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Part of the book series: Studies in Economic Transition ((SET))

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Abstract

Trade and access to international capital markets are often assumed to support countries’ development, notably through technology transfers that support convergence. In this chapter we review economic developments in the EU Central, Eastern and Southeastern (CESEE) countries (namely Bulgaria, Croatia, Czechia, Estonia, Latvia, Lithuania, Malta, Poland, Romania, Slovenia and Slovakia) since the late 1990s, linking their take-off to the opening to trade and infusion of foreign direct investment (FDI), largely facilitated by the EU accession and geographical proximity. The region has had one of the most significant growth of foreign investment as a share of GDP in the recent global history, and this has contributed to productivity convergence. We argue that FDI increased the well-being of people, by bringing in new jobs and higher wages, led to technological spillovers to domestic firms and increased efficiency and innovation in the market. Various trade-offs, particularly regarding the political implications of privatising national resources, repatriating profits and agglomeration effects are also acknowledged. We conclude that FDI can act as a force of growth and convergence when it comes alongside with a strong institutional, legal and regulatory environment, on the likes of the EU Single Market.

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Notes

  1. 1.

    Poland and Hungary were the first countries to sign the Association Agreements in 1994. Croatia signed it in 2005.

  2. 2.

    At various times in the 1990s, inflation in Romania or Bulgaria reached more than 300% but Slovenia, Poland or Czechia also witnessed rates of 30% to 50% in the early 1990s.

  3. 3.

    See Annex A with some basic charts. The Baltics are Estonia, Latvia and Lithuania; Visegrád is the Czech Republic, Slovakia, Poland and Hungary; the South is Bulgaria, Romania, Slovenia and Croatia.

  4. 4.

    For consistency with UN data, we use US Dollars when comparing the CESEE countries with the rest of the world. We use euro when comparing the countries at the EU level.

  5. 5.

    Albania, Bosnia-Herzegovina, Georgia, Moldova, Montenegro, North Macedonia, Serbia, Ukraine.

  6. 6.

    The Netherlands appears often among top investors because of their intermediate role: many investment projects are channelled via special purpose vehicles and entities for fiscal and regulatory reasons (see, e.g. Weyzig 2013).

  7. 7.

    An SPE is legal entity with no or few non-financial assets and employees, little or no production or operations and sometimes no physical presence beyond a ‘brass plate’ confirming its place of registration. Half of EU’s FDI is channelled via SPEs, particularly in Netherlands, Luxembourg and Malta.

  8. 8.

    Figures for Bulgarian regions only include non-financial FDI.

  9. 9.

    However, some of the data may be misleading. A case in point is Estonia where outward FDI in the financial sector is driven by local branches of Swedish banks operating in the region (see, e.g. Durán 2019).

  10. 10.

    Due to data availability, all data in this section include FDI generated via SPEs.

  11. 11.

    Lithuania has higher productivity levels, but the car manufacturing sector is very small in the country.

  12. 12.

    There is a vast literature on this. For FDI and long-term growth see, for example, Hansen and Rand (2006). For a general overview of theory and empirics of technology diffusion, see Keller (2004).

  13. 13.

    This is, of course, not mechanical. Borenszteina et al. (1998) explore the conditions under which FDI increases productivity more than domestic investment. Not surprisingly, the formation of human capital turns out to be a critical factor.

  14. 14.

    See Chiacchio et al. (2018) for the effect of FDI on the absorptive capacity of frontier firms and the trickle-down effect on laggards.

  15. 15.

    For a more nuanced view on FDI in general, see Mencinger (2003) and references therein.

  16. 16.

    In general, foreign firms often perform better in terms of capital, labour and corporate governance.

  17. 17.

    In this regard, the EU has recently adopted a new EU framework for the screening of FDI in order to better scrutinise purchases by foreign companies that target Europe’s strategic assets. The area remains a national competency but it will enhance cooperation among member states on these matters.

  18. 18.

