National competitiveness and perception of corruption.

INTRODUCTION

The advent of the forces of globalization has led most nations of the world to open their economies to market forces. This has also enabled international capital and expertise to flow across borders. Many national governments eager to obtain a share of such capital and expertise and to spur economic growth have put in place public policies and programs that encourage private enterprise and foreign investment. Potential investors now have a wider range of countries to choose from to locate their business facilities or to put in their resources for profit. Not all countries are equally attractive to foreign investors; some are more than others. Increasingly, countries are being calibrated on the basis of how competitive they are as places to do business in.

The conduct of international business in many places of the world is accompanied by bribe giving. Bribery is defined as "the offering, promising, or giving something in order to influence a public official in the execution of his/her official duties" (OECD Observer, 2000). Bribes take the form of money, other pecuniary advantages, such as a scholarship for a child's college education, or non-pecuniary benefits, such as favorable publicity. Bribery has been one of the enduring ethical challenges in international business. It is generally acknowledged that bribery undermines public and business confidence, breeds cynicism, increases inefficiency, and leads to other crimes such as money laundering (Theobald, 1990). Honest businesses lose out in obtaining contracts because of their refusal to acquiesce to corrupt practices. Bribes also add to the costs of doing business and extensive corruption in a country tends to depress investment and economic growth (Mauro, 1997).

Given this, the competitive status of a nation can be hurt if bribery is part of the prevailing culture of doing business in that country. Rampant bribe taking in certain countries will likely discourage investment and orderly business activities. Investors are likely to bypass such countries for those that are perceived to have a more ethical business climate. Thus, the competitiveness of a nation can be affected by the level of bribe taking activity prevalent therein. It is this relationship that this paper examines.

INTERNATIONAL COMPETITIVENESS

As national economies have deregulated, privatized, and opened up to international competition, countries have become conscious of the need to adopt policies that will create a favorable climate for business activities and offer incentives that will encourage foreign investments. Countries are often in a race with each other to attract resources to enhance their economic wellbeing. Competitiveness of nations may be defined as the facts and policies that shape the ability of a nation to create and maintain an environment that sustains more value creation for its enterprises and more prosperity for its people. It implies that businesses depend a great deal on the national environment in which they operate. However, competitiveness is not a zero sum game--enhanced competitiveness of one country does not have to come at the expense of another; many countries can improve their productivity and prosperity at the same time. Of course, some countries support competitiveness more than others by actively creating and maintaining a climate that facilitates the competitiveness of firms and encourages long-term sustainability.

Porter (1990) has written extensively on the subject of national competitiveness. He argues that a country's competitiveness "depends on the capacity of its industry to innovate and upgrade." Based on extensive studies in industries in several countries, he concludes, "Nations succeed ... because their home environment is the most forward looking, dynamic, and challenging." Porter goes on to argue that a country's standard of living depends on the ability of its companies to achieve high levels of productivity over time. Sustained productivity growth requires that an economy continue to upgrade itself to enable businesses to take advantage of these upgraded assets. In his famous "diamond of national advantage," Porter identifies four interacting determinants of national advantage: factor conditions, demand conditions, related and supporting industries, and firm strategy, structure, and rivalry--which creates the environment in which companies are born and learn how to compete.

Governments have an important role to play in creating this nurturing environment. They craft policies that serve as a catalyst to challenge companies to raise their sights and move them to higher levels of performance. The appropriate role of governments is to encourage change, promote domestic rivalry, and stimulate innovation. An open economy contributes to this environment by encouraging foreign inflow of investment and technologies. Fitzgerald (2002) reported that the development of an entrepreneurial culture, so essential for development, faced a major hurdle in the form of corruption in the transition economies of Central and Eastern Europe.

Several studies have indicated the relationship between perceived levels of bribery in a country and flows of foreign direct investment therein. Wei (2000) looked at bilateral investment from 12 source countries to 45 host countries and found that a rise in the corruption level in a host country reduced inward foreign direct investment there. A study by Habib and Zurawicki (2002) looked at aggregate investment flows from seven countries among themselves and 82 other countries over a three year period (1996-98) and related those flows to the individual country's perceived level of corruption. They concluded that, "corruption is a serious obstacle to investment." In an undated paper, Smarzynska and Wei studied the impact of corruption in a host country on the preference of foreign investors for a joint venture or a wholly-owned subsidiary. They concluded, based on firm-level data, that corruption reduces foreign direct investment and shifts the ownership structure towards joint ventures.

