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Tax havens and disclosure aggregation

Journal of International Business Studies volume 49, pages 49–69 (2018)Cite this article

Abstract

Multinational firms have been accused by politicians, regulators, and citizen groups of shifting profits to low-tax geographic areas. We present evidence that multinational firms with tax-haven operations tend to aggregate their geographic disclosures to a greater extent. The results are consistent with managers attempting to avoid criticism by reducing the transparency of their tax-avoidance activities. We find these results to be stronger for larger firms with higher political costs and for firms in natural-resources industries, in retail industries, or with low competition. The evidence is relevant to policymakers and others interested in multinational firms’ financial reporting and tax activities.

Résumé

Les firmes multinationales ont été accusées par les politiciens, les régulateurs et les groupes de citoyens de déplacer les profits vers les zones géographiques à faibles taxation. Nous fournissons la preuve que les firmes multinationales ayant des opérations dans les paradis fiscaux ont tendance à agréger leurs déclarations géographiques dans une plus large mesure. Les résultats sont cohérents avec les dirigeants qui tentent d’éviter le criticisme en réduisant la transparence de leurs activités destinées à éviter la taxation. Nous trouvons que ces résultats sont plus importants pour les grandes entreprises ayant des coûts politiques plus élevés et pour les entreprises dans les industries des ressources naturelles, les industries de la distribution, ou avec une faible concurrence. La preuve est pertinente pour les responsables politiques et d’autres acteurs intéressés par les activités de reporting financier et de taxation des firmes multinationales.

Resumen

Las empresas multinacionales han sido acusadas por políticos, reguladores y grupos de ciudadanos de traslados de ganancias a áreas geográficas con bajos impuestos. Presentamos evidencias que las empresas multinacionales con operaciones paraísos fiscales tienden a agrupar sus declaraciones geográficas en mayor proporción. Los resultados son consistentes con los gerentes que tratan de evitar las críticas al reducir la transparencia de las actividades de evasión de impuestos. Encontramos que estos resultados son más fuertes para las empresas más grandes con más costos políticos y para empresas en industrias de recursos naturales, en industrias de ventas minoristas, o con baja competencia. La evidencia es relevante para formuladores de políticas y otros interesados en las actividades de reportes financieros y actividades fiscales de las empresas multinacionales.

Resumo

Empresas multinacionais têm sido acusadas por políticos, reguladores e grupos de cidadãos de transferir lucros para áreas geográficas de baixa tributação. Apresentamos evidências de que empresas multinacionais com operações em paraísos fiscais tendem a agregar suas divulgações geográficas em maior extensão. Os resultados são consistentes com os gerentes que tentam evitar críticas, reduzindo a transparência de suas atividades de evasão fiscal. Achamos que esses resultados são mais fortes para as grandes empresas com maiores custos políticos e para as empresas das indústrias de recursos naturais, nas indústrias de varejo ou com baixa concorrência. A evidência é relevante para formuladores de políticas e outros interessados em relatórios financeiros das empresas multinacionais e atividades fiscais.

Chinese

跨国公司被政治家、监管机构和公民组织指责将利润转移到低税地域。我们提出证据表明,避税运作的跨国公司更大程度上倾向于汇总其地理位置披露。研究结果与管理者试图通过减少其避税活动透明度来避免批评是一致的。我们发现,这些研究结果较强地表现于政治成本较高的大公司以及自然资源行业的公司,零售行业的公司,或低竞争力的公司。该证据对政策制定者和那些对跨国公司财务报表和纳税活动有兴趣兴趣者切实重要。

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Acknowledgements

We appreciate comments from Gary Biddle (Editor), Alain Verbeke (Editor-in-Chief), two anonymous reviewers, Frances Ayres, Robert Duquette, David Folsom, Tamara Lambert, Stephen Lin (discussant), Yvonne Lu, Leila Peyravan, Jesus Salas, Barbara Su, Wuyang Zhao, and workshop participants at the University of Connecticut, Lehigh University, University of Oklahoma, Hong Kong Polytechnic University, Virginia Tech, Accounting Doctoral Students Association Conference, and International Accounting Section Midyear Meeting. This article received the Best Paper Award at the 2014 International Accounting Section Midyear Meeting. Hope acknowledges the financial support of the Deloitte Professorship.

Author information

Authors and Affiliations

  1. College of Business Administration, University of Nebraska – Lincoln, Lincoln, USA

    Herita Akamah

  2. Rotman School of Management, University of Toronto, Toronto, Canada

    Ole-Kristian Hope

  3. BI Norwegian Business School, Oslo, Norway

    Ole-Kristian Hope

  4. Michael F. Price College of Business, University of Oklahoma, Norman, USA

    Wayne B Thomas

Authors
  1. Herita Akamah
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  2. Ole-Kristian Hope
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  3. Wayne B Thomas
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Corresponding author

Correspondence to Ole-Kristian Hope.

Additional information

Accepted by Gary Biddle, Area Editor, 24 April 2017. This article has been with the authors for four revisions.

