Download Analysis of the Effects of Foreign Capital Inflows on Investment... China

Analysis of the Effects of Foreign Capital Inflows on Investment in
China
WANG Xiping1 MENG Ming2
1, School of Business Administration, North China Electric Power University, Baoding 071003, China
2, School of Electrical Engineering, North China Electric Power University, Baoding 071003, China
[email protected]
Abstract Under the condition of opening economy, foreign capital inflows will have significant effects
on hosting country’s investment, which is reflected in the types of crowding out effects or crowding in
effects. The purpose of this paper is to examine the effects of foreign capital inflows on domestic
investment in China. Regression results show that foreign capital inflow has a significant positive effect
on the total investment while crowd out the domestic investment.
Keywords Capital inflows, Domestic investment, Crowd in effect, Crowd out effect
1 Introduction
Standard economic theory predicts that capital inflows, particularly FDI, unambiguously increase
investment rates in developing countries. Most academic economists believe that the surge in
cross-border capital flows has created unprecedent opportunities for developing countries to achieve
accelerated economic growth since the early 1990s. International financial institutions routinely advise
developing countries to adopt policy regimes which encourage capital inflows. A large majority of the
developing countries have substantially reduced restrictions on capital inflows, and some have
proceeded to offer substantial incentives in the form of tax concessions or subsidies to international
investors.
However, from an empirical point of view, although the issue has been extensively analyzed, the
results are mixed. Borensztein et al. (1998)[1] tested the effects of FDI on investment in a cross-country
regression framework, utilizing data on FDI flows from industrial countries to 69 developing countries
over the period of 1970-1989, and found that one dollar increase in the net inflow of FDI was associated
with an increase in total investment in the host economy of more than one dollar. The results supported
the crowding-in effects. Bosworth and Collins (1999)[2] provided evidence concerning the effect of
capital inflows on domestic investment for 58 developing countries during 1978-1995. They found that
an increase of one dollar in capital inflows was associated with an increase in domestic investment of
about 50 cents. Further study indicated significant differences among types of inflows. FDI appeared to
bring about a one-for-one increase in domestic investment; there was virtually no discernible
relationship between portfolio inflows and investment; the impact of loans falled between those of the
other two. Agosin and Mayer (2000)[3] developed a theoretical model of investment which included an
FDI variable, and then tested it with panel data during the period of 1970-1996. And the results
indicated that there has been strong crowding in effects on domestic investment by FDI in Asia- but not
so strong in Africa, by contrast, strong crowding out effects has been the norm in Latin America.
Recently, a number of domestic studies have analyzed the impact of capital inflows on investment
in China. Yang Liuyong and Shen Guoliang (2002)[4] evaluated the effects of FDI on domestic
investment, using the data of total investment, GDP and FDI. The result indicated that FDI have
crowded out China’s domestic investment. Lu Jianjun (2003)[5] investigated the impact of FDI on
China’s domestic investment during the period 1987-2001 and the results showed that over the past 15
years, FDI has the effect of crowding in to domestic investment, and also crowding out effect in some
coastal provinces. There are also differences in the extent of impact among different regions. Wang
Zhipeng and Li Zinai (2004)[6] used larger sample of panel data and compared the different estimates
from “absolute” and “relative” models. They found no significant crowding in effects or crowding out
This paper is supported by the Science Foundation of North China Electric Power University for ph. D teachers.
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effects in China from the whole country level. However, further study revealed that the crowding in
effects or crowding out effects showed a fine regional characteristic: crowding out effects dominate in
eastern China, crowding in effects dominate in mid China, and crowding out effects are insignificant in
western China.
Essentially, what above reviewed suggested that the relationship between foreign capital inflows
and domestic investment has no agreement in the existing literature. And most of the existing studies
were focused on the criteria of Agosin and Mayer’s regression equation and thought the evidence of
crowd in effects are that one additional dollar FDI becomes more than one additional dollar of total
investment. On the contrary, the crowd out effects were defined as one additional dollar of FDI leading
to less than one dollar increasing in total investment.
Starting with discussion of the relationship between saving and investment, this paper provides a
new investment equation to empirically analyze the effects of capital inflows on domestic investment
based on the data of 1982-2003. An important advantage of this equation is that it can make us to
compare different effects of FDI and non-FDI inflows on domestic investment.
The remaining of this paper is structured as follows. Section 2 proposes a theoretical model for
investment in developing countries which includes an FDI variable. Section 3 presents the results of
econometric tests of the model using data of 1982-2003. The main conclusions of the paper are given in
Section 4.