MEASURE OF INTERNATIONAL COMPETITIVENESS

There are many measures of international competitiveness. One of the most well known is that published annually by IMD, an independent not-for-profit foundation based in Lausanne, Switzerland. IMD is a leading organization in the field of training and preparing managers to lead international companies. Through its annual World Competitiveness Yearbook, IMD ranks the various countries of the world with respect to their business environment (World Competitiveness Year Book, 2004).

Quantitative and qualitative information are gathered separately. Hard data, which represents two-thirds of the overall weight in the final rankings, are statistics from international, national, and regional organizations; for example, the OECD, World Bank, United Nations, WTO, IMF and IMD's own network of 57 partner institutes around the world who provide first hand information on their economies. Soft data, representing the remaining one third of the total weight is compiled from an annual survey of more than 4,000 executives who form a representative cross-section of the business community in each country or region analyzed. The survey is designed to complement the hard data in order to help quantify competitiveness issues that are not easily measured (such as management practices, labor relations, and quality of life).

IMD's World Competitiveness Data (WCD), first published in 1989, has emerged as a major measure in this field. It is the world's most comprehensive study of the competitiveness of nations, ranking and analyzing how a nation's environment sustains the competitiveness of enterprises. The data is used by the business community to assess national environments to decide on investment plans and location choices. National governments use the data to benchmark their own policy successes and to see how other nations are doing. Academicians too have used this information to understand and analyze how nations compete in world markets.

Their annual overall scoreboard shows an economy's competitiveness position relative to those of others. The score, which is on a scale of 100 to 0 where 100 represents the highest degree of competitiveness, is based on 323 competitiveness criteria which are grouped into four factors--economic performance, government efficiency, business efficiency, and infrastructure. For example, economic performance is based on macroeconomic environment, macroeconomic stability, and many other macroeconomic factors. Similarly, business environment is assessed on the basis of physical infrastructure, capital availability, human resources, science and technology, demand conditions, etc. Using such a large number of criteria ensures a clear picture of competitiveness for the countries covered and serves as a security net if any particular criterion is misinterpreted. Also, the impact of any one criterion is limited. Appendix I lists the factors used to assess a nation's competitiveness.

BRIBERY

The most well-known measure of bribery comes annually from Transparency International, a Berlin (Germany) based non-governmental organization committed to combating corruption, in the form of the Corruption Perception Index (CPI) (Transparency International, 2004). This annual index ranks countries in terms of the degree to which corruption (in the form of bribe taking) is perceived to prevail among their public officials and politicians. The CPI draws on 17 different polls and surveys from 10 different institutions carried out among businesspersons, risk analysts, the general public, and country experts. Every year, more and more countries are being assessed.

By being a single composite score ranging from 10 to 0 where 10 means virtually no bribery to 0 where bribery is rampant, the CPI has increased the reliability of the data of each individual source on which it is based. It best captures the perception of the level of bribery in a country as it affects the international businessperson. Note that the CPI is a measure of perception of bribery, not actual levels of bribery. The CPI has emerged as the principal indicator of the state of bribery worldwide and is used by government officials, businesspersons, social activists, and academicians to address this social scourge. An explanatory note on the CPI is provided in Appendix II.

RESEARCH QUESTION

Given the worldwide concern over bribery in international business and the importance of being competitive in a global economy, this paper examines the relationship between these two issues. More specifically, the research question focuses on whether a nation's competitive status is associated with how it is perceived with respect to bribe taking. The paper draws upon data from the World Competitiveness Yearbook and the Corruption Perception Index to answer the question. Data for four years--2000, 2001, 2002 and 2003--were examined. It is hypothesized that there will be a high degree of correlation between the two listings. The competitiveness of a country is likely to be affected by whether bribery is a prevailing part of the culture of doing business in that country. If the perceived level of bribery in a country is high it will discourage foreign investors from going into that country; the business climate in that country would appear to be vitiated. In contrast, in countries where the prevalence of bribe taking to conduct business is low, it signals a more inviting operating environment to businesses. Firms are likely to be more confident of doing business in such a country.

