Evaluation of the level of shadow economy in Lithuanian regions
Abstract
The article addresses a topical issue which is extremely relevant in crisis periods – evaluation of the level of the shadow economy in all Lithuanian regions. By applying the MIMIC modelling, three equations were developed for three different periods: economic upturn, economic downturn (crisis) and economic recovery. The number of immigrants, employment rate and population’s density were identified as the major shadow economy determinants in Lithuanian regions. The determinants identified are unique in the case of Lithuania because they reveal that the labour market (employment rate, the number of immigrants) and population’s density are the key factors that show how municipalities address the issues of the shadow economy. 10 municipalities with respectively high or low levels of the shadow economy were ranked for each period under consideration. The maps developed for different periods illustrate the general trends of the evolution of the shadow economy. This is the first study that estimates the size of the shadow economy in 60 municipalities (a small regional division) with different economic periods taken into account. Scientific novelty manifests through consideration of the regional shadow economy and proving significance of the labour market and immigration in reducing regional disparities.
Keyword : region shadow economy, the level of shadow economy in municipalities, MIMIC model, Lithuanian regions, municipalities, determinants of shadow economy
How to Cite
Remeikienė, R., Gasparėnienė, L., Yorulmaz, Özlem, Schieg, M., & Stasiukynas, A. (2021). Evaluation of the level of shadow economy in Lithuanian regions. Journal of Business Economics and Management, 22(5), 1360-1377. https://doi.org/10.3846/jbem.2021.15405
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Schneider, F., Buehn, A., & Montenegro, C. E. (2010). New estimates for the shadow economies all over the world. International Economic Journal, 24(4), 443–461. https://doi.org/10.1080/10168737.2010.525974
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Tafenau, E., Herwartz, H. & Schneider, F. (2010). Regional estimates of the shadow economy in Europe. International Economic Journal, 24(4), 629–636. https://doi.org/10.1080/10168737.2010.526010
Ullman, J. B. (2001). Structural equation modeling. In B. G. Tabachnick & L. S. Fidell (Eds.), Using multivariate statistics. Pearson Education.
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Williams, C. C., & Horodnic, I. A. (2017). Tackling the participation of Europe’s rural population in the shadow economy. https://www.redalyc.org/pdf/296/29650532001.pdf
Zellner, A. (1970). Estimation of regression relationships containing unobservable variables. International Economic Review, 11, 441–454. https://doi.org/10.2307/2525323
Borlea, S., Achim, M. V., & Miron, M. G. A. (2017). Corruption, shadow economy and economic growth: an empirical survey across the European Union countries. Studia Universitatis Economic Series, 27(2), 19–32. https://doi.org/10.1515/sues-2017-0006
Bosh, M., & Farre, L. (2013). Immigration and the informal labour market (Discussion paper, no. 7843). IZA. http://ftp.iza.org/dp7843.pdf
Buček, J. (2017). Determinants of the shadow economy in the Czech regions: a region-level study. Review of Economic Perspectives, 17(3), 315–329. https://doi.org/10.1515/revecp-2017-0016
Buehn, A. (2012). The shadow economy in German regions: an empirical assessment. German Economic Review, 13(3), 275–290. https://doi.org/10.1111/j.1468-0475.2011.00557.x
Buszko, A. (2017). The level of shadow economy in Warminsko-Mazurski and Kujawsko-Pomorski regions. Copernican Journal of Finance & Accounting, 6(4), 9–21. https://doi.org/10.12775/CJFA.2017.020
Davidescu, A. A., & Schneider, F. (2017). Nature of relationship between minimum wage and the shadow economy size: an empirical analysis for the case of Romania (Discussion paper series IZA DP, No. 11247). IZA. http://ftp.iza.org/dp11247.pdf
Davydova, G., Tagiev, M., Tagiev, I., & Ryabinina, E. (2020). Shadow economy in logging activities (on the example of the Irkutsk region). Baikal Research Journal, 11(4), 1–8. https://doi.org/10.17150/2411-6262.2020.11(4).11
Du Plessis, V., Beshiri, R., Bollman, R. D., & Clemenson, H. (2002). Definitions of “rural”. https://ageconsearch.umn.edu/bitstream/28031/1/wp020061.pdf
Frey, B., & Weck-Hanneman, H. (1984). The hidden economy as an “unobservable” variable. European Economic Review, 26(1), 33–53. https://doi.org/10.1016/0014-2921(84)90020-5
Gadsby, L., & Samson, R. (2016). Strengthening rural Canada. Why place matters in rural communities. https://www.decoda.ca/wp-content/uploads/Strengthening-Rural-Canada_Final.pdf
Gasiūnas, U. (2018). Šešėlinės ekonomikos lygio vertinimas Europos regioniniu aspektu [Shadow economy estimation at the European regional level] [Master’s Final Thesis]. Mykolas Romeris University, Vilnius.
Giles, D. E. A., & Tedds, L. M. (2002). Taxes and the Canadian underground economy (Canadian Tax Paper, Vol. 106). Canadian Tax Foundation, Toronto.