    Contessi et al. (2013) note that FDI inflows are countercyclical in developing countries, most likely because of the low price of local firms for potential foreign owners during recessions, particularly during large devaluations or depreciations of the local currency.

  19. 19.

    Javorcik and Poelhekke (2017) show for a sample of Indonesian firms that disinvestment is associated with a drop in total factor productivity, output, mark-ups and export and import intensities.

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Acknowledgements

The views expressed in this chapter are those of the authors and should not be attributed in any way to the European Commission. We thank Jolita Adamonis, Judita Cuculic Zupa, Natalie Lubenets, Janis Malzubris, Ana Xavier, István P. Székely and others for many discussions, comments and suggestions.

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Correspondence to Jorge Durán Laguna .

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Appendices

Annex A: Some Basic Figures

Fig. A.1
figure 1figure 1

Trade and investment in CEE countries. (a) Real exports per capita, (b) share of intra-EU exports, (c) investment rate, excluding dwellings, (d) balance of FDI flows. Notes: (i) The Baltics are Estonia, Latvia and Lithuania; Visegrád countries are Czechia, Slovakia, Poland and Hungary; the South is Bulgaria, Romania, Slovenia and Croatia. (Source: Own calculations based on the AMECO database and UNCTAD)

Table A.1 Detailed data on inward and outward FDI in CESEE in 2016
Table A.2 Breakdown of the FDI stock in CESEE
Table A.3 The share of FDI to GDP in different regional blocks around the world
Table A.4 Productivity in CESEE (gross value added per hour worked of employees in €)
Table A.5 FDI stock as a share of GVA

Annex B: Some Tables with Detailed Data

Annex C: Value Added, Productivity and FDI in NUTS3 Regions

Code

NUTS 2 region

Significant city

Top employment sector

Change of GDP vs EU 2007–2016

GVA/h

Wages and salaries per number of employees

Largest foreign investor

FDI stock (mil. EUR)

GDP (mil. EUR)

FDI stock/GDP (%)