A related issue that is examined in this paper is whether the correlation between high competitive status and low bribe taking and vice versa applies in both developed and developing countries. There is no a priori hypothesis as to whether developed and developing countries will differ with regard to competitiveness. While studies (e.g., Sanyal and Samanta, 2004, 2002) have indicated that countries with high per capita income usually tend to be perceived as less corrupt, the prevalence of bribery is one of many factors that could negatively affect a country's competitive posture. Indeed, in an increasingly open global trading and investing environment, many advanced industrial countries are finding the competition from low-wage, low-tax, and less regulated countries demanding.

RESULTS

A Spearman Rank Correlation test and regression was performed for each of the four years using the two indices--Corruption Perception Index (CPI) and Country Competitiveness Score (CCS). In the regression equation, CPI is the independent variable; it was run for each of the four years and also for the four years together. Table 1 presents the rank correlation results; Table 2 shows the regression results (simple and panel).

To test whether the relationship between the two indices holds up for developed and developing countries, the 2003 data was divided into two groups and a two-group comparison was performed. There were 51 countries--29 developed and 22 developing--in the sample. (The list of countries included in this study is provided in Appendix III). Since this is a cross-sectional analysis, robust errors estimation method was used to estimate the relationship between the two variables. A dummy variable was used to distinguish the two set of countries. These results are reported in Table 3.

The results presented in Table 1 confirm that the listings of countries on the Corruption Perception Index and the Country Competitiveness Index for all four years are positively and significantly correlated. Countries rated as highly competitive are also perceived as less likely to take bribes and vice versa. Recall that a high CPI score means less bribery. A country ranked higher on the CPI list is likely to rank high on the CCI list. That is, countries high in competitiveness are also perceived as less corrupt.

Table 2 confirms the proposition that perception of corruption in a country is a significant variable affecting the competitiveness status of that country. The variable is significant in each of the four years at the 0.05 level. We set up a test where the regression coefficient of the corruption perception index is equal to one. The corresponding t-statistic values are -0.012, -0.0106, -0.0068 and -0.0072 for the year 2000, 2001, 2002 and 2003, respectively. The intercept terms are not significantly different from zero. This clearly shows the extent of the relationship between these two variables. So, the results presented in Tables 1 and 2 confirm that the listings of countries on the Corruption Perception Index and the Country Competitiveness Score for all four years are positively and significantly correlated. A country ranked higher on the CPI list is likely to rank high on the CCS list. That is, countries high in competitiveness are also perceived as less corrupt.

This conclusion is further corroborated when we take into consideration all the four years together (Part B results in Table 2). Simple regression results show that the coefficient of the CPI is significant. The constant term also becomes significant, implying the existence of other factors that affect national competitiveness in addition to the perceived prevalence of corruption. A fixed effects model panel estimation was done to incorporate the possible individual effects of each country (separate country effects are not reported here). Here too, the results indicate that corruption is a significant factor in influencing the competitiveness of an economy.

Looking at Part A results for 2003, the absolute value of the coefficient for the variable CPI is 0.899. Note that in the multiyear estimation (Part B), it declines to 0.477. Thus, the coefficient of CPI is significantly different from 1 (t statistic is -20.74). This means that the CPI does not explain entirely the competitiveness of nations--there are other factors. When individual country effects (panel data estimation) are incorporated, the coefficient decreases to 0.158. This is further evidence that while perception of corruption is a significant factor affecting a nation's competitiveness, there are other important explanatory variables too.

To test whether the relationship between the two indices (CPI and CCS) hold up for developed and developing countries, we incorporated a dummy variable (where 1 = developed country, 0 = developing country) to capture the status of development of a national economy. The criterion used for determining a country's development status was taken from the World Bank which uses per capita GDP of less than USD 11,000 to indicate underdevelopment. The statistical results are presented in Table 3.

