The-MNC-AS-An-Agent-Of-Change.pdf

THE WILLIAM DAVIDSON INSTITUTE AT THE UNIVERSITY OF MICHIGAN

The MNC as an Agent of Change for Host-Country

Institutions: FDI and Corruption

By: Chuck Kwok & Solomon Tadesse

William Davidson Institute Working Paper Number 882 September 2006

The MNC as an Agent of Change for Host-Country Institutions: FDI and Corruption

Chuck Kwok + and Solomon Tadesse ++

This version: Sept. 2006

Abstract Most empirical research examines how the institutional environment of corruption shapes the behavior of MNCs. In this study, we would like to highlight the other side of the picture: how the presence of MNC may shape the institutional environment of corruption over time. We propose three avenues through which the MNC may have an impact on its host institutions: the regulatory pressure effect, the demonstration effect, and the professionalization effect. Based on extensive data on FDI and corruption for a large sample of countries over the last 30 years, the empirical results are consistent with our general hypothesis that foreign direct investment generates positive spillover effects on the institutional environment of host countries. Such findings provide a glimmer of hope for the future of the host country where corruption is most prevalent. Key Words: Foreign Direct Investment, Corruption JEL Codes: F21, F23, M14, M16, O73 + Moore School of Business, University of South Carolina, Columbia, SC 29208. E-mail: [email protected]. ++ Corresponding author. Stephen M. Ross School of Business, University of Michigan, Ann Arbor, MI 48109. E-mail: [email protected]. The authors would like to thank participants and the editors of the JIBS Special Issue on the “Three Lens” conference for comments and valuable suggestions.

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Introduction

With the expansion of international business activities, the study of corruption and its effects has

received increased attention recently. Multinational corporations (MNCs) are careful in choosing host

countries for their foreign subsidiaries, as they are concerned that pervasive corruption could increase

their operational costs and risks. So are also multinational banks, since corruption could drain the

investment funds of a country, hampering its economic growth and debt service capacity. International

development agencies are concerned that financial aids meant to help economic development and the

poor may be squandered by corrupt government officials.

Following Macrae (1982), in this study, we define corruption as an arrangement that involves an

exchange between two parties (the “demander” and the “supplier”) which i) has an influence on the

allocation of resources either immediately or in the future; and ii) involves the use or abuse of public or

collective responsibility for private ends. The harmful effects of corruption have been extensively

documented in the literature (see, e.g., Mauro (1995, 1997), and Rose-Ackerman (1975)). Corrupt

payments amount to a significant percentage of gross national product, since the rents extracted by a

corrupt system gets built into the cost structure of organizations. Corruption distorts efficient resource

allocation. Corruption rewards unproductive behavior by channeling unmerited contracts and rights to

companies in exchange for bribes, at the expense of efficient and innovative firms. The toleration of

corruption in some areas of public life can facilitate a downward spiral in which the malfeasance of some

encourages more and more people to engage in corruption over time. Pervasive corruption undermines

the legitimacy of governments. Corruption in the provision of public goods and services in the imposition

of costs casts a cloud over governments seeking popular legitimacy (Rose-Ackerman (1999)).

Most empirical work regarding corruption assumes the context where the institutional setting

shapes the behavior of the MNC. We certainly recognize that, in order to strive for external legitimacy,

the MNC needs to adapt to its institutional context (Glynn and Abzug (2002)). However, in this study, we

would like to point out the other side of the picture: how the presence of MNCs could shape the

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institutional environment of corruption over time. We propose three avenues through which the MNC

may have an impact on its host institutions: regulatory pressure effect, demonstration effect, and

professionalization effect.

The balance of the paper is organized into five sections. Following the introduction, the second

section II reviews the literature on corruption. The third section III explores how the MNC interacts with

its host environment and formulates the research hypotheses. In the fourth section, we describe the data

and methodology used in the paper. Section V reports the empirical results. Finally, section VI

concludes the paper and discusses the implications of our findings.

II. Literature review

As a topic of key concern, the study of corruption has generated numerous published scholarly

studies. In the academic literature, there are two main streams of studies on the subject. The first stream

employs the approach of mathematical modeling to analyze the causes, effects and various conditions

related to corruption. For examples, Rose-Ackerman (1975) examines the relationship between market

structures and the incidence of corrupt dealings in the government contracting process. She then discusses

how revising contracting procedures and reorganizing market structures can reduce criminal incentives of

corruption. Shleifer and Vishny (1993) contend that weak governments that do not control their agencies

experience high corruption levels. Moreover, the illegality of corruption and the need for secrecy make it

much more distortionary and costly than taxation.

The second research stream consists of various empirical studies. This line of research is

facilitated by the publication of worldwide corruption indices by agencies such as the Transparency

International, World Bank, Economist Intelligence Unit and so forth. The corruption indices can be used

either as an independent or dependent variable. For instance, using corruption as an independent variable,

studies have found that corruption contributes to suboptimal economic growth (Barro (1996)), poor

economic competitiveness (Ades and di Tella (1999)), less investment and inefficient government (Knack

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and Keefer (1995); Mauro (1997)), and a decrease in the level of trust or social capital by citizens (La

Porta et al. (1997); Knack and Keefer (1997)).

Using the corruption index as the dependent variable, Husted (1999) finds that corruption is

significantly associated with GNP per capita and related to the cultural variables power distance,

masculinity and uncertainty avoidance. Robertson and Watson (2004) find that in the short run, the more

rapid the rate of change of foreign direct investment (FDI), the higher level of corruption.

III. MNCs and corruption in host countries

MNC as an organization shaped by the host institution

Empirical studies have been conducted to show how a host country’s corruption significantly

reduces its inflows of foreign direct investment (Lambsdorff (1999); Mauro (1995); Wei (1997)). Besides

the volume of FDI inflows, Rodriguez, Uhlenbruck and Eden (2005) contend that the type of corruption

in the host country would also affect the choice of entry modes. Using the institutional framework, they

introduce a two-dimensional framework of corruption: pervasiveness and arbitrariness. They argue that

the higher the pervasiveness of corruption, the higher is the likelihood that an MNC will choose to enter

via a wholly owned subsidiary rather than a local partner.

Most of the studies mentioned above examine how the institutional environment of corruption

may shape the behavior of MNCs. We certainly recognize that in order to strive for external legitimacy,

the MNC needs to adapt to its institutional context (Glynn and Abzug (2002)). However, in this study, we

would like to highlight the other side of the picture: how the presence of MNC may shape the institutional

environment of corruption over time. We contend that the MNC is not just a passive subject; it may also

serve an agent of change.

