Testing the relationships between shadow economy and unemployment: empirical evidence from linear and nonlinear tests

Abstract

The aim of this paper is to empirically investigate the dynamic linkages between unemployment and shadow economy for 32 developing and developed countries for the period 1980 -2009 using parametric and non-parametric techniques. To this end, the Hansen and Seo (2002) threshold cointegration approach and the nonlinear causality test of Kyrtsou and Labys (2006) are applied to assess these relationships. Results obtained clearly do not support the view that unemployment and shadow economy are neutral with respect to each other, except in the case of Bolivia, China, Colombia, Pakistan, Philippines and Portugal, where a neutral relationship is found. We find, however, considerable evidence of bi-directionality in Finland and Sweden. This indicates that high levels of unemployment lead to high levels of shadow economy and vice versa. We also find clear evidence of unidirectional causality running from unemployment to shadow economy in the US, Jamaica and Venezuela which implies that, in these three countries, a faster rate of unemployment promotes a higher share of the underground economy in total GDP. Further, the causality relationship appears to be uni-directional but reversed for Chile. Overall, our findings suggest that policy implications of the unemployment-shadow economy relationships should be interpreted with caution, taking into account the test-dependent and country-specific results.

Relationship between unemployment rate and shadow economy of selected mena countries: a toda -yamamoto and panel causality approach

“…In comparison, the results of the shadow economy granger cause the unemployment rate to be statistically significant in all cases, excluding lag number 6 is not statistically significant. The finding of the panel study confirmed previous empirical studies by Saafi, Farhat and Mohamed(2015) and Sahnoun and Abdennadher(2019),They found mixed results of bidirectional causality between the two variables under investigation and unidirectional causality running from unemployment rate to the shadow economy. However, the present study found strong unidirectional causality running from the shadow economy to the unemployment rate.…”

Causal Nexus between Financial Integration and Economic Growth : Does Nonlinearity Matter?

“…This approach has also become a prominent technique to study the linear causal relation between economic and financial variables. For example, it has been shown to be especially useful for exploring the relations between healthcare expenditure and GDP (Amiri and Ventelou (Nazlioglu and Soytas 2011), oil price shocks and stock market performance (Le and Chang 2015), terms of trade and economic growth (Jawaid and Raza 2013), energy consumption and output (Payne 2009, Menyah andWolde-Rufael 2010), debt and growth (Kemba and Khan 2016), the shadow economy and unemployment (Saafi et al 2015a(Saafi et al , 2015b, and economic growth and financial development (Abu-Bader andAbu-Qarn 2008, Wolde-Rufael 2009). Toda and Yamamoto (1995) used the modified Wald (MWALD) statistic for testing linear restrictions on the coefficients in an augmented VAR (k + d max ) model, where k is the optimal lag order in the VAR system and d max is the maximal order of integration in the model.…”

“…integration and economic growth are likely to exhibit a nonlinear pattern, and their joint dynamics imply a more complex than just a simple and stable relationship. In view of this, nonparametric analysis techniques are more suitable because they place direct emphasis on prediction without imposing a linear functional form (Saafi et al 2015a). The failure in previous literature to account for asymmetry and nonlinearity between financial integration and economic growth may have resulted in incorrect inferences about the existence/non-existence of the financial integration-growth relation.…”

“…The most important feature of the nonlinear M-G process is that it enables the filtering of the more complex dependent dynamics in a time series (Kyrtsou and Labys 2006). Because of this advantage, it has been widely used in the literature (Kyrtsou and Labys 2006, Hristu Varsekelis and Kyrtsou 2008, Kumar 2009, Kumar and Thenmozhi 2012, Ajmi et al 2013, Bildirici and Turkmen 2015, Saafi et al 2015a, 2015b. It is expected that the analysis in this study will add new insights to the existing literature that will help the policymakers to formulate and implement sound economic policies in order to sustain economic development.…”

Researching the Main Causes of the Romanian Shadow Economy at the Micro and Macro Levels: Implications for Sustainable Development

“…Luo and Shang [73] stated that the unemployment rate serves as an index for describing the economy. Saafi and Farhat [74] and Saafi, Farhat, Mohamed, and Bel [75] proved that there is causality between unemployment and the unofficial sector.…”