Gillanders, R., & Parviainen, S. (2018). Corruption and the shadow economy at the regional level. Review of Development Economics, 22(4), 1729–1743. https://doi.org/10.1111/rode.12517
Gonzalez-Fernandez, M., & Gonzalez-Velasco, C. (2015). Analysis of the shadow economy in the Spanish regions. Journal of Policy Modelling, 37(6), 1049–1064. https://doi.org/10.1016/j.jpolmod.2015.09.006
Hauser, R. M., & Goldberger, A. S. (1971). The treatment of unobservable variables in path analysis. In H. L. Costner (ed.), Sociological methodology (pp. 81–117). Jossey-Bass. https://doi.org/10.2307/270819
Helberger, C., & Knepel, H. (1988). How big is the shadow economy? A re-analysis of the unobserved-variable approach of B.S. Frey and H.Weck-Hannemann. European Economic Review, 32(4), 965–976. https://doi.org/10.1016/0014-2921(88)90055-4
Hubert, M., & Debruyne, M. (2010). Minimum covariance determinant. WIREs Computational Statistics, 2, 36–43. https://doi.org/10.1002/wics.61
Kireenko, A., Ivanov, Y., Nevzorova, E., & Polyakova, O. (2017). Shadow economy in the regions of the Russian Federation and the Ukraine. https://doi.org/10.1007/978-3-319-49559-0_28
Kireenko, A., & Nevzorova, E. (2019). Shadow economy in the countryside of Russian regions. Regional Research of Russia, 9, 66–77. https://doi.org/10.1134/S2079970519010052
Kline, R. B. (1998). Methodology in the social sciences. Principles and practice of structural equation modeling. Guilford Press.
Li, Y., Wang, J., Liu, Y., & Long, H. (2014). Problem regions and regional problems of socio- economic development in China: a perspective from the coordinated development of industrialization, informatization, urbanization and agricultural modernization. Journal of Geographical Sciences, 24(6), 1115–1130. https://doi.org/10.1007/s11442-014-1142-y
Li, Z., Li, J., & He, B. (2018). Does foreign direct investment enhance or inhibit regional innovation efficiency? Evidence from China. Chinese Management Studies, 12(1), 35–55. https://doi.org/10.1108/CMS-02-2017-0034
Liu, H., Chen, Y., & Long, H. (2011). Regional diversity of peasant household response to new countryside construction based on field survey in Eastern costal China. Journal of Geographical Sciences, 21(5), 869–881. https://doi.org/10.1007/s11442-011-0886-x
Medina, L., & Schneider, F. (2017). Shadow economies around the world: new results for 158 countries over 1991-2015 (CESifo Research Paper No. 6430). America. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2965972
Nchor, D. (2021). Shadow economies and tax evasion: The case of the Czech Republic, Poland and Hungary. Society and Economy, 43(1), 21–37. https://doi.org/10.1556/204.2020.00029
Pick, D., Dayaram, K., & Butler, B. (2010). Regional development and global capitalism: the case of the Pilbara, Western Australia. Society and Business Review, 5(1), 99–110. https://doi.org/10.1108/17465681011017282
Polovyan, O. V. (2015). Evaluation of shadow economy size in region. Economy of Industry, 1(69), 53–64. https://doi.org/10.15407/econindustry2015.01.053
Prytula, K. M., Shults, S. L., Samilo, A. V., & Masiov, V. O. (2019). The magnitude and nature of the shadow economy in Ukrainian border regions. Financial and Credit Activity: Problems of Theory and Practice, 4(31), 394–401. https://doi.org/10.18371/fcaptp.v4i31.190958
Ramasamy, M., Dhanapal, D., & Murugesan, P. (2017). Effects of FDI spillover on national productivity: Evidence from panel data analysis using stochastic frontier analysis. International Journal of Emerging Markets, 12(3), 427–446. https://doi.org/10.1108/IJoEM-11-2015-0246
Reimer, B. (2004). Exploring diversity in rural Canada. Measuring Rural Diversity Policy Series, 1(2), 1–7.
Remeikiene, R., Rozsa, Z., Gaspareniene, L., Chadysas, V., & Ginevicius, R. (2018). Regional estimates of shadow economy in Lithuania. Engineering Economics, 29(4), 386–396. https://doi.org/10.5755/j01.ee.29.4.19438
Schneider, F., Buehn, A., & Montenegro, C. E. (2010). New estimates for the shadow economies all over the world. International Economic Journal, 24(4), 443–461. https://doi.org/10.1080/10168737.2010.525974
Schneider, F., & Buehn, A. (2016). Estimating the size of the shadow economy: Methods, problems and open questions. (IZA Discussion Papers 9820). Institute of Labor Economics (IZA).
Schwettmann, J. (2020). COVID-19 and the informal economy. http://library.fes.de/pdf-files/iez/16414.pdf
Tafenau, E., Herwartz, H. & Schneider, F. (2010). Regional estimates of the shadow economy in Europe. International Economic Journal, 24(4), 629–636. https://doi.org/10.1080/10168737.2010.526010
Ullman, J. B. (2001). Structural equation modeling. In B. G. Tabachnick & L. S. Fidell (Eds.), Using multivariate statistics. Pearson Education.
Vorobyev, P. (2015). Estimating informal economy share in Russian regions (Working Paper No. E15/02, pp. 1–45). Economics, Education and Research Consortium.
Weng, X. (2015). The rural informal economy. Understanding drivers and livelihood impacts in agriculture, timber and mining. http://pubs.iied.org/pdfs/16590IIED.pdf
Williams, C. C. (2011). Entrepreneurship, the informal economy and rural communities. Journal of Enterprising Communities: People and Places in the Global Economy, 5(2), 145–157. https://doi.org/10.1108/17506201111131578
Williams, C. C., & Horodnic, I. A. (2017). Tackling the participation of Europe’s rural population in the shadow economy. https://www.redalyc.org/pdf/296/29650532001.pdf
Zellner, A. (1970). Estimation of regression relationships containing unobservable variables. International Economic Review, 11, 441–454. https://doi.org/10.2307/2525323