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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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