Submerging Markets™

 

IMF: Emergency Banker to the World, or to W. Europe and FSU?

As of 2015, not only is the IMF a leading lender to eight tiny Caribbean havens and Cyprus,[i]  with more than $752 million outstanding to them at very low interest rates.  In addition, more than two-thirds of the IMF's total loans outstanding went to just three developedcountries in Western Europe and the former Soviet Union:  Portugul, Greece and the Ukraine.

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[i] As of September 2015, the IMF had outstanding credits to the following tax havens:  Antigua ($43.4mm), Cyprus ($594mm), Dominica ($5.4mm), Grenada ($21mm), the Seychelles ($30mm),  St. Kitts ($ 22mm ), St. Lucia ($9.7 ), St. Vincent ($10.5) and Vanuatu ($17mm). These are priced at real interest rates that are close to zero.  See IMF (2015), http://www.imf.org/external/np/fin/tad/balmov2.aspx?type=TOTAL.

 

IMF's top 10 Debtors: W. Europe plus Failing States?

On the verge of the annual IMF/World Bank meetings in Lima in October 2015

The first time the meetings have been held in a developing country that is not a tax haven!

Let's recall who really runs the IMF.  

 

Hint: havens and creditors!  Those those of you who expect the IMF or the OECD to assist the tax justice reform movement should wake up and smell the Peruvian coffee! 

 

(Fast Capitalism is speeding up, creating more excess every day. To keep up, please follow us on Twitter: @submergingmkt)

 

Rethinking Spillovers of Tax Evasion and Trade Discrepancies

Case of China, Hong Kong and the Republic of Korea

Seung Won Suh

(Columbia Center on Sustainable Investment--Supervised by James S. Henry, Esq.)

Full report including the analysis of all appendixes & tables can be provided, upon request 

(contact to [email protected])

Lost Tax Revenue in Developing Countries

Tax revenue losses due to tax evasion in developing countries are significant in terms of the international components including profit shifting by corporations and offshore holdings of financial assets by private individuals. As capital becomes more mobile, developing countries are dealing with new international  challenges, such as taxing multinational enterprises effectively, building effective transfer pricing regimes, establishing and using information sharing agreements to obtain tax information about their taxpayers from other countries, and managing tax incentives to attract international investors (OECD, 2014).

Estimates of the level of tax evasion are based on measures of the size of the shadow economy (Fuest and Riedel, 2009). In the context of taxation, the term ‘shadow economy’ can be defined as unreported income from the production of legal goods and services, either from monetary or barter transactions, hence all economic activities that would generally be taxable, were they reported to the tax authorities (Schneider and Enste, 2000). Cobham’s (2005) approach[1*] based on macro indicators of shadow economy presents explicit consequences of lost tax revenue in developing countries. Shadow economies are mounting due to weakness of tax administration and policy structure in developing countries. For example, Bangladesh loses around $2 billion every year because of the tax evasion and profit shifting by the MNCs who evade taxes through the abuse of transfer pricing or mispricing in different ways including capital flight, transfer of dividend and profit to its permanent establishments including over and under-invoicing during transactions of goods and services within their associated enterprises  (EquityBD, 2014). Due to consistent expansion of the underground economy, the Bangladesh government cannot collect taxes to build up internal resources and consequently, development expenditures cause domestic budget deficit and financial default. Another example is a set of tax evasion practices of logging companies in the Democratic Republic of Congo (DRC). Details of tax revenues from DRC’s natural resource sector that have been released by the country’s Ministry of Finance over the last year as part of an effort to meet ‘economic governance’ benchmarks agreed with the World Bank are followings: in 2011 and 2012, the Treasury should have received USD 7,470,967 per year but, in fact, it received only USD 3,090,586 in 2011 and USD 777,908 in 2012 (Global Witness, 2013). In other words, USD 11,073,441 were missing for two years because of tax evasion practices. Provincial authorities in the Provinces of Equateur, Bandundu and Orientale - where huge swathes of forest have been allocated for logging – may have expected a welcome boost to their finances for regional development (Global Witness, 2013). However, they could not develop in the absence of these egregious tax abuses by logging companies.

