Internationalisation of State Owned Enterprises: An Institutional View

Saul EstrinDepartment of ManagementLondon School of Economics

Presentation for UCL Workshop, ‘Transition Economics meets New Structural Economics’, June 25/26 2013

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• Paper joint with:

• Klaus Meyer, CEIBS, Shanghai, China• Bo Nielsen, Copenhagen Business School• Sabina Nielsen, Copenhagen Business School

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Outline• Theoretical framework

• State ownership and internationalisation• Benevolent( “Helping hand”) and non-benevolent (“grabbing hand”)

managerial motives • Institutions and State ownership

• Hypotheses• Informal institutions• Formal institutions• Governance

• Data• Results• Conclusions

Outward FDI Flows Worldwide 1970 - 2010

[Source: Created based on data obtained from UNCTAD FDI database]

1980 1985 1990 1995 2000 2005 20100%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

Developed

NIE

Other Emerging

BRICS

1980 1985 1990 1995 2000 2005 20100%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

FDI Stock 1980 to 2010Other Emerging

South Africa

Russia

India

China

Brazil

Taiwan (RoC)

Singapore

Korea (Rep)

Hong Kong

Other developed

Japan

France

Germany

UK

USA

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State Ownership and Internationalisation

• Theories of internationalisation focus on firm specific resources and capabilities• As share of FDI from developed economies declines, increasing

heterogeneity of organisation forms and ownership; i.e. state ownership of enterprises (SOEs)

• Research question: How does state ownership impact on firm’s internationalisation? – SOEs differ from private firms in objectives, attitudes to risk and access to

resources– Impact of these differences influenced by specifics of local institutional

environment.– Build on Williamson, 2000 hierarchy of institutions – informal, formal,

corporate governance.

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Institutions, State Ownership and Internationalisation

• Institutions affect firm’s allocation of resources to international operations in both markets and hierarchies (SOEs). Institutions constrain decision makers in SOEs by limiting ability of insiders to

exploit SOE for own objectives The more that institutions constrain leaders in SOEs, the more likely that SOEs

pursue ‘benevolent’ objectives and their internationalisation strategies resemble those of private firms.

• Very little literature on SOEs and internationalisation; Mazzolini 1979, Vernon 1979 and recent work on China (Ramasamy et al 2012, Wang 2012)

• Two recent papers on other countries:– Spain (Garcia-Canul and Gwellen, 2008)– Norway (Knutsen et al 2011)

• No work on how institutions moderate internationalisation of SOEs

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SOEs, Institutions and Internationalisation

• Distinguish ‘benevolent’ (Helping hand) contribution of SOEs to society and non –benevolent “grabbing hand” (Shleifer and Vishny, 1998)

• Benevolent impact depends on political economy and institutions e.g.– in liberal economies, SOEs address market failures– in social democracies, SOEs redistribute income– in state capitalist and transition economies, SOEs guide economic development

• Grabbing hand– SOEs used by politicians to exploit state apparatus in pursuit of personal and political

gain.– Used by managers to extract rents

• If benevolent motives dominate, SOE acts like private firms, perhaps with certain objectives added

• If non-benevolent motives dominate, SOEs used to extract rents, which are usually found domestically

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Institutions and SOEs

• The extent SOEs follow benevolent or non-benevolent motives depends on local institutional context– Private firms benefit from good institutions at all

levels – increase resources available and enhance internationalisation strategies

– Same applies to SOEs – inspire monitoring and shift balance in favour of benevolent managerial strategies

– Hence interactions with institutions moderate SOE strategies to internationalise

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Figure 1: Theoretical Framework derived from Williamson (2000)

State Ownership

Allocation of resources to international operations

Formal institutions

Informal institutions

Governance institutions

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Hypothesis 1: Informal Institutions

• Informal institutions represent a cultural filter that provides continuity (North, 1990). Not prone to deliberate change (Hofstede, 1991).

• Most relevant concept is Hofstede’s 1980 “power distance” – “extent to which less powerful members of organisations … accept and expect power is distributed unequally”.

• High power distance makes organisations less entrepreneurial and competitive in global markets. Decision makers less likely to be challenged. Also discourages risk taking e.g. internationalisation.

• High power distance places the leader in greater authority – in SOEs, more likely to use power to pursue political interest and rent extraction.

H1: Informal institution of power distance will have a negative effect on the relationship between state ownership and internationalisation.

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Hypothesis 2: Formal institutions

• Operating in vaguely defined or weakly enforced legal framework reduces constraints on self serving objectives, especially in SOEs.

• Weak formal institutions raise importance of non-market capabilities, i.e. lobbying, government relationship etc. These cannot be easily leveraged into foreign markets.

• Hence, strong institutions more likely to ensure SOEs have benevolent rather than non-benevolent motives.

H2: Better formulated and enforced institutions of the rule of law will have a positive effect on the relationship between state ownership and internationalisation

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Hypothesis 3: Governance

• Effectiveness of domestic capital markets has greatest effect on behaviour of firms. Acts as benchmarks to assess performance and in aligning managerial and investor objectives.

