The Impact of Foreign Capital on the Country Economy
Sofia L. Eremina[1]
Abstract: An influence effect of penetration
of foreign direct investments (FDI) is not clear for economy of a home country.
There are quantitative and qualitative indicators measuring the role of foreign
direct investments: macro economical indicator characterizes an ability of a
country to attract FDI; and micro economical indicator characterizes how
transnational the country is. The effects for countries exporters and importers
of capital are being discovered through the effects of issues (employment,
competition), surplus and rent payments. To measure out the investment effect
is possible within portfolio theory.
It is offered to modify the criteria accepted
for factories to measure out macro economical effectiveness of foreign
investment. Figuring out the macro economical effects assumes an analysis of
foreign capital inflow on the size of GDP, level of export / import and
employment. Due to help of Pierson’s correlation coefficient it was found out
that there is a connection between these indicators without a temporal log at
first and then with a temporal log in Russia, Hungary and China.
We chose Hungary as it was the first country of
Eastern Europe to attract the foreign capital; China as a country attracting
the largest volume of FDI among the emerging markets countries. On a base of
statistical materials of central banks in Russia, Hungary and China tables
arranged and graphs were imaged. They help to make a conclusion that the inflow
of foreign capital in home country is not absolutely positive. It leads to
another conclusion: the national investors must be stimulated.
Keywords: foreign direct investments; home countries; investment policy; correlation coefficient; effect valuation; temporal log
Investment statistics of several countries, international organizations reports as well as a number of scientific publications analysis enables us to single out some showings which measure the impact of foreign direct investment (FDI). Namely, there are the total volume of attracted foreign direct investment; the volume of attracted foreign direct investment per head; FDI/national investment ratio; annual (average annual) growth; the share of foreign direct investment in GDP; the share of foreign direct investment (companies) in production, total profits, importing country tax revenue; project average cost; minimum amount of investment (in China).
During the period from 1995 to
2003 most of FDI, of both exporters and importers, accounted for developed
countries. Companies from EC countries turned into major FDI owners (about $ 3.4
trillion in 2002)
what is more than twice as much as USA ($1,5 trillion). In 2003 the global FDI was
declining (three years running) and came to $ 560 billion owing to 25 % slump
in FDI influx in developed countries as compared to 2002 ($367 billion). 111
countries saw FDI flow growth while the decrease took place in 82 nations.
Especially sharp drop (by 53 %) in FDI influx was seen by USA and the figure made
up $30 billion – the lowest value of late 12 years. In CEEC countries FDI influx fell from $31
to 21 billion. Developing countries saw 9 % FDI growth and came to $172 billion a year while accumulated
FDI volume ran up to about 30 % of GDP, having increased from 13 % in 1980.
Operating
with international statistics we can calculate FDI volume indexes. (FDI – development policy;
national and international issues, 2003)
a) Macroeconomic – the ability of country to attract FDI, that is revelation of compliance of country’s share in global FDI with its economic state, in particular, expressed with three ratios of country’s share in global FDI to its share in:
GDP,
employment,
export.
b)
Microeconomic – transnational ratio – average value of three figures:
the
ratio of foreign assets to the total assets volume,
abroad
sales to the total sales volume,
staff
number abroad to the total employed number.
Modern
Scandinavian economic school representatives distinguish three types of effects
for both capital exporting and capital importing countries: (Hoekman B., Saggi К., 2001)
Output,
employment,
competition.
Surplus.
Rent.
1. For the exporting countries the problem of loss of jobs caused by
FDI influx is extremely controversial
meaning that the capital is being exported but the labor force remains. FDI
export can lead to native employment pattern change: the employment rate of
low-skilled workers will fall while concerning high-skilled workers this figure
will increase as in the homeland scientific activities are being carried out
and there is a possibility to create office, managerial and engineering jobs.
It’s highly likely that new jobs wouldn’t be created at all because of the
competition with foreign companies. The transfer of the part of the production
process abroad increases company’s gross yield and competitiveness and even
strengthens the parent company.
For
the importing countries the total effect of FDI on their employment rate
is also vague. On the one hand, imported workforce contributes to net domestic
employment rate growth; and if there is unemployment in the country-recipient,
such situation becomes beneficial for its economy. However, firstly, employment
rate growth caused by FDI can put pressure upon native labor-market through
wages growth effect. No doubt, this effect is favorable for employees of
companies that attract FDI, yet cost escalation in labor remuneration causes
decrease in purchasing capacity of another part of population. Secondly, FDI
influx in the form of mergers and takeovers is often accompanied with employed
number reduction in the country-recipient. Thus, for output effect to ensure
country development and its common wealth growth, two terms should be met:
firstly, additional employment shouldn’t induce the reduction in real income of
population; secondly, FDI influx should provide the most favorable workforce
use.
With
foreign companies emerging the competition becomes more severe what can lead to
deterioration of national producers on the domestic market of the
country-recipient.
2. For the
exporting countries the surplus effect is expressed with steady
concentration on R&D, new knowledge acquisition, methods and directions of
work organization and other skills that spur the production process
intensification.
The
positive impact of FDI on the importing country is relative surplus of
work and cash flows; new acquired foreign technologies, management strategies
or knowledge of higher quality can enable local companies to modernize their
technologies. The surplus can be both direct (from firm to firm) and indirect
(through other markets: labor, etc.). FDI can reduce the technological gap.