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MNC as an agent of change to the host institution

Using the framework of the institutionalization theory, Westney (1993) discusses the potential

significant impacts of MNCs on the organizational patterns within a country. MNC subsidiaries in some

countries can play a major role in establishing building blocks of organizations. The introduction of new

modes of business practice in MNC subsidiaries can challenge the legitimacy of existing patterns and

stimulate debates on better business practice in the host country. The mirror image of this influence is the

“de-institutionalization” of local firms’ existing organizational patterns. Similarly, Dacin, Ventresca and

Beal (1999) review research on organizations to highlight prevailing and emerging conceptions on

embeddedness. They briefly discuss the concept of “disembeddedness”. They argue that globalization

may be regarded as a disembedding process that strips individuals and firms from their local structures

and allows for restructuring at a more global level.

Following this perspective, we contend that the presence of foreign-owned subsidiaries will, on

the average, reduce the level of corruption of the host country. We propose that the MNC influences its

institutional environment over time via three major effects: regulatory pressure effect, demonstration

effect, and professionalization effect.1 For better explanation, our main ideas are illustrated in Figure 1.

This diagram conveys as a general framework on how the MNC may serve as an agent of change for

host-country institutions.

Within the host country environment, local governments and the business community influence

the behavior of foreign-owned subsidiaries. In Figure 1, we use a thick arrow line to represent such

influence, indicating that such influence tends to be strong and immediate. However, we argue that there

is a milder force of influence flowing back from the MNC to the host government and business

1 We benefited much from the insights of DiMaggio and Powell (1983) who discuss institutional isomorphism.

Isomorphism is a constraining process that forces one unit in a population to resemble other units that face the similar set of environmental conditions. Our proposed three effects correspond with their three mechanisms of isomorphism: coercive isomorphism; mimetic isomorphism; and normative isomorphism. However, the focus of DiMaggio and Powell is on isomorphism. In order not to confuse readers who are familiar with the institutional theory, we use three other terms to represent the effects through which the MNC may shape the host country institution over time.

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community. We use a thin arrow line to represent such influence as it is mild, subtle and takes long time

to realize. Besides conforming to the local business practice to gain legitimacy, MNCs are also

accountable to and constrained by their home-country environment and the international business

community at large. Through the regulatory pressure, demonstration, and professionalization effects,

MNCs gradually shape the host-country institutions. One motivating factor for the host institutions to

change is that the host country also wants to gain legitimacy within the bigger, global business

environment. As the host country grows, it would like to enhance its international reputation and attracts

more business. Under this general framework of how MNCs may shape host-country institutions over

time, we study the specific relationship between FDI and host-country corruption.

Regulatory pressure effect

In a business culture where corruption is pervasive, corruption becomes the modality of business

practice in local businesses and government offices. It becomes part of the regular practice and both

parties of the transaction would take it for granted. However, when a government official deals with a

foreign entity, he or she may not be able to conduct business as usual. The business people representing

the MNCs may be reluctant in offering a bribe. Firstly, the subsidiary of an MNC is faced with two sets

of isomorphic pressures — the MNC’s and the host country’s (Davis et al. (2000); Kostova and Roth

(2002)). Besides trying to gain external legitimacy by adopting the common corrupt business practice of

the host country, it also has to strive for internal legitimacy as the headquarter in the home-country

environment may have adopted norms and practices that ban corrupt behaviors by their subsidiaries.

Secondly, there is the regulatory pressure from the home government and the international

business community (DiMaggio and Powell (1983), Oliver (1997)). For instance, the U.S. Foreign

Corrupt Practices Act, enacted in 1977, was prompted by a series of scandals involving questionable

payments by U.S. firms to overseas government officials. This act prohibits U.S. firms from giving

anything of value (such as a payment, gift or bribe) to induce a foreign government to enter into a

contract or business advantage or relationship. This act carries criminal penalties, imprisonment for up to

five years, fines of up to $100,000 for individuals, and fines up to $2 million for companies.

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Similar legislation is enacted in the global business community. On November 21, 1997,

representatives from 33 countries signed the Convention on Combating Bribery of Foreign Public

Officials in International Business Transactions. Among them were 28 of the 29 member states of the

Organization for Economic Cooperation and Development (OECD), together with Argentina, Brazil,

Bulgaria, Chile, and the Solvak Republic (Doh et al., 2003).

Under regulatory pressure from home country and the international business community, the

employees of MNC’s subsidiaries are reluctant to offer bribes. If the MNC has enough bargaining power

and its presence is much desired by the host government, it may simply refuse offering bribes. Even if the

subsidiary employees think that they need to engage in bribery in order to secure business, the local

officials may need to think of some circuitous ways to accept the bribes so that the MNC employees are

less likely to get caught. Facing a foreign business party, the local government officials are constrained

somewhat in their bribery acts. It cannot be just business as usual.

Demonstration effect

In the international business literature, there is a line of research that studies spillover effects of

foreign direct investment (Globerman (1979), Haddad and Harrison (1993), Eden et al. (1997), Aitken

and Harrison (1999), and Liu et al. (2000)). The discussion of the spillover effects concentrates mainly on

productivity and technological transfer. For instance, Blomström and Kokko (1998) and Gorg and Strobl

(2001) summarize how FDI may affect the productivity of domestic firms. First, competition from FDI

may force domestic firms to update production technology and change management styles in order to

maintain their competitiveness. Second, domestic firms may learn from observing the MNCs’ practice

when there are close relationships between them. Thirdly, MNCs train their employees who may later

move to domestic firms with learnt skills.

Following this line of thought, we argue that there may also be a spillover or demonstration effect

on corruption (Oliver (1997)). In some host countries, corruption has been immersed deep in the local

business culture. Local business people and government officials may think that this is the “normal” way

to get business done. However, when they deal with the MNCs through negotiations, joint ventures,

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upstream or downstream relationships in the business chains, being geographically and operationally

proximate, they have opportunities to observe closely how business decisions and allocations are made

within the MNCs (Eden et al. (1997)). Business can be conducted more efficiently in an environment

built on trust and ethical conduct. In the past, local advocates might also “talk” about ethical business

practice but might not produce a concrete, real example to follow. The presence of MNCs demonstrates

how a cleaner way of conducting business can be more effective and efficient in the long run.

Furthermore, outward-looking local business people and government officials also want to gain

legitimacy within the global business community. They want to enhance the country’s international

reputation and to attract more business. They may model themselves after the MNCs and change their

traditional business practices gradually.

Professionalization effect

DiMaggio and Powell (1983) discuss two important aspects of professionalization. One is the

resting of formal education and of legitimation in a cognitive base produced by university specialists. The

other is the growth and elaboration of professional networks that span organizations and across which

new models diffuse rapidly.

