foreign direct investment in southeastern europe: what do the …525769e2-4c44-4f46-a28f-2ae1... ·...

‚ O e s t e r r e i c h i s c h e N a t i o n a l b a n k C o n f e r e n c e o n E u r o p e a n E c o n o m i c I n t e g r a t i o n

November 28 to 30, 2004, Vienna

Foreign Direct Investment in Southeastern Europe:

What Do the Data Tell Us?

Dimitri Demekas Chief, Southeastern I Division

International Monetary Fund

PRELIMINARY DO NOT QUOTE

COMMENTS WELCOME



Dimitri G. Demekas, Balázs Horváth, Elina Ribakova, and Yi Wu1

International Monetary Fund

Authors’ email addresses: [email protected] [email protected] [email protected] [email protected]

1 The views expressed in this paper are those of the authors and do not necessarily represent those of the IMF or IMF policy. Excellent research assistance by Madhuri Edwards is gratefully acknowledged, without implication.

FDI in Southeastern Europe: What do the data tell us?



Dimitri Demekas, Balázs Horváth, Elina Ribakova, and Yi WuInternational Monetary Fund

“Southeastern European Challenges and Prospects”, Vienna, November 28-30, 2004



Prosknowledge/technology transferproductivity spilloversenhanced competition improved access to export markets non debt-creating external financing high productivity jobs

Consabuse of dominant market powerattempts to influence domestic politics“beggar thy neighbor”through incentiveslarge and volatile BoP outflows

Impact of FDI: old controversies live on...


...but in transition economies, the pros are compelling

Need for extensive enterprise restructuring and technological upgradingReliance on foreign savings and emerging market crises put premium on non debt-creating flows



Determinants of FDI: What do we know?

There is consensus on some explanatory variables:“Gravity” factors (proximity, market size)Factor endowments (infrastructure, human capital)

Other variables have significant but ambiguous effects:Barriers to trade (tariffs, NTBs, transport costs) stimulate horizontal FDI and thwart vertical FDIRegional integration has the opposite effect


Determinants of FDI (cont.)

The evidence on some further variables is inconclusive:Tax policies and tax incentives (but more recent research strengthens the evidence in favor)Labor costs (but this may reflect measurement problems)Agglomeration and herding




The facts for SEEs and comparisons with CEEs

The findings of the empirical research on determinants of FDI in the region

Survey of 20+ papers with original empirical research on CEEs—but only 3 cover SEEsOur own econometric investigation (D-H-R-W), based on a bilateral FDI database between 22 source and 16 host CEE/SEEs for 2000-02

Conclusions and areas for further research




Stock of FDI and Privatization Receipts, 2003(In millions of U.S. dollars)

ROM

BGRHRV SVK

SVN EST LTUYUGLVA BIH ALBMKDMDA

CZEHUN

POL

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

Sources: The Vienna Institute for International Economic Studies (WIIW), Gábor Hunya, "FDI in South-Eastern Europe in the early 2000s" and "Foreign Direct Investment in South East Europe in 2003-2004;" and UNCTAD database.



FDI clusters in CEEs and SEEs(logs of rank and total FDI in US$ billion)

POL

HUN

CZE

ROMHRVSVK

BGRSVN

ESTLTUSMLVABIHALBMKDMDA

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

2.5 3.0 3.5 4.0 4.5 5.0



0

1,000

2,000

3,000

4,000

5,000

HUN CZE EST HRV SVN SVK PLN LVA LTU BGR ROM MKD ALB SM BIH MDA

FDI per capita(End-2003 stock, US$)



Top 5 source countries (end-2001 stock, US$)

Source: WiiW.

1/ Data for Serbia and Montenegro refer to cumulated inflows 1996-1998.