Buying of half-finished products by foreign firm from local suppliers is likely
to spur the rise in make quantity, higher productivity and national industry
modernization. If a foreign company supplies new or more quality productions,
both national producers and consumers will benefit from this situation. Thus,
both countries will be developing.
3. For the
exporting countries the rent effect concerns the profit share that will
be left in the home country. This effect is also not always positive. It’s well
known that companies of some countries transfer their property to other
countries, so the bulk of tax proceeds come to the foreign country.
For
the FDI importing countries the presence of foreign ownership can lead
to capital outflow in the form of rent and other outgoings. As rent is the
investment income of foreigners its outflow should be taken into consideration.
On the other hand, if foreign investors have special benefits (understated
rent) the rent transfer lowers the benefits of the recipient country and
violates mutually beneficial nature of the transaction.
Investment effect
evaluation can also be carried out within the framework of the portfolio theory
where two competing approaches were distinguished in the second half of the
last century:
eastern
(the Russian school), based on operating economies and
western
(European and American approaches) based on investment effect evaluation from certain
project realization. Nevertheless, the correlation of the two approaches is
clear: operating economies always increase the profit margin and profit earning
doesn’t exclude its augmentation owing to operating economies.
World experience (UNIDO
standards, World bank) testifies the fact that during project design
commercial, technical, financial, institutional and economical feasibility
analysis is necessary.
In short, project commercial feasibility analysis envisages competition environment analysis. Technical analysis of the investment project sets task to find out the most
appropriate technologies, resources availability and cost. Project financial analysis is a calculation and interpretation of liquidity and solvency
ratios, company profitability and management efficiency. Project financial analysis is the calculation and interpretation of the liquidity and
solvency ratios, company profitability and management efficiency. Institutional analysis evaluates the whole of internal and external factors: organizational,
legal, political and administrative situation. Finally, economical analysis (what, in fact, is our interest) includes the evaluation of
project contribution to the country development, realization of its objectives.
As
it is well known, for the project investment economical efficiency evaluation
on the microeconomic level international and Russian experts mostly use
the following interrelated criteria: net present value (NPV), profitability index (PI),
Benefits to Costs Ratio, Internal Rate
of Return.
For
the macroeconomic efficiency evaluation of FDI we suggest the same
criteria that are customary for a company. We just need to make some
modification. From the direction of society the growth of production volume
(GDP), reduction of production unit costs, decrease in delivery and storing
costs and product improving could be their real benefit.[2] Here we should take into
consideration the fact that for the society, which is considered to be the
country resources owner and the recipient of all the benefits from project
realization, the total growth of benefits should exceed the growth of costs
taking into account possible alternative resources involved into the project.
The most significant effects when evaluating the investment are: the change in jobs
number in a region; improvement of workers’ housing, cultural, living and
working conditions; the change of operative personnel structure (the number of
employed holding positions demanding higher or special education), standards of
education (the number of workers subject to training, retraining and skill
level raising), other development showings.
Let’s
calculate macroeconomic effects, i.e. analyze the impact of foreign capital
influx on GDP value (country “value” criterion), export/import volume and
employment rate. First, we will evaluate the impact without taking time gap
into account, i.e. suppose that the impact of foreign investment attracting for
the recipient country – small open economy – comes at once. However, since this
situation is unlikely to take place we should conduct the evaluation with
regard to the time gap between FDI influx and the result (the change in GDP
value, export/import volume and employment rate) by the example of Russia,
Hungary and China. In order to do so, let’s determine the type and closeness of
correlation between foreign direct investment and
population
mean income,
export/import
volume,
unemployment
rate and
GDP.
using
Pirson's correlation coefficient (formula 1) and the data of the Federal state
statistics service (table 1, 2) about the volume of foreign investment
attracted to Russia, population mean income, export/import volume and
unemployment rate.
,
Formula 1. Pirson's correlation coefficient
where
хi- the volume of
attracted foreign direct investment,
yi
- dependent variables, in our
case mean income value, export/import volume, unemployment rate and GDP value,
where:
FDI – foreign direct investment (FDI) volume, in
terms of $ billion
GDP–
gross domestic product, in terms of $ billion
XP
– export, in terms of $ billion
IM
– import, in terms of $ billion
UNP – unemployment rate, (%)
Interdependence
correlation coefficient between foreign direct investment and:
Average
per capita population income equals – 0,0438,
Unemployment
rate equals – 0,0999,
GDP
equals – 0,0291.
«–» sign indicates the inverse negative
relationship between analyzed characteristics while «+» sign indicates the
direct relation. As in all the cases correlation coefficient tends to zero
(<0,1) we could draw a conclusion that there is no linear dependence between
present showings and foreign direct investment.
The
absence of interdependence between the volume of investment attracted to Russia
and calculated showings is indicated visually in the following figures (1-4).