It is difficult for government officials in developing countries to stand against tax evasion activities because illicit financial flows of multinationals and private individuals are often ironically main sources of foreign investment and economic development. However, they need to understand how much their lost tax revenue will impact sustainable economic development. Persistent and prospective potential to develop and engage in fair competition with other developed countries cannot be achieved with an increasing rate of lost tax revenue.

Prior to planning how to avoid vicious cycle of tax evasion practices, it is instrumental to understand how we can identify the underlying symptoms of tax evasion practices. There are a variety of methodologies to track down who are illegally not paying tax yet it is difficult to evaluate what methodology is concise and effective. One methodology presented in this report is to investigate discrepancies in multilateral trade.

Discrepancies in Multilateral Trade

 Trade data of imports and exports have discrepancies in between. The quantity and value of exports from reporting countries are not identical to those of import that partner countries record. Ferratino and Wang (2007) categorize eight possible sources of discrepancies: (1) timing; (2) shipping and insurance costs; (3) general versus special trade in terms of       goods in transit; (4) classification of goods; (5) re-exports; (6) partner country’s attribution and treatment of processing trade; (7) mis-invoicing, transfer pricing, and mis-attribution; and 8) smuggling. Accordingly, researchers add hypotheses to reconcile the growing statistical discrepancies: (1) recording of export-and-import trade using inconsistent customs standards of valuation (FOB, FAS and CIF); (2) geographic-coverage inconsistencies; and (3) exchange rate fluctuations.

Ferrato and Wang (2007) present mirror statistics to measure the magnitude of statistical discrepancies. Underlying assumption is that export statistics from one country to its partner countries are equal to import statistics from their partner countries. Suppose that there are three countries in trade relations: A, B, C and D. Country C is regarded as tax haven and Country D includes a set of every country other than A, B and C. There are two sides of mirror: eastbound (Country A to Country B) and westbound (Country B to Country A). Ferrato and Wang categorize five possible trade flows for each side of mirror: (1) Country A’s direct exports to Country B; (2) Country A’s reported exports to Country B via Country C; (3) Country A’s reported exports to Country B via Country D; (4) Country C’s reported domestic exports to Country B; and (5) Country C’s reported re-exports of goods of Country A’s origin to Country B.

Raymond Fisman, professor at Columbia University Business School conducted research of tax evasion models followed with findings on discrepancies in multilateral trade. Tax Rates and Tax Evasion: Evidence from “Missing Imports” in China (2004) and Outsourcing Tariff Evasion: A New Explanation for Entrepôt Trade (2007) identify possible causes of trade discrepancies which are developed from Ferrato and Wang’s hypotheses. Fisman examines the estimated amount of lost tax through indirect trade through an Entrepôt and his econometric analysis of measuring discrepancies is valid and instrumental.

Yet, there are some loopholes that need to be improved. Measures of trade values in transit (transshipment not re-export) and error terms are not reliable. In fact, challenges are raised from the nature of trade data which countries do not track down every flow of commodities transactions. Furthermore, there is no international uniform database developed to explain trade discrepancies and misinvoicing.

Trade misinvoicing is a method for moving money illicitly across borders which involves deliberately misreporting the value of a commercial transaction on an invoice submitted to customs. A form of trade-based money laundering, trade misinvoicing is the large component of illicit financial outflows (Global Financial Integrity Web, 2014). It is possible due to the fact that the trading partners write their own trade documents. Usually, through export under-invoicing and import over-invoicing, corrupt government officials, criminals and commercial tax evaders are able to easily move assets out of countries and into tax havens, anonymous companies and secret bank accounts (Kar and Spanjers, 2014). Multinational corporations do engage in trade misinvoicing and their activities involve the deliberate misreporting of the value of a customs transactions which is illegal tax evasion. 

Multilateral Trade: China, Hong Kong and the Republic of Korea

 

Measuring Discrepancies

According to empirical research of tax evasion using trade data discrepancies, multilateral trade data is provided through UN COMTRADE. The new interface of UN COMTRADE is available online to everyone and aggregate trade data accustomed to any set of preferences is available. In order to examine data availability and discuss about the issues of tax evasion, I conducted an interview with Ronald Jansen, Chief of Trade Statistics Branch and Department of Economic and Social Affairs, United Nations Statistics Division and Luis Gonzales Morales, Statistician on June 30^th (Appendix 7).

