect contribution is the impact of FDI on total factor productivity (TFP) through the introduction of new technologies, managerial know-how, and other efficiency gains. In addition, this chapter examines whether the presence of foreign-funded enterprises (FFEs) produces spillovers to other sectors. According to the literature, these spillovers can be either positive or negative, depending on the nature of the linkages generated by FFEs (Rodríguez-Clare, 1996).1

The results of the analysis indicate that FDI is a significant contributor to GDP and productivity growth in China. The contribution of FDI to annual GDP growth through capital deepening was on average 0.4 percentage point a year in the 1990s, and the contribution to long-run TFP growth was on average 2.5 percentage points a year over the same period. Hence the total contribution of FDI to GDP growth during the 1990s is estimated at about 3 percentage points a year. The positive link between FDI and GDP growth is found at both the national and the provincial level: provinces with larger inflows of FDI have tended to see both faster GDP growth and faster TFP growth. In addition, analysis of the output of FFEs suggests that their presence has generated positive spillover effects to other sectors in local economies.

The main policy conclusions are that FDI will continue to play an important role in sustaining growth in China, and that a more even distribution of FDI across provinces could help reduce income disparities. Additional FDI will not only add more high-productivity units to the capital stock, but also allow additional domestic enterprises to benefit from the presence of FFEs and raise their productivity. Because China’s open-door policy initially focused on the coastal provinces, the inland provinces have had much less exposure to FDI and FFEs. FDI has been a catalyst of growth in the coastal provinces, and a policy aimed at attracting FDI to the inland provinces could help reduce the growing income disparity between these regions.

Background

China has gradually lowered barriers to FDI over the past three decades. As noted in Chapter 5, the open economic zones (OEZs) have played a central role in the opening of the economy to foreign investors, and, over time, economic links between the OEZs and the domestic economy have increased. The OEZs that were set up in the 1980s were located outside China’s industrial centers, as the authorities sought to experiment with market-oriented reforms in limited localities and in the coastal provinces, which had natural advantages in terms of infrastructure and transport. In the early reform period, FDI was dominated by investors based in Hong Kong SAR and Taiwan Province of China, who sought to exploit relatively low-cost labor in the OEZs for export processing (Branstetter and Feenstra, 1999). As a result, links with domestic enterprises tended to be minimal. By contrast, in the 1990s, interaction between FFEs and domestic enterprises increased. As Naughton (1995) notes, the economic environment in the coastal areas was substantially changed by an emerging alliance between FFEs and township and village enterprises. In addition, FDI in China increasingly consisted of investments by European, Japanese, and U.S. multinationals seeking to supply the Chinese domestic market through local production capacity. These developments contributed to stronger links between FFEs and local economies and created channels for domestic firms to benefit from the presence of FFEs.

Contribution to Output Growth

Developments in the stock of FDI and in real GDP are closely linked in China (Figure 6.1). This chapter attempts to quantify the relation between these variables. A complicating factor in estimating this relation is that causality can run in both directions: FDI contributes to GDP through the transfer of resources, both tangible (physical capital) and intangible (new technologies, managerial know-how, and spillover effects), but at the same time FDI inflows can be motivated by the market size of the host economy.2

Figure 6.1.Real GDP and the Stock of FDI

(In logarithms)

Source: Author’s estimates.

Zhang (1999) shows that long-run causality between the stock of FDI and GDP per capita runs in both directions in China. He also estimates (using a Johansen cointegration test) that a permanent 1 percent increase in the stock of FDI raises real GDP by 0.6 percent in the long run, and that a 1 percent increase in real GDP raises the stock of FDI by 1.7 percent. (The estimated short-run elasticity of GDP with respect to FDI is 0.032.) Whereas these estimates measure the total impact of FDI on GDP, this chapter, as noted, attempts to quantify both the direct and the indirect effects of FDI on GDP.