It’s
possible that the absence of interdependence between FDI influx and analyzed
national measures is the result of negligibly small amount of FDI attracted to
Russia. In our opinion, to test
this assumption we should follow the experience of the countries-small open
economies, which were leading in FDI attraction. And it’s desirable to take
non-developed countries. As we know that at that time Hungary took the first
place in investment attraction among CEEC countries
(tab.3) and China – among South-East Asia nations (tab.4) let’s make detailed
calculations and graphs for these countries. Since we didn't manage to find the
information about population mean income for the period of 1992-2002 in these
countries we would use export/import showings what corresponds to UNCTAD
practice.
Correlation
coefficient between foreign direct investment in Hungary and:
export
volume equals 0.0840,
import
volume equals – 0.0422,
Unemployment
rate equals – 0.0481,
GDP
equals – 0.0594.
Correlation
coefficient between foreign direct investment in Hungary and:
export
volume equals 0.3661,
import
volume equals – 0.3650,
Unemployment
rate equals – 0.4938,
GDP
equals – 0.3746.
Let’s
also make a graphical interpretation of the information on Chinese economy.
According
to regression and correlation analysis theory we can only talk about the
interdependence when the coefficient value lies in the range from 0.7 to 1.0.
If the range is from 0.4 to 0.7 the dependence is small and if the coefficient
value is less than 0.4 – there is no dependence at all. In our calculations
only in China the dependence slightly exceeded the threshold of 0.4.
In
accordance with the adopted approach which consists in using the project
investment analysis method for the evaluation of FDI impact on the small
economy development we should take time gap into account. It’s clear that we
can’t obtain a result at once, i.e. in 1992 we can’t gain effect from the
investment put up in the same year. Therefore, we have calculated the
dependence of GDP, export/import volume and unemployment rate on FDI taking the
time gap into account. The purpose of the research was to find out whether the
time gap corresponded to a seven-year grace period given by the legislation of
most of the world countries to investment projects. In Russia the correlation
with the time gap was discovered in 2 and 3 years only concerning export; all
other showings were below 0.7. And since the 4-th year almost all the showings
have demonstrated negative correlation coefficient. In Hungary, the correlation
by GDP was seen in the 7-th and 9-th years (in 8-th there wasn’t), by
export/import – in the 8-th year.
There was no correlation between FDI and unemployment rate. In China since the 6-th year the
correlation was seen only by GDP (Appendix 1).
Nevertheless,
we think that foregoing calculations don’t give the ground to draw a conclusion
about the total lack of FDI impact on the economy of the recipient country. But
we can undoubtedly talk about the lack of the dependency between the volume of
the attracted foreign direct investment and the examined national measures. The
conducted research proves that for the elaboration of foreign direct investment
attraction policy we need to make the predesign of the FDI effect (quantitative
and qualitative). Our calculations
also have revealed that seven-year grace period adopted in many countries is
not always warranted.
There
are small counties which are heavily dependant on FDI. Belgium and Ireland
belonging to the European Community (EC); Argentina, Chile, Venezuela
(MERCOSUR); Malaysia, Singapore (ASEAN) depend heavily on the foreign direct
investment. At the end of the nineties, Hungary, Bolivia and Sweden were the
most dependent on the foreign investment. In these countries an economic
progress was up to the foreign direct investment almost to the same extent as
to the national investment.
Why
do attracted FDI volumes differ from country to country? Why do the effects of
FDI differ? What are the reasons for such differences? Why do some countries
succeed in this activity and others don’t?
Perhaps
the answers to these questions are as follows:
countries
have different objectives and use different strategies,
the
objectives of the recipient country and transnational corporations as FDI
bearers don’t concur,
it’s
necessary to take into account ethnic and cultural business traditions,
recipient
countries entered the international capital market in different times (some
were earlier, others-later).
As
for FDI impact on other showings and activities of the recipient country –
small open economy, in general there are both positive and negative effects of
FDI. The completion phase of the research should be the evaluation of the
positive and negative effects of FDI attraction for the small open economy
development.
Certainly,
there are many examples of both positive and negative FDI impact on small
countries development.
Appendix 1
National measures correlation
(with the time gap)
References
FDI –
development policy; national and international issues. (2003). Another
turn in irregular FDI sinking. International investment report – 2003. –
www. unctad.org.
Hoekman
B.Saggi К. (2001). Multilateral Discipline for Investment - Related Policies.
Paper presented at the conference Global Regionalism. Rome. Turrini A., Urban
D. A theoretical perspective on multilateral agreements on investments. Discussion paper. – London. – 2001. - №.
2774.Center for Economic Policy Research.