The Part A results are from a linear regression model where all the data (countries and time periods) are pooled together. Comparing the regression results of Table 3 with Table 2 (Part B), note that the coefficient of the Corruption Perception Index has changed from 0.477 to 0.31, but it is still highly significant. Not only that, the coefficient of the dummy variable of the developed countries is also significant (coefficient of -11.427 with a p-value of 0.00). Since the coefficient of developed countries is significant, it implies there is a statistical discrepancy between the developed and developing countries. However, the negative sign suggests that a country with a very high per capita income is not always a highly competitive country.

In Part B of Table 3, we present the results for a fixed effects panel model. Again, the coefficient of the corruption index is significant (0.31). The dummy variable is also significant and it is negative (-11.66). This reaffirms the results from the linear regression model (Part A).

Overall, the results reported in Table 3 clearly indicates that the more developed a country is, the impact of corruption on its competitiveness is likely to be negative. Given the same level of perceived corruption, a more developed country may be less competitive compared to a less developed country. So, while lower perception of corruption improves national competitiveness, countries with high per capita income may find that their ability to stay ahead and remain highly productive becomes challenging. High labor costs, rigidities in labor market conditions, larger tax burdens to support aging populations, the obligations of a welfare state and many regulations in many wealthy countries may indeed contribute to a blunting of their competitive edge. It appears that competitiveness is also affected by the development stage of the economy. Thus, whether a country is developed or developing, the relationship between these two variables (competitiveness and perceived corruption) remains the same across the countries. However, countries that are more developed are likely to be less competitive and many less developed countries are proving to be competitive, thanks to liberal trade and investment regimes, lower input costs, and fewer legacy obligations.

ANALYSIS

The results indicate full support for the research propositions tested in this study. A country's competitive status matches its rating with respect to bribe taking. A country high on competitiveness is less likely to have a culture of bribery in its business practices. Similarly, a country ranked low on competitiveness is likely to be perceived as a corrupt place to do business where bribery is widespread. The results are consistent over time. This relationship between competitiveness and bribery does hold up even when the sample is broken down into developed and developing countries. But countries with high per capita income are not necessarily highly competitive and less wealthy countries may have policies and endowments that mark them as competitive. Indeed, developing countries seeking to raise its citizen's living standards would be expected to adopt policies and create the conditions that lead to faster economic growth and consequently be friendly to investment and trade. Although the results suggest that there are many determinants of national competitiveness, it is clear that high levels of perceived corruption in a country hurts that country's competitive profile.

One of the major implications of this finding is that national governments need to pay attention to the prevalence of bribery in conducting business in its territories and how the country is perceived by the rest of world on this metric. Reducing the practice of bribery and cleaning up the image goes a long way to ensure competitiveness. Countries that want to be competitive and attract foreign investment need to address this issue of bribery. Obviously, this is a more pressing issue for countries which are perceived very negatively on the Corruption Perception Index. However, reducing bribery is not a simple task. A combination of measures needs to be adopted to address this problem and the results may bear fruit only over the long haul.

A second implication is that for businesspersons and foreign investors, these indices of bribery and competitiveness send out very meaningful signals about particular countries. These signals influence decisions on where to invest or where not to invest and thus provide for a more informed assessment of country risk and the cost of doing business. A country ranked high in competitiveness can assure the potential foreign businessperson that the likelihood that s/he would have to give bribes to conduct business in this particular country is very low or nonexistent. Conversely, a low competitiveness ranking is intimately associated with a high incidence of bribe taking. Similarly, the international businessperson, looking at a country ranked high in the Corruption Perception Index (which means there is little or no bribery there) is likely to conclude that that country has characteristics that make it very competitive. The same businessperson would be correct in assuming that a country which is perceived as one where bribe giving is rampant also lacks the other essential elements that contribute to a place being an attractive destination for investment--that is, the country is not highly competitive.

A third implication is that countries with high per capita income may not always have the policies and practices to be currently competitive. Less developed countries, desiring to enhance the living standards of their population, may be putting in place the enabling infrastructure to lure investors, provide quality and cost-effective inputs, and deregulate practices. Thus, from an investment perspective, a businessperson would be wise to consider per capita income as only one factor in the decision-making process.