United Nations officials suggested me to examine the commodities of at least HS 4 level (6 level is more specified) and conduct bilateral symmetries of fixed continuous time period. There are two choices in commodity categories: SITC and HS[1]. SITC is generally used for high-level analysis and HS codes (varies from 2 to 10 digits) are used in this report. Prior to choose the pilot case of multilateral trade: China, Hong Kong and the Republic of Korea, from the UN COMTRADE, I first selected the Republic of Korea as a reporting country and all other countries as partner countries. The time period was fixed to one year, 2012 and the commodity was chosen as total (HS as reported). All trade values of world’s imports (based on CIF) and Korea’s exports (based on FOB)[2] are measured in US dollars and under-invoicing is calculated from a simple equation: world’s imports-Korea’s exports (Table 1). There are two patterns of this value: (1) positive, which can be noted as “over”-under-invoicing and this is the common outcome; and (2) negative, which can be noted as under-invoicing and this is an unusual outcome. There are a number of cases of this unusual outcome and I found out that Hong Kong is the destination with the largest value of under-invoicing (USD -11,153,938,618). On the other hand, China is the partner country with the largest value of “over”-under-invoicing (USD 34,406,006,712) (Appendix 8, Graph). The difference of these two inequalities is significantly large and I generated more concentrated dataset of fixed variables: multilateral trade of China, Hong Kong and the Republic of Korea in terms of detailed commodities noted as HS codes throughout a fixed time period.

Table 2 is the filtered data set (filtered HS 4 level commodities of large quantities (more than 1,000,000) and values(more than USD 10,000,000) in multilateral trade of China, Hong Kong and The Republic of Korea. I looked at 5-year time interval periods of 2000, 2005, 2010. There was one HS 4 level commodity (HS 7210) that consistently displayed “over”-and under-invoicing in China and Hong Kong. In this report, I term this pattern as a “wicked” trade discrepancy. This pattern might imply that Korean exporting enterprises have evaded paying tax by parking commodities via Hong Kong.

I enlarged the range of HS level to 6 levels within the boundary of HS 7210 and set the time period from 2000 to 2012. Table 3 displays how two commodities, HS721069 (Flat-rolled products of iron/non-alloy steel, of a width of 60mm/more, plated/coated with aluminum) and HS721070 (Flat-rolled products of iron/non-alloy steel, of a width of 60mm/more, painted with plastics) belong to the “wicked” trade discrepancies throughout 13 years (from 2000 to 2012). The differences are significantly large and more comprehensive analysis of detailed data is in need to examine the tax evasion practices through Hong Kong.

Analysis and Results

UN officials at Statistics Division suggested that these discrepancies might have occurred because of the difference in time sequence, amount of tax incentives, repackaging and trade costs including transportation and shipping costs. In response to their recommendations, I outlined the list of interviewees (Appendix 5) and distributed an interview request form in Korean (Appendix 6) to them. 

Throughout the interviews I conducted in remote basis (international call meetings from Columbia Center on Sustainable Investment), I realized that detailed data sets explaining the “wicked” trade discrepancies are not available at ease. Statisticians at Korea Statistical Information Service told me that data regarding tax evasion rate might be available at National Tax Service and Korea Customs Service. However, Ministry of Finance, National Tax Service and Korea Customs Service did not permit me to access the detailed data sets of HS721069 and HS721070 under the “Personal Information Protection Law.” Even, Jaeho Jeong who is a senior researcher at Korea Institute of Public Finance was skeptical of this research due to the difficulties regarding data availabilities. 

From August 5^th to August 21^st, I stayed in Korea and tried to reach out other researchers who are expert on this issue. I had an interview with one of the employees at Korea Iron and Steel Association (Dohyun Kim) and I could find out that big Korean multinational enterprises (POSCO, SEAH Steel Industry and Hyundai Industry) are in charge of trading HS721069 and HS721070. Mr. Kim told me that these commodities require high technology and it is rare that repackaging practices (mostly value added) would occur at Hong Kong. He also argued that tax evasion practices would not be involved in these commodities. 