Tables and
Figures
Table 1: National measures of the Russian economy
(1994-2003)
Years |
GDP, $billion |
Export volume $billion |
Import volume $billion |
Unemployment rate % |
FDI, $billion |
1994 |
254,46 |
67,38 |
50,45 |
7,40 |
0,40 |
1995 |
373,00 |
82,42 |
62,60 |
8,50 |
1,50 |
1996 |
419,90 |
89,69 |
68,09 |
9,60 |
1,70 |
1997 |
430,31 |
86,90 |
71,98 |
10,80 |
1,70 |
1998 |
290,06 |
74,44 |
58,02 |
11,80 |
1,50 |
1999 |
186,35 |
75,55 |
39,54 |
12,90 |
1,30 |
2000 |
264,76 |
105,03 |
44,86 |
10,60 |
4,42 |
2001 |
307,46 |
101,88 |
53,76 |
9,10 |
3,98 |
2002 |
350,66 |
107,30 |
60,97 |
8,00 |
4,00 |
2003 |
434,4428 |
163,60 |
84,50 |
8,60 |
|
Table
2: National
measures of the Russian economy (1994-2002)[3]
Years |
Average per capita population
income (rubles a month) |
GDP (billion rubles) |
Rate of $ to ruble |
Average per capita population
income ($ a year) |
1 |
3 |
5 |
6 |
7=3:6 |
1994 |
206,3 |
610,7 |
2,4 |
85,96 |
1995 |
515,5 |
1540,5 |
4,13 |
124,82 |
1996 |
770.0 |
2145,7 |
5,11 |
150,68 |
1997 |
942,1 |
2478,6 |
5,76 |
163,56 |
1998 |
1012.0 |
2741,1 |
9,45 |
107,09 |
1999 |
1658,9 |
4766,8 |
25,58 |
64,85 |
2000 |
2281,2 |
7302,2 |
27,58 |
82,71 |
2001 |
3060,5 |
9040,8 |
29,41 |
104,09 |
2002 |
3887.0 |
10863,4 |
30,98 |
125,47 |
Table
3: Main national measures of Hungary, 1992-2003[4]
Years |
GDP, $billion |
Export volume $billion |
Import volume $billion |
Unemployment rate % |
FDI, $billion |
1990 |
58,81 |
9,60 |
8,67 |
1,70 |
0,31 |
1991 |
61,10 |
10,48 |
11,73 |
8,50 |
1,47 |
1992 |
61,25 |
10,68 |
11,11 |
9,80 |
1,48 |
1993 |
61,70 |
8,89 |
12,52 |
11,90 |
2,45 |
1994 |
65,00 |
10,69 |
14,38 |
10,70 |
1,14 |
1995 |
82,83 |
12,44 |
15,05 |
10,20 |
5,17 |
1996 |
101,61 |
12,65 |
15,86 |
9,90 |
2,38 |
1997 |
126,01 |
18,61 |
20,65 |
8,70 |
2,24 |
1998 |
132,44 |
22,96 |
25,60 |
7,80 |
2,08 |
1999 |
138,00 |
26,33 |
29,42 |
7,00 |
2,04 |
2000 |
145,17 |
34,22 |
38,98 |
6,40 |
1,69 |
2001 |
150,69 |
38,10 |
42,01 |
5,70 |
2,60 |
2002 |
155,66 |
40,92 |
44,68 |
5,80 |
0,86 |
2003 |
147,70 |
45,46 |
48, 89, |
5,90 |
0.25 |
Table
4: Main national measures of China (1990 – 2003)
Years |
GDP, $billion |
Export volume $billion |
Import volume $billion |
Unemployment rate % |
FDI, $billion |
1990 |
370,00 |
62,25 |
53,57 |
2,5 |
32,36 |
1991 |
379,00 |
71,90 |
63,80 |
2,3 |
6,60 |
1992 |
436,00 |
84,77 |
80,39 |
2,3 |
11,98 |
1993 |
571,98 |
91,34 |
103,44 |
2,6 |
58,12 |
1994 |
527,27 |
121,02 |
115,69 |
2,8 |
111,44 |
1995 |
711,44 |
148,80 |
129,11 |
2,9 |
82,68 |
1996 |
834,73 |
151,19 |
138,94 |
3 |
91,28 |
1997 |
917,68 |
182,88 |
142,19 |
3 |
73,28 |
1998 |
947,29 |
183,59 |
140,31 |
3,1 |
51,00 |
1999 |
1024,64 |
216,41 |
213,16 |
3,1 |
52,10 |
2000 |
1101,99 |
249,24 |
225,12 |
3,1 |
41,22 |
2001 |
1179,35 |
266,64 |
243,60 |
3,6 |
62,38 |
2002 |
1256,70 |
325,68 |
295,32 |
4 |
69,19 |
2003 |
1334,05 |
438,48 |
413,04 |
4,1 |
82,77 |
Figure
1: The
dependence of GDP value on the volume of foreign investment attracted to Russia
Figure 2: The dependence of unemployment rate on
the volume of attracted foreign investment.
Figure 3: The dependence of export/import volume on
the volume of foreign investment attracted to Russia
Figure 4: The dependence of population mean income on the volume of
foreign investment attracted to Russia.