MNCs have been in the forefront of the application of automation, information technology and

managerial techniques in order to enhance business efficiency. Alternatively, academicians strive to

improve business knowledge and develop practical applications by conducting theoretical and empirical

research. All areas of business have, to one degree or another, become sciences. Academic curricula have

become increasingly standardized and professionalized. Business schools around the world tend to adopt

textbooks and course contents from the same pool of leading authors and universities. In order to excel

above their peers, managers want to acquire professional business training. Afraid of being left out by

competitors, even family-owned businesses consider sending their “heirs” to business schools (Ramirez

and Kwok (2006)).

To the younger generation, the MNCs have special appeal. MNCs usually offer substantially

better salaries than domestic companies in host countries. Not only is working for MNCs prestigious, they

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can be exposed to sophisticated management practices, which will equip them with skills for a successful

business career in the long run. Furthermore, they may be given opportunities to go overseas for short-

term training or business assignments.

To enhance their chance of being recruited by MNCs, the young generation needs to learn about

global business practices. They attend schools to acquire professional business training. To certify their

qualifications, they may take public examinations and join professional associations. Such professional

organizations may set industry-wide ethical codes of conduct, product quality standards, uniform training

or credentialing in occupational professions (Oliver (1997)). Socialized by the professional business

values, they become increasingly critical of the traditional ways. As the “new blood” rise in the corporate

ladder, they become business leaders. They may work for the MNC, they may have started their own

business, or they may have become senior advisors to government officials. They may use their influence

to gradually reform the more corrupt old business practices. In short, the professionalization of the

management practice and the socialization of the younger generation lead to the changes in the host

country institutions over time.

Through the three effects mentioned above, we contend that the presence of MNCs may help

reduce corruption in the host country over time. We put forward the following research hypothesis:

H1: The level of foreign direct investment in a host country is negatively related to its level of corruption over time. 2

However, we need to add quickly that it would be naïve to think that the influence of MNCs on

its environmental institution is always good. There are plenty of anecdotal evidences that MNCs

sometimes bring undesirable influences. In some situations, MNCs exploit natural resources, cause

environmental pollution, employ child labor, or take advantage of the looser regulations of the host

countries (to bypass the stringent regulations and costly requirements of parent countries). In fact,

2 Our hypothesis is on an average effect. First, some MNCs may still engage in corrupt transactions to facilitate

their operation. Second, there are also foreign direct investment flows among developed countries where both the home and host countries do not experience a high level of corruption. In that case, the corruption-reduction effect may be minimal. To examine this latter point, in our robustness tests, we exclude OECD countries from our sample of host countries. The findings are generally robust. Owing to space constraint, the tables of these additional findings are not included in this paper but will be made available to readers upon request.

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Robertson and Watson (2004) argue that foreign direct investment will lead to an increase of corruption

in the host country in the short run. Firstly, the increase in FDI represents a larger amount of foreign

money flowing into country and, therefore, an expansion of opportunities for bribery. Secondly, the

eagerness of foreign investors to enter the market may tempt host country nationals to resort to corruption

as a means of sharing in the opportunities for profit presented by their own country (Robertson and

Watson (2004)).3 Thirdly, equipped with advanced knowledge in international business and a vast

international network, MNCs may have developed sophisticated skills of bribery. Such practices will

“contaminate” firms in the host country. To represent this opposite view, we put forward the following

alternative hypothesis:

H1a: The level of foreign direct investment in a host country is positively related to its level of corruption over time.

IV. Data and research methodology We attempt to explain the cross-country variations in the extent of corruption based on variations

in the degree of past foreign investment penetration in the economy and other known controls. To that

end, we construct a database composed of three sets of data: (1) measures of corruption in the 2000s (the

dependent variable); (2) measures of MNC presence or foreign direct investment, education, and culture

(the independent variables); and (3) other controls. We have data on these sets of variables for up to 140

countries.

The dependent variable: corruption

Our dependent variable is the extent of corruption in recent years, and is measured by the average

of yearly corruption perception indices over the period 2000 through 2004 obtained from Transparency

International (TI). The TI Corruption Perception Index provides yearly ranking of countries in terms of

the extent of perceived corruption among, primarily, public officials. The index is a composite measure

3 Robertson and Watson (2004) find empirical support for their hypothesis. They use a 1- and 2-year lag-time

between the predictor variable (FDI) and the dependent variable (corruption). Their result reflects more on the short-term effect. On the other hand, the focus of this paper is on the long-term effect of FDI on corruption as the suggested three effects take time to realize.

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based on polls and surveys of business leaders, residents and country analysts on their experience of

corruption in the respective countries drawn from seven different independent institutions.4 Table 1

reports the summary statistics of the variables while Table 2 shows their correlation coefficients. There is

a wide cross-country variation in the corruption index, ranging from 0.22 in Finland and 0.44 in Denmark

to 8.9 in Bangladesh and 8.66 in Nigeria. Consistent with previous research (e.g., Husted (1999)),

wealthier countries tend to be less corrupt. The corruption perception index is significantly negatively

correlated with log of per capita GDP.

The main independent variable: FDI

We measure the presence of MNCs in a host country by the average net Foreign Direct

Investment (FDI) inflows as a percentage of GDP. We attempt to explain variations in corruption in the

2000s based on the degree of foreign investment penetration in the past. We expect a significant time lag

for the effects to realize but we do not know how far in the past the FDI should be in explaining current

variations in corruption. Nonetheless, we have available data on FDI inflows from 1970 through 1997.

Thus, we consider decade averages of FDI per GDP in the 1970s, the 1980s and the 1990s, as well as an

average over the period 1970 through 1997 respectively. The data on FDI inflows and GDP is obtained

from the World Development Database maintained by the World Bank.

Table 1 provides a summary of the decade averages of FDI to GDP ratios for the sample. The

flow of FDI shows an increasing trend, the average growing from 0.93 percent of GDP in 1970s to 1.089

percent in the 1980s and 2.128 percent in the 90s. In general, high level of FDI appears to be associated

with low corruption in the 2000s. The correlation coefficients between FDI and corruption are mostly

negative and significant (see Table 2).

4 The corruption perception index is a continuous scale variable, taking values from 0 to 10. The higher the value,

the less corrupt the country is. To make the scaling more intuitive, we rescale the corruption perception index by deducting it from 10, so that a 0 on the new scale signifies a corruption-free country and a 10 represents an absolutely corrupt country.

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V. Empirical findings

FDI and corruption To explore the relations between corruption and the extent of past FDI while controlling for other

potential country factors, we estimate multivariate empirical models. Table 3 presents the main results of

the multivariate regression of corruption on FDI, controlling for a host of control variables. The model is

of the form:

cCin

iiorsss

CC ZFDICORRUPTION ελβα +++= ∑ =

−

119971970,90,80,70* , (1)

where FDI is the FDI inflows as a fraction of GDP, and Z is a set of country-specific control variables

representing the macro-economic, political, legal, religious orientation and institutional environments of

countries that potentially explain the cross-country variations in corruption. FDIC will alternatively take

the values of decade averages of FDI in 1970s, in 1980s, in 1990s and the average FDI to GDP ratio over

1970 through 1997, whereas CORRUPTION will take the average per country of the yearly Corruption

Perception Index averaged over the period 2000 through 2004.