2 Empirical Frameworks
By national account, under the condition of closed economy, expenditure-based GDP can be
calculated as: Y = C + I + G
(1)
Based on equation (1), the investment equation can be written as: I = Y - C - G
(2)
However, income-based GDP can be listed as: Y = C + S + G
(3)
Where, S, presenting gross national savings, equals to gross national income minus private
consumption and government expenditures. Equation (3) means: S = Y - C - G
(4)
Incorporating (2) and (4), we can get the relationship between saving and investment: I = S (5)
Equation (5) suggests that domestic saving is the only source for domestic investment under the
condition of closed economy. However, under the open economy, the relationship between saving and
investment is getting more complicated because of capital inflows. To fix ideas, it is useful to consider a
simple accounting identity for any given country:
(6)
I = DI + NFDI = DS + NFDI + NFR - CIR
Where I is the national aggregate investment, including DI and NFDI. DI is investment by
domestic entrepreneurs (including national governments); DS is domestic saving; NFDI is net foreign
direct investment (FDI) inflow (= inflow – outflow); NFR is net inflow of non-FDI financial resources
and CIR is the changes in international reserve. We abstract from complications associated with
exchange rates by considering all values in current US Dollars. NFR includes net inflows of private
equity, private loans, and loans and grants form bilateral and multilateral sources. The left-hand side of
the identity represents aggregate investment in the economy. NFDI, in definition, is investment; its
appearance on both sides of the equation underlines the fact that it finances itself. It is easy to see that
aggregate investment exceeds domestic saving whenever NFDI > DS – DI, equals to domestic saving
whenever NFDI = DS – DI, and falls short of domestic saving whenever NFDI < DS – DI. Thus it is
only when domestic saving is fully used to finance domestic investment in all circumstances that any
positive net FDI inflows necessarily raises aggregate investment above domestic saving. Since non-FDI
inflows can be used to finance domestic investment in principle, the upper limit to DI is given by DS +
NFR. Whenever DI < DS + NFR, CIR must be positive. The parts of domestic saving and net non-FDI
inflow that are not used to finance domestic investment end up financing accumulation of foreign
currency reserve.
Based on equation (6), we use the following regression equation to test the effects of foreign capital
inflows on domestic investment:
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( DI / Y ) t = β 0 + β 1 ( DS / Y ) t + β 2 ( NFDI / Y ) t + β 3 ( NFR / Y ) t + ε t
（
）
(7)
Where Y is GDP, β i i=0,…,3 is the coefficient need to be estimated. ε t is the random variable.
In equation (7), domestic investment as share of GDP is taken as dependent variable. The
explanatory variables used here are domestic saving as share of GDP ( DS / Y ) , net foreign direct
investment inflows as share of GDP ( NFDI / Y ) , and net foreign indirect investment inflows as share
of GDP (NFR/Y). This equation will also allow us to compare the relative effectiveness of NFDI and
NFR.
For our purpose, the crucial variable here is NFDI/Y. The coefficient β 2 of NFDI/Y should be
zero, if NFDI has no impact on investment by local or national sources. If NFDI is associated with a
decline investment from domestic investors, β 2 should be negative while if NFDI is associated with an
increase in investment by local investors, the coefficient
β2
should be positive.
3 Empirical Results
All data used in the estimations are taken from China Statistical Yearbook and International
Financial Statistics Yearbook (various years of 1983-2004). In our regression, DI is defined as (I – NFDI)
and NFR is defined as the sum of net official inflows (excluding loans and grants from the IMF) and net
private inflows. I is measured as the gross fixed domestic capital formation, including foreign
investment. DS is measured as domestic saving, which is defined as aggregated expenditure minus final
consumption expenditure. NFDI and NFR are measured as the net foreign direct investment and net
foreign indirect investment respectively.
By now there is compelling evidence that many macroeconomic time series are nonstationary and,
as a result, OLS estimates using these data may produce spurious results. In order to avert this problem,
we first examine the time series properties of the data using Augmented Dickey Fuller (ADF) test. The
results are given in Table 1. Table 1 indicates, that all variables have a unit root in levels and are
stationary in first difference.