ALB

ITA

GRC

MKD

TUR

FRA

0

1000

2000

3000

4000

5000

BiH

AUS

HRV

DEU

SVN

KWT

0

100

200

300

400

500

BGR

GRC

DEU

ITA

AUS

USA

0

200

400

600

800

1000

HRV

AUS

DEU

USA

HUN

NLD

0

500

1000

1500

2000

2500

MKD

HUN

GRC

CYP

CHE

GBR

0

100

200

300

400

MDV

RUS

ESP

USA

NLD

CHE

0

40

80

120

160

ROM

FRA

DEU

USA

ITA

NLD

0

500

1000

1500

2000

SCG1/

GRC

DEU

ITA

USA

Russ

ia

050

100150200250300350400450500



Econometric investigation

Panel regressions for bilateral FDI flow (average 2000-02) and stock (2002)

Panel regressions for aggregate FDI stock and flow for the period 1997-2003



Explanatory variables in D-H-R-WSize ProximityGDP Bilateral distancePopulation Cultural link (dummy)

Trade liberalization Labor costBilateral investment agreements Average gross US$ wage Non-tariff barriers Productivity-adjusted wageTrade restrictiveness index (IMF)Tariff revenue to GDP ratio Tax systemAverage tariff rate Corporate income tax rate

Corporate income tax % GDP Institutional variables Free economic zones (dummy)Average bribe tax in % of firm revenue Indirect tax exemptions (dummy)EBRD transition index Tax holidays for investment (dummy)% of firms making bribes frequentlyTransparency International (TI) index Infrastructure qualityWorld Bank governance index Days of power outagesEU candidate/member status EBRD's infrastructure index



● = Highly significant ○ = Sometimes significant or ambiguous sign

Other empirical ● ● ● ○ ● ○ ○ ● studies on SEEs1/1/ Bevan & Estrin (2000); Brenton et al. (1999); Campos & Kinoshita (2003); Carstensen & Toubal (2003); Christie (2003); Deichmann (2001); Holland & Pain (1998); Janicki & Wunnava (2004); Resmini (2000).

FDI determinants in SE EuropeSize Distance Trade- Liberal Labor Business Infra- Institutions

from to-GDP trade cost tax structure (incl. EU)host ratio regime burden

D-H-R-W ● ● ○ ○ ● ● ○



Main conclusions

Results are robust to various specifications (bilateral-aggregate, stocks-flows) Gravity variables (size and proximity) have major explanatory powerQuality of infrastructure and business tax burden also important for FDIThe impact of trade policy and governance is weak



Impact of corporate tax burden on bilateral FDI flows

-50

5e(

lfdi

bf |

X )

-4 -2 0 2 4 6e( tax | X )

coef = -.10008985, (robust) se = .04409653, t = -2.27



Impact of infrastructure quality on bilateral FDI flows

-50

5e(

lfdi

bf |

X )

-.5 0 .5e( infra0002 | X )

coef = 1.3388429, (robust) se = .71836523, t = 1.86



Trade Restrictiveness

Source: IMF,Trade Restrictiveness Database.1/ Average of all tariff lines, including other duties and charges.

Trade Restrictiveness Ratings, 2003

HUN

SVN

YUG

ROM

BGR

MKD

POL

ALB

BIH

HRV

CZE

EST

LVA

LTU

MDA

SVK

0

1

2

3

4

5

6

Average Tariff, 2003 1/RO

MMK

DPO

LHU

NBG

RSV

NYU

GBI

HAL

BHR

VMD

ACZ

ESV

KLT

ULV

AES

T

0

2

4

6

8

10

12

14

16

18



Areas for further investigation

Feedback/persistence effects could explain the emergence of “leaders” and “laggards” among host countries Threshold effects in attracting FDIDistinguishing between “exogenous” and “policy”factors could give insights into the potential of SEEsto attract additional FDI

Explanatory variables in D-H-R-W

Variable Source

FDI bilateral flowsOECD; data from national statistics offices and central banks; Hunya (2004)

FDI stocksOECD; data from national statistics offices and central banks; Hunya (2004); and estimates based on cumulated flows

Market size GDP IMF databasePopulation IMF database

Geographic/cultural proximityBilateral distance (capital to capital) Distance between capitalsCultural link dummy Staff estimate

Wage costsAverage gross wage IMF databaseProductivity adjusted wage IMF database

Trade liberalizationBilateral investment agreement dummy UNCTADNon-tariff barriers IMFTrade restrictiveness index IMFTrade revenue to GDP Government Finance Statistics, IMF Trade tariff rate IMF

Tax systemCorporate Income Tax rate CEEBIC; Heritage Foundation; and KPMG.Corporate Income Tax revenue to GDP GFS, SRs

Free economic zonesPWC, various editions, International Bureau of Fiscal Documentation (IBFD), various editions

Tax holidays PWC, various editions, IBFD, various editions

Infrastructure qualityDays of power outages World BankEBRD's infrastructure reform index EBRD transition report