• Listed SOEs subject to state and (minority) private owners. • Deviations towards non-benevolent objectives, which militate

against internationalisation, are harder to conceal and to implement as capital market institutions improve.

H3: Higher levels of development of the governance institution of capital markets will have a positive effect on the relationship between state ownership and internationalisation.

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Figure 2: Framework for Empirical Testing

State Ownership

Formal institutions

Informal institutions

Governance institutions

H2H1 H3Internationalization

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Data

• Sample from Worldscope, for world’s largest 5000 firms based on sales in 2010.

• Thomson One Banker used for firm level data, except ownership data from Orbis.

• Country level data from World Bank and Hofstede, 2001. • Sample contains 153 SOEs (firm with >50% equity held by

state). For example from the Top 100 in 2010:– There were ten Chinese firms, 9 were SOEs– There were two Brazilian firms, both were SOEs

• Matched sample created from the remaining 4847 firms by size (sales) and industry (SIC)

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Table 1: Sample Matched by Industry and Size

Country POE SOE Total Country POE SOE TotalArgentina 0 1 1 Japan 25 1 26Australia 2 1 3 Kuwait 0 1 1Austria 0 1 1 Malaysia 0 3 3Belgium 1 2 3 Holland 1 0 1Bahrain 1 0 1 Norway 0 3 3Brazil 1 8 9 Pakistan 0 2 2Canada 3 0 3 Philippines 3 0 3Switzerland 3 2 5 Poland 0 3 3China 3 36 39 Portugal 1 0 1Germany 10 2 12 Qatar 0 2 2Finland 2 1 3 Russia 5 15 20France 4 4 8 Saudi Arabia 1 3 4United Kingdom 7 0 7 Singapore 1 3 4Greece 0 2 2 Sweden 4 1 5Hong Kong 2 8 10 Thailand 1 2 3Indonesia 2 5 7 Turkey 1 0 1India 4 36 40 Taiwan 3 0 3Ireland 0 1 1 USA 51 0 51Israel 2 0 2 South Africa 2 0 2Italy 7 2 9 United Arab Emirates 0 2 2

Total 153 153 306

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Measures

• Dependent variable: foreign assets/total sales• Focal variable: State ownership: defined as whether a state

entity controls more than 50% of the firms’s equity • Moderating variables:

– Informal institutions (power distance) measure by Hofstede’s cultural dimension score

– Formal institutions measure by “rule of law” from Worldwide Governance Indicators (Kaufman et al 2010)

– Governance institutions by capital market development, i.e. share price x number of shares outstanding as percentage of GDP (World Bank 2010).

• Estimated using Tobit because left-centred.

Control Variables

• Country level– GDP per capita ($)

• Industry level (3-digit SIC)– Industry concentration (“C4”)– Industry growth (%)– Resource based industries (SIC < 1500).

• Firm level– Product diversification (entropy measure)– size (log employees)– R&D expenditures (% of sales)

VIF and correlation tables shows high interdependency between institutional variables so included separately and with interaction.

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Descriptive statistics and correlationsVariable Mean St.d. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15Internationalization 0.13 0.21 1 State ownership 0.5 0.5 -.18 1

R&D intensity 0.59 1.72 .21-.2

2 1

R&D presence 0.44 0.5 .15-.1

4 .39 1

Firm size 9.13 1.51 .10 .19-.0

1-.1

1 1 Product diversification 0.73 0.52 .11 .10 .05 .04 .17 1

Firm age 45.38 40.91 .11-.1

2 .13-.0

5 .14 .06 1

Industry growth 0.03 0.06 -.09 .05 .04-.0

8 .04 .09-.0

6 1

Industry concentration 0.63 0.22 .09-.1

2 .05 .20-.0

9-.0

4-.0

9-.1

4 1

Resource-based industry 0.1 0.3 .05 .13-.0

8 .09 .03-.0

3-.1

2-.2

7 .23 1

Currency reserves685.9

7 898.06 -.20 .23 .06 .18 .03 .10-.2

6 .11-.0

3 .08 1

Power distance 62.2 20.03 -.21 .59-.1

7-.1

4 .09 .03-.2

5 .01-.2

0 .12 .32 1

Rule of law 0.69 0.93 .33-.5

5 .22 .15-.0

5-.0

4 .27 .00 .20-.1

9-.3

8-.8

3 1 Capital market development

103.84 80.4 .19

-.01

-.06

-.10

-.11

-.07

-.01 .01 .03 .02

-.12

-.09 .31 1

GDP per capita 9.58 1.33 .33-.5

6 .21 .12-.0

9-.0

2 .13 .00 .22-.1

3-.2

7-.7

2 .83 .17 1

a Currency reserves is in $ billions.All correlations = .11 or above are

significant at p<.05

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Results

• H1 supported - Positive significant moderating influence of power distance on internationalisation of SOEs

• H2 supported – positive significant moderating influence of rule of law on internationalisation of SOEs

• H3 supported – positive significant moderates impact of market capitalisationon internationalisation of SOEs

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Estimation of Tobit regressions for internationalizationVariable Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7

