Factors for the Underground Economy in G7 Countries

Yıl 2020, Cilt: 5 Sayı: 1, 177 - 189, 30.04.2020

Hakan Kum

https://doi.org/10.30784/epfad.722582

Öz

This study aims to determine the factors leading to the underground economy (UE) for G7 countries. During the 11-year period since the 2007-2008 financial crisis, the factors determined by the informal economy were investigated. For this reason, the analysis covers the years 2007-2017. Studies within the grouped country are extremely limited. To date, few studies have been carried out in the European Union, the European Euro Area and the developed countries, whose framework is unclear. The literature is in need of extensive research areas in this field. Within the scope of both developed countries, developing countries and underdeveloped countries, there are areas suitable for research and missing. Analyzes in accordance with newly developed techniques are also needed for determining variables. Especially in the determination of the variables in the MIMIC model, which is the most reliable method in the quantitative field, the use of new techniques should be an inevitable trend. In this respect, analyzing the variables to be selected in the models in terms of multiple connections is one of the most important elements that was not emphasized before. In the literature, there are studies both on country basis and within country groups. The literature is progressing mostly in the field of single country. MIMIC model was chosen as the method in the study. The results obtained show that the most important reason of UE in G7 countries is the external migration factor.

Anahtar Kelimeler

Underground Economy, MIMIC Model, G7 Countries

G7 Ülkelerinde Kayıtdışı Ekonomiye Yol Açan Faktörler

Öz

Bu çalışma, kayıtdışı ekonomiye yol açan faktörlerin G7 ülkeleri için belirlenmesini hedeflemektedir. 2007-2008 finansal krizinden itibaren geçen 12 yıllık süreç içerisinde, kayıtdışı ekonominin hangi faktörler tarafından belirlendiği araştırılmıştır. Bu nedenle analiz 2007-2017 yıllarını kapsamaktadır. Gruplandırılmış ülke kapsamındaki çalışmalar son derece kısıtlıdır. Bugüne kadar Avrupa Birliği, Avrupa Euro Bölgesi ve çerçevesi tam belli olmayan Gelişmiş Ülkeler alanlarında az sayıda çalışma yapılmıştır. Literatür bu alanda oldukça geniş araştırma alanlarına muhtaç durumdadır. Hem gelişmiş ülkeler hem gelişmekte olan ülkeler hem de az gelişmiş ülkeler kapsamında araştırmaya uygun ve eksik alanlar bulunmaktadır. Değişkenlerin belirlenme konusunda da yeni geliştirilen tekniklere uygun analizlere ihtiyaç duyulmaktadır. Özellikle kantitatif alandaki en güvenilir metot olan MIMIC modeldeki değişkenlerin belirlenme aşamasında, yeni tekniklerin kullanılması kaçınılmaz bir eğilim olmalıdır. Bu yönüyle, modellerde seçilecek değişkenlerin çoklu bağlantı yönünden analiz edilmesi daha önceleri üzerinde çok durulmayan fakat en önemli unsurlardan biridir. Literatürde hem ülke bazında hem de ülke grupları kapsamında çalışmalar bulunmaktadır. Literatür daha çok tekil ülke alanında ilerlemektedir. Çalışmada yöntem olarak MIMIC modeli seçilmiştir. Elde edilen sonuçlar, G7 ülkelerindeki KDE’nin en önemli nedeninin dış göç faktörü olduğunu göstermektedir.