Table 3 clearly shows that past FDI inflows explains a significant portion of the cross-country

variations in corruption. Columns I through IV include the decade averages of FDI to GDP ratios in

combination with the level of GDP per capita as a measure of wealth in the regression. The results show

that the prevalence of corruption today is, on average, lower in countries with larger foreign direct

investment in the past, regardless of how far back we measure the FDI. The coefficients on the key

variables of interest, FDI in 1970s, 1980s, 1990s and 1970 through 1997, are robustly negative and

statistically significant at the one per cent level. The result is broadly consistent with and suggestive of

our hypothesis. Consistent with earlier studies (e.g., Husted (1999) and Mauro (1995)), wealthier

countries have less prevalence of corruption. In general the model works well; in this large sample of 87

to 100 countries, the model explains up to 79 percent of the cross-country variation in the prevalence of

current corruption. To strengthen the veracity of the findings, we control for other variables suggested in

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the literature, which may also influence a country’s propensity to corruption. We group these controls

into three categories: 1) Education/Human Capital; 2) Political Tradition; and 3) Legal Environments.

Control for education/human capital

The benefits of education as an institution to economic welfare have been well documented.

Education explains cross-country differences in economic growth across countries (see, e.g., Barro

(1991). Education opens up peoples’ eyes to new ways of thinking and practice, and is a source of

increased productivity, efficiency and growth. The development of a critical mass of educated class

would have the potential to change the old ways of life, including corruption. In some way, the effects of

education are similar to those of FDI; much of the benefits are not immediate. To control for the impacts

of education, we include decade averages of secondary school enrollment (as a percentage of eligible

population of the age group) from the World Development database. Columns (V) through (VIII) of

Table 3 show that the effect of educational investment on corruption is similar, though weak, as that of

FDI.

Control for political tradition

The political tradition of the country has a significant impact on its institutional environment.

Governments differ in their role as facilitators of institutional change, and the effect they have on

business practices (see, e.g., Rao et al. (2005)). Autocratic political cultures that lack transparency where

political actors are prone to undermine the rule of law tend to be a breeding ground for abuse of public

office, including corruption. In contrast, open societies with democratic political culture and appropriate

checks and balances in place for constraining actions of political actors are less prone to such abuse. To

control for the effects of political traditions, we use two variables: a measure of the extent of democratic

political system in the country (Jaggers and Marshall (2000)) and a measure of constraints on political

actors in the system (Henisz (2000)). The two variables have significant correlation. To reduce the

possibility of multicollinearity from inclusion of both in the same regression, we orthogonalize the

democracy variable on political constraint and include only the residual value of political constraint.

Columns IX through XII report that the marginal effect of political traditions is not as significant, once

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one controls for wealth, FDI and education. More democratic countries tend to be less corrupt on

average, though the result is weak and is not sustainable in all specifications.

Control for legal environment

A weak legal system where basic rule of law is lacking would be permissive of abuse of public

office through its failure of legally constraining those in power. In addition, even in the presence of basic

rule of law, the substantive and procedural contents of the law could be a source of variation in the

efficiency of the legal system. Legal systems that are cumbersome in procedural formalism and short of

the legal flexibility that are needed for judicial actions tend to increase the costs of legal proceedings,

prompting the public to seek extra-judicial means of resolution, including corruption. We include the

‘rule of law’ and the ‘legal formalism’ variables developed by Djankov et al. (2003) in our regressions.

Consistent with our conjecture, columns (XIII) through (XV) show that countries with the prevalence of

rule of law tend to be less prone to corruption. Legal systems that are more formal and less flexible

appear to be associated with higher corruption.

As seen in the regression results in Table 3, our main finding that increased past FDI reduced the

prevalence of current corruption is robust to the inclusion of controls for the legal environment, political

tradition, education and economic development.5 The findings are broadly consistent with our main

hypothesis H1 and not supportive of the alternative hypothesis H1a. We argue earlier that the MNC

influences its institutional environment over time via three major effects: regulatory pressure effect,

demonstration effect, and professionalization effect. While it is difficult to provide precise, direct tests of

5 To check for other institutional control variables, instead of the political and legal variables, we also used a

variable that denotes the religious orientation of the country – the percentage of population that follow Protestantism. Religion appears to be a dominant influence on the institutional environment of countries, showing significant correlation with our legal and political variables. Our results are robust to such specification, showing that countries with past FDI exhibit lower rate of corruption, after controlling for religion. The coefficient on FDI is -0.385, significant at 1 percent level. Also countries with dominant protestant influence display lower incidence of corruption. In addition, we considered a much broader measure of institutional development (instead of the political and legal variables we have) from Kaufmann et al. (1999). This measure reflects the institutional quality, based on measures of voice and accountability, political stability and absence of violence, government effectiveness, regulatory burden, law and order, and freedom from graft. The results show robust negative relation between FDI and corruption. The coefficient estimate is -0.139 which is significant at 10 percent level. The results using religious orientation or institutional development as controls are not reported in the tables owing to page constraint. They will be made available to readers upon request.

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these three effects, we attempt to shed more light on these avenues of influence by examining the

moderating role of past FDI on the known effects of two variables on corruption: Culture and Education.

Culture, education and corruption: the moderating effects of FDI

In this section, we interact the FDI variable with two sets of variables, Culture and Education.

The objectives of this exercise are twofold. First, evidence that FDI presence moderates the negative

effects of culture, or it strengthens the positive effects of education on corruption would be suggestive of

the effects of FDI in play. Second, examining interaction (rather than direct) effects also addresses the

potential endogeneity problem we are cognizant of. In the previous section, we regress corruption in

2000s on lagged values of FDI, the lagged values going as far back as 30 years. The fact that the FDI

values are not contemporaneous with the corruption data minimizes the concerns on reverse causality.

However, it can be argued that past FDI is made in anticipation of the institutional environment in the

future so much so that prediction of low corruption in the future attracts more FDI today. One effective

way of addressing such endogeneity is to focus on the marginal effect of FDI on the effect of a known

variable, such as culture, on corruption. The literature indicates that some cultures, as country effects,

breed in corruption. We find earlier that education as a social investment deters corruption. If we find

that marginally, the known negative effects of culture is moderated and the known positive effects of

education is strengthened by the presence of FDI, then we can say that we have a clearer indicator of

causality running from FDI to corruption.

Using Hofstede’s measures of national culture, Husted (1999) identifies power distance,

uncertainty avoidance and masculinity to have significant impact on national corruption. Kimbro (2002)

reports power distance and individualism as related to corruption after controlling for legal and

monitoring variables the way we do. It appears that the consensus is that individualism and power

distance are the cultural traits that are associated with corruption; collectivistic cultures and cultures with

high power distance gravitate towards high prevalence of corruption. If FDI has the catalyst role through

the three effects, it would moderate the harmful effects of culture on corruption.