Figure 5: The dependence of GDP value on the
volume of foreign direct investment in Hungary
Figure
6:
The dependence of export/import volume on the volume of foreign direct
investment in Hungary
Figure 7: The dependence of unemployment rate on
the volume of foreign direct investment in Hungary
Figure 8: The dependence of GDP value on the volume of foreign direct investment in China
Figure 9: The dependence of export/import volume
on the volume of foreign direct investment in China
Figure 10: The
dependence of unemployment rate on the volume of foreign direct investment in
China
Figure 11: The correlation
between the foreign direct investment and export volume in Russia
Figure
12: The
correlation between the foreign direct investment and GDP value in Hungary
(year 7)
Figure
13: The
correlation between the foreign direct investment and export volume in Hungary
(8 year)
Figure 14. The correlation
between the foreign direct investment and GDP value in China (years 6-8)
Appendix
1
National measures correlation (with
the time gap)
Russia
Years |
FDI |
GDP, $billion |
XP, $ billion |
IM $ billion |
UNP, % |
1994 |
0,4 |
254,4583 |
67,38 |
50,45 |
7,4 |
1995 |
1,5 |
373,0024 |
82,42 |
62,6 |
8,5 |
1996 |
1,7 |
419,9022 |
89,69 |
68,09 |
9,6 |
1997 |
1,7 |
430,3125 |
86,9 |
71,98 |
10,8 |
1998 |
1,5 |
290,0635 |
74,44 |
58,02 |
11,8 |
1999 |
1,3 |
186,3487 |
75,55 |
39,54 |
12,9 |
2000 |
4,425 |
264,7643 |
105,03 |
44,86 |
10,6 |
2001 |
3,978 |
307,4579 |
95,8 |
54 |
9,1 |
2002 |
4,002 |
350,6585 |
121,5 |
67,1 |
8 |
2003 |
|
434,4428 |
163,60 |
84,50 |
8,60 |
Correlation coefficient |
0,1593 |
0,6548 |
0,3426 |
-0,4676 |
year 1 |
FDI |
GDP, $ billion |
XP, $ billion |
IM $ billion |
UNP, % |
1995 |
0,4 |
373,0024 |
82,42 |
62,6 |
8,5 |
1996 |
1,5 |
419,9022 |
89,69 |
68,09 |
9,6 |
1997 |
1,7 |
430,3125 |
86,9 |
71,98 |
10,8 |
1998 |
1,7 |
290,0635 |
74,44 |
58,02 |
11,8 |
1999 |
1,5 |
186,3487 |
75,55 |
39,54 |
12,9 |
2000 |
1,3 |
264,7643 |
105,03 |
44,86 |
10,6 |
2001 |
4,425 |
307,4579 |
95,8 |
54 |
9,1 |
2002 |
3,978 |
350,6585 |
121,5 |
67,1 |
8 |
2003 |
4.002 |
434,4428 |
163,6 |
84,5 |
8,6 |
Correlation coefficient |
0,15931 |
0,654752 |
0,342616 |
-0,46759 |
year 2 |
FDI |
GDP, $ billion |
XP, $ billion |
IM $ billion |
UNP, % |
1996 |
0,4 |
419,9022 |
89,69 |
68,09 |
9,6 |
1997 |
1,5 |
430,3125 |
86,9 |
71,98 |
10,8 |
1998 |
1,7 |
290,0635 |
74,44 |
58,02 |
11,8 |
1999 |
1,7 |
186,3487 |
75,55 |
39,54 |
12,9 |
2000 |
1,5 |
264,7643 |
105,03 |
44,86 |
10,6 |
2001 |
1,3 |
307,4579 |
95,8 |
54 |
9,1 |
2002 |
4,425 |
350,6585 |
121,5 |
67,1 |
8 |
2003 |
3,978 |
434,4428 |
163,6 |
84,5 |
8,6 |
Correlation coefficient |
0,1876 |
0,754134 |
0,4492 |
-0,5292 |
year 3 |
FDI |
GDP, $ billion |
XP, $ billion |
IM $ billion |
UNP, % |
1997 |
0,4 |
430,3125 |
86,9 |
71,98 |
10,8 |
1998 |
1,5 |
290,0635 |
74,44 |
58,02 |
11,8 |
1999 |
1,7 |
186,3487 |
75,55 |
39,54 |
12,9 |
2000 |
1,7 |
264,7643 |
105,03 |
44,86 |
10,6 |
2001 |
1,5 |
307,4579 |
95,8 |
54 |
9,1 |
2002 |
1,3 |
350,6585 |
121,5 |
67,1 |
8 |
2003 |
4,425 |
434,4428 |
163,6 |
84,5 |
8,6 |
Correlation coefficient |
0,2430 |
0,7927 |
0,4254 |
-0,3311 |
year 4 |
FDI |
GDP, $ billion |
XP, $ billion |
IM $ billion |
UNP, % |
1998 |
0,4 |
290,0635 |
74,44 |
58,02 |
11,8 |
1999 |
1,5 |
186,3487 |
75,55 |
39,54 |
12,9 |
2000 |
1,7 |
264,7643 |
105,03 |
44,86 |
10,6 |
2001 |
1,7 |
307,4579 |
95,8 |
54 |
9,1 |
2002 |
1,5 |
350,6585 |
121,5 |