Contribution to Capital Accumulation

FDI raises the rate of GDP growth by adding to the stock of capital. To assess the direct contribution of FDI to GDP growth, a simple growth accounting framework is employed with the following Cobb-Douglas production function:

where Y is real GDP, a is the share of labor compensation in GDP, A is TFP, L is labor, and K = (Kd + Kf) is the total capital stock, including domestic and foreign capital (this implicitly assumes that domestic capital, Kd, and foreign capital, Kf, are perfect substitutes). At this stage it is assumed that the marginal products of domestic and foreign capital are the same, that is, that the derivatives of the production function with respect to Kd and Kf are identical. This assumption will be relaxed at the next stage when estimating the impact of FDI on TFP. Taking the derivatives of equation (1) with respect to A,L,Kd, and Kf, and rearranging terms, gives

where dKd is net fixed-asset investment by domestic investors and dKf is that by foreign investors. (A dot above a variable indicates a percentage change.) The direct impact of foreign investment on GDP growth is then given by (1 – α)dKf/K. Estimates for a can be obtained directly from China’s national accounts: these give an average labor share for 1990-99 of about 0.54, which implies a capital share parameter of 0.46. The capital stock has been constructed with data from the Statistical Yearbook of China.

When estimating the direct impact of FDI on GDP growth, the fact that not all FDI in the balance of payments contributes to fixed-asset investment should be taken into account. In some cases FDI inflows are used to finance the acquisition of a controlling share of the stock of a domestic company. Such a transaction is very similar to portfolio investment, that is, a transfer of claims on capital, not an augmentation of the capital stock. Hence FDI is not identical to dKf. During 1990–99 FDI inflows were on average 1.7 percent of the total capital stock, and fixed-asset investment by foreigners is estimated at 0.9 percent of the total capital stock, Thus the direct contribution of FDI to GDP growth was about 0.4 percentage point a year during that period.

The direct contribution of FDI to GDP growth has been greatest in provinces with OEZs, as they have attracted most foreign investment (Table 6.1). The direct contribution of FDI to GDP growth varies considerably across provinces, from more than 4 percentage points a year in Guangdong to almost zero in the western provinces of Qinghai and Ningxia.3 The open-door policy has clearly been effective in mobilizing resources for economic development, although the emphasis on coastal areas has also contributed to the widening income gap between coastal and inland provinces.

Table 6.1.FDI and Growth of GDP by Province, 1990–97
ProvinceGDP Growth1

(in Percent)
FDI as a

Fraction of GDP

(in Percent)
Direct Contribution

of FDI to GDP Growth

(in Percentage Points)
All China10.884.630.69
Cities
Beijing11.136.490.87
Tianjin12.1511.691.55
Provinces with OEZs2
Fujian18.0313.043.51
Zhejiang16.992.660.73
Guangdong16.6214.014.11
Jiangsu15.566.381.44
Shandong15.273.620.86
Hainan14.8417.30
Guangxi14.483.520.47
Hebei14.141.650.29
Shanghai12.979.281.99
Liaoning9.814.110.79
Mean14.877.561.58
Provinces without OEZs
Anhui13.901.460.23
Jiangxi13.261.740.30
Hubei12.971.860.31
Henan12.721.130.14
Hunan11.231.880.32
Jilin11.082.120.32
Sichuan10.922.790.41
Xinjiang10.710.420.05
Tibet10.420.00
Shanxi10.270.740.09
Yunnan10.090.530.10
Inner Mongolia10.080.590.09
Gansu9.750.690.08
Ningxia9.420.530.04
Shaanxi8.982.310.25
Guizhou8.890.570.05
Heilongjiang8.561.630.26
Qinghai7.920.140.01
Mean10.621.170.18
Sources: China Statistical Yearbook and author’s estimates.

Compounded at an annual rate.

Open coastal cities or special economic zones.

Sources: China Statistical Yearbook and author’s estimates.

Compounded at an annual rate.

Open coastal cities or special economic zones.

Contribution to TFP Growth

FDI and TFP have moved together over time (Figure 6.2). Again, a cursory look at the data suggests a positive relation between the stock of FDI and TFP, but in this case, too, causality can run both ways. FDI can, for example, contribute to TFP growth through the introduction of new technologies and managerial know-how, but it is also possible that FDI is attracted by high levels of know-how and technical expertise in the host economy, which make it easier for multinationals to introduce more-sophisticated production processes (Findlay, 1978; Borensztein and others, 1998). In this case FDI that does not contribute to fixed-asset investment is also included in the analysis, because technology transfers are not necessarily linked to such investment. New technologies or managerial know-how can also be introduced, for example after a foreign investor acquires a controlling share in the stock of a Chinese company and reorganizes the production process.

Figure 6.2.TFP and the Stock of FDI

(In logarithms)

Source: Author’s estimates.