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Columns (I) through (IV) of Table 4 examine the interaction between power distance and FDI.

The results show that, consistent with previous research (see, for examples, Husted (1999), Triandis et al.

(2001)), high power-distance countries tend to have high prevalence of corruption. More significantly, the

effect of high power-distance on corruption is significantly lower in the presence of FDI; the interaction

terms between FDI and power-distance are robustly negative and statistically significant at the one per

cent level. Columns (V) through (VIII) provide similar results on the interaction of

individualism/collectivism and FDI. Though the coefficient is positive, individualism has no discernible

direct effect on incidence of corruption. This is consistent with existing, though ambiguous, evidence

about individualism in the literature. For example, Husted (1999) finds no direct effect from

individualism to corruption, while Kimbro (2002) finds direct effects, once the effect of countries’ wealth

is controlled for. More importantly, the effects of individualism/collectivism on corruption are

significantly lower in the presence of FDI.6

Our analysis in the previous section reveals that one of the critical variables that explain the

variations in the prevalence of corruption is education. It can be argued that, via the professionalization

effect, FDI presence complements education in transforming the institutional environment of countries.

Columns (IX) through (XI) report the results. For education we use the average yearly secondary school

enrollment, averaged over 1970 though 2000.7 The use of decade averages over 1970s, 1980s and 1990s

does not change the results. Consistent with our earlier results, education has positive, though moderate,

direct effects on corruption. The coefficients on the education variable are negative and significant at ten

per cent level. Consistent with our conjecture, the positive effects of education on corruption are

significantly larger in the presence of FDI; the interaction terms between education and FDI are robustly

negative and statistically significant as one per cent level. The models in Table 4 perform well, explaining 6 For reasons outlined earlier, we focus on the power distance and individualism attributes of national culture.

Though not reported for brevity, the results using the other two attributes, masculinity and uncertainty avoidance, provide qualitatively similar evidence. Again for brevity, we use the overall average FDI over the entire period of 1970 through 1997 as the FDI variable. However, the results are robust when we use the decade averages instead.

7 Secondary school enrollment is a standard measure of human capital in the literature of economic growth (e.g. Barro (1991)).

16

more than 80 percent of the cross-country variations in corruption, though our sample has significantly

shrunk because of missing values.

Robustness tests Using alternative measures for the independent variable We provide additional sensitivity checks in this section. First, instead of using the actual values

of FDI as independent variable, we include group indicator of high or low FDI countries in the regression.

We group the countries into three categories based on their rankings of FDI flows, and designate the

bottom-third countries as low-FDI countries with a dummy variable value of 0, and the top-third

countries as high-FDI countries with a dummy variable value of 1. Columns (I) through (IV) of Table 5

show that our main findings are robust to the alternative measure of FDI. For brevity, we report the

results using the FDI and Education variables generated based on averages over the period 1970 through

1997. The results are similar if we use values based on decade averages in 1970s, 1980s or 1990s.

Instrumental variables methodology

Our findings are based on regressing corruption in 2000s on lagged values of FDI, the lagged

values going as far back as 30 years. The fact that the FDI values are not contemporaneous with the

corruption data minimizes the concerns one may have about the possibility of reverse causality.

However, it could still be argued that past FDI is made based on predictions about the institutional

environment in the future such that a forecast of low corruption in the future attracts more FDI today. The

robust findings on the channels through which past FDI moderates the harmful effects of culture and

strengthens the beneficial effects of education, shown in the previous section, go a long way in allaying

our concerns on reverse causality.

An alternative approach to address the endogeneity issue would be to use instruments that

disentangle the link between FDI and corruption. We estimate the basic models using the instrumental

variables methodology, where we attempt to relate the exogenous component of FDI to corruption. The

ideal instruments are variables that might affect corruption but less likely to be affected by it. The most

17

difficult task in this setting, however, is the identification of appropriate instruments. It is customary in

the finance and economics literature to use such institutional variables as legal origin or colonial history.

These variables however, are not useful for our case, as both corruption and FDI are driven by the

institutional environment. We look for variables that explain FDI but less likely to be related with

corruption. The literature provides a menu of FDI determinants, but most variables are institutional. In

addition to variables related to the host country investment climate, FDI is facilitated by better

infrastructure including communication networks and supply of power. We use two variables of this

nature as instruments: (a) per capita electricity power consumption, and (b) telephone lines (per 1,000

people). We examine the effects of the exogenous component of FDI (the component explainable by our

instruments) on corruption. Columns (V) through (VIII) of Table 5 present the instrumental variables

(IV) results. Column (V) confirm the major findings from Table 4 that corruption is lower in countries

with high past FDI predicted by the instruments. Columns (VI) through (VIII) confirm the main results

that FDI moderates the harmful effects of culture and strengthens the positive effects of education.8

Change in corruption as a dependent variable

To address the concern on causality further, we also examine the relation between past FDI and

changes (rather than levels) in the corruption measures. Based on the data, we compute the difference

between the average corruption level over 2000 through 2004 and the average corruption index between

1995 and 1999, and examine whether the change in the index levels is related to past FDI flows as

hypothesized. The results, shown in Table 6, confirm the main results so far. The change in corruption is

inversely related to past FDI. In addition, FDI appears to moderate the harmful effects of culture and

8 We follow a two-step procedure where we predict the level of FDI using our two instruments in the first step,

and use the predicted FDI values and other predetermined variables to explain variations in corruption. The test for the validity of the instruments using GMM estimation does not support the hypothesis. However, in this test, the set of instruments include both the two instrumental variables we specified and the six exogenous explanatory variables in the model; since, with only two instruments, the model will be under-identified. Nevertheless, this result reflects the difficulty of finding good instruments in our context and suggests that the readers should interpret our instrumental variables results with this limitation in mind.

18

strengthens the positive effects of education, as the interaction terms between past FDI and our proxies of

culture and education are significantly negative.9

VI. Summary and conclusions

Most empirical research so far examines how the institutional environment of corruption shapes

the behavior of MNCs. In this study, we highlight the other side of the picture: how the presence of MNC

may shape the institutional environment of corruption over time. We recognize that, in order to strive for

external legitimacy, the MNC needs to adapt to its institutional context. Most FDI represents flows from

developed countries, where there is generally less corruption. The behavior of MNC in host country is

constrained by the regulatory pressure from home country and the international business community (e.g.

U.S. Foreign Corrupt Practices Act and OECD Convention on Combating Bribery of Foreign Public

Officials in International Business Transactions). In dealing with a foreign business party, the local

government officials are constrained somewhat in their bribery acts; it cannot be just business as usual.

