DETERMINANTS OF INFORMAL ECONOMY ESTIMATION IN ETHIOPIA: MULTIPLE-INDICATORS, MULTIPLE-CAUSES (MIMIC) APPROACH
DOI:
https://doi.org/10.12775/CJFA.2020.008Keywords
informal economy, taxes burden, institutional quality, MIMIC model, EthiopiaAbstract
This paper explored the determinants of the informal economy size estimations with survey data in the multiple indicators, multiple causes (MIMIC) model. This model enables us to estimate the unknown variable with the known observable variables. The size of the informal economy estimated with observable variables and to conduct the estimation with this model grouped the observable variables of the study as causes and indicators. In the underlying study, the size of informal economy estimations the variables such as harmfulness of shadow economy, growth of money outside banks, taxes burden, the intensity of government regulations, self-employment, unemployment rate, and agricultural sector dominance have the positive effects whereas the real GDP per capita, total employment, institutional quality, and tax morality have negative effects in the estimation of the informal economy size. The study recommended a future line of studies for scholars to undertake the study on the size of the informal economy estimations with the indirect approach using panel data to know the impacts on the regular economy and other related consequences on the economy.References
Alm, J., Martinez-Vazquez, J., & Schneider, F. (2004). “Sizing” the Problem of the Hard -to-Tax. Contributions to Economic Analysis, 286, 11-75.
Andersen, E.A., & Andersen, E.A. (2019). The shadow economy. An Ethnic Perspective on Economic Reform, 330-333. https://dx.doi.org/10.4324/9780429460098-25.
Cassel, D., & Cichy, U. (1986). Explaining the growing shadow economy in East and West: A comparative systems approach. Comparative Economic Studies, 28(1), 20-41.
Davcik, N.S. (2014). The use and misuse of structural equation modeling in management research: A review and critique. Journal of Advances in Management Research, 11(1), 47-81. https://dx.doi.org/10.1108/JAMR-07-2013-0043.
Dilnot, A., & Morris, C. N. (1981). What do we know about the black economy? Fiscal Studies, 2(1), 58-73. https://dx.doi.org/10.1111/j.1475-5890.1981.tb00457.x.
Doğan, İ., & Özdamar, K. (2017). The effect of different data structures, sample sizes on model fit measures. Communications in Statistics-Simulation and Computation, 46(9), 7525-7533. https://dx.doi.org/10.1080/03610918.2016.1241409.
Eilat, Y., & Zinnes, C. (2000). The evolution of the shadow economy in transition countries: consequences for economic growth and donor assistance. Harvard Institute for International Development, CAER II Discussion Paper, 83.
Feige, E.L. (2016). Reflections on the Meaning and Measurement of Unobserved Economies: What Do We Really Know About the “Shadow Economy”. Journal of Tax Administration, 2(1), 5-41.
Feld, L.P., & Schneider, F. (2010). Survey on the shadow economy and undeclared earnings in OECD countries. German Economic Review, 11(2), 109-149. https://dx.doi.org/10.1558/jsrnc.v4il.24.
Ferman, P.R., & Ferman, L.A. (1973). The structural underpinnings of the irregular economy. Asia Pacific Journal of Human Resources, 8(1), 1-17. https://dx.doi.org/10.1177/103841117300800101.
Frey, B.S., Weck, H., & Pommerehne, W.W. (1982). Has the shadow economy grown in Germany? An exploratory study. Weltwirtschaftliches Archiv, 118(3), 499-524.
Gutmann, P.M. (1977). The subterranean economy. Financial Analysts Journal, 33(6), 26- -27. https://dx.doi.org/10.2469/faj.v33.n6.26.
Hennessy, M., & Greenberg, J. (1999). Bringing it all together: Modeling intervention processes using structural equation modeling. American Journal of Evaluation, 20(3), 471-480. https://dx.doi.org/10.1177/109821409902000306.
Igudia, E., Ackrill, R., Coleman, S., & Dobson, C. (2016). Determinants of the informal economy of an emerging economy: a multiple indicator, multiple causes approach. International Journal of Entrepreneurship and Small Business, 28(2/3), 154-177. https://dx.doi.org/10.1504/ijesb.2016.076643.
Karakaya-Ozyer, K., & Aksu-Dunya, B. (2018). A Review of Structural Equation Modeling Applications in Turkish Educational Science Literature, 2010-2015. International Journal of Research in Education and Science, 4(1), 279-291. https://dx.doi.org/10.21890/ijres.383177.