Appendices

Appendix 1: Sample selection

 

Observations

Firm-year-countries

Firm-years

Firms

Exhibit 21 data from 1998 to 2010a

272,167

30,110

5,470

Missing control variables

(9,923)

(608)

(109)

Missing geographic segment datab

(59,293)

(8,521)

(846)

Segment sales not >0c

(65,534)

(8,935)

(1,817)

Final Sample

137,417

12,046

2,698

  1. a The sample begins in 1998 because a new reporting standard (ASC 280 or previously SFAS 131) took effect that year and ends in 2010 because this is the last year Exhibit 21 data are available from Scott Dyreng’s website (https://sites.google.com/site/scottdyreng/Home/data-and-code).
  2. bFirms did not have geographic titles reporting in the Segment file in Compustat.
  3. cFirms had at least one geographic segment with sales less than or equal to zero.

Appendix 2: Variable definitions

Dependent variable (measure of aggregation)

 

NOMATCH %

= Portion of countries in Exhibit 21 not disclosed at the country level in geographic disclosures

Test variables (measures of tax-haven intensity)

 

DHAVEN

= 1 (0 otherwise) if a country is one of the tax-haven locations as described in Dyreng and Lindsey (2009): Andorra, Anguilla, Antigua and Barbuda, Aruba, Bahamas, Bahrain, Barbados, Belize, Bermuda, British Virgin Islands, Brunei, Cape Verde, Cayman Islands, Cook Islands, Costa Rica, Cyprus, Dominica, Gibraltar, Grenada, Guernsey and Alderney, Hong Kong, Ireland, Isle of Man, Jersey, Kitts and Nevis, Latvia, Lebanon, Liberia, Liechtenstein, Luxembourg, Macau, Maldives, Malta, Marshall Islands, Mauritius, Monaco, Montserrat, Motswana, Nauru, Netherlands Antilles (or Dutch Antilles), Niue, Palau, Panama, Samoa, San Marino, Seychelles, Singapore, St. Lucia, St. Vincent and The Grenadines, Switzerland, US Virgin Islands, Uruguay, and Vanuatu

HAVEN %

= Percentage of countries in Exhibit 21 classified as tax havens

LOGHAVEN

= Natural log (one plus) the number of tax-haven countries listed in Exhibit 21

Control variables

 

BIG4

= 1 (0 otherwise) if the company is audited by a top four accounting firm or its predecessors

SIZE

 = Natural log of total assets (AT)

MTB

 = Ratio of market value (PRCC_F × CSHO) to book value (CEQ)

NOL

 = 1 (0 otherwise) if tax loss carry forward (TLCF) is negative at the beginning of the year

CNOL

= 1 (0 otherwise) if tax loss carry forward (TLCF) is more negative at the end of year t than the beginning of year t

FORINC

= Foreign pre-tax income (PIFO) divided by lagged total assets (AT)

ROA

= Net income (NI) divided by lagged total assets (AT)

LEV

= Long-term debt (LT) divided by total assets (AT)

ADV

= Advertising expense (XAD) divided by lagged total revenue (REVT)

RD

= Research and development expense (XRD) divided by lagged total assets (AT)

INTANG

= Intangible assets (INTAN) divided by lagged total assets (AT)

PPE

= Property, Plant and Equipment (PPENT) divided by lagged total assets (AT)

EQINC

= Equity income in subsidiaries (EINC) divided by lagged total assets (AT)

SUBMAT

= Number of foreign subsidiaries divided by number of countries listed in Exhibit 21

FSR

= Foreign sales (computed from Compustat Segment database) divided by total revenue (REVT)

Alternative dependent variables (measures of aggregation)

 

LEVEL

= Average aggregation score of countries in Exhibit 21. Each country receives an aggregation score based on its related geographic disclosure. Geographic disclosures are scored as follows

 

0.0 = Countries (e.g., Ireland)

 

0.5 = Aggregate countries (e.g., Germany/Ireland)a

 

1.0 = Subcontinents or aggregate countries/other (e.g., Western Europe or Germany/Ireland/Other)

 

1.5 = Continents or aggregate subcontinents (e.g., Europe or Western Europe/Southeast Asia)

 

2.0 = Aggregate continents (e.g., Europe/Asia)

 

2.5 = Aggregate continents/other (e.g., Europe/Asia/Other)

 

3.0 = Major geographic regions (e.g., Eastern Hemisphere)

 

4.0 = All foreign (e.g., Foreign, International, Abroad, etc.)b

LEVEL_SALESWT

= Average aggregation score of countries in Exhibit 21 weighted by sales in each disclosed geographic area

NOMATCH %_NOTES

= Portion of geographic segments not disclosed at the country level

LEVEL_NOTES

= Average aggregation score of disclosed geographic segments

LEVEL_SALESWT_NOTES

 = Sales-weighted average aggregation score of disclosed geographic segments

NGEO_NOTES(−1)

 = Number of disclosed geographic segments multiplied by −1

  1. aThe notation “Germany/Ireland” indicates that the firm discloses operations of Germany and Ireland as a single segment without any disclosure of the separate operations in each country.
  2. bAggregation scores increase by increments of 0.5, except for disclosure of all foreign operations in a single segment. Such aggregation essentially offers very limited (if any) information useful in understanding specific geographic operations and the use of structured transactions in foreign countries to avoid taxes. Thus we increase the aggregation score by 1.0 beyond disclosure of major geographic regions (from 3.0 to 4.0).

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Akamah, H., Hope, OK. & Thomas, W.B. Tax havens and disclosure aggregation. J Int Bus Stud 49, 49–69 (2018). https://doi.org/10.1057/s41267-017-0084-x

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Keywords

  • tax havens
  • aggregation
  • disclosure transparency
  • tax avoidance
  • geographic reporting
  • Exhibit 21