Intercept-1.14 (0.24) *** -1.19 (0.28) *** -1.15 (0.27) *** -0.66 (0.32) * -0.56 (0.32) + -1.06 (0.23) *** -1.04 (0.23) ***

R&D intensity0.03 (0.01) ** 0.03 (0.01) ** 0.03 (0.01) ** 0.03 (0.01) ** 0.03 (0.01) ** 0.03 (0.01) ** 0.03 (0.01) **

R&D presence0.03 (0.05) 0.02 (0.05) 0.03 (0.05) 0.01 (0.05) 0.02 (0.05) 0.04 (0.05) 0.05 (0.04)

Firm size0.03 (0.01) * 0.04 (0.01) * 0.04 (0.01) ** 0.03 (0.01) * 0.04 (0.01) ** 0.04 (0.01) ** 0.04 (0.01) **

Product diversification0.11 (0.04) ** 0.12 (0.04) ** 0.11 (0.04) ** 0.11 (0.04) ** 0.10 (0.04) ** 0.12 (0.04) ** 0.11 (0.04) **

Firm age0.00 (0.00) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00)

Industry growth0.06 (0.37) 0.06 (0.38) 0.09 (0.37) 0.01 (0.36) 0.04 (0.36) 0.02 (0.36) 0.05 (0.35)

Industry concentration-0.13 (0.10) -0.13 (0.10) -0.10 (0.10) -0.14 (0.10) -0.14 (0.10) -0.12 (0.10) -0.11 (0.09)

Resource-based industry0.19 (0.07) ** 0.20 (0.07) ** 0.19 (0.07) ** 0.21 (0.07) ** 0.20 (0.07) ** 0.17 (0.07) * 0.18 (0.07) *

Currency reserves-0.00 (0.00) *** -0.00 (0.00) ** -0.00 (0.00) * -0.00 (0.00) * -0.00 (0.00) + -0.00 (0.00) ** -0.00 (0.00) **

GDP per capita0.09 (0.02) *** 0.09 (0.02) *** 0.08 (0.02) *** 0.04 (0.03) 0.03 (0.05) 0.07 (0.02) *** 0.07 (0.02) **

State ownership-0.05 (0.05) -0.08 (0.05) -0.08 (0.05) -0.04 (0.05) -0.06 (0.05) -0.07 (0.05) -0.07 (0.05)

Informal (Power distance) 0.00 (0.00) 0.00 (0.00) *

Informal (Power distance)* SOE

-0.01 (0.00) *

Formal (Rule of law) 0.09 (0.04) * 0.03 (0.05)

Formal (Rule of law)* SOE

0.14 (0.05) **

Governance (Market based) 0.00 (0.00) ** -0.00 (0.00)

Governance (Market based)* SOE

0.00 (0.00) **

N 301 286 286 301 301 301 300

2 87.2***

80.29***

86.08***

91.72***

98.84***

96.68***

104.43***

Log-likelihood -112.96 -107.04 -104.15 -110.7 -107.14 -108.22 -103.69

McFadden's pseudo R2 a 0.28 0.27 0.29 0.29 0.32 0.31 0.33

a McFadden's pseudo R2 as Tobit regression does not have an equivalent to the R-squared that is found in OLS regression. + p<0.10, * p<0.05, ** p<0.01, *** p<0.001

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Robustness Checks

• Results hold when continuous measure of State ownership used

• Results hold when alternative proxies for hypotheses used e.g. IPR rather than rule of law; Globe measures of power distance

• Results hold with additional controls e.g. for India and China; listing on stock exchanges overseas

• Results hold on estimates for full model as well as matched sample.

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Implications: Power Distance

In general, we find that the more that institutions provide for effective controls over decision makers, the more that SOEs pursue internationalisation strategies in the same way as private firms. Hence:• As power distance within a country increases, SOEs

internationalise less and private firms more - see table 3. • Suggests “managerial hubris” for private firms and private

benefits at home for SOEs.

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-.1

-.05

0.0

5.1

Linear Prediction

42 62 82Power Distance

POE SOE

Figure 3: Interaction of State Ownership and Power Distance

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Implications Ctd.: Rule of Law and Capital Markets

• Strong institutions at these two levels propel SOEs to internationalise.

• However effect on private firms of stronger institutions is these areas is small.

• Hence improvements in institutional arrangements reduce the gap between these types of firm.

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-.2

-.1

0.1

.2

Line

ar

Pre

dict

ion

-.242 .687 1.617

Rule of Law

POE SOE

Figure 4: Interaction of State Ownership and Rule of Law

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-.15

-.1

-.05

0.0

5

Line

ar P

redi

ctio

n

23.4 103.8 184.2

Capital Markets

POE SOE

Figure 5: Interaction of State Ownership and Capital Markets

Note to Figures 3 to 5: The horizontal axis shows the range of the explanatory variables from one standard deviation below the mean to one standard deviation above the mean.

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Conclusions

• SOEs have emerged as important international players. However their role and impact are strongly influenced by home country institutions

• Lower power distance, highly developed legal systems and high levels of capital market development reduce home bias of SOEs.

• For policy makers, higher level institutions change very slowly if at all. Immediate effects likely to be left via governance institutions.