Institutional variablesAverage bribe tax as a percent of annual firm revenues EBRD transition reportEBRD transition index EBRD transition reportPercentage of firms making bribes frequently EBRD transition reportTransparency international corruption index Transparency InternationalWB governance index World Bank

Feedback/persistence effectsLagged FDI stock

Table 1: Bilateral FDI Regressions Dependent variable: log(bilateral FDI), average flows for 2000-02 or 2002 stock)

Flows Flows Flows Stock Corporate tax rate -0.092** -0.090** -0.082* 0.021 (0.044) (0.045) (0.045) (0.035) Tax incentives 0.114 (0.383) Corruption (TI index) 0.275 0.381 0.269 0.584*** (0.219) (0.333) (0.225) (0.222) Tariff rate 0.004 0.001 0.004 -0.011 (0.039) (0.042) (0.039) (0.039) Non-tariff barriers -1.264*** -1.051* -1.206*** -0.483 (0.367) (0.608) (0.383) (0.406) EBRD infrastructure 1.432** 1.384* 1.421** 1.485** index (0.704) (0.709) (0.709) (0.582) Log (unit labor costs) -0.946* -0.769 -0.842 -0.243 (0.525) (0.595) (0.673) (0.431) Log (GDP) 0.396* 0.347 0.401* 0.643*** (0.233) (0.242) (0.231) (0.196) Bilateral investment 0.025 0.025 0.037 0.347 agreements (0.299) (0.301) (0.293) (0.295) Log (distance) -2.458*** -2.435*** -2.455*** -2.390*** (0.379) (0.380) (0.381) (0.404) Cultural proximity dummy 1.026** 1.045*** 1.035** 1.303*** (0.400) (0.398) (0.406) (0.440) EU members/candidates 0.481 dummy (0.968) R-squared 0.67 0.67 0.67 0.71 No. of obs. 179 179 179 202

Notes: 1. Source countries: EU15 plus the U.S., Switzerland, Russia, Poland, Hungary, Cyprus, Croatia, Slovenia, and Czech Republic. Host countries: Albania (for stock regression only), Baltic countries (as one unit), Czech Republic, Hungary, Poland, Slovak Republic, Slovenia. Bulgaria, Croatia, Moldova, Macedonia, Romania, Serbia & Montenegro (for stock regression only). 2. *, **, *** represent significant at 10, 5, and 1% respectively. A source country dummy is included in all regressions. 3. All explanatory variables are averaged over 2000-2002 when data are available. 4. Unit labor costs are calculated as the ratio of wage rates to GDP per capita. 5. Tax incentives include tax holidays, accelerated depreciation, and investment credits.

Table 2: Aggregate FDI panel regressions (1997-2003)

Stock Stock Stock

Fixed effects Random effects

Random effects

Corporate tax revenue/GDP 0.009 0.088 0.093

(0.087) (0.070) (0.072)

Quality of governance -0.916** -0.251 -0.357

(0.455) (0.224) (0.259)

Tariff rate -0.051** -0.043*** -0.037**

(0.021) (0.015) (0.017)

Non-tariff barriers 0.208 0.043 0.040

(0.214) (0.154) (0.157)

EBRD infrastructure index 0.994*** 0.908*** 0.949***

(0.181) (0.155) (0.164)

Log (unit labor costs) -1.083 -0.591* -0.614*

(0.672) (0.318) (0.328)

Log (GDP) 0.697 0.774*** 0.723***

(0.453) (0.111) (0.132)

Log (weighted distance to -2.094

FDI source countries) (2.553)

R-squared 0.88 0.94 0.94

No. of obs. 72 72 72

p-value for Hausman test 0.26 0.29

1. Countries included in the regressions: Albania, Bosnia and Herzegovina, Baltic countries (as one unit), Czech Republic, Hungary, Poland, Slovak Republic, Slovenia. Bulgaria, Croatia, Moldova, Macedonia, Romania, Serbia and Montenegro. 2. *, **, *** represent significant at 10, 5, and 1% respectively. 3. The null hypothesis for Hausman test is that difference in coefficients between fixed effects and random effects specifications are not systematic. Thus a small p-value suggests the rejection of random effects specification. 4. Bilateral distance to source countries (as specified in the bilateral regressions) are weighted by source countries’ GDP to calculate the weighted distance.

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