Table 1 Test of theunit root hypothesis
Level
First Difference
Variables
ADF
5% Critical
5% Critical
(C,T,K)
(C,T,K)
ADF Statistic
Statistic
Value
Value
DI/Y
C,N,1
-2.0155
-3.0199
N,N,1
-2.4776
-1.9602
DS/Y
C,N,1
-0.5075
-3.0199
N,N,1
-2.4190
-1.9602
NFDI/Y
C,N,1
-1.5877
-3.0199
N,N,1
-2.9453*
-1.9602
NFR/Y
C,N,1
-1.7492
-3.0199
N,N,1
-2.8200*
-1.9602
C,T and K indicate the model statistics with intercept, trend and the number of lags, N indicates without trend,
* Indicates significance at the 1% levels.
（
（
（
（
）
）
）
）
（
（
（
（
）
）
）
）
Given the time series of the data are integrated of order one, i.e. I (1). We then tested for a
cointegrating relationship using Johansen's test. Since the results of Johansen's test are very sensitive to
the number of lag to be included in the model, we followed the theorem of minimum AIC to choose the
optimum lag length of 2. And the results are showed in Table 2:
Eigenvalue
0.713326
0.612585
0.218606
0.142613
Likelihood Ratio
49.366
25.6272
7.61029
2.92346
Table 2 Johansen's test for cointegration
5% Critical Value
1% Critical Value
39.89
45.58
24.31
29.75
12.53
16.31
3.84
6.51
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Hypothesized No. of CE(s)
None**
At most 1*
At most 2
At most 3
**(*) denotes rejection of the hypothesis at 1% (5%) significance level
Results of Table 2 suggest that at 5% significance level, a single cointegrating vector is existed in
model (7). So we can regress model (7) and get the equation (8):
(DI/Y)t=0.1553+0.5515(DS/Y)t+0.7673(NFR/Y)t-0.5329(NFDI/Y)t+ ε t
(8)
*
*
*
**
(2.5277 ) (3.1409 )
(4.2630 )
(-1.5979 )
R2=0.63 Adj-R2=0.56
D.W=1.59
F=10.25
The figures in parentheses are t-statistics and *, **denote statistical significance at 5% and 10%
level respectively. The crucial variable, NFDI/Y in (8) has a negative effect with a coefficient of -0.5329,
while only significant at 10% level. In reality, NFDI may have lagged effects on domestic economy, thus
using one period lagged variable (NFDI/Y)t-1 instead of (NFDI/Y)t to perform estimation again, the
result is shown in the following equation:
(DI/Y)t=0.149253+0.574775(DS/Y)t+0.688760(NFR/Y)t-0.679586(NFDI/Y)t-1+ ε t
(9)
(3.0720*) (4.2055*)
(4.1419*)
(-2.615*)
R2=0.6998
Adj-R2=0.6469
D.W= 1.8668
F=13.21
In equation (9), we can see that all coefficients for each variable are significant at 5%, and the
overall regression results are improved judging by R2, Adj-R2, and the value of D.W. Equation (9)
indicates that net foreign direct investment has strongly crowd out effects on domestic investment, and
1% increase of NFDI in the year (t-1) will lead to domestic investment decrease by 0.67% at t year.
However, since one unit of net FDI inflow crowds out less than one unit of domestic investment,
aggregate investment still rises above the domestic saving rate. NFDI still contributes positively to the
aggregate investment I overall. In fact, we can regress the aggregate investment based on equation (7)
and get the following results:
(I/Y)t=0.1553+0.55159(DS/Y)t+0.467(NFDI/Y)t+0.767(NFR/Y)t+ ε t
(10)
*
*
*
*
(2.5277 )
(3.140 )
(2.4003 )
(4.263 )
R2=0.823
Adj-R2=0.794
D.W=1.598
F=27.98
Although NFDI has crowd out effects on domestic investment, while the equation (10) suggests
that, ceteris paribus, net inflows of foreign capital can help accelerate economic growth in our country.
But, even in the best of circumstances (when there are net inflows of both FDI and non-FDI finance),
the growth effect is much smaller than that may be expected. This is because the quantity of incremental
investment is only a fraction, often a small fraction of the quantity of actual inflows. Moreover, the
growth effect of non-FDI inflows is further reduced by their volatility, which makes them rather risky
sources of investment finance.
