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FDI DeterminantsN S Siddharthan

Lecture Notes

FDI Paradox

FDI Paradox

More than 60% FDI inflow to Developed Countries2006 66%

Technology Transfer

88% of Royalty Payments Among Developed CountriesLess Developed Countries get less FDI and Technology

Table 1: FDI stock by region (in million US $) 1990 2000 2007

FDI inward stockWorld 1941252 5786700 15210560

Developed economies1412605

(72.8)3987624

(68.9)10458610

(68.8)

Developing economies528638(27.2)

1738255(30.0)

4246739(27.9)

China20691(1.1)

193348(3.3)

327087(2.2)

India1657(0.1)

17517(0.3)

76226(0.5)

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Table 2: FDI Flows by region (in million US $)

2005 2006 2007

FDI inflow

World 958697 1411018 1833324

Developed economies611283(63.8)

940861(66.7)

1247635(68.1)


412990(29.3)

499747(27.3)

Asia210026(21.9)

272890(19.3)

319333(17.4)

China72406(7.6)

72715(5.2)

83521(4.6)

India7606(0.8)

19662(1.4)

22950(1.3)

FDI outflowWorld 880808 1323150 1996514

Developed economies748885(85.0)

1087186(82.2)

1692141(84.8)


212258(16.0)

253145(12.7)

Asia79412(9.0)

141105(10.7)

194663(9.8)

China12261(1.4)

21160(1.6)

22469(1.1)

India

2978

(0.3)

12842

(1.0)

13649

(0.7)Note: percentage share of the FDI inward and outward flow to the world total is given inthe parenthesisSource: UNCTAD (2008)

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OWNERSHIP ADVANTAGES

INTANGIBLE ASSETSTechnology

R&DPatents

Brand NameGoodwill

SkillMarketing

Management

TransferMarket or FDI

INTERNALISATION ADVANTAGES

Transaction Costs

Information AsymmetryEvolving Technology

Tacit NatureBrand Names

Goodwill

Appropriability

External Economies

Intra-firm Trade

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FDI LOCATION ADVANTAGES

MARKET SEEKING

Size, Income and Growth RateMembership of Regional Union

EFFICIENCY SEEKING

Cost: Labour and Skill(In empirical studies cheap labour has not emerged significant)

Infrastructure: Transport, Telecommunications, Electricity, Port facilitiesCustoms, Legal Dispute Settlements, Rule of Law

OTHER LOCATION ADVANTAGESTechnological Status

Brand Name and Goodwill of Local FirmsOpenness of the Economy (This has also not emerged important)

Trade Macro Policies of the GovernmentIPR ( In studies this variable is also unimportant)

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Dunning (1980) JIBS

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Important Studies

Caves, R.E.(1974). "Causes of Direct Investment: Foreign Firms' Share inCanadian and UK Manufacturing Industries", Review of Economics and Statistics, 56,

272-93.Hypothesis

Intangible Capital

Product differentiation differentiated oligopoly entry barriers

Relevant source of Intangible capital home of MNCs

Multiplant Enterprise

Entrepreneurial Resources

Outlet for underutilised entrepreneurial resources; Servan-Schreiber 1968; FDImore prevalent in industries requiring higher entrepreneurial skills NP, Wage rate.

Diseconomies of ScaleDeterminants of foreign firms shares, UK manufacturing industries

FS FS FSConstantt value

-0.330-3.09

-3.50-0.367

-0.354-2.96

MP 0.0830.713

0.0720.632

0.2201.61

AD 2.544.51

2.824.09

ADB 1.784.03

RD 3.752.94

3.392.48

DSB 0.2493.81

0.3134.71

0.2273.13

NR -0.027-1.23

-0.019-1.25

VW -0.016-0.485

R2 0.581 0.501 0.469

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MP, Percentage of shipments in the US industry accounted for by multiplant firms.AD, Advertisement as a percentage of salesDSB, value added per worker in the largest plants accounting for 50% of net output,divided by the value added per worker in the smallest plant accounting for the other 50%.NR, Royalty receipts of the UK industry divided by payments of royalties by the

industry.VW, value added per worker in UKLall,S. and Siddharthan,N.S. (1982): "The monopolistic advantages of multinationals:Lessons from foreign investment in the US", Economic Journal, 92, 668-683.Hypothesis

Strong US bias in existing studies

Implicit assumptions not valid Ref. Host countryCourse of innovation different for US and EuropeDifferences in technological and marketing strengthsOther countries have specialised areas of strength