67,1 |
8 |
2003 |
1,3 |
434,4428 |
163,6 |
84,5 |
8,6 |
Correlation coefficient |
-0,0807 |
0,2564 |
-0,2207 |
-0,3414 |
Hungary
Years |
FDI |
GDP, $billion |
XP, $ billion |
IM $ billion |
UNP, % |
1990 |
312,14 |
58806,46 |
9597 |
8671 |
1,7 |
1991 |
1474,4 |
61100 |
10482,07 |
11732,4 |
8,5 |
1992 |
1477,2 |
61250 |
10676 |
11106 |
9,8 |
1993 |
2446,2 |
61700 |
8888 |
12521 |
11,9 |
1994 |
1143,5 |
82827,05 |
12435 |
15046 |
10,2 |
1995 |
5174,3 |
101611,6 |
12647 |
15856 |
9,9 |
1996 |
2375,5 |
126009 |
18613 |
20652 |
8,7 |
1997 |
2243,1 |
132435,4 |
22955 |
25596 |
7,8 |
1998 |
2084,5 |
137997,7 |
26329,25 |
29417,89 |
7 |
1999 |
2039,7 |
145173,6 |
34218,95 |
38983,23 |
6,4 |
2000 |
1691,9 |
150690,2 |
38095,41 |
42007,16 |
5,7 |
2001 |
2597,1 |
155663 |
40920,37 |
44684,16 |
5,8 |
2002 |
855,16 |
147700 |
45459 |
48886 |
5,9 |
2003 |
2500 |
147700 |
45459 |
48886 |
5,9 |
Correlation coefficient |
0,0924 |
-0,0083 |
0,0244 |
0,4417 |
year 1 |
FDI |
GDP, $bilion |
XP, $billion |
IM $billion |
UNP, % |
1992 |
312,14 |
61100 |
10482,07 |
11732,4 |
8,5 |
1993 |
1474,4 |
61250 |
10676 |
11106 |
9,8 |
1994 |
1477,2 |
61700 |
8888 |
12521 |
11,9 |
1995 |
2446,2 |
65000 |
10689 |
14383 |
10,7 |
1996 |
1143,5 |
101611,6 |
12647 |
15856 |
9,9 |
1997 |
5174,3 |
126009 |
18613 |
20652 |
8,7 |
1998 |
2375,5 |
132435,4 |
22955 |
25596 |
7,8 |
1999 |
2243,1 |
137997,7 |
26329,25 |
29417,89 |
7 |
2000 |
2084,5 |
145173,6 |
34218,95 |
38983,23 |
6,4 |
2001 |
2039,7 |
150690,2 |
38095,41 |
42007,16 |
5,7 |
2002 |
1691,9 |
155663 |
40920,37 |
44684,16 |
5,8 |
2003 |
2597,1 |
147700 |
45459 |
48886 |
5,9 |
Correlation coefficient |
0,1789 |
-0,0810 |
-0,0534 |
0,1175 |
year2 |
FDI |
GDP, $billion |
XP, $illion |
IM $bilion |
1993 |
312,14 |
61250 |
10676 |
11106 |
1994 |
1474,4 |
61700 |
8888 |
12521 |
1995 |
1477,2 |
65000 |
10689 |
14383 |
1996 |
2446,2 |
82827,05 |
12435 |
15046 |
1997 |
1143,5 |
126009 |
18613 |
20652 |
1998 |
5174,3 |
132435,4 |
22955 |
25596 |
1999 |
2375,5 |
137997,7 |
26329,25 |
29417,89 |
2000 |
2243,1 |
145173,6 |
34218,95 |
38983,23 |
2001 |
2084,5 |
150690,2 |
38095,41 |
42007,16 |
2002 |
2039,7 |
155663 |
40920,37 |
44684,16 |
2003 |
1691,9 |
147700 |
45459 |
48886 |
Correlation coefficient |
0,4202 |
0,2036 |
0,1966 |
year 3 |
FDI |
GDP, $billion |
XP, $billion |
IM $billion |
1994 |
312,14 |
61700 |
8888 |
12521 |
1995 |
1474,4 |
65000 |
10689 |
14383 |
1996 |
1477,2 |
82827,05 |
12435 |
15046 |
1997 |
2446,2 |
101611,6 |
12647 |
15856 |
1998 |
1143,5 |
132435,4 |
22955 |
25596 |
1999 |
5174,3 |
137997,7 |
26329,25 |
29417,89 |
2000 |
2375,5 |
145173,6 |
34218,95 |
38983,23 |
2001 |
2243,1 |
150690,2 |
38095,41 |
42007,16 |
2002 |
2084,5 |
155663 |
40920,37 |
44684,16 |
2003 |
2039,7 |
147700 |
45459 |
48886 |
Correlation coefficient |
0,4284 |
0,2064 |
0,1945 |
|
year 4 |
FDI |
GDP, $billion |
XP, $billion |
IM $billion |
1995 |
312,14 |
65000 |
10689 |
14383 |
1996 |
1474,4 |
82827,05 |
12435 |
15046 |
1997 |
1477,2 |
101611,6 |
12647 |
15856 |
1998 |
2446,2 |
126009 |
18613 |
20652 |
1999 |
1143,5 |
137997,7 |
26329,25 |
29417,89 |
2000 |
5174,3 |
145173,6 |
34218,95 |
38983,23 |
2001 |
2375,5 |
150690,2 |
38095,41 |
42007,16 |
2002 |
2243,1 |
155663 |
40920,37 |
44684,16 |
2003 |
2084,5 |
147700 |
45459 |
48886 |
Correlation coefficient |
0,5311 |
0,3288 |
0,3175 |
year 5 |
FDI |
GDP, $billion |
XP, $billion |
IM $billion |
1996 |
312,14 |
82827,05 |
12435 |
15046 |