4 Conclusion
In this paper, an equation reflecting the relationship between saving and investment in open
economy was used to analyze the effects of foreign capital inflows on domestic investment, getting the
following conclusions:
It is noted from equation (9) that net foreign direct investment (NFDI) has a fairly strong
crowding-out effect on domestic investment. This can be explained by many reasons: At the
macroeconomic level, crowding-out effect is generated fundamentally by problems of absorption of
exogenous capital inflows encountered by developing countries. Such inflows typically threaten to
provoke currency appreciation on the one hand and inflationary pressures on the other hand. Policy
responses usually consist of what are known as “sterilization” measures, which have the effect of
restraining aggregate investment in the economy. In the absence of any specific restraint on FDI, the
restraint on aggregate investment translates into reduced domestic investment. At the microeconomic
level, exogenous FDI inflows imply competition between domestic and international entrepreneurs. It is
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reasonable to think that international entrepreneurs would normally be the winners in this competition so
that a crowding out effect of NFDI on DI is a distinct possibility. In concrete terms, FDI inflows are
associated either with establishment of affiliates by multinational firms or with (partial or full)
acquisition of domestic firms by foreign firms. In the first case, domestic firms could be adversely
affected by competition for (internal and external) market share and inputs (finance, raw materials,
infrastructure facilities and human resources) from the newly established affiliates, which usually have
access to superior technology and management skills. In the second case, domestic entrepreneurs may
not necessarily find, indeed may not even look for (e.g., in the case of privatization programmes),
opportunities for investing the proceeds from asset sales in new activities.
Equation (9) also indicates that non-FDI inflows, like domestic saving, can be used to finance
domestic investment. The reason is that both non-FDI inflows and domestic saving have positive effects
on domestic investment. From the point of view of domestic entrepreneurs, non-FDI inflows differ from
domestic saving in one important respect: non-FDI inflows are associated with direct availability of
foreign exchange. Using non-FDI inflows as a source of finance allows domestic entrepreneurs to
import capital and intermediate goods, which might otherwise be infeasible. In other words, non-FDI
inflows are an attractive source of finance for domestic entrepreneurs unnecessarily because the cost of
external finance is lower than that of domestic finance, nor because the available domestic saving is
inadequate to finance the desired level of investment, but because such inflows provide direct access to
imports. In the presence of non-FDI inflows, therefore, we should expect domestic entrepreneurs to use
both domestic saving and non-FDI inflows as sources of investment finance. We should note, however,
that the whole of the net non-FDI inflow to any given country is normally not available to domestic
entrepreneurs for financing investment. The reason is that such inflow tends to increase the recipient
country’s short-term external payment obligations. And any perception in financial markets that the
country concerned has not put aside sufficient foreign currency reserve to meet these obligations can
cause a sudden reversal of private non-FDI inflow, thereby engendering a financial crisis. The recipient
country, therefore, usually has to use a substantial part of the inflow to accumulate foreign currency
reserve so as to forestall panic in financial markets.
From equation (10), we can see that foreign capital has positive contribution to the aggregate
investment. Net FDI inflows to developing countries have a fairly strong crowding out effect on
domestic investment. However, since one unit of net FDI inflow crowds out less than one unit of
domestic investment, aggregate investment still rises above the domestic saving rate. But the same fact
also implies that net inflows of FDI necessarily increase the share of foreign investors in aggregate
investment. Moreover, because net FDI inflows reduce domestic investment, the recipient economy
becomes saving-surplus.
Based on the discussion above, we find that utilizing foreign capital properly contributes to make
up some shortage enhancing the level of development. However if neglect to control the scale, structure
and investing direction of foreign capital inflows, it is impossible to absorb appropriate foreign capital
which accords with real needs of economy development. So we should make full use of foreign capital
and strive to improve its performance.
，
References
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Journal of International Economics, 1998, vol. 45, no. 1, pp. 115-135
[2] Bosworth, Barry P. and M. Collins, Capital Flows to Developing Economies: Implications for Saving and
Investment, Brookings Papers on Economic Activity, 1999, vol. 1, pp. 143-169
[3] Agosin, M. R. and R. Mayer, Foreign Investment in Developing Countries: does It Crowd in Domestic
Investment? Discussion Paper 2000, no. 146, UNCTAD, Geneva
[4] Yang Liuyong, Shen Guoliang, The crowd in/out Effects of FDI on Domestic Investment, Statiatical Research,
2002, no. 3, 6-8 (in Chinese)
[5] Lu Jian-jun, Positive Study on the Impact of FDI to China’s Domestic Investment, Research on Financial and
Economic Issues, 2003, no. 9, 36-40
[6] Wang Zhipeng, Li Zinai, Reexamine the Crowd in or Crowd out Effects of FDI on Domestic Investment,
Statiatical Research, 2004, no. 7, 37-43 (in Chinese)
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