CONCLUSION

Both national competitiveness and bribery in international business have moved to the top of the agenda of national government leaders, corporate leaders, advocacy groups, and international financial institutions. The need to improve national competitiveness as a prerequisite for raising living standards and the barrier that bribe taking poses towards achieving that goal have been recognized. This study confirms the relationship. Policy makers need to continue to address how bribery can be reduced or even eliminated in the conduct of international business. It hurts developed and developing countries alike.

APPENDIX I

Criteria for Competitiveness

ECONOMIC PERFORMANCE

* Domestic Economy

* International Trade

* International Investment

* Employment

* Prices

GOVERNMENT EFFICIENCY

* Public Finance

* Fiscal Policy

* Institutional Framework

* Business Legislation

* Societal Framework

BUSINESS EFFICIENCY

* Productivity

* Labor Market

* Finance

* Management Practices

* Attitudes and Values

INFRASTRUCTURE

* Basic Infrastructure

* Technological Infrastructure

* Scientific Infrastructure

* Health and Environment

* Education

Source: World Competitiveness Year Book. (2004). IMD. Lausanne: Switzerland Retrieved March 2004 from www.imd.ch/wcy.

APPENDIX II

Corruption Perception Index Explanatory Note

1. The CPI gathers data from sources that span the last three years (for the CPI 2003, this includes surveys from 2001, 2002 and 2003).

2. All sources provide a ranking of countries, i.e., include an assessment of multiple countries.

3. All sources measure the overall extent of corruption (frequency and/or size of bribes) in the public and political sectors.

4. For CPI sources that are surveys, and where multiple years of the same survey are available, all annual data are included to provide a smoothing effect.

5. For sources that are scores provided by experts (risk agencies/country analysts), only the most recent iteration of the assessment is included, as these scores are generally peer reviewed and change very little from year to year.

6. Evaluation of the extent of corruption in countries is done by country experts, non resident and residents (in the CPI 2003, this consisted of the following sources: Columbia University, EIU, FH, MIG, UNECA and WMRC); non-resident business leaders from developing countries (in the CPI 2003, this consisted of the following sources: Information International); and resident business leaders evaluating their own country (in the CPI 2003, this consisted of the following sources: IMD, PERC, and World Economic Forum).

7. To determine the mean value for a country, standardization is carried out via a matching percentiles technique. This uses the ranks of countries reported by each individual source. This method is useful for combining sources that have a different distribution. While there is some information loss in this technique, it allows all reported scores to remain within the bounds of the CPI, that is to say, to remain between 0 and 10.

8. A beta-transformation is then performed on scores. This increases the standard deviation among all countries included in the CPI and avoids the process by which the matching percentiles technique results in a smaller standard deviation from year to year.

9. Next, all values for a country are averaged, to determine a country's score.

10. The CPI score and rank are accompanied by the number of sources, high-low range, standard deviation and confidence range for each country.

11. The confidence range is determined by a bootstrap (non-parametric) methodology, which allows inferences to be drawn on the underlying precision of the results. A 90% confidence range is then established, where there is 5% probability that the value is below and 5% probability that the value is above this confidence range.

12. Research shows that the unbiased coverage probability for the confidence range is lower than its nominal value of 90%. The accuracy of the confidence interval estimates increases with a growing number of sources: for 3 sources, 65.3%; for 4 sources, 73.6%; for 5 sources, 78.4%; for 6 sources, 80.2%; and for 7 sources, 81.8%.

13. The overall reliability of data is demonstrated in the high correlation between sources. In this regard, Pearson's and Kendall's rank correlations have been performed, which provided average results of .87 and .72 respectively.

Source: Transparency International. (2004). Corruption Perception Index. Retrieved March 2004 from www.transparency.org.