Empirical analysis suggests a significant positive relation between the stock of FDI and TFP. Table 6.2 reports the estimation results of several regressions designed to examine this relation. The following ordinary least squares regressions were run independently with the stock of FDI and TFP (in logarithms) both as the dependent and as the independent variable:

Table 6.2.Estimation Results from Single-Equation Regressions
Regression Equation1
Variable(1)(2)(3)(4)
Dependent variableTFPFDIChange in TFPChange in FDI
Sample period1985–991984–991985–991985–99
Constant1.3241–4.9029–0.01300.1851
(0.0851)***(1.3728)***(0.0134)(0.0320)**
Regression coefficient
Trend–0.02050.1645
(0.0077)**(0.0185)***
FDI0.1649
(0.0289)***
TFP4.3330
(0.7595)***
Change in FDI0.1443
(0.0497)**
Change in TFP2.7227
(0.0320)***
Summary statistics
R20.97710.99500.39280.3928
F-statistic277.921,3058.40868.4086
Source: Author’s estimates.

All equations are estimated by the ordinary least squares method; numbers in parentheses are standard errors.

Indicates statistical significance at the 1 percent level.

Indicates statistical significance at the 5 percent level.

Source: Author’s estimates.

All equations are estimated by the ordinary least squares method; numbers in parentheses are standard errors.

Indicates statistical significance at the 1 percent level.

Indicates statistical significance at the 5 percent level.

Augmented Dickey-Fuller tests were performed on the error terms in the two equations (μt and Vt) and were found to be stationary in both cases, which suggests a long-run relation between TFP and the stock of FDI. The same equations (without a trend) were also run in first differences and yielded comparable parameter estimates. The relation between FDI and TFP has also been examined in a vector autoregression (this was done in a Johansen cointegration framework). The results suggest a long-run elasticity between TFP and the stock of FDI of 0.09, and a short-run elasticity of 0.08. Furthermore, it is found that neither of the two variables is weakly exogenous, which indicates that causality runs both ways. On the basis of these findings, it is estimated that the indirect contribution of FDI to TFP growth was about 2.5 percentage points a year during the 1990s, a period during which the FDI stock is estimated to have increased by about 30 percent a year.

A positive relation between FDI and TFP growth is also identified at the provincial level in a cross section of provinces (Figure 6.3). Provinces with large inflows of FDI relative to their GDP have generally had higher growth rates of TFP.

Figure 6.3.Provincial FDI and TFP Growth1

Source: Author’s estimates.

1Each square represents a single province.

Spillover Effects

FFEs tend to be the most dynamic and productive firms in the economy. Output of FFEs in the industrial sector expanded at four times the rate of other industrial enterprises during 1994–97, and their labor productivity was almost double that of state-owned enterprises.4 Because FFEs in the industrial sector are also the main recipients of FDI in China, it is possible that provinces with large FDI inflows grow faster simply because the share of fast-growing FFEs in provincial GDP is larger. However, the positive contribution of the FFEs may extend beyond their own operations if other enterprises benefit from their presence. This could be the case if FFEs produce inputs for local enterprises or if they use local enterprises as their suppliers, thereby contributing to higher output and efficiency in enterprises that receive no FDI (Rodríguez-Clare, 1996). Such spillovers may have become progressively more important as the links between FFEs and domestic enterprises grew tighter in the 1990s.

Econometric analysis suggests the presence of positive spillovers from FFEs to the rest of the economy. To test for the presence of such spillovers, the following equation was estimated using panel data from 30 provinces with observations for 1995–97:5

where xi, t is the growth rate of GDP excluding FFEs in province i in period t, si, t is the share of value added of FFEs in GDP in province i in period t, β is a slope parameter, γi, t is a province-specific intercept, and μi, t is the error term. A dummy variable, dum97t, has been added to account for the onset of the Asian financial crisis in 1997. A fixed-effects panel estimation of equation (2), with γi, t = γi for all i and t, provides supporting evidence of the hypothesis that FFEs generate positive spillover effects to the rest of the economy (Table 6.3).6 The estimation results suggest that spillover effects from FFEs in China contributed 2.2 percentage points to annual GDP growth during 1995–97. Because there are many ways in which FFEs can contribute to increased output by other firms, the spillover effect is not directly comparable to the contribution of FDI to TFP growth calculated earlier in the chapter. The presence of FFEs may, for example, lead to more investment if their demand leads suppliers to increase capacity.