Over time, together with the demonstration and the professionalization effects, local government officials

and business people may model themselves after the MNCs and modify their traditional business

practices. They may want to enhance legitimacy within the global business community, raise the

country’s international reputation, and attract more business into their country.

We empirically examine our propositions based on an extensive data on FDI and corruption

around the world, for a large sample of countries, over the last 30 years. First, consistent with our thesis,

we find that current corruption level is significantly lower in countries with high FDI flows in the past.

This is true whether we use FDI in 1970s, 1980s or 1990s. Second, we find strong evidence that the

harmful effects of culture on corruption are lower and the beneficial effects of education on corruption are

higher in countries with higher FDI in the past. Our results are robust to omitted variables bias as we 9 In this study, we do not use the change of corruption level as our main dependent variable. Transparency

International computes the Corruption Perception Index as a composite of a number of independent surveys. As explained in Robertson and Watson (2004, p. 390), the sources used differ from year to year. Hence, the CPI is suitable for cross-sectional comparisons but unsuitable for longitudinal comparisons. To alleviate the concern of varying sources over time, we use the average corruption levels of two broad periods to compute the difference. Nevertheless, the readers should interpret the findings with such limitation in mind.

19

control for a host of host-country characteristics, including the level of economic development, political

tradition, education, culture, legal system, religious orientation and institutional development.

We use multiple ways to alleviate the potential concerns of reverse causality. Firstly, we regress

corruption in 2000s on lagged values of FDI, the lagged values going as far back as 30 years. Secondly,

we explore the interaction effects between FDI and variables such as culture and education. Thirdly, we

employ the instrumental variables methodology, using two instrumental variables, communication

network and supply of power, to relate the exogenous component of FDI to corruption. Fourthly, we

regress changes (rather than levels) in the corruption measures on past FDI. The robust results give us

confidence that there is a causal effect flowing from FDI to corruption.

Our findings confirm the fruitfulness of studying the potential impact of MNCs on the

organizational patterns within a country. As contended by Westney (1993), MNC subsidiaries in some

countries can play a major role in establishing building blocks of organizations. The introduction of new

modes of business practice in MNC subsidiaries can challenge the legitimacy of existing patterns and

stimulate debates on better business practices, initiating a “de-institutionalization” process.

Certainly, it would be naïve to think that the influence of MNCs on its institutional environment

is always good. There are plenty of anecdotal evidences that MNCs sometimes bring in undesirable

influences. However, in the area of corruption, our empirical findings show that the average effect is

positive: the presence of FDI could help reduce the corruption level of a host country over time. It enables

the MNC to point out to the host government and its people another potential benefit of opening its doors

to foreign direct investment. Such a dynamic perspective provides a glimmer of hope to host countries

where corruption is widely prevalent.

20

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23

Figure 1: MNC as an Agent of Change for Host-Country Institutions

MNC

Host Country Government and Business Community

International Business Community

Home Country Environment

Host Country Environment

Global Business Environment

• Regulatory Pressure Effect • Demonstration Effect • Professionalization Effect

24

Table 1: Summary Statistics

Variable Mean Std Dev Minimum Maximum N

Dependent Variables: Corruption 2000-04

5.634

2.313

0.220

8.900

120

Independent Variables: FDI to GDP in 1970s FDI to GDP in 1980s FDI to GDP in 1990s FDI to GDP 1970-1997

0.933 1.089 2.128 1.488

1.318 2.089 4.057 2.204

-1.844 -4.206 -11.028 -4.365

5.838 14.838 37.284 14.191

113 136 140 142

Control Variables: Per Capita GDP

8.291

1.123

6.064

10.164

133

Education in 1970s 36.846 27.741 1.000 94.667 128 Education in 1980s 47.376 30.237 3.460 107.679 131 Education in 1990s 55.001 33.795 5.257 129.966 130 Education in 1970-1997 44.408 29.482 1.171 104.442 143 Democracy 5.051 3.775 0 10.000 85 Political Constraint 0.348 0.324 0 0.893 133 Rule of Law 6.907 2.445 1.670 10.000 76

Legal Formalism 3.549 1.015 1.414 5.907 94

Culture

Power Distance

56.41

21.48

11.00

104.00

56

Individualism/Collectivism 43.50 25.20 6.00 91.00 56

Instrumental Variables:

Telephone Lines

85.85

123.44

0.65

594.81

134 Electricity Consumption

(kwh per capita) 7.2E10 2.8E11 2.6E7 2.7E12 104

25

Table 2: Correlation Matrix (figures in parentheses are p values) Corruption Per capita

GDP FDI in 1970s

FDI in 1980s

FDI in 1990s

FDI 1970-1997

Education in 1970s

Education in 1980s

Education in 1990s

Education in 1970-

1997

Power

Distance

Individualism Collectivism

Democracy Political Constraint

Per Capita GDP -0.835 (0.0001)

FDI in 1970s -0.1154 (0.141)

0.125 (0.207)

FDI in 1980s -0.285 (0.003)

0.208 (0.022)

0.464 (<.0001)

FDI in 1990s -0.174 (0.076)

0.109 (0.223)

0.078 (0.409)

0.419 (<.0001)

FDI in 1970-1997 -0.208 (0.032)

0.119 (0.180)

0.405 (<.0001)

0.761 (<.0001)

0.867 (<.0001)

Education in 1970s -0.771 (0.0001)

0.889 (<.0001)

0.086 (0.386)

0.088 (0.343)

0.019 (0.839)

0.022 (0.817)

Education in 1980s -0.745 (0.0001)

0.834 (<.0001)

0.775 (<.0001)

0.054 (0.557)

0.108 (0.233)

0.069 (0.439)

0.954 (<.0001)

Education in in 1990s -0.799 (0.0001)

0.881 (<.0001)

0.089 (0.371)

0.087 (0.347)

0.079 (0.388)

0.027 (0.766)

0.923 (<.0001)

0.951 (<.0001)

Education in 1970-1997

-0.746 (0.0001)

0.824 (<.0001)

0.120 (0.208)

0.091 (0.303)

-0.026 (0.762)

-0.019 (0.818)

0.964 (<.0001)

0.989 (<.0001)

0.975 (<.0001)

Power Distance 0.682 (<.0001)

-0.616 (<.0001)

-0.002 (0.984)

-0.018 (0.904)

-0.043 (0.765)

-0.004 (0.977)

-0.594 (<.0001)

-0.618 (<.0001)

-0.627 (<.0001)

-0.591 (<.0001)

Individualism/Collectivism

-0.702 (<.0001)

0.742 (<.0001)

-0.122 (0.418)

-0.030 (0.833)

-0.151 (0.295)

-0.136 (0.344)

0.686 (<.0001)

0.666 (<.0001)

0.749 (<.0001)

0.669 (<.0001)