Kenny, D.A., & McCoach, D.B. (2003). Effect of the number of variables on measures of fit in structural equation modeling. Structural Equation Modeling, 10(3), 333-351. https://dx.doi.org/10.1207/S15328007SEM1003_1.
Kline, R.B. (2010). Promise and pitfalls of structural equation modeling in gifted research. In B. Thompson, R.F. Subotnik (Eds.). Methodologies for conducting research on giftedness. Washington: American Psychological Association. https://dx.doi.org/10.1037/12079-007.
Leite, C., & Master, S. (2014). Shadow Economy in Portugal: computation by different approaches. Porto: FEP Economics and Management University of Porto.
McCrohan, K., Smith, J.D., & Adams, T.K. (1991). Consumer purchases in informal markets: estimates for the 1980s, prospects for the 1990s. Journal of Retailing, 67(1), 22-50.
McCrohan, K.F., & Smith, J.D. (1987). Consumer participation in the informal economy. Journal of the Academy of Marketing Science, 15(4), 62-68. https://dx.doi.org/10.1007/BF02723291.
Öğünç, F., & Yılmaz, G. (2000). Estimating the underground economy in Turkey. CBRT Research Department Discussion Paper.
Pesut, M. (1992). Statistics of the hidden economy and informal activities inside the production boundary of the national accounts. An overview of national practices. Statistical Journal of the United Nations Economic Commission for Europe, 9(1), 1-26. https://dx.doi.org/10.20595/jjbf.19.0_3.
Quintin, E. (2014). The Informal Sector in Developing Countries: Output, Assets and Employment. Washington: World Institute for Development Economic Research. https://dx.doi.org/10.1093/acprof:osO/9780199548880.003.0018.
Rafael, G., & Castro, B. (2018). The Informal Economy and Its Impact on Tax Revenues and Economic Growth. Analysis of OCDE members and Latin America Countries (1995- -2016), 0-54.
Sancak, C., Devine, H., Cangul, M., Wu, F., Liu, Y., Nose, M., & Thomas, A. (2017). 3. The Informal Economy in Sub-Saharan Africa. Washington: Regional Economic Outlook, International Monetary Fund.
Schneider, F., & Buehn, A. (2016). Estimating the Size of the Shadow Economy: Methods, Problems and Open Questions. IZA Discussion Paper, 9820.
Schneider, F., & Enste, D. (2002). Hiding in the shadows: the growth of the underground economy. International Monetary Fund, 30.
Schneider, F. (2003). The size and development of the shadow economies and shadow economy labor force of 22 transition and 21 OECD countries: what do we really know? The informal economy in the EU access countries: Size, scope, trends and challenges to the process of EU enlar. Center for Study of Democracy, 23-61.
Schneider, F. (2014). The shadow economy: an essay. Linz: Johannes Kepler University of Linz.
Schneider, F. (2015). Size and Development of the Shadow Economy of 31 European and 5 other OECD Countries from 2003 to 2014: Different Developments? Journal of Self- Governance and Management Economics, 3(4), 7-29. https://repositorio.unan.edu.ni/2986/1/5624.pdf (accessed: 12.12.2019).
Singh, A., & Masuku, M. (2014). Sampling Techniques & Determination of Sample Size in Applied Statistics Research: an Overview. Ijecm.Co.Uk, II(11), 1-22. http://ijecm.co.uk/wp-content/uploads/2014/11/21131.pdf (accessed: 6.12.2019).
Sison, C.P., & Glaz, J. (1995). Simultaneous confidence intervals and sample size determination for multinomial proportions. Journal of the American Statistical Association, 90(429), 366-369.
Smith, T.D., & McMillan, B.F. (2001). A Primer of Model Fit Indices in Structural Equation Modeling. New Orleans: Southwest Educational Research Association.
Trebicka, B. (2014). Mimic Model: A Tool to Estimate the Shadow Economy. Academic Journal of Interdisciplinary Studies, 3(6), 295-300. https://dx.doi.org/10.5901/ ajis.2014.v3n6p295.
Usp, N., & Winter, S.E.M. (2012). Some Clarifications and Recommendations on Fit Indices. Structural Equation Modeling, 523/623, 1-4.
Williams, C.C., & Schneider, F. (2013). The shadow economy. London: Institute of Economic Affairs.
Downloads
Published
How to Cite
Issue
Section
Stats
Number of views and downloads: 1042
Number of citations: 0