Table 6.3.Results of Regressions of Growth in Non-FFE Output on FFE Share of GDP, Using Provincial Data
Pooled EstimationRandom-Effects

Estimation
Fixed-Effects

Estimation
Variable1CoefficientStandard

error
CoefficientStandard

error
CoefficientStandard

error
Constant0.11010.0003***0.11040.0053***
Share of FFEs in GDP–0.07220.0268***–0.05030.06190.34240.0613***
Dummy for 1997–0.00840.0002***–0.01000.0047**–0.01100.0003***
Summary statistics
Adjusted R20.99800.44540.9977
Fstatistic21,90338,290
Source: Author’s estimates.

The dependent variable is the growth rate of GDP excluding FFEs. Data are for 30 provinces over the period 1995–97 (balanced panel with 90 observations). The estimation method is generalized least squares with cross-sectional weights.

Indicates statistical significance at the 1 percent level.

Indicates statistical significance at the 5 percent level.

Source: Author’s estimates.

The dependent variable is the growth rate of GDP excluding FFEs. Data are for 30 provinces over the period 1995–97 (balanced panel with 90 observations). The estimation method is generalized least squares with cross-sectional weights.

Indicates statistical significance at the 1 percent level.

Indicates statistical significance at the 5 percent level.

Conclusions

FDI inflows have contributed significantly to China’s impressive growth performance. Apart from being a significant source of fixed-asset investment, FDI has also enhanced TFP. Empirical results suggest that the impact on TFP accounted for about 2.5 percentage points of annual GDP growth in the 1990s. The contribution of FDI through fixed-asset investment is estimated at 0.4 percentage point a year. Hence the total contribution of FDI to GDP growth during the 1990s is estimated at about 3 percentage points a year.

FFEs, which are the main recipients of FDI, have generated significant positive spillovers to other firms in the economy. It is estimated that these spillovers added 2.2 percentage points to annual GDP growth in the 1990s. This suggests that the impact of FDI on productivity and output growth extends beyond the firms receiving FDI.

The empirical results also show that FDI has been attracted by the rapid expansion of China’s economy. Both GDP and TFP are found to be significant determinants of FDI. The influx of FDI has been facilitated by external sector reforms that have gradually opened the door to foreign investors. China’s accession to the World Trade Organization, which is expected to lead to more reforms and a reduction in barriers to foreign investment, is likely to trigger a further increase in FDI, particularly into the services sector.

Not all provinces appear to have benefited to the same extent from the presence of FDI. To date, the positive effects appear to be strongest in the coastal provinces. Hence a policy that attracts FDI and FFEs to the inland provinces could help those provinces catch up with the coastal provinces in terms of productivity and income.

FDI is expected to remain an important source of growth and can help to offset potential output losses resulting from state enterprise reform. In addition, promoting FFEs will generate positive spillovers to other sectors in the economy and result in a wider dispersion of new technologies and managerial know-how. Given the important role of FDI in private sector development, FDI can also help absorb workers that have become redundant in the state enterprise sector.

References

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For example, FFEs that make intensive use of locally produced intermediate goods generate positive “backward” linkages when they raise the demand for intermediate goods in the host economy. By contrast, FFEs that displace local firms and import most of their intermediate goods might create negative backward linkages. FFEs can also create forward linkages when, for example, they bring new goods to the host economy that raise the productivity of domestic firms.

Both directions of causality have received attention in the literature. Borensztein, De Gregorio, and Lee (1998) have shown, in a panel of 69 developing economies, that FDI inflows have contributed to GDP growth; Brainard (1997), Lecraw (1991), and Wheeler and Mody (1992) have shown the statistical significance of GDP growth in attracting FDI.

The provincial labor shares for the calculation of the direct contribution of FDI to GDP were obtained from the China Statistical Yearbook.

The analysis of FFEs focuses on the period 1994–97, because that is the longest period for which consistent data for industrial output by FFEs and other enterprises are available.

The sample period is reduced by one year because of the calculation of the growth rate of provincial GDP excluding FFEs.

A fixed-effects model was chosen because it allows for structural differences across provinces. For completeness, the table also gives the results of a pooled estimation, with γi, t = γ for all i and t, and a random-effects estimation, with γi, t = γi and Eiμi, t) = 0 for all i and t, of equation (2). The pooled estimation shows a small but negative spillover effect from FFEs to the rest of the economy, whereas the random-effects estimation fails to demonstrate the presence of any spillover effects.

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