1st sector

2nd sector

Industry

Construction

Wholesale, retail, transport, hotels & rest

ITC

Controlling group

From

Rank Coface500

BG31

Northwestern

Pleven

Textiles

Food

2.4

15.3

2982

2714

1851

N/A

Great Wall Motors

CN

N/A

521

3486

15

BG32

Northern Central

Ruse

Textiles

Food

5.0

15.3

3818

1976

2614

2923

HSE

SI

N/A

1023

4017

25

BG33

Northeastern

Varna

Food

Textiles

4.3

16.7

4495

3269

2563

5000

Energo Pro

CZ

N/A

2568

5457

47

BG34

Southeastern

Burgas

Food

Metals

9.8

17.2

5419

3333

2582

2339

Lukoil

RU

35

2983

6685

45

BG41

Southwestern

Sofia

Textiles

Food

11.5

26.0

5958

4638

5902

14,901

Aurubis

DE

43

14,496

24,742

59

BG42

Southern Central

Plovdiv

Textiles

Food

4.9

14.8

4023

1789

2409

5411

Molson Coors

US

N/A

2842

7258

39

CZ01

Prague

Prague

Wood

Metals

2.7

67.5

16,909

10,532

18,169

27,208

Alpiq

CH

11

80,185

48,751

164

CZ02

Central Bohemia

Mlada Boeslav

Motor

Metals

2.8

47.3

11,461

3842

6525

2344

VW

DE

2

10,306

22,784

45

CZ03

Southwest

Plzeň

Metals

Motor

4.0

42.8

9261

5746

6298

7968

Robert Bosch

DE

209

7399

19,090

39

CZ04

Northwest

Ústí nad Labem

Metals

Plastics

−1.2

38.8

8724

4591

4729

5309

PKN Orlen

PL

16

4186

14,315

29

CZ05

Northeast

Liberec

Motor

Metals

4.3

41.3

8807

4643

6277

7540

IVECO

IT

234

6727

22,981

29

CZ06

Southeast

Brno

Metals

Machinery

8.2

44.2

9321

6209

7431

18,170

Automotive Lighting

DE

334

8364

27,760

30

CZ07

Central Moravia

Olomuc

Metals

Plastics

8.0

40.0

8665

5348

6061

9940

Continental

DE

58

4484

18,024

25

CZ08

Moravian-Silesia

Ostrava

Metals

Motor

6.8

43.7

9927

4963

6649

9635

Hyundai Motor Group

KR

12

8334

18,017

46

EE00

Estonia

Tallin

Wood

Food

5.7

43.1

11,558

8130

10,286

13,485

Ericsson

SE

245

19,924

23,615

84

HR03

Adriatic Croatia

Split

Food

Metals

−2.8

36.5

10,965

8226

7956

11,053

OTP

HU

N/A

28,108

15,750

57

HR04

Continental Croatia

Zagreb

Food

Wood

−0.3

36.5

10,670

7937

9373

15,156

Deutsche Telekom

DE

239

33,240

LV00

Latvia

Riga

Wood

Food

7.3

35.6

8434

6446

8013

14,510

Uralchem

RU

226

14,605

27,033

54

LT00

Lithuania

Vilnius

Wood

Food

15.0

38.4

8278

6758

7390

14,678

PKN

PL

20

14,816

42,191

35

HU10

Central Hungary

Budapest

Food

Metals

2.3

38.3

10,836

5583

9535

19,548

General Electric

US

55

43,261

53,045

82

HU21

Central Transdanubia

Székes-fehérvár

Motor

Metals

8.4

34.4

9233

3309

5235

6000

Suzuki

JP

66

7795

11,646

67

HU22

Western Danubia

Gyor

Motor

Wood

15.2

37.4

10,093

3795

6035

9333

VW

DE

6

11,846

12,452

95

HU23

Southern Danubia

Pecs

Food

Electronics

3.9

30.0

6636

3774

5419

12,139

Flex

US

74

1002

6847

15

HU31

Northern Hungary

Miskolc

Electronics

Metals

6.4

31.8

7737

3691

5276

9633

Robert Bosch

DE

23

3489

8732

40

HU32

Northern Great Plain

Debrecen

Food

Electronics

5.3

29.1

6136

3366

5205

8506

Teva

IL

215

4545

10,801

42

HU33

Southern Great Plain

Szeged

Food

Plastics

8.5

30.5

6811

4047

5273

8485

Mercedes

DE

25

2776

10,374

27

PL12

Masovian

Warsaw

Food

Wood

26.4

42.1

7811

6050

11,524

15,734

Orange

FR

40

95,721

94,978

101

PL21

Lesser Poland

Krakow

Metals

Food

14.7

33.4

7905

4166

6207

14,380

Tesco

UK

36

8106

33,943

24

PL22

Silesian

Katowice

Metals

Motor

14.8

36.7

10,298

5570

5358

8553

ArcelorMittal

LU

21

18,718

52,498

36

PL31

Lublin

Lublin

Food

Wood

10.0

20.4

4276

3071

2895

4586

Maxima Group

LT

348

1386

16,334

8

PL32

Subcarpathian