1997 |
1474,4 |
101611,6 |
12647 |
15856 |
1998 |
1477,2 |
126009 |
18613 |
20652 |
1999 |
2446,2 |
132435,4 |
22955 |
25596 |
2000 |
5174,3 |
150690,2 |
38095,41 |
42007,16 |
2001 |
2375,5 |
155663 |
40920,37 |
44684,16 |
2002 |
2243,1 |
147700 |
45459 |
48886 |
2003 |
2084,5 |
147700 |
45459 |
48886 |
Correlation coefficient |
0,5855 |
0,5026 |
0,5306 |
year 6 |
FDI |
GDP, $billion |
XP, $billion |
IM $billion |
1997 |
312,14 |
101611,6 |
12647 |
15856 |
1998 |
1474,4 |
126009 |
18613 |
20652 |
1999 |
1477,2 |
132435,4 |
22955 |
25596 |
2000 |
2446,2 |
137997,7 |
26329,25 |
29417,89 |
2001 |
1143,5 |
150690,2 |
38095,41 |
42007,16 |
2002 |
5174,3 |
155663 |
40920,37 |
44684,16 |
2003 |
2375,5 |
147700 |
45459 |
48886 |
Correlation coefficient |
0,6520 |
0,5770 |
0,5685 |
year 7 |
FDI |
GDP, $billion |
XP, $billion |
IM $bilion |
1998 |
312,14 |
126009 |
18613 |
20652 |
1999 |
1474,4 |
132435,4 |
22955 |
25596 |
2000 |
1477,2 |
137997,7 |
26329,25 |
29417,89 |
2001 |
2446,2 |
145173,6 |
34218,95 |
38983,23 |
2002 |
1143,5 |
155663 |
40920,37 |
44684,16 |
2003 |
5174,3 |
147700 |
45459 |
48886 |
Correlation coefficient |
0,7464 |
0,6379 |
0,6423 |
year 8 |
FDI |
GDP, $billion |
XP, $billion |
IM $billion |
1999 |
312,14 |
132435,4 |
22955 |
25596 |
2000 |
1474,4 |
137997,7 |
26329,25 |
29417,89 |
2001 |
1477,2 |
145173,6 |
34218,95 |
38983,23 |
2002 |
2446,2 |
150690,2 |
38095,41 |
42007,16 |
2003 |
1143,5 |
155663 |
40920,37 |
44684,16 |
Correlation coefficient |
0,3716 |
0,7465 |
0,7251 |
China
Years |
FDI |
GDP, $billion |
XP, $billion |
IM $billion |
UNP, % |
1990 |
32,36 |
370 |
62,2455 |
53,5725 |
2,5 |
1991 |
6,6 |
379 |
71,9 |
63,8 |
2,3 |
1992 |
11,98 |
436 |
84,77 |
80,3925 |
2,3 |
1993 |
58,12 |
571,9792 |
91,335 |
103,444 |
2,6 |
1994 |
111,44 |
527,2657 |
121,0235 |
115,6905 |
2,8 |
1995 |
82,68 |
711,4371 |
148,797 |
129,113 |
2,9 |
1996 |
91,28 |
834,7292 |
151,187 |
138,944 |
3 |
1997 |
73,28 |
917,684 |
182,877 |
142,189 |
3 |
1998 |
51 |
947,2892 |
183,589 |
140,305 |
3,1 |
1999 |
52,1 |
1024,642 |
216,4145 |
213,1563 |
3,1 |
2000 |
41,22 |
1101,995 |
249,24 |
225,12 |
3,1 |
2001 |
62,38 |
1179,348 |
266,64 |
243,6 |
3,6 |
2002 |
69,19 |
1256,7 |
325,68 |
295,32 |
4,0 |
2003 |
82,77 |
1334,053 |
438,48 |
413,04 |
4,3 |
Correlation coefficient |
0,3746 |
0,3661 |
0,3650 |
0,4885 |
year 1 |
FDI |
GDP, $billion |
XP, $billion |
IM $billion |
UNP, % |
1990 |
32,36 |
370 |
62,2455 |
53,5725 |
2,5 |
1991 |
6,6 |
379 |
71,9 |
63,8 |
2,3 |
1992 |
11,9800 |
436 |
84,77 |
80,3925 |
2,3 |
1993 |
58,12 |
571,9792 |
91,335 |
103,444 |
2,6 |
1994 |
111,44 |
527,2657 |
121,0235 |
115,6905 |
2,8 |
1995 |
111,44 |
711,4371 |
148,797 |
129,113 |
2,9 |
1996 |
82,68 |
834,7292 |
151,187 |
138,944 |
3 |
1997 |
91,28 |
917,684 |
182,877 |
142,189 |
3 |
1998 |
73,28 |
947,2892 |
183,589 |
140,305 |
3,1 |
1999 |
51 |
1024,642 |
216,4145 |
213,1563 |
3,1 |
2000 |
52,1 |
1101,995 |
249,24 |
225,12 |
3,1 |
2001 |
41,22 |
1179,348 |
266,64 |
243,6 |
3,6 |
2002 |
62,38 |
1256,7 |
325,68 |
295,32 |
4,0 |
2003 |
69,19 |
1334,053 |
438,48 |
413,04 |
4,3 |
Correlation coefficient |
0,3617 |
0,2936 |
0,2142 |
0,3635 |
year 2 |
FDI |
GDP, $billion |
XP, $billion |
IM $bilion |
UNP, % |
1992 |
32,36 |
436 |
84,77 |
80,3925 |
2,3 |
1993 |
6,6 |
571,9792 |
91,335 |
103,444 |
2,6 |
1994 |
11,98 |
527,2657 |
121,0235 |
115,6905 |
2,8 |
1995 |
58,12 |
711,4371 |
148,797 |
129,113 |
2,9 |
1996 |
111,44 |