Can the usual variables explain FDI in US a leader in Prod.diff

Intangible assets: AD R&D SKILL SIZE not important

MP likely to be importantOligopolistic interaction

ProtectionDeterminants of foreign share in US manufacturing

FS FS FS FS

Constant -4.456 -0.513 -14.534 -4.469***

RD -0.193 -0.010

AD 0.103 0.076

CR -0.532 -0.612* -0.624

MP 2.089*** 2.128*** 2.632*** 2.252***

AW 0.555 1.072

NP 1.145 0.853

Scale -0.475*ConD 0.146

EP 0.452*** 0.432*** 0.435*** 0.444***

R2 0.464 0.452 0.448 0.438

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Chen, Shih-Fen S, (2010), A general TCE model of internationalbusiness institutions: Market failure and reciprocity, Journal ofInternational Business Studies, 41, 935-959

Developer-manufacturer cooperation:Integrated Circuits (IC): Designed by one firm and are usually fabricated by another firm.They could also be located in two different nations. Other examples engine

manufacturer and automobile assemblers.As long as the customer possesses sufficient information to hold the design house and thefabricator separately responsible for the value of their respective outputs, the twospecialists can co-market the IC to this common customer while keeping an arms lengthdistance from each other, an institutional mode that I call arms length co-marketing.The two parties must keep a contractual relationship to smooth out the design/fabricationinterface so that they can co-market their joint output to a common customer underperformance inseparability, another institutional mode called contractual co-marketing.

Single party marketing: Technology licensing and sub-contract manufacturing (Productsourcing).

Investment Climate and FDI

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Batra, Geeta; Daniel Kaufmann and Andrew H. W. Stone (2003): InvestmentClimate Around the World: Voices of the Firms from the World Business

Environment Survey, The World Bank, Washington DC. i-ix, 1-154.It uses a uniform core questionnaire for enterprises in eighty countries and as stated in its

introduction it provides a basis for inter country comparisons of investment climate andbusiness environment conditions, and comparisons of the severity of constraints thataffect enterprises.It also permits some evaluation of conditions in specific countries.It captures companies perceptions of key constraints in the business environment perceptions that shape operational and investment decisions as well as severalquantitative indices of companies experiences

General Constraints to Operation and Growth

Country/Variables India China Malaysia Thailand Singapore

Corruption 60.43 31.25 22.73 87.06 8.00

Judiciary 29.12 13.83 21.35 25.00 9.09

Financing 52.13 80.20 41.05 75.24 30.30

Infrastructure 61.98 30.69 19.79 64.89 11.00

Policy Instability 62.96 41.00 27.37 90.85 11.00

Inflation 67.91 42.42 39.26 90.59 12.00

Exchange Rates 42.77 21.74 28.26 94.77 26.00

Street Crime 22.91 18.18 18.48 92.59 6.00

Organised Crime 21.84 19.59 14.61 100.00 10.10

Anti CompetitivePolicies

na 38.78 27.27 95.40 20.62

Taxes andRegulations

39.23 28.71 20.43 84.25 11.00

Note: na refers to not asked.

Tax and Regulatory ConstraintsCountry/Variable India China Malaysia Thailand Singapore

BusinessRegistration

26.18 27.72 27.55 26.92 9.28

Customs 50.27 21.05 29.89 47.64 10.75

Labour 63.68 16.00 42.71 53.98 24.00

ForeignCurrency

34.95 14.63 29.67 42.44 9.28

Environmental 40.64 19.79 26.88 42.07 5.10

Fire 19.58 14.43 17.53 33.73 5.00

High Taxes 67.86 50.00 36.17 80.91 31.96

Tax 41.15 30.00 20.83 69.93 12.00

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Administration

Obstacles to Firm FinancingCountry/Variable India China Malaysia Thailand Singapore

Collateral 50.53 20.20 41.49 49.35 29.17Bank Paperwork 50.53 29.00 32.99 44.61 21.65