Rzeszów

Plastics

Wood

10.7

27.8

8389

3970

3704

6971

Goodyear

US

466

3619

16,631

22

PL33

Holy Cross

Kielce

Metals

Plastics

6.8

21.8

6531

2968

3348

N/A

CELSA Group

ES

327

1665

9957

17

PL34

Podlaskie

Białystok

Food

Wood

9.1

23.3

6118

3796

4087

4889

BAT

UK

128

514

9335

6

PL41

Greater Poland

Poznan

Wood

Food

18.5

39.0

9440

4932

9102

12,797

Jerónimo Martins

PT

4

15,842

42,120

38

PL42

West Pomeranian

Szczecin

Wood

Food

10.3

36.0

7148

3815

5202

13,136

IKEA

SE

163

3530

15,899

22

PL43

Lubusz

Zielona Góra

Wood

Motor

10.0

29.6

7161

2203

3668

N/A

Krono Holding

CH

435

1795

9476

19

PL51

Lower Silesian

Wroclaw

Motor

Plastics

17.9

39.3

10,126

4628

6294

10,287

Schwarz Gruppe

DE

49

9970

35,712

28

PL52

Opole

Opole

Metals

Food

9.9

30.5

7150

3792

3734

N/A

Brenntag

DE

482

1396

8786

16

PL61

Kuyavian-Pomeranian

Bydgoszcz

Wood

Metals

10.1

27.5

7031

4098

4327

3636

Framondi

NL

264

2605

18,872

14

PL62

Warmian-Masurian

Olsztyn

Wood

Food

9.5

24.7

6712

3288

3208

N/A

VH Group

CN

130

993

11,373

9

PL63

Pomeranian

Gdansk

Wood

Metals

13.7

30.3

7172

4126

4880

12,598

Glencore

CH

200

6415

24,855

26

RO11

North-West

Cluj

Textiles

Wood

9.7

21.8

4350

2515

2965

12,343

MOL

HU

148

4108

20,065

20

RO12

Centre

Sibiu

Textiles

Motor

10.2

26.6

5406

2432

3626

5292

Daimler

DE

102

6379

19,255

33

RO21

North-East

Iasi

Textiles

Food

8.1

14.8

3579

1318

2378

6192

Delphi Technologies

UK

498

1606

17,180

9

RO22

South-East

Constanta

Textiles

Food

14.1

24.2

4386

2497

3440

6280

KazMunayGas

KZ

51

3477

17,789

20

RO31

South Muntenia

Ploiesti

Motor

Textiles

10.4

23.9

5189

1693

2514

3973

Renault

FR

14

4837

20,859

23

RO32

Bucharest-Ilfov

Bucharest

Food

Textiles

37.2

50.0

11,414

6121

6895

16,954

OMV

AT

31

42,021

46,262

91

RO41

South-West Oltenia

Craiova

Textiles

Food

9.5

20.2

5009

3095

3231

5880

Ford

US

181

2080

12,328

17

RO42

West

Timisoara

Motor

Textiles

12.4

27.8

4916

3680

3478

14,536

Louis Delhaize

BE

187

5605

16,539

34

SI03

Eastern Slovenia

Maribor

Metals

Wood

−2.9

54.5

17,185

13,477

11,642

9629

Renault

FR

98

2205

17,092

13

SI04

Western Slovenia

Ljubliana

Metals

Electronics

−7.8

64.5

19,327

16,053

17,957

19,319

Mercator

HR

144

9121

21,772

42

SK01

Bratislava Region

Bratislava

Motor

Other & repairs

25.9

73.5

19,652

11,677

17,843

30,268

VW

DE

7

29,041

22,283

130

SK02

Western Slovakia

Trnava

Metals

Plastics

7.0

46.0

7542

2678

4737

3883

Peugeot

FR

41

5995

24,663

24

SK03

Central Slovakia

Žilina

Metals

Wood

8.6

43.0

7658

2293

5322

4386

Hyundai Motor Group

KR

13

3836

15,696

24

SK04

Eastern Slovakia

Košice

Metals

Motor

7.9

45.7

6659

2433

3252

7217

US Steel

NL

489

3392

16,497

21

  1. Source: Own calculations based on data from the European Commission, Eurostat, Coface Group, BoP data available at the national level (central bank and/or statistics institute)
  2. Note: Most recent data. Data for Bulgarian regions exclude FDI in financial services. No FDI regional data for Croatia

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Szabo, S., Laguna, J.D. (2021). FDI as Force of Convergence in the CESEE Countries. In: Landesmann, M., Székely, I.P. (eds) Does EU Membership Facilitate Convergence? The Experience of the EU's Eastern Enlargement - Volume II. Studies in Economic Transition. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-57702-5_3

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