1. Structural Effects of Corruption and Anticorruption in Visegrad Countries: Trade Channel Michal Paulus 7.5. AAEM

2. Motivation Corruption and export Hypothesis ◦ Similar institutional level shape the trade Empirics ◦ V4 countries x core EU Current state: in progress

3. Outline Motivation and Literature ◦ Corruption and FDI ◦ Corruption and Exports ◦ Hypotheses ◦ Expected contribution Policy Relevance Methodology ◦ Cluster analysis ◦ Gravity model ◦ Expected results Appendix: results of cluster analysis

4. Motivation and Literature Corruption and Development Effects on GDP: prevailing negative effects ◦ E.g. Davoodi and Tanzi (1997) More relevant: effects on sustainable growth ◦ GDP ignores many aspects ◦ Aidt (2009 and 2011)

5. Motivation and Literature Corruption and FDI Negative effects ◦ Busse and Hefeker (2007) Positive effects ◦ Egger and Winner (2005) Results not conclusive

6. Motivation and Literature Corruption and Exports Negative effects ◦ Horsewood and Voicu (2012) Partial positive effects ◦ De Jong and Bogmans (2011) ◦ Dutt and Traca (2010).

7. Motivation and Literature Exports: general explanatory theory missing FDI: Brada, Drabek and Perez (2012) ◦ “corruption matching” or “middle-man” hypothesis Research follows the work of Brada, Drabek and Perez (2012)

8. Motivation and Literature Hypotheses H1: Countries tend to trade with the partners of similar corruption level. ◦ “Corruption matching” H2: Middle corrupt countries tend to have large trade with low and high corrupt countries. ◦ “middle-man hypothesis”

9. Motivation and Literature Expected contribution Empirics and policy Structural differences btw. core EU and V4 countries ◦ Potential conflicts between EU members Identification sensitivity of various sectors to corruption reduction Theoretical Establishing of “corruption matching” and “middle-men” hypotheses in export sphere and their partial tests (limited to EU level) Base for further tests of more general relevance

10. Policy relevance Opposition x anticorruption laws Winners x losers ◦ International level  EU integration and potential conflicts ◦ National level Solution ◦ Compensation payments Research identifies position of V4 and core EU countries

11. Methodology 2 steps ◦ Corruption clusters (done) ◦ Micro-founded Gravity model (pre- estimation)  Clusters included in the RHS Data ◦ Exports: V4 core EU (BE, DE, FR, IT, LU, NL) ◦ Explanatory variables: app. 130 countries ◦ Time period: 1996-2013

12. Methodology Corruption clusters 134 countries Index from Heritage Foundation (COR= CPI*10) Time 1996-2014 Method: average linkage clustering Published in Physica A (ISSN: 0378-4371) ◦ See Paulus and Kristoufek (2015) for further details Results in Appendix of ppt

13. Methodology

14. Methodology Other planned extensions Dependent variable Exports on sectoral level Value-added sectors Independent variable Cultural distance measures (CEPII) Various corruption measures ◦ CCI (WB), EFWI (CATO), BPI (IT), ICRG

15. Methodology Expected results Structural differences in role of corruption in exports: V4 x core EU Identification of different “corruption sensitivity” of key sectors Revelation of potential conflicts btw V4 and core EU

16. Appendix 4 clusters ClusterAv. corr. Av. GDP (p.c. current USD) ratio richest/poorest 182.952 1386.8 259.223 5217.8 441.39 75145.1 324.23 88852.9

17. Cluster #1 AustraliaAustriaBelgiumCanadaChile DenmarkFinlandFranceGermanyHong Kong IrelandJapanLuxembourgNetherlandsNew Zealand NorwaySingaporeSwedenSwitzerlandUnited Arab Emirates United KingdomUSA Cluster #2 BahamasBahrainBarbadosBotswanaCyprus EstoniaIsraelKuwaitMaltaOman PortugalSloveniaSpainTaiwanUruguay Cluster #3 AlbaniaAzerbaijanBangladeshBelarusBolivia BrazilBulgariaBurkina FasoBurmaCameroon ChinaColombiaCuba Dominican RepublicEcuador EthiopiaFijiGeorgiaGuineaGuyana HaitiHondurasIndiaIndonesiaIran Ivory CoastKenyaLaosLebanonLesotho LibyaMadagascarMalawiMaliMauritania MoldovaMozambiqueNepalNicaraguaNiger NigeriaNorth KoreaPakistanParaguayPeru PhilippinesRepublic of KongoRomaniaRussiaSuriname SwazilandSyriaTanzaniaTurkeyUganda UkraineVenezuelaVietnamYemenZimbabwe Cluster #4 AlgeriaArgentinaArmeniaBelizeBenin Cape VerdeCosta RicaCroatiaCzech RepublicEgypt El SalvadorGabonGhanaGreeceGuatemala HungaryItalyJamaicaJordanLatvia LithuaniaMalaysiaMexicoMongoliaMorocco PanamaPolandSaudi ArabiaSenegalSlovakia South AfricaSouth KoreaSri LankaThailandTrinidad and Tobago TunisiaZambia

19. Bibliography Aidt, T. S. (2009). Corruption, institutions, and economic development. Oxford Review of Economic Policy, 25(2), 271-291. Aidt, T. S. (2011). 1 Corruption and sustainable development. In International Handbook on the Economics of Corruption, Edward Elgar. Busse, M., & Hefeker, C. (2007). Political risk, institutions and foreign direct investment. European Journal of Political Economy, 23(2), 397–415. Brada, J. C., Drabek, Z., & Perez, M. F. (2012). The Effect of Home-country and Host-country Corruption on Foreign Direct Investment. Review of Development Economics, 16(4), 640–663. Davoodi, H., & Tanzi, V. (1997). Corruption, Public Investment, and Growth. IMF Working Papers No. 97/139. De Jong, E., & Bogmans, C. (2011). Does corruption discourage international trade? European Journal of Political Economy, 27(2), 385–398. Egger, P., & Winner, H. (2005). Evidence on corruption as an incentive for foreign direct investment, European Journal of Political Economy, 21(4), 932– 952.