FDI as Force of Convergence in the CESEE Countries

Szabo, Septimiu; Laguna, Jorge Durán

doi:10.1007/978-3-030-57702-5_3

Septimiu Szabo⁵ &
Jorge Durán Laguna⁵

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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Convergence of Non-EU Countries in the CESEE Region

Shaping Globalization: Recent Trends in Asia-Pacific Foreign Direct Investment

The middle-income trap in Central and Eastern Europe in the 2010s: institutions and divergent growth models

Article Open access 02 November 2021

Notes

1.
Poland and Hungary were the first countries to sign the Association Agreements in 1994. Croatia signed it in 2005.
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.
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.
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.
Albania, Bosnia-Herzegovina, Georgia, Moldova, Montenegro, North Macedonia, Serbia, Ukraine.
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.
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.
Figures for Bulgarian regions only include non-financial FDI.
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.
Due to data availability, all data in this section include FDI generated via SPEs.
11.
Lithuania has higher productivity levels, but the car manufacturing sector is very small in the country.
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.
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.
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.
For a more nuanced view on FDI in general, see Mencinger (2003) and references therein.
16.
In general, foreign firms often perform better in terms of capital, labour and corporate governance.
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.
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.
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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Authors and Affiliations

DG ECFIN, European Commission, Brussels, Belgium
Septimiu Szabo & Jorge Durán Laguna

Authors

Septimiu Szabo
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Jorge Durán Laguna
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Corresponding author

Correspondence to Jorge Durán Laguna .

Editor information

Editors and Affiliations

Vienna Institute for International Economic Studies (WIIW), Vienna, Austria
Michael Landesmann
DG ECFIN, European Commission, Brussels, Belgium
István P. Székely

Appendices

Annex A: Some Basic Figures

Table A.1 Detailed data on inward and outward FDI in CESEE in 2016

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Table A.2 Breakdown of the FDI stock in CESEE

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Table A.3 The share of FDI to GDP in different regional blocks around the world

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Table A.4 Productivity in CESEE (gross value added per hour worked of employees in €)

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Table A.5 FDI stock as a share of GVA

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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 (%)
Code	NUTS 2 region	Significant city	1st sector	2nd sector	Change of GDP vs EU 2007–2016	GVA/h	Industry	Construction	Wholesale, retail, transport, hotels & rest	ITC	Controlling group	From	Rank Coface500	FDI stock (mil. EUR)	GDP (mil. EUR)	FDI stock/GDP (%)
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	28,108	33,240	57
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

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)
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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DOI: https://doi.org/10.1007/978-3-030-57702-5_3
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