APPENDIX III

Countries included in the Study (51)

Argentina, Australia, Austria, Belgium, Brazil, Canada, Chile, China, Colombia, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hong Kong, Hungary, Iceland, India, Indonesia, Ireland, Israel, Italy, Japan, Jordan, Luxembourg, Malaysia, Mexico, Netherlands, New Zealand, Norway, Philippines, Poland, Portugal, Romania, Russia, Singapore, Slovakia, Slovenia, South Africa, South Korea, Spain, Sweden, Switzerland, Taiwan, Thailand, Turkey, United Kingdom, United States of America, and Venezuela

REFERENCES

Fitzgerald, Elizabeth. (2002). Identifying variables of entrepreneurship, privatization, and competitive skills in Central Europe: A survey design. Competitiveness Review, 12(1), 53-65.

Habib, Mohsin., & Zurawicki, Leon. (2002). Corruption and foreign direct investment. Journal of International Business Studies, 33(2), 291-307.

Mauro, P. (1995). Corruption and growth. Quarterly Journal of Economics, 110(3), 681-712. OECD Observer. (2000, September). The fight against bribery and corruption. Paris: OECD.

Porter, Michael E. (1990, March-April). The competitive advantage of nations. Harvard Business Review, 73-93.

Sanyal, Rajib., & Samanta, Subarna. (2002). Corruption across countries: The cultural and economic factors. Business and Professional Ethics Journal, 21(1), 21-46.

--. (2004). Determinants of bribery in international business. Thunderbird International Business Review, 46(2), 133-148.

Smarzynska, Beata., & Wei, Shang-Jin. (Undated). Corruption and composition of foreign direct investment: Firm-level evidence. Washington, DC: The World Bank.

Theobald, Robin. (1990). Corruption, development and underdevelopment. Durham, NC: Duke University Press.

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

World Competitiveness Year Book. (2004). IMD. Lausanne: Switzerland Retrieved March 2004 from www.imd.ch/wcy.

Transparency International. (2004). Corruption perception index. Retrieved March 2004 from www.transparency.org.

Subarna K. Samanta ([e-mail]) is Professor of Economics at the School of Business at The College of New Jersey, PO Box 7188, Ewing, NJ 08628, USA.

Rajib N. Sanyal ([e-mail]) is Professor of Management and Dean of the College of Business, Northern Michigan University, 1401 Presque Isle Avenue, Marquette, MI 49855, USA.

TABLE 1
Spearman Rank Correlation (All Years)

Year   Rank Correlation   t-value   p-value

2000        0.736          11.45     0.00
2001        0.759          12.45     0.00
2002        0.812          14.27     0.00
2003        0.809          14.12     0.00

TABLE 2
Regression Results (Ranks of Corruption Perception Index and Country
Competitiveness Score) by Year

Variable                      Co-efficient   T-Statistic   Significance

Part A: Individual Years

Year 2000
Constant                      3.547          1.648         0.106
Corruption Perception Index   0.858          11.45         0.000
Centered R Square = 0.736

Year 2001
Constant                      3.222           1.565        0.124
Corruption Perception Index   0.871          12.154        0.000
Centered R Square = 0.759

Year 2002
Constant                      2.459           1.355        0.182
Corruption Perception Index   0.902          14.265        0.000
Centered R Square = 0.812

Year 2003
Constant                      2.502           1.367        0.178
Corruption Perception Index   0.899          14.118        0.000
Centered R Square = 0.736

Part B: Four years (2000-03) taken
together Simple linear regression model -
Constant                      10.044          9.576        0.000
Corruption Perception Index    0.477         18.903        0.000
Centered R Square = 0.650

Panel model -
Constant                      37.341         12.11         <.0001
Corruption Perception Index    0.158          4.99         <.0001

TABLE 3
Regression Results for Developed and Developing Countries (All Years
Taken Together)

Variable                      Co-efficient   T-Statistic   Significance

Part A: Simple linear regression model
Constant                       21.82          10.55        0.00
Corruption Perception Index     0.31           9.03        0.00
Dummy Variable (Developed)    -11.427         -6.42        0.00
Centered R Square = 0.712

Part B: Panel model
Years 2000-2003: All the years taken together in a Panel Model
Constant                       22.195         78.776       0.00
Corruption Perception Index     0.31          67.566       0.00
Dummy Variable (Developed)    -11.66         -47.611       0.00