834,7292 |
151,187 |
138,944 |
3 |
1997 |
82,68 |
917,684 |
182,877 |
142,189 |
3 |
1998 |
91,28 |
947,2892 |
183,589 |
140,305 |
3,1 |
1999 |
73,28 |
1024,642 |
216,4145 |
213,1563 |
3,1 |
2000 |
51 |
1101,995 |
249,24 |
225,12 |
3,1 |
2001 |
52,1 |
1179,348 |
266,64 |
243,6 |
3,6 |
2002 |
41,22 |
1256,7 |
325,68 |
295,32 |
4,0 |
2003 |
62,38 |
1334,053 |
438,48 |
413,04 |
4,3 |
Correlation coefficient |
0,3908 |
0,2038 |
0,1234 |
0,2101 |
year 3 |
FDI |
GDP, $billion |
XP, $billion |
IM $billion |
UNP, % |
1993 |
32,36 |
571,9792 |
91,335 |
103,444 |
2,6 |
1994 |
6,6 |
527,2657 |
121,0235 |
115,6905 |
2,8 |
1995 |
11,98 |
711,4371 |
148,797 |
129,113 |
2,9 |
1996 |
58,12 |
834,7292 |
151,187 |
138,944 |
3 |
1997 |
111,44 |
917,684 |
182,877 |
142,189 |
3 |
1998 |
82,68 |
947,2892 |
183,589 |
140,305 |
3,1 |
1999 |
91,28 |
1024,642 |
216,4145 |
213,1563 |
3,1 |
2000 |
73,28 |
1101,995 |
249,24 |
225,12 |
3,1 |
2001 |
51 |
1179,348 |
266,64 |
243,6 |
3,6 |
2002 |
52,1 |
1256,7 |
325,68 |
295,32 |
4,0 |
2003 |
41,22 |
1334,053 |
438,48 |
413,04 |
4,3 |
Correlation coefficient |
0,4083 |
0,1345 |
0,0583 |
0,0381 |
year 4 |
FDI |
GDP, $billion |
1994 |
32,36 |
527,2657 |
1995 |
6,6 |
711,4371 |
1996 |
11,98 |
834,7292 |
1997 |
58,12 |
917,684 |
1998 |
111,44 |
947,2892 |
1999 |
82,68 |
1024,642 |
2000 |
91,28 |
1101,995 |
2001 |
73,28 |
1179,348 |
2002 |
51 |
1256,7 |
2003 |
52,1 |
1334,053 |
Correlation coefficient |
0,4544 |
year 5 |
FDI |
GDP, $billion |
1995 |
32,36 |
711,4371 |
1996 |
6,6 |
834,7292 |
1997 |
11,98 |
917,684 |
1998 |
58,12 |
947,2892 |
1999 |
111,44 |
1024,642 |
2000 |
82,68 |
1101,995 |
2001 |
91,28 |
1179,348 |
2002 |
73,28 |
1256,7 |
2003 |
51 |
1334,053 |
Correlation coefficient |
0,5352 |
year 6 |
FDI |
GDP, $billion |
1996 |
32,36 |
834,7292 |
1997 |
6,6 |
917,684 |
1998 |
11,98 |
947,2892 |
1999 |
58,12 |
1024,642 |
2000 |
111,44 |
1101,995 |
2001 |
82,68 |
1179,348 |
2002 |
91,28 |
1256,7 |
2003 |
73,28 |
1334,053 |
Correlation coefficient |
0,7316 |
year 7 |
FDI |
GDP, $billion |
1997 |
32,36 |
917,684 |
1998 |
6,6 |
947,2892 |
1999 |
11,98 |
1024,642 |
2000 |
58,12 |
1101,995 |
2001 |
111,44 |
1179,348 |
2002 |
82,68 |
1256,7 |
2003 |
91,28 |
1334,053 |
Correlation coefficient |
0,8347 |
year 8 |
FDI |
GDP, $billion |
1998 |
32,36 |
947,2892 |
1999 |
6,6 |
1024,642 |
2000 |
11,98 |
1101,995 |
2001 |
58,12 |
1179,348 |
2002 |
111,44 |
1256,7 |
2003 |
82,68 |
1334,053 |
Correlation coefficient |
0,7915 |
[1] Professor,
Doctor in Economics. Tatiana
V. Kalashnikova, PhD in Technique. Russia.
* Received 5 September 2009; accepted 10 September 2009
[2] The effect of agricultural products processing transfer from specialized region processing plants directly to the farms in respect to the society lies in transportation costs reduction, i.e. finished product transportation is cheaper than raw material transportation, and processing companies’ capacity utilization decrease as well. Here quality improvement and costs reduction are not guaranteed. Competition could be the indirect effect of such a project, however, forming of competitive environment like this is rather expensive.
[3] Source: author’s calculations based on data of the RF Federal state statistics service, the rate of exchange is taken as average annual rate of the Bank of Russia.
[4] Source: author’s calculations based on data of the Bank of Hungary.
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