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International movements of money and men: impact on the informal economy

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Abstract

Using panel data for a large cross-country sample, we consider the influences of FDI inflows, inward development aid, and immigration on the informal sector. Both FDI and immigration increase the informal sector, with the effect of immigration being relatively more robust. Aid inflows reduce the informal sector, but the statistical significance is low. Among the control variables, government size persistently increases the informal economy, while inflation sometimes lowers the informal sector. As a secondary exercise, we consider the effect of globalization and note the informality-increasing role of social and overall globalization, with economic and political globalization being statistically insignificant.

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Notes

  1. Strictly speaking, some AID or FDI might be in-kind, involving some movements of personnel.

  2. An important aspect, although difficult to grapple with both theoretically and empirically, is the dualism between the formal sector and the informal sectors (see Rauch 1991), especially when one examines linkages with foreign countries.

  3. To empirically estimate the size and development of a shadow economy is a very challenging task, as there are no direct observations about shadow economy issues. Surveys about this issue can be found in Feld and Schneider (2010); Schneider and Enste (2000); and Williams and Schneider (2016). In these surveys, the interested reader can evaluate how difficult it is to estimate the shadow economy and what are the strengths and weaknesses of the various approaches involved.

  4. Our selection of control variables is also limited, because the shadow economy variable is not directly observable; it has to be calculated, where direct and indirect tax burden variables, good governance regulation, unemployment, etc., (to cite some important variables), are used to calculate the size of the shadow economy for a country. In order to avoid an identification problem, we cannot use these variables twice.

  5. Another potential issue is the possibility of bi-directional causality between the shadow economy and some of its determinants (see Ali and Bohara 2017; Hassan 2017; Nikopour et al. 2009; Schneider and Enste 2000). With regard to our three focus determinants, FDI, AID and MIG, the possibility of reverse feedback seems relatively more likely with regard to migration - i.e., the presence of shadow economy in a country might induce some migrants in the hope of easy employment entry in the informal sector (see Bacchetta et al. 2009; Banerjee 1983). On the other hand, decisions about FDI or foreign aid seem less likely to be affected by the presence of the informal sector. These aspects are addressed in Section 4.4.

  6. A historical perspective on the development of the informal sector in a few nations is provided by Géidigh et al. (2016).

    The prevalence of the shadow economy can also be seen as capturing tax avoidance, although some informal activity may be to avoid stringent regulations.

  7. The migration variable used (MIG) captures net migration per capita (Table 1); however, given the clandestine nature of illegal immigration, reliable and comparable cross-country data on illegal immigration are not available.

  8. One could, alternatively, estimate single-year cross sections. However, that would not provide insights that pooling the dataset provides.

  9. Note that MIG has a fewer number of years of data available than the other variables (Table 1).

  10. A part of the reason for the insignificance of the coefficient on FDI might be the qualitative differences across types of FDI (see Harms and Méon 2018).

  11. A negative effect of democracy on the shadow economy was shown by Schneider and Teobaldelli (2012) in a sample of 56 nations, while a larger sample of nations considered by Goel and Nelson (2016) found the effect to be mixed across alternate measures of the underground sector. Further, the aggregate index of economic freedom might mask certain aspects of economic freedom (e.g., tax complexity, labor market regulations, etc.) that could significantly affect the shadow economy (see Goel and Nelson 2016; Neck et al. 2012).

  12. FDI would also figure in the overall index of globalization – GLOBidx, but its weight is considerably smaller there (see KOF Index of Globalization for details).

  13. In a recent study, Pham (2017) also found informality to be significantly affected by social globalization.

  14. The effects of globalization on the shadow economy are somewhat different from those found by Berdiev and Saunoris (2018) who use a different model, and their data covers a small number of countries over the period 2000–2007.

  15. In particular, a rejection of the null hypothesis of the under-identification test implies that the model is identified, and the weak- and over-identification test results show that the instruments are valid.

    We also considered combinations of these instruments along with religious fractionalization (see Roodman 2009). Additional details are available upon request.

  16. An earlier study by Nikopour et al. (2009) notes the two-way causality between FDI and the shadow economy.

  17. Additional details are available upon request.

  18. One could, alternatively, use the highest marginal tax rate as a regressor in place of tax burden. However, given the variance in tax laws and related exemptions across nations, data on international tax rates are not consistently comparable.

  19. Note that since tax burden is a component of economic freedom and that tax burden and government size are related, we dropped EF and GCONS as regressors in Models A.3 and A.4.

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Acknowledgment

We thank James Payne, Niklas Potrafke, James Saunoris, anonymous referees and seminar participants at the Western Economics Association International meetings and CNR/ISSM, Napoli for helpful comments and Thuy Dung Ngo and Abenaa Birago for research assistance.

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Authors and Affiliations

  1. Department of Economics, Illinois State University, Normal, IL, 61790-4200, USA

    Rajeev K. Goel, Rati Ram & Ashley Potempa

  2. Kiel Institute for the World Economy, Kiel, Germany

    Rajeev K. Goel

  3. Johannes Kepler University, Linz, Austria

    Friedrich Schneider

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  1. Rajeev K. Goel
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  2. Rati Ram
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  3. Friedrich Schneider
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  4. Ashley Potempa
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Correspondence to Rajeev K. Goel.

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Appendix

Appendix

Table 9 International movements of money and men and the informal economy: Robustness check dropping EF, adding TAXbur (Models 3.7, 3.8) [Dependent variable: Shadow]
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Goel, R.K., Ram, R., Schneider, F. et al. International movements of money and men: impact on the informal economy. J Econ Finan 44, 179–197 (2020). https://doi.org/10.1007/s12197-019-09480-w

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