Based on the information that Mr. Kim provided, I had a meeting with Sanghyung Sim, who is a senior researcher at POSCO Research Institute (POSRI). Since POSCO is the largest firm in trading HS721069 and HS721070 to Hong Kong and China, it was a great opportunity to interview her. She provided a number of answers regarding this issue. She contacted some employees at POSCO’s Hong Kong and China mainland branches and shared their opinions with me. 

According to POSCO employees, the time differences in terms of transactions between Korea and Hong Kong and Korea and China are not large enough (about only 4 or 5 days) to the “wicked” trade discrepancies. They also said that HS 6 digits are specific enough and the value throughout China, Hong Kong and the Republic of Korea is uniformly categorized. They insisted that POSCO has not practiced tax evasion and argued that Tax Tracking Service at Korea Customs Service is well advanced to find out these practices.   

Rather, they provided two possible explanations: (1) Korean iron and steel companies including POSCO do a large amount of transshipment to smaller ships on Hong Kong border shore and these values are recorded as Hong Kong’s import, not China’s import; and (2) Since corporate tax in Hong Kong is “0,” POSCO makes profits by executing transactions in Hong Kong but exporting goods to China. In this case, the values are not recorded as Hong Kong’s import, but China’s import. 

In reference to two possible explanations outlined above, Korean iron and steel enterprises might be doing round-tripping. Round-tripping is a trade-tax-investment strategy whereby Korean enterprises undervalue exports or artificially overvalue imports, in order to move Korean capital across the border through current-account transactions. Specifically, Korean enterprises export domestic capital to the related-party enterprises situated outside China in offshore tax havens, such as Hong Kong, pursuant to non-arm’s length transfer-pricing transactions that are designed to circumvent Korean capital controls. The exported Korean domestic capital is then recycled abroad and returns to Korea in the form of foreign investment, and as such, receives a lower tax rate on profits (Liu and Giesze, 2008). Round-tripping is a pattern of transfer mispricing and it is an offshore tax evasion practices. “Over”-and under-invoicing of iron and steel imports in China and Hong Kong are representative case studies of trade misinvoicing that present virtual offshore tax evasion practices.

Challenges

Followed with a wide variety of interviews and data analysis, the biggest challenge was to investigate data in depth. Based on theoretical explanations of trade data discrepancies and tax evasion practices, “wicked” trade discrepancies reflect unusual pattern of financial flows. Even if it is not the complete evidence of illicit transfer pricing and tax evasion, we need to know why this pattern continues.

Indeed, “Personal Information Protection Law” is important but decomposition of missing values in trade is significantly instrumental for the research. Each sovereign nation has privilege to secure its own information and data but government officials need to realize the importance of this research. Conformed to a universal data set such as UN COMTRADE, data including re-exports, transportation/shipping costs, transshipment costs and other missing variables (at least estimates) need to be accessible for researchers. 

Conclusion

Efforts to identify tax evasion practices and construct the compliance frameworks accordingly are still in progress. Compared with the previous approaches that tax authorities and academic scholars conducted, this report has its significance of making connections between trade data discrepancies and tax evasion practices. A pilot case of multilateral trade: China, Hong Kong and the Republic of Korea is indeed a representative work and needs more improvements ahead.

In order to identify puzzles in the wilderness of illicit financial flows and tax evasion practices, active collaboration with United Nations, World Bank, OECD, IMF, Non-governmental organizations and academic research centers is recommended. Appendix 4 (Table 4) represents another new set of the “wicked” trade discrepancies in Argentina and Latin America and indeed, research should expand and tackle this issue. A complete set of defanging process to complex trade data discrepancies, developed from this work, will be a remarkable frontier in the fields of tax evasion and compliance. 

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[1] The SITC was developed by the United Nations with the intention of classifying traded products not only the basis of their material and physical properties, but also according to which stage of processing, as well as their economic functions in order to facilitate economic analysis. The HS was introduced in 1988, and has since then it has become an internationally accepted method of classification wherever products are traded. The HS classification is “harmonized” in relation to the classifications of the United Nations and the European Communities (International Trade Centre Web, 2014).