High Interests 81.18 35.35 52.58 84.24 32.99

SpecialConnections

34.97 25.53 34.74 51.24 18.75

Banks FundShortage

18.48 37.00 20.22 79.39 3.23

Access toForeign Banks

22.03 17.14 14.29 71.67 5.43

Access to Non-Banks

23.98 12.79 15.19 61.90 11.24

Access to ExportFinance

25.61 21.33 14.71 64.84 10.11

Access to LeaseFinance

20.59 22.47 7.69 60.61 8.70

Access to Credit 32.12 44.44 21.84 75.34 13.04

Percentage of Firms Rating the Quality of Services as Bad

Country/Variables India China Malaysia Thailand Singapore

Customs 40.00 14.29 11.59 28.76 1.09

Courts 28.34 20.55 29.51 20.26 0

Roads 68.53 22.47 21.11 40.00 0

Postal na 11.46 8.60 6.31 0

Telephone 26.24 14.14 7.29 15.89 0

Power 40.30 14.74 7.29 17.52 2.02

Water 29.63 12.64 14.58 20.42 0

Health 48.17 30.77 14.46 28.42 2.06

Military 8.94 Na 15.63 19.86 1.10

Government 40.35 Na 17.78 39.59 1.16

Parliament 60.24 Na 25.00 45.17 1.16

Central Bank na 15.58 10.45 43.90 1.11

Wei, Shang-jin (2000). How taxing is corruption on international investors?, TheReview of Economics and Statistics, 82(1), 1-11.

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Analyses the determinants of the bilateral stocks of FDI from 12 source countries to 45host countries. The source countries include the US, Japan, Germany, UK, FranceCanada and Italy.Following explanatory variables are used: tax rate, corruption, tax credit, political

stability, GDP, population, distance between the two countries, linguistic ties betweencountries and wage rates.Dep.Var. Inward FDICorruption and FDI: Tobit model

Equations 1 2 3 4 5

Tax rate -2.39** -2.57** -2.61 -3.51** -3.66**

Corruption -0.18** -0.18** -0.16** -0.11** -0.10**

Tax credit 0.75 0.71 0.83 0.84

Pol.Stabi 0.13** 0.20** 0.17**logGDP 0.39** 0.39** 0.32** 0.02 0.04

LogPOP 0.20** 0.20** 0.26** 0.56** 0.63**

LogDIST -0.30** -0.29** -0.29** 0.28** 0.27**

LANG-TIE 0.33** 0.33** 0.27* 0.31* 0.33**

OECD 0.50**

Log wage 0.35** 0.42**

OECD*Lwage -0.19*

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Globerman, Steven and Daniel Shapiro (2002), Global foreign direct investmentflows: The role of governance infrastructure, World Development, 30(11),1899-1919.

FDI Inflows averaged 1995-97GDP Real GDP average 1994-96HDI combines GDPCI, EDUCI & LIFEI ave. 1995-97GDPCI GDP/capita indexEDUCI Combining adult literacy, primary and sec enrollment rates.LIFEI Life expectancy at birthGII First principal component of LAW, INSTAB, REG, GOV, GRAFT, VOICELAW Rule of law indexINSTAB Pol.instability and violence indexREG Regulatory burden indexGOV Govt effectiveness indexGRAFI Corruption index

VOICE Voice and accountability

All Ln FDI All Ln FDI LDC Ln FDI LDC

Ln GDP 0.826***(0.080) 0.764***(0.062) 0.903***(0.093) 0.845***(0.078)

HDI -0.374 (0.881) -0.328 (0.850)

EDUC 1.190**(0.556) 1.183***(0.570)

GII 2.803***(0.735) 0.969***(0.219)

REG 1.101***(0.156) 1.080***(0.173)

Ln x GDP xGII -0.124**(0.062)

Constant -2.26***(0.644) -2.98***(0.549) -2.98***0.732) -3.698***(0.70)

R2 0.73 0.78 0.61 0.68

NOBS 144 144 115 115

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Cuervo-Cazurra, Alvaro (2006). Who cares about corruption?, Journal of

International Business Studies, 37(6), 807-822.

Corruption results not only in a reduction in FDI but also in a change in thecomposition of country of origin of FDI.

Two cases: (1) FDI from countries that have signed the OECD convention ofcombating bribery of foreign public officials in international businesstransactions and (2) FDI from countries with high levels of corruption.

Relationship between corruption and FDI in modified by the country of originof FDI.

Corruption in the host country results in relatively less FDI from countries thathave signed the OECD convention, but in relatively more FDI from countries

with high levels of corruption.Corruption indicators taken from World Bank publications.Variables

Dependent variable:Ln FDI Inflows (FDI) Natural log of FDI inflows into the country in the year in US $Independent VariablesHCC, Host country corruption 0-5 (0 low)OECD Country

HCHC, home country with high corruption 1-0 variableControl VariablesLn GDP, Population, In Distance, Landlocked (0 none, 1 one of the countries, 2 bothcountries), Island (0,1,2), CB (Common Border, dummy), CL (common language,dummy), CC (Common colony, dummy), ECL (ever colonial line, dummy), Rtrade(restrictions on trade 1 low 5 high), RFDI (restrictions on FDI 1 very low 5 high).

