The Shadow Economy and Shadow Economy Labor Force in OECD Countries: What do we (not) know?

This work analyzes the tourist sector, the employment generated by the tourism industries, and its relationship with tourism receipts. The hypothesis is that there are tourist subsectors with a potentially higher level of income. The article studies the impact of the distribution of the employed population in the different subsectors of the tourism industry, controlling for the most important economic variables, on the level of income per arrival in 24 OECD countries, using panel data for the period 2008–2018. As its main result, the model indicates that the labor force that increases most the receipts per arrival is the ‘travel agencies and other reservation services’, followed by the ‘sports and recreation industry’ labor force, while having a large labor force in the ‘food and beverage’ or ‘cultural industry’ operates in the opposite direction.

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Shadow Economies: Size, Causes, and Consequences

Journal of Economic Literature ◽

10.1257/jel.38.1.77 ◽

2000 ◽

Vol 38 (1) ◽

pp. 77-114 ◽

Cited By ~ 1089

Author(s):

Friedrich Schneider ◽

Dominik H Enste

Keyword(s):

Developing Countries ◽

Shadow Economy ◽

Driving Forces ◽

Positive Impact ◽

Oecd Countries ◽

Gdp Growth ◽

State Regulations ◽

Shadow Economies ◽

Negative Effect ◽

Average Size

Using various methods, the size of the shadow economy in 76 developing, transition, and OECD countries is estimated. Average size varies from 12 percent of GDP for OECD countries, to 23 percent for transition countries and 39 percent for developing countries. Increasing taxation and social security contributions combined with rising state regulations are driving forces for the increase of the shadow economy, especially in OECD countries. According to some findings, corruption has a positive impact on the size of the shadow economy, and a growing shadow economy has a negative effect on official GDP growth.

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Are Labor Force Participation Rates Really Non-Stationary? Evidence from Three OECD Countries

SSRN Electronic Journal ◽

10.2139/ssrn.2157918 ◽

2012 ◽

Author(s):

Zeynel Abidin Ozdemir ◽

Mehmet Balcilar ◽

Aysit Tansel

Keyword(s):

Labor Force ◽

Labor Force Participation ◽

Oecd Countries ◽

Participation Rates

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The Shadow Economy-Environmental Quality Nexus In OECD Countries: Empirical Evidence From Panel Quantile Regression

10.21203/rs.3.rs-1047259/v1 ◽

2021 ◽

Author(s):

Lan Khanh Chu ◽

Dung Phuong Hoang

Keyword(s):

Quantile Regression ◽

Informal Economy ◽

Ecological Footprint ◽

Shadow Economy ◽

Trade Openness ◽

Oecd Countries ◽

Causality Test ◽

Panel Quantile Regression ◽

Determining Factors ◽

The One

Abstract This study explores the determinants of ecological footprint by integrating the influence of the shadow economy. The findings based on the panel quantile regression indicate that the environmental effects of the shadow economy, trade openness, energy intensity, renewable energy, and income are not homogeneous across various levels of ecological footprint. The shadow economy-ecological footprint nexus follows an inverted U-shaped pattern. Initially, the higher size of the informal economy leads to more ecosystem degradation. When the shadow economy increases to certain thresholds, its environmental impact reverts to benefit. Such threshold changes with the evolution of ecological footprint. Specifically, it first rises then decreases along with the degradation of the ecosystem. Moreover, the heterogeneous panel causality test reports the one-way directional running from the shadow economy to the ecological footprint in OECD countries. The significant and heterogeneous relationships between ecological footprint and its determining factors are also established.

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