U.S. Shadow Economies: A State-Level Study

Wiseman, Travis

doi:10.2139/ssrn.2208637

Cited by 9 publications

(16 citation statements)

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“…An unresolved issue with the multiple indicators multiple causes (MIMIC) model relates to the difficulty with differentiating between the causes and indicators of the shadow economy (Dreher and Schneider 2010;Schneider and Buehn 2014). We follow the extant literature in the choice of shadow determinants (Dreher and Schneider 2010;Wiseman 2013aWiseman , 2013b and also perform various robustness checks to alleviate these concerns.…”

Section: Empirical Setupmentioning

confidence: 99%

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Casting a Long Shadow? Cross-border Spillovers of Shadow Economy across American States

Goel

Saunoris

2015

Public Finance Review

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This article examines the determinants of the shadow economy across American states, with emphasis on cross-border spillover effects. Results show positive spillovers of shadow activities across state borders with different specifications. In other effects, greater unionization in a state induces businesses to go underground, while states without a sales tax had a smaller shadow economy, ceteris paribus. Greater state product checked shadow growth, with military and nonmilitary state products having opposite effects. Finally, states bordering Canada and Mexico had different flows from the shadow sector.

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Section: Empirical Setupmentioning

confidence: 99%

“…1 The prevalence of the shadow sector across various states is variable and often a significant part of the overall economic activity (Wiseman 2013a(Wiseman , 2013b. The federalist structure of the U.S. government provides enough autonomy to individual states in that in many respects they behave like individual nations (Craig and Sailors 1987).…”

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confidence: 99%

Casting a Long Shadow? Cross-border Spillovers of Shadow Economy across American States

Goel

Saunoris

2015

Public Finance Review

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“…β1 is a coefficient for the determinant of interest; β0 is a constant. Data for shadow economy size come from MIMIC model estimates provided in Wiseman (2013). The size of the shadow economy is represented as a proportion of state-level GDP.…”

Section: Baseline Modelmentioning

confidence: 99%

“…These entrepreneurs are of the lot who serve as a foundation for underground activity, as their participation in the underground to developing shadow economies in the face of increased cronyism.Using state-level data on shadow economy size fromWiseman (2013), productive entrepreneurship scores fromWiseman and Young (2014), and data on federal corruption convictions of U.S. public officials, this paper investigates the relationships among shadow economies, corruption, and entrepreneurship in regression analyses, with the above theory in mind.…”

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confidence: 99%

U.S. Shadow Economies, Corruption, and Entrepreneurship: State-Level Spatial Relations

Wiseman

2014

SSRN Journal

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This paper offers a new theory of relationship between corruption and the shadow economy, one that defines it as either collusive -i.e., crony -or non-collusive. Using new estimates of state-level shadow economy size and data on corruption convictions of U.S. public officials for the 48 contiguous states, this study revisits this relationship empirically, controlling for spatial dependence. Additionally, the relationship between entrepreneurship and cronyism is investigated using productive entrepreneurship scores from Wiseman and Young (2014). Findings suggest that corruption and shadow economy size are positively related and both contagious and cross-contagious in the U.S. states. These results are fairly robust to several methods of spatial modeling. Results also reveal that productive entrepreneurship is contagious across states. Finally, this study attempts to draw a linkage among formal sector entrepreneurial outcomes, corruption, and the shadow economy using spatial GMM/IV modeling in an entrepreneurship regression.

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“…Such an increase may imply a reduction in government transfers, which in turn might incentivize more labor force participation in low‐skill jobs. Low‐income states also have larger shadow economies (Wiseman ) and therefore possibly a larger pool of underground labor ready to join the official sector should a change in regulation make it easier to do so. High‐income jobs may not be readily available or difficult to create in low‐income states because, in part, of low average skill sets.…”

Section: Introductionmentioning

confidence: 99%

Economic Freedom and Growth in U.S. State‐level Market Incomes at the Top and Bottom

Wiseman

2016

Contemporary Economic Policy

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This paper investigates the relationship between economic freedom and income growth and inequality across U.S. states over the period 1979-2011. The focus is on market income at the top and bottom of the income distribution. Results show that increases in overall freedom are associated with average income growth. When viewed separately, an increase in overall freedom is associated with larger income growth rates for income earners in the bottom 90% relative to the top 10%. Interestingly, results show that increases in overall economic freedom are related to larger relative growth rates for the top 10% incomes within high-income states and larger relative growth rates for the bottom 90% incomes within low-income states. Top-to-bottom income ratio regressions suggest a negative and statistically significant relationship between economic freedom and income inequality. (JEL D63, P16, R11)

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U.S. Shadow Economies: A State-Level Study

Cited by 9 publications

References 0 publications

Casting a Long Shadow? Cross-border Spillovers of Shadow Economy across American States

Casting a Long Shadow? Cross-border Spillovers of Shadow Economy across American States

U.S. Shadow Economies, Corruption, and Entrepreneurship: State-Level Spatial Relations

Economic Freedom and Growth in U.S. State‐level Market Incomes at the Top and Bottom

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