This study investigates the influences of economic uncertainty and Internet usage on the informal economy. Notably, the study focuses on the effects of the association of economic uncertainty and Internet usage on the informal economy. The empirical analysis is carried out for a global sample of 124 economies from 1996 to 2017. Applying different estimates and different robustness checks, the results are consistent and robust. Internet usage leads to a decline in the shadow economy, while economic uncertainty has the effect of increasing the shadow economy. Interestingly, the positive influence of economic uncertainty on the shadow economy is likely exacerbated by Internet development. Lastly, analyses for several subsamples by time periods, income levels, and regions reveal additional findings. The negative impact of Internet usage on the shadow economy is consistent across income groups, regions, and time periods, except for a surprising positive impact in North America. The positive impact of economic uncertainty is also consistent in most income groups but more dominant in a period of low economic uncertainty. Interestingly, economic uncertainty is found to have a negative impact on the informal sector in low‐income economies and Sub‐Saharan Africa. Overall, the results have an important implication: Increases in economic uncertainty motivate economic agents to move to informal sectors, and this is supported by information technologies.
Intro: The literature indicates that economic complexity (the geography of economic activities) is an important explanatory factor in income inequality; however, empirical evidence is still inconclusive. This study addresses this gap by considering the nonlinear influence of economic complexity on income inequality. Methods: Panel quantile regression with fixed effects is applied for a global sample of 121 countries from 1995 to 2018, showing robust findings. Results: Economic complexity appears to have an inverted-U-shaped effect on income inequality. That is, economic complexity likely increases income inequality up to a threshold, beyond which economic complexity helps to reduce income inequality. This inverted-U-shaped effect is found consistently in low-income, lower-middle-income, and upper-middle-income countries, while the opposite effect is found in high-income countries. Evidence of an inverted-U-shaped effect is also documented in most regions except the Middle East & North Africa and South Asia. Interestingly, the study finds that improvements in economic complexity appear to have U-shaped effects on the income share of the bottom earners and inverted-U-shaped effects on the income share of the top earners. Conclusion: These effects explain the inverted-U-shaped effect of economic complexity on income inequality. The results are robust across different quantiles, proxies of income inequality, and various control variables KEYWORDS economic complexity, income inequality, income share, nonlinear effect, panel data JEL CLASSIFICATION D63, O11, O33
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