Anahtar Kelimeler

Kayıtdışı Ekonomi, MIMIC Model, G7 Ülkeleri

Kaynakça

• Bose, N., Capasso, S. and Wurm, M. A. (2012). The impact of banking development on the size of shadow economies. Journal of Economic Studies, 32(6), 620-638. https://doi.org/10.1108/01443581211274584
• Breusch, T. (2005). Estimating the underground economy using MIMIC models (University Library of Munich Econometrics Working Paper No. 0507003). Retrieved from https://econwpa.wustl.edu/eps/em/papers/0507/0507003.pdf
• Buehn, A. and Schneider, F. (2012). Shadow economies around the world: Novel insights, accepted knowledge, and new estimates. International Tax and Public Finance, 19, 139-171. https://doi.org/10.1007/s10797-011-9187-7
• Chong, A. and Gradstein, M. (2004). Inequality, institutions and informality (Inter-American Development Bank IDB Working Paper No. 427). Retrived from Retrieved from https://poseidon01.ssrn.com/delivery.php?ID=796114123085008074113103102094083092038004029014029041005011004117122112076031004093006013067115119110092099102112102104115005015006118068113123070101084072020106009003&EXT=pdf
• Dey, C., Russell, S. and Thomson, I. (2011). Exploring the potential of shadow accounts in problematizing institutional conduct. In A. Ball ve A. S. Osbourne (Eds.), Social accounting and public management: Accountability for the common good (pp. 1-16). London: Routledge.
• Gasparėnienė, L. and Remeikienė, R. (2016). The methodologies of shadow economy estimation in the world and in Lithuania: Whether the criterions fixing digital shadow are included?. Procedia Economics and Finance, 39, 753-760. https://doi.org/10.1016/S2212-5671(16)30277-5
• Hassan, M. and Schneider, F. (2016). Size and development of the shadow economies of 157 countries worldwide: Updated and new measures from 1999 to 2013 (IZA Discussion Paper Series No. 10281). Retrived from https://ftp.iza.org/dp10281.pdf
• Im, K. S., Pesaran, M. H. and Shin, Y. (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics, 115, 53–74. Retrived from www.jstore.org
• Juškienė, G. (2015). Overview of the methods used to ensure exhaustiveness the national accounts of Lithuania (Workshop on Measurement of the Non-Observed Economy Sochi). Retrieved from https://www.oecd.org/std/na/2069700.pdf
• Krstič, G. and Sanfey, P. (2010). Earnings inequality and the informal economy: Evidence from Serbia (European Bank for Reconstruction and Development Working Paper No. 114). Retrieved from https://www.ebrd.com/downloads/research/economics/workingpapers/wp0114.pdf
• Levin, A., Lin, C. F. and Chu, C. S. J. (2002). Unit root tests in panel data: Asymptotic and finite-sample properties. Journal of Econometrics, 108, 1–24. www.jstore.org
• Quirk, P. J. (1998). Macroeconomic implications of money laundering (IMF Working Paper No. 96:66). Retrieved from https://www.elibrary.imf.org/doc/IMF001/04385-9781451962123/04385-9781451962123/Other_formats/Source_PDF/04385-9781455295791. pdf
• Rigdon, E. (2004). What is structural equation modeling? (GSU Working Paper No. 12). Retrieved from http://www2.gsu.edu/~mkteer/
• Schneider, F. (2007). Shadow economies and corruption all over the world: new estimates for 145 countries (CESifo Working Paper No. 1806). Retrieved from (CESifo Working Paper No. 1806). Retrieved from https://www.researchgate.net/publication/5141532_ Shadow_Economies_and_Corruption_All_Over_the_World_What_Do_We_Really_Know
• Schneider, F. (2017). Implausible large differences in the sizes of the underground economies highly developed European countries? A comparison of different estimation (CESifo Working Paper Series No. 6522). Retrieved from https://www.econ.jku.at/members/Schneider /files/publications/2017/EstShadEc_OECDCountries.pdf
• Schneider, F. and Buehn, A. (2016). Estimating the size of the shadow economy: Methods, problems and open questions (IZA Discussion Paper Series No. 9820). Retrieved from https://ftp.iza.org/dp9820.pdf
• Schneider, F. and Enste, D. (2000). Shadow economies: Size, causes, and consequences. Journal of Economic Literature, 38, 77-114. https://doi.org/10.1257/jel.38.1.77
• Schneider, F. and Kearney, A. T. (2013). The shadow economy in Europe (VISA Sponsored Working Paper). Retrieved from http://feelingeurope.eu/Pages/Shadow_Economy_in_Europe.pdf
• Schneider, F., Raczkowski, K. and Mróz, B. (2015). Shadow economy and tax evasion in the EU. Journal of Money Laundering Control, 18(1), 34-51. https://doi.org/10.1108/JMLC-09-2014-0027
• Schneider, F. and Williams, C. (2016). The shadow economy. London: IEA Publications.
• Tregidga, H. (2017). Speaking truth to power: Analysing shadow reporting as a form of shadow accounting. Accounting, Auditing & Accountability Journal, 30(3), 510-533. https://doi.org/10.1108/AAAJ-01-2015-1942
• Williams, C. C. (2009). Rationales for outsourcing domestic services to off-the-books workers. Journal of Economic Studies, 36(4), 343-354. https://doi.org/10.1108/01443580910973565
• Williams, C. C. (2010). Out of the shadows: explaining the undeclared economy in Baltic countries. Journal of Baltic Studies, 41(1), 3-22. https://doi.org/10.1080/01629770903525282
• Williams, C. C. and Nadin, S. (2012). Tackling entrepreneurship in the informal economy: Evaluating the policy options. Journal of Entrepreneurship and Public Policy, 1(2), 111-124. https://doi.org/10.1108/20452101211261408
• Winkelried, D. (2005). Income distribution and the size of the informal sector (Social Science Research Network Research Paper). Retrived from https://doi.org/10.2139/ssrn.777144
• World Bank. (2018). World Bank Development Indicators [Dataset]. Retrieved from https://data.worldbank.org/
• Wu, J. and Yang, H. (2016). More on the unbiased ridge regression estimation. Statistical Papers, 57, 31–42. https://doi.org/10.1007/s00362-014-0637