The Impact of Corruption on International Trade
Shirazi, Moiz A., Denver Journal of International Law and Policy
The issue of corruption is a continuing one in legal literature and is the premise of many laws, regulations, and international norms, such as the Foreign Corrupt Practices Act ("FCPA"), the Organisation of Economic Cooperation and Development ("OECD") Anti-Bribery Convention, the UK Bribery Act, the United Nations anti-corruption rules, as well as local anti-corruption laws and regulations. All of these measures aim to deter corrupt practices and encourage, and often require, multinational corporations to implement policies and procedures to not only monitor the behavior of employees, but also the actions of third parties, including, but not limited to, business partners, suppliers, and potential acquisition targets. These laws and regulations are often backed by strong enforcement mechanisms that can lead to severe fines and punishment for multinational corporations and individuals engaging in, or failing to identify and prevent corrupt practices.
While most, if not all, developed countries have adopted these international norms and have well established cultures of enforcement, the countries designated as emerging and frontier markets have only recently started to tackle the issue of corruption. For these markets, it is vitally important to get ahead of the corruption issue as not tackling corruption can come at a high economic price. As these countries compete for international trade opportunities, they should assign a high priority to combating corruption, as a high perception of corruption is strongly correlated with low levels of international trade. As shown in this article, a significant reduction in the perception of corruption for certain countries can have as much, if not more, of an impact on international trade as favorable labor laws, tax rates, and capital (currency) control measures.
In this article, we affirm the link between perceptions of corruption and perceptions regarding ease of doing business. Having established this link, we conduct a comparative analysis of the countries considered to be emerging or frontier markets based on perceptions of corruption and ease of trading across borders, as well as an analysis of actual levels of international trade per capita for each market. Based on the takeaways from this comparison, we identify the countries that could have the most to gain from combating corruption and quantify the possible impact on international trade levels from improvements in the perception of corruption.
II. CORRELATION BETWEEN CORRUPTION AND EASE OF TRADE
In general, corruption, or the perception of corruption, is highly correlated with perceptions regarding difficulty of trade. Figure 1 below illustrates this point by comparing the ranking of 178 countries based on Transparency International's ("TI") Corruption Perception Index ("CPI") (1) for 2010 to the ranking of the same countries based on the ease of Trading Across Borders as reported in the Ease of Doing Business Index (2) for 2010 as published by the World Bank. A higher number on TI's CPI equates to a lower perception of corruption. Singapore has the highest value of 9.3 (perceived as least corrupt) and Afghanistan has the lowest value of 1.4 (perceived as the most corrupt). A higher number on the Trading Across Borders category of the Ease of Doing Business Index translates to a worse perception in regards to the ease of conducting international trade, meaning that countries with the highest value are considered to be the least business friendly jurisdictions for international trade. Based on 2010 data, Singapore has the lowest value and is considered to be the most business friendly and Afghanistan has the highest value and is considered the most difficult place to conduct international trade.
[FIGURE 1 OMITTED]
As TI's CPI is one of many indices that aim to provide cross-country indicators of levels of corruption, we also present a comparison of the World Bank's Worldwide Governance Indicators ("WGI") to the Trading Across Borders data in figure 2. …