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Tobit model

OECD x HCC -0.323**

HCHC x HCC 0.460**

HCC -0.345*** -0.170

Ln GDP 0.480*** 0.473***Population 0.008*** 0.008***

Ln Distance -0.833*** -0.756***

Landlocked -0.039 -0.112

Island -0.479* -0.515**

CB 0.709** 0.543*

CL 0.542** 0.602**

CC -0.197 -0.281

ECL 0.714** 0.676**

RFDI -0.218* -0.244*

RTrade 0.027 0.030

Log Likelihood -1881.763 -1776.249

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Regional Differences in FDI Inflows: China India Comparison

The inter country studies on the determinants of FDI inflows show theimportance of governance factors in influencing investments.

The results further indicate that tax and other fiscal concessions alone cannotattract FDI. Role of good governance in attracting FDI to different states and provinces

within a country. Inter-state/province differences in governance is captured byvariables representing physical infrastructure like roads, electricity andtelecommunications, expenditures on social services like health, education andsanitation, and variables representing the impact of these expenditures like,percentage of children going to middle schools, life expectancy and otherrelated measures. For this purpose this paper considers China and India ascase studies.

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China: Share of Regions in FDIProvince FDI FDI% Province FDI FDI%

2003 2003 2003 2003

Beijing 219,1264.10%

Henan 53,903 1.01%

Tianjin 153,473 2.87% Hubei 156,886 2.93%

Hebei 96,405 1.80% Hunan 101,835 1.90%

Shanxi 21,361 0.40% Guangdong 782,294 14.62%

Inner Mongolia 8,854 0.17% Guangxi 41,856 0.78%

Hainan 42,125 0.79%

Liaoning 282,410 5.28%

Jilin 19,059 0.36% Chongqing 26,083 0.49%

Heilongjiang 32,180 0.60% Sichuan 41,231 0.77%

Guizhou 4,521 0.08%

Shanghai 546,849 10.22% Yunnan 8,384 0.16%

Jiangsu 1,056,365 19.74% Tibet 0 0%

Zhejiang 498,055 9.31% Anhui 36,720 0.69% Shaanxi 33,190 0.62%

Fujian 259,903 4.86% Gansu 2,342 0.04%

Jiangxi 161,202 3.01% Qinghai 2,522 0.05%

Shangdong 601,617 11.24% Ningxia 1,743 0.03%

Xinjiang 1,534 0.03%

Regional Total 5,294,028 98.95%

FDI in US$10,000

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India: Share of States and Union Territories in FDI and Industrial Output

2004

FDI

Approvals FDI %

%Gross ValueAdded by

IndustryState/UT (in Rs. 10 mil) Andhra Pradesh 11658.71 4.61 7.03

Assam 2.41 0.001 0.67

Bihar 739.71 0.29 0.42

Gujarat 12748.98 5.04 13.42

Haryana 3928.34 1.55 4.48

Himachal pradesh 1226.64 0.48 0.87

J& K 8.41 0.003 0.12

Karnataka 19202.55 7.60 6.71

Kerala 1812.45 0.72 2.20

Madhya Pradesh 9271.41 3.67 4.02

Maharashtra 37250.67 14.75 19.71

Orissa 8235.45 3.26 1.52

Punjab 2213.65 0.88 3.50

Rajasthan 2911.21 1.15 3.35

Tamil Nadu 22872.18 9.06 9.94

Uttar Pradesh 4846.22 1.91 6.93

West Bengal 8016.87 3.17 4.39

Delhi 30843.14 12.21 1.33Goa 999.38 0.40 1.03

Pondicherry 1286.21 0.51 0.95

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Regional Distribution of FDI in India

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Regional Distribution of Industrial Output in India

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China: Per capita foreign direct investment inter province differences (2003)PCFDI PCTRADE SS PCY PCELEC FREIGHT