-0.647 (<.0001)

Democracy -0.686 (<.0001)

0.689 (<.0001)

0.104 (0.366)

0.061 (0.585)

0.071 (0.528)

0.091 (0.413)

0.709 (<.0001)

0.673 (<.0001)

0.737 (<.0001)

0.704 (<.0001)

-0.688 (<.0001)

0.721 (<.0001)

Political Constraint -0.607 (<.0001)

0.579 (<.0001)

0.103 (0.315)

0.075 (0.429)

-0.026 (0.776)

-0.018 (0.840)

0.648 (<.0001)

0.596 (<.0001)

0.611 (<.0001)

0.610 (<.0001)

-0.449 (<.0001)

0.533 (<.0001)

0.825 (<.0001)

Rule of Law -0.801 (<.0001)

0.703 (<.0001)

0.050 (0.694)

0.175 (0.151)

0.074 (0.542)

0.120 (0.322)

0.632 (<.0001)

0.571 (<.0001)

0.608 (<.0001)

0.583 (<.0001)

-0.645 (<.0001)

0.693 (<.0001)

0.524 (<.0001)

0.420 (<.0001)

26

Table 3: FDI and Corruption

I II III IV V VI VII VIII IX X XI XII XIII XIV XV

FDI

FDI in 1970s -0.191b

(0.095) -0.169c

(0.092) -0.186

(0.117)

FDI in 1980s -0.289a

(0.088) -0.313a

(0.086) -0.359a

(0.092) -0.322a

(0.092)

FDI in 1990s -0.206a

(0.066) -0.197a

(0.064) -0.198b

(0.019) -0.162b

(0.076)

FDI in 70-1997 -0.281a

(0.088) -0.269a

(0.085) -0.327a

(0.103) -0.263b

(0.102) Education Education in 1970s -0.016b

(0.008) -0.0.13

(0.011)

Education in 1980s -0.013b

(0.006) -0.014c

(0.008) -0.023b

(0.009)

Education in 1990s -0.016b

(0.006) -0.019b

(0.008) -0.025a

(0.008)

Education in 70- 1997

-0.015a (0.006)

-0.016b

(0.008) -0.019b

(0.008) Political Tradition Democracy -0.091

(0.071) -0.149b

(0.063) -0.107 (0.065)

-0.117c

(0.064) -0.066 (0.051)

-0.003 (0.054)

-0.035 (0.050)

Political Constraint 0.798 (0.759)

0.619 (0.703)

0.788 (0.718)

0.719 (0.708)

0.305 (0.777)

0.426 (0.779)

0.341 (0.786)

Legal Environment

Rule of Law -0.281a

(0.094) -0.273a

(0.088) -0.276a

(0.089) Legal Formalism 0.285b

(0.094) 0.323b

(0.133) 0.302b

(0.137) GDP per Capita -0.0004a

(2E-5) -0.0004a

(2E-4) -0.0004a

(2E-4) -0.0004a

(2E-4) -0.0004a

(5E-5) -0.0004a

(4E-5) -0.0003a

(4E-5) -0.0004a

(3E-5) -0.0004a

(6E-5) -0.0003a

(5E-5) -0.0003a

(5E-5) -0.0001a

(4E-5) -0.0001b

(7E-5) -0.0001b

(7E-5) -0.0002a

(6E-5)

Adjusted R-Square 0.78 0.79 0.79 0.79 0.80 0.81 0.82 0.81 0.80 0.83 0.82 0.82 0.86 0.85 0.84 Sample 87 96 100 100 84 92 95 99 66 68 69 71 56 57 59

a Significant at 1 per cent; b significant at 5 per cent; c significant at 10 per cent. The figures in parentheses are standard errors.

27

Table 4: FDI and Corruption – Channels of Influence I II III IV V VI VII VIII IX X XI

Culture Power Distance

0.040a

(0.009)

0.035a

(0.010)

0.036a

(0.011)

0.026b

(0.012)

Individualism/Collectivism 0.000 (0.009)

0.005 (0.009)

0.011 (0.012)

0.017 (0.012)

Education Education in 70-1997

-0.021b

(0.009)

-0.024b

(0.010)

-0.023b

(0.010)

-0.0221b

(0.008

-0.023b

(0.010)

-0.024b

(0.010)

-0.009 (0.006)

-0.021c

(0.010)

0.021c

(0.010) FDI X Power Distance Interactions

FDI in 1970-1997 X Power Distance

-0.006a

(0.002) -0.006a

(0.001) -0.006a

(0.002) -0.004b

(0.001)

FDI X Individualism/Collectivism Interaction

FDI in 70-1997 X Individualism/Collectivism

-0.014a

(0.003) -0.013a

(0.003) -0.015a

(0.003) -0.010b

(0.004)

FDI X Education Interaction FDI in 70-1997 X Education

in70-1997

-0.006a

(0.002)

-0.007a

(0.002)

-0.004b

(0.002)

Political Tradition Democracy

0.011 (0.091)

0.088 (0.102)

-0.033 (0.091)

0.0311 (0.094)

-0.066 (0.085)

0.040 (0.099)

Political Constraint -0.216 (0.948)

-0.175 (0.970)

-0.483 (0.979)

-0.194 (0.980)

-0.305 (0.996)

-0.128 (1.005)

Legal Environment Rule of Law

-0.195 (0.119)

-0.238b

(0.116)

-0.238c

(0.121) Legal Formalism 0.276

(0.189) 0.325

(0.213) 0.327

(0.198) GDP per Capita -0.0003a

(4E-5) -0.0003a

(5E-5) -0.0003a

(5E-5) -0.0002a

(7E-5) -0.0004a

(5E-5) -0.0003a

(5E-5) -0.0003a

(6E-5) -0.0003a

(7E-4) -0.0003a

(3E-5) -0.0003a

(6E-5) -0.0002a

(7E-5)

Adjusted R-Square 0.83 0.85 0.83 0.84 0.83 0.84 0.82 0.84 0.83 0.81 0.83 Sample 48 48 42 42 48 48 42 42 99 42 42

a Significant at 1 per cent; b significant at 5 per cent; c significant at 10 per cent. The figures in parentheses are standard errors.

