Optimal Design of Transport Tax on the Way to National Security: Balancing Environmental Footprint, Energy Efficiency and Economic Growth
Abstract
1. Introduction
2. Materials and Methods
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Country | The Name of the Tax | Tax Base | Tax Rates |
---|---|---|---|
Czech Republic | Road tax | Vehicle type and weight | In Czech crowns per year |
Finland | Car tax | Cost of the vehicle/Emissions from the vehicle | In % of the cost/In euros |
Transport tax | Vehicle type and weight | In euros for 1 day per 100 kg of vehicle weight | |
France | Annual tax on company cars | The amount of carbon dioxide emissions from the car | In euros for 1 g of CO2 emissions per 1 km |
Ireland | Tax on vehicles | Type of vehicle | In euros per year |
Vehicle registration tax | The cost of the vehicle | In % of the cost | |
Israel | Vehicle registration or use tax | Cost and age of the vehicle | In new Israeli shekels per car |
Portugal | Vehicle turnover tax | Type of vehicle | In euros per year |
Slovakia | Transport tax | Vehicle type and weight | In euros per year |
Romania | Annual transport tax | Volume of engine cylinders | In Romanian lei for 500 cm3 |
Turkey | Vehicle ownership tax | Type, age and volume of engine cylinders | In euros per year |
Country | Type | Weight | Type of Fuel | Volume of Engine Cylinders | CO2 Emissions | Cost | Age |
---|---|---|---|---|---|---|---|
Czech Republic | 1 | 1 | 0 | 1 | 0 | 0 | 0 |
Finland | 1 | 1 | 0 | 0 | 1 | 0 | 0 |
France | 0 | 0 | 0 | 0 | 1 | 0 | 0 |
Ireland | 0 | 0 | 0 | 1 | 1 | 0 | 0 |
Israel | 0 | 0 | 0 | 0 | 0 | 1 | 1 |
Portugal | 1 | 0 | 1 | 1 | 0 | 0 | 0 |
Romania | 1 | 0 | 0 | 1 | 0 | 0 | 0 |
Slovakia | 1 | 1 | 0 | 1 | 0 | 0 | 0 |
Turkey | 1 | 0 | 0 | 1 | 0 | 0 | 1 |
Variable | Coefficient | Std. Error | t-Value | p-Value | Lower 95% | Higher 95% |
---|---|---|---|---|---|---|
ETR | 3.26 × 10−6 | 0.0000 | 0.32 | 0.752 | −0.0000 | 0.0000 |
Dummy_Type | 0.0375 *** | 0.0099 | 3.78 | 0.000 | 0.0180 | 0.0570 |
Constant | 0.2850 *** | 0.0295 | 9.64 | 0.000 | 0.2271 | 0.3430 |
Model-adequacy parameters | ||||||
Wald chi2(2) | 14.70 | |||||
Prob > chi2 | 0.0006 |
Variable | Coefficient | Std. Error | t-Value | p-Value | Lower 95% | Higher 95% |
---|---|---|---|---|---|---|
ETR | 4.84 × 10−6 | 9.49 × 10−6 | 0.51 | 0.610 | −0.0000 | 0.0000 |
Dummy_Weight | 0.0272 ** | 0.0122 | 2.22 | 0.027 | 0.0031 | 0.0513 |
Constant | 0.2998 *** | 0.0237 | 12.65 | 0.000 | 0.2534 | 0.3463 |
Model-adequacy parameters | ||||||
Wald chi2(2) | 6.09 | |||||
Prob > chi2 | 0.0477 |
Variable | Coefficient | Std. Error | t-Value | p-Value | Lower 95% | Higher 95% |
---|---|---|---|---|---|---|
ETR | 1.89 × 10−6 | 0.0000 | 0.18 | 0.854 | −0.0000 | 0.0000 |
Dummy_Fuel | 0.0168 | 0.0167 | 1.01 | 0.314 | −0.0159 | 0.0496 |
Constant | 0.3092 *** | 0.0265 | 11.67 | 0.000 | 0.2572 | 0.3611 |
Model-adequacy parameters | ||||||
Wald chi2(2) | 1.01 | |||||
Prob > chi2 | 0.6021 |
Variable | Coefficient | Std. Error | t-Value | p-Value | Lower 95% | Higher 95% |
---|---|---|---|---|---|---|
ETR | 1.34 × 10−6 | 0.0000 | 0.13 | 0.900 | −0.0000 | 0.0000 |
Dummy_Capacity | 0.0134 | 0.0210 | 0.64 | 0.522 | −0.0277 | 0.0546 |
Constant | 0.3024 *** | 0.0400 | 7.56 | 0.000 | 0.2240 | 0.3808 |
Model-adequacy parameters | ||||||
Wald chi2(2) | 0.63 | |||||
Prob > chi2 | 0.7300 |
Variable | Coefficient | Std. Error | t-Value | p-Value | Lower 95% | Higher 95% |
---|---|---|---|---|---|---|
ETR | −4.77 × 10−7 | 0.0000 | −0.04 | 0.966 | −0.0000 | 0.0000 |
Dummy_Emissions | 0.0186 | 0.0196 | 0.95 | 0.343 | −0.0198 | 0.0571 |
Constant | 0.3065 *** | 0.0216 | 14.17 | 0.000 | 0.2641 | 0.3489 |
Model-adequacy parameters | ||||||
Wald chi2(2) | 1.90 | |||||
Prob > chi2 | 0.3874 |
Variable | Coefficient | Std. Error | t-Value | p-Value | Lower 95% | Higher 95% |
---|---|---|---|---|---|---|
ETR | 9.11 × 10−7 | 0.0000 | 0.09 | 0.929 | −0.0000 | 0.0000 |
Dummy_Price | −0.0807 *** | 0.0104 | −7.75 | 0.000 | −0.1011 | −0.0603 |
Constant | 0.3204 *** | 0.0269 | 11.88 | 0.000 | 0.2675 | 0.3738 |
Model-adequacy parameters | ||||||
Wald chi2(2) | 68.31 | |||||
Prob > chi2 | 0.0000 |
Variable | Coefficient | Std. Error | t-Value | p-Value | Lower 95% | Higher 95% |
---|---|---|---|---|---|---|
ETR | 0.0000 *** | 7.02 × 10−6 | 3.19 | 0.001 | 8.62 × 10−6 | 0.0000 |
Dummy_Age | −0.0955 *** | 0.0244 | −3.91 | 0.000 | −0.1434 | −0.0475 |
Constant | 0.3170 *** | 0.0271 | 11.69 | 0.000 | 0.2639 | 0.3702 |
Model-adequacy parameters | ||||||
Wald chi2(2) | 39.45 | |||||
Prob > chi2 | 0.0000 |
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Samusevych, Y.; Lyeonov, S.; Artyukhov, A.; Martyniuk, V.; Tenytska, I.; Wyrwisz, J.; Wojciechowska, K. Optimal Design of Transport Tax on the Way to National Security: Balancing Environmental Footprint, Energy Efficiency and Economic Growth. Sustainability 2023, 15, 831. https://doi.org/10.3390/su15010831
Samusevych Y, Lyeonov S, Artyukhov A, Martyniuk V, Tenytska I, Wyrwisz J, Wojciechowska K. Optimal Design of Transport Tax on the Way to National Security: Balancing Environmental Footprint, Energy Efficiency and Economic Growth. Sustainability