Shanghai 319.61 6459.1444 5.53 46718 0.44 8492.3

Tianjin 151.762969.4848

6.79 26532 0.30 6521.1

Beijing 150.46 2151.4769 9.98 32061 0.32 462.5

Jiangsu 142.64 1637.6835 3.41 16809 0.20 1772.6

Zhejiang 106.43 1417.1890 4.22 20147 0.26 2047.2

Guangdong 98.35 3636.1823 5.63 17213 0.26 3158.0

Fujian 74.51 1105.5797 4.23 14979 0.17 1222.9

Liaoning 67.08 709.2962 6.43 14258 0.22 2385.2

Shangdong 65.93 541.4922 2.93 13661 0.15 3908.9

Hainan 51.97 235.8375 4.48 8316 0.07 250.7

Jiangxi 37.89 69.5035 2.45 6678 0.07 768.6

Hubei 26.14 96.7777 4.09 9011 0.10 1212.6

Hunan 15.28 70.5251 4.18 7554 0.08 1350.6

Hebei 14.24 143.0825 2.51 10513 0.16 3223.2Shaanxi 8.99 96.3463 3.13 6480 0.11 849.1

Guangxi 8.62 66.3306 2.42 5969 0.09 863.4

Heilongjiang 8.44 162.9132 3.36 11615 0.13 991.4

Chongqing 8.33 81.7658 6.44 7209 0.09 367.7

Jilin 7.05 248.9266 2.57 9338 0.13 531.0

Shanxi 6.45 156.2705 2.74 7435 0.22 1 259.1

Anhui 5.73 88.5333 3.26 6455 0.07 1 328.6

Henan 5.58 57.7483 3.07 7570 0.11 1 891.6

Sichuan 4.74 66.4326 3.36 6418 0.09 768.3

Qinghai 4.72 64.2131 2.59 7277 0.28 124.2

Inner Mongolia 3.72 135.5818 2.99 8975 0.18 1 160.3Ningxia 3.00 128.3198 2.29 6691 0.37 244.5

Yunnan 1.91 62.1640 2.57 5662 0.08 612.2

Guizhou 1.17 40.1440 3.02 3603 0.10 547.0

Gansu 0.90 49.6327 1.78 5022 0.15 738.7

Xinjiang 0.79 251.0209 3.10 9700 0.12 636.6

Source: www.stats.gov.cn/english/statisticaldata/yearlydata/Note:PCFDI, per capita foreign direct investment flows, FDI in UD$10,000 and population in10,000 persons.PCTRADE, total exports and imports in US$10,000.

SS, expenditure on social services..PCY, per capita income, gross regional product in 100 million yuan and population in10,000 persons.PCELEC, per capita electricity consumption by region in 100 million kws. andpopulation in 10,000 persons.FREIGHT, fright 100 million ton-KM. by region total of roads and railways andwaterways.

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China: determinants of inter-province differences in FDI (2000-2003)Generalised Least Square estimates (with cross-section weights, corrected for

heteroskedasticity)

Dep. Variable: Per capita FDI

Variable Coefficient t Stat

Constant -13.81819*** -17.62173

Per capita trade 0.035120*** 11.50093

Social Security 2.084534*** 13.43053

Per capita income 0.001635*** 8.607487

Freight 0.003469*** 5.648421

NOBS 120 (4 years * 30regions)

R2 (weighted) 0.8856***

*** significant at 1% level.

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India: Per capita foreign direct investment inter-state differences

PCFDI SEI HDIEDEN

R PCY URBPP PCELECPCIND

O PCYCP TELE

LIFEEX

Maharashtra 362.8924 112.80 0.523 87.55 29204 42.40 17281.78 19470 16050 9.498 66.2

Tamil Nadu 353.8177 149.10 0.531 100.41 23358 43.86 19447.53 16763 13423 10.911 65.2

Karnataka 346.4661 104.88 0.478 76.20 21696 33.98 8334.04 8829 11799 11.803 64.5

Orissa 216.9032 81.00 0.404 54.01 12388 14.97 7816.70 3628 6427 3.646 58.5

Gujarat 211.3817 124.31 0.479 70.40 26979 37.35 12097.61 25496 16779 12.065 63.4

Haryana 174.9299 137.54 0.509 65.51 29963 29.00 8969.80 21391 15721 10.163 65.2

Andhra Pradesh 146.8943 103.30 0.416 64.86 20757 27.08 16182.17 8161 11333 9.185 63.5

Madhya Pradesh 145.5653 76.79 0.394 63.30 14011 26.97 12163.07 6150 8284 4.830 56.9

West Bengal 93.7230 111.25 0.472 64.28 20896 28.03 7649.71 4914 10952 2.776 63.9

Punjab 84.3017 187.57 0.537 60.06 27851 33.95 7969.17 14530 15800 21.861 68.5

Kerala 54.4352 178.68 0.638 93.64 24492 25.97 6553.02 8424 12109 17.846 73.5Rajasthan 48.8218 75.86 0.424 61.54 15486 23.38 10521.79 5507 8571 5.777 61.1

Uttar Pradesh 27.5089 101.23 0.388 48.64 10817 20.78 22439.20 3948 5610 3.882 59.1

Bihar 8.4865 81.33 0.367 25.33 5780 10.47 5456.02 883 3707 2.014 60.8

Assam 0.0535 77.72 0.386 56.22 13139 12.72 2510.63 3313 6520 2.706 57.9

Source: www.indiastat.comNotes:PCFDI, per capita stock of FDI approvals since 1991 (liberalisation). FDI figures are inRupees ten million. and population figures are in million persons.SEI, socio economic index presented by the government.HDI, human development index prepared by the government.