28

Table 5: Robustness Tests

FDI as a dummy Variable Instrumental Variables I II III IV V

VI VII VIII

FDI in 1970-1997 -0.535b

(0.182) -1.221a

(0.342)

Culture Power Distance

0.026b

(0.012)

0.025b

(0.012)

Individualism/Collectivism 0.027 b (0.013)

0.026b

(0.012)

Education in 70-1997 -0.015c

(0.008) -0.014

(0.010) -0.022b

(0.010) -0.013

(0.011) -0.016b

(0.008) -0.017

(0.010) -0.023b

(0.010) -0.006 (0.011)

FDIXPD Interaction

FDI in 1970-1997 X Power Distance

-0.011b

(0.004) -0.013

(0.008)

FDI X IC Interaction

FDI in 70-1997XIC -0.010b

(0.004)

-0.014b

(0.005)

FDI X Education FDI in 70-1997 X Education in 70-1997

-0.007b

(0.003)

-0.010b

(0.004)

Political Tradition Democracy

-0.058 (0.072)

0.066

(0.099)

0.041

(0.093)

0.068

(0.093)

0.023

(0.071)

0.161

(0.100)

0.107

(0.093)

0.121

(0.091) Political Constraint 0.533

(0.775) 0.386

(0.939) 0.121

(0.956) 0.112

(0.980) 0.266

(0.735) 0.030

(0.994) -0.016 (0.946)

-0.047 (0.969)

Legal Environment Rule of Law

-0.256a

(0.088)

-0.258b

(0.111)

-0.273b

(0.112)

-0.251b

(0.116)

-0.237a

(0.086)

-0.249b

(0.119)

-0.270b

(0.110)

-0.262b

(0.113) Legal Formalism 0.316b

(0.133) 0.307

(0.174) 0.458b

(0.185) 0.362c

(0.182) 0.382a

(0.129) 0.429b

(0.174) 0.564a

(0.176) 0.467a

(0.168) GDP per Capita -0.0002a

(6E-5) 0.0002a

(7E-5) 0.0003a

(7E-5) 0.0002a

(7E-5) -0.00008

(6E-5) -0.0002b

(8E-5) -0.0002a

(7E-5) -0.0002a

(7E-5) Adjusted R-Square 0.85 0.84 0.85 0.84 0.85 0.83 0.84 0.83 Sample 59 42 42 42 57 42 42 42

a Significant at 1 per cent; b significant at 5 per cent; c significant at 10 per cent. The figures in parentheses are standard errors.

29

Table 6: FDI and Change of Corruption

Corruption as a Change I II III IV

FDI in 1970-1997 -0.595a

(0.221)

Culture Power Distance

0.064b

(0.024)

Individualism/Collectivism 0.051 c (0.026)

Education in 70-1997 -0.043a

(0.017) -0.047b

(0.019) -0.054b

(0.021) -0.040 c

(0.021) FDIXPD Interaction

FDI in 1970-1997 X Power Distance

-0.010a

(0.004)

FDI X IC Interaction

FDI in 70-1997XIC -0.020b

(0.0086)

FDI X Education FDI in 70-1997 X Education

in 70-1997

-0.011b

(0.005)

Political Tradition Democracy

-0.090 (0.152)

0.174

(0.198)

0.025

(0.186)

0.034

(0.193) Political Constraint 0.714

(1.709) -1.703 (2.127)

-1.115 (2.121)

-1.516 (2.230)

Legal Environment Rule of Law

-0.631a

(0.175)

-0.401c

(0.231)

-0.549b

(0.227)

-0.485b

(0.237) Legal Formalism 0.667b

(0.289) 0.715 c (0.387)

0.906c

(0.481) 0.733c

(0.409)

GDP per Capita -0.0003a

(1E-4) 0.0004a

(1E-4) 0.0005a

(1E-4) 0.0004a

(1E-4)

Adjusted R-Square 0.86 0.86 0.85 0.84

Sample 54 40 40 40

a Significant at 1 per cent; b significant at 5 per cent; c significant at 10 per cent. The figures in parentheses are standard errors.

30

Appendix 1: Variables and Sources Variables Definition Sources Dependent Variables: Corruption

A measure of the corruption perception. Corruption is defined as abuse of public office, and the corruption index measures the corruption perception based on survey of business people and analysts. The measure is rescaled from the original by taking the difference from 10. The values are averages over the period 2000 through 2004

Source: Transparency International (various issues)

Independent Variable: FDI to GDP ratio (%) in 70s, 80s, 90s and 1970-1997

Foreign direct investment is inflows of investment to acquire a lasting management interest (10 percent or more of voting stock) in an enterprise operating in an economy other than that of the investor. It is the sum of equity capital, reinvestment of earnings, other long-term capital, and short-term capital as shown in the balance of payments. The values are decade averages over 1970s, 1980s, 1990s and over the period 1970 through 1997.

Source: World Bank (1999)

Education (in 70s, 80s, 90s, and 1970-1997)

Gross secondary enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. It is measured as secondary school enrollment at a fraction of the age group eligible to the level of education. The values are decade averages over the 1970s, the 1980s, the 1990s and overall average over the period 1970 through 1997.

Source: World Bank (1999)

Culture Power Distance Individualism/Collectivism

Hofstede’s cultural value that reflects the response of people to inequality. It represents the extent to which the less powerful members of society accept, expect or prefer injustice.

Hofstede’s cultural value that reflects the degree to which people in society are primarily concerned with their own self-interest over that of the collective.

Source: Hofstede (2001) Source: Hofstede (2001)

Control Variables Per capita GDP

The logarithm of average per capita GDP

Source: World Bank (1999)

Democracy Political Constraints

A measure of the degree of democracy in a given country based on: (1) the competitiveness of political participation; (2) the openness and competitiveness of executive recruitment; and (3) the constraints on the chief executive. The variable ranges from zero to ten, where higher values equal a higher degree of institutionalized democracy. This variable is calculated as the average from 1960 through 2000, or for specific years as needed in the tables. A measure of the extent of institutionalized constraints on the decision making of political actors. The values are averages over 1970 through 2000

Source: Jaggers and Marshall (2000). Source: Henisz (2000)

Rule of Law Legal Formalism

A measure of the prevalence of law and order and is based on the Political Risk Services Group’s International Country Guide (various issues), on a scale of 0 to 10. The index measures substantive and procedural statutory intervention in judicial cases at lower-level civil trial courts, and is formed by adding up the following indices: (i) professionals vs. laymen, (ii) written vs. oral elements, (iii) legal justification, (iv) statutory regulation of evidence, (v) control of superior review, (vi) engagement formalities, and (vii) independent procedural actions. The index ranges from 0 to 7, where 7 means a higher level of control or intervention in the judicial process.

Source: Djankov et al. (2003) Source: Djankov et al. (2003)

Instrumental Variables Telephone Lines Electricity Consumption

Telephone lines are the total number of fixed lines and mobile phone subscribers (per 1,000 people). Fixed lines are telephone mainlines connecting a customer's equipment to the public switched telephone network. Mobile phone subscribers refer to users of portable telephones subscribing to an automatic public mobile telephone service using cellular technology that provides access to the public switched telephone network. The values are averages over 1970 through 1997.

Electric power consumption measures the production of power plants and combined heat and power plants, less distribution losses, and own use by heat and power plants per capita. The value is average over 1970 through 1997.

Source: World Bank (1999) Source: World Bank (1999)

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