[2] CIF(cost, insurance and freight)-type values include the transaction value of the goods, the value of services performed to deliver goods to the border of the exporting country and the value of the services performed to deliver the goods from the border of the exporting country to the border of the importing country. FOB(free on board)-type values include the transaction value of the goods and the value of services performed to deliver goods to the border of the exporting country (UN COMTRADE Web, 2014)

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[1*] Cobham’s (2005) approach is an innovative and important contribution to the debate on revenue mobilization in developing economies. The hypothetical tax revenue of a country in the absence of tax evasion is T₀ = tw, where t is average tax rate and w is the overall economic activity, which is assumed to be equivalent to the tax base. Assume that the share of the shadow economy in overall economic activity is given by a proportional factor denoted by s, so that the actual tax base is T₁ = tw(1-s) (Fuest and Riedel, 2009). Then the tax revenue lost is T₀ - T₁ = tws.

Reference 

1. Andriamananjara, Arce and Ferrantino, Transshipment in the United States, U.S. International Trade Commission Office of Economics Working Paper, 2004 

2. Cobham, Tax Evasion, Tax Avoidance and Development Finance, University of Oxford, 2005 

3. Equity and Justice Working Group, Who Will Bell the Cat: Revenue Mobilization, Capital Flight and MNC’s Tax Evasion in Bangladesh, EquityBD, 2014 

4. Ferrantino and Wang, Accounting for Discrepancies in Bilateral Trade: The Case of China, Hong Kong, and the United States, United States International Trade Commission, 2007 

5. Fisman, Tax Rates and Tax Evasion: Evidence from “Missing Imports” in China, Journal of Political Economy, 2004 

6. Fisman, Outsourcing Tariff Evasion: A New Explanation for Entrepot Trade, National Bureau of Economic Research, 2007 

7. Fuest and Riedel, Tax Evasion, Tax Avoidance and Tax Expenditures in Developing Countries: a Review of the Literature, Oxford University Centre for Business Taxation, 2009 

8. Global Financial Integrity Web, Issues: Trade Misinvoicing, retrieved from the website, http://www.gfintegrity.org/issue/trade-misinvoicing/, Global Financial Integrity, 2014 

9. Global Witness, The Cut-Price Sale of DRC’s Forests: Tax Avoidance, Illegal Deals: 90% of Taxes Missing from Public Coffers, Global Witness, 2013 

10. Henry, The Price of Offshore Revisited: New Estimates for “Missing” Global Private Wealth, Income, Inequality, and Lost Taxes, Tax Justice Network, 2012 

11. Henry, The Global Haven Industry-Impacts on Developing Countries, Tax Justice Network, 2014 

12. International Monetary Fund, Issues in International Taxation and the Role of the IMF, IMF, 2013 

13. International Trade Centre Web, Difference between the Standard International Trade Classification (SITC) and the Harmonized System (HS), International Trade Centre, 2014 

14. Kar and Spanjers, Illicit Financial Flows from Developing Countries: 2003-2012, Global Financial Integrity, 2014 

15. Liu and Giesze, China’s Global Trade Balance Discrepancy: Hong Kong Entrpot Effects and Round Tripping Chinese Capital, The Trade Lawyers Advisory Group LLC, 2008 

16. OECD, Improving Tax Compliance-the Role of OECD’s Committee on Fiscal Affairs, OECD, 2012 

17. OECD, Illicit Financial Flows from Developing Countries: Measuring OECD Responses, OECD, 2014 

18. OECD Web, Introduction about the Forum on Tax Administration, retrieved from the website, http://www.oecd.org/tax/administration/, OECD, 2014 

19. Schneider and Enste, Shadow Economies: Size, Causes and Consequences, Journal of Economic Literature, 2000 

20. UN COMTRADE Web, United Nations Commodity Trade Statistics Database Metadata and Reference Glossary, retrieved from the website, http://comtrade.un.org/db/mr/rfGlossaryList.aspx, 2014 

 

 

 

 

[NEW] E-Commerce Access to Report & Data - Investigative Economics - Submerging Markets, Capital Flight, Corruption, Global Poverty and Inequality, Tax Justice & Inclusive Financial Markets, Sustainable Development

[NEW] E-Commerce Access to Report & Data - Investigative Economics - Submerging Markets, Capital Flight, Corruption, Global Poverty and Inequality, Tax Justice & Inclusive Financial Markets, Sustainable Development

Report & Data