EDNER, enrolment ratio in schools in the age group 11 14 years.PCY per capita income at current prices.URBPP, percentage of urban population in total population.PCELEC, gross annual per capita consumption of electricity.PCINDO, per capita gross industrial output in rupees.PCYCP, per capita income at constant prices.TELF, Overall teledensity.LIFEEX, life expectancy at birth.

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India: determinants of Inter-State differences in FDI (2000-2004)

Generalised Least Square estimates (with cross-section weights, corrected for

Heteroskedasticity)

Dep. Variable: Per capita FDI

Variable Coefficient t Stat

Constant -383.7504*** -5.268220

Socio-Economic Index -3.224413*** -8.869783

Education-Enrolment 0.954087*** 3.688089

% of Urban Population 10.99286*** 20.22645

Per capita Industrial Output 0.004445*** 14.84318

Tele density 3.358361*** 2.829902

Life expectancy 7.293228*** 4.204932

NOBS 75(years 5 andStates 15)

R2 (weighted) 0.9887***

*** significant at 1% level.

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FDI From Developing CountriesSumon Kumar Bhaumik, Nigel Driffield and Sarmistha Pal (2010), Doesownership structure of emerging-market firms affect their outward FDI? The case

of the Indian automotive and pharmaceutical sectors, Journal of InternationalBusiness Studies 41, 437450Our results suggest that family firms and firms with concentrated ownerships (bothubiquitous in emerging markets) are less likely to invest overseas, and that strategicequity holding by foreign investors facilitates outward FDI.Our data are drawn from two industrial sectors, pharmaceuticals and automotives.During 20002006 these two sectors accounted for nearly 30% of acquisitions ofoverseas assets by Indian firms, jointly tying for first place with the much-discussed ICTsector.

Family firms tend to be more reluctant to subject themselves to the external scrutiny ofregulators, investors, creditors and credit-rating agencies. This aversion to scrutiny maydeter them from undertaking outward FDI, a process that would require them to accesscapital markets and subject themselves to due diligence and regulatory scrutiny.On the other hand, however, outward FDI might actually be preferred, because it canfacilitate expropriation through mechanisms such as transfer pricing.Family firms are heterogeneous. Hence, even as family controlled

firms such as LG, Hyundai, Honda and Mitsubishi feature prominently in the globalleague tables on outward FDIData are taken primarily from OrbisInformation on 196 automotive firms and 581 pharmaceutical firms of Indian ownership.Of these, 80 automotive sector firms (41%) and 44 pharmaceutical sector firms (7.5%)report ownership of assets outside India.The data coverage is from 2000 to 2006, resulting in 5410 firmyear observations.Supplement the Orbis data with additional ownership information obtained from theProwess database and Capital Line.

The dependent variable: the proportion of a firms assets that are held overseas (FDI).Independent Variables:FAM takes the value 1 if a family is the single largest shareholder in a firm.BGR, which takes the value 1 when a firm is affiliated to a businessgroup.

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SHARECON, the Herfindahl index for all shareholdings,F10 and F25, each a binary variable. These capture 10% and 25% ownership of sharesby foreign investors, respectively.

Two interaction terms, I1 and I2, between foreign ownership (F10, F25) and familyownership (FAM or BGR).We control for a number of firm-level characteristics.These are sales (SALES) and age (AGE) of a firm, the ratio of internal accrual of a firmto its total cash flow (CASH), the number of Indian subsidiaries (INDSUB), the ratio ofintangible assets to total assets (INTAN), the debt-to-equity ratio (TDTA) and return onassets (PROFIT).

Pradhan, Jaya Prakash and Singh, Neelam (2010), Group Affiliation and Locationof Indian Firms' Foreign Acquisitions, Online at http://mpra.ub.uni-muenchen.de/24018/MPRA Paper No. 24018, posted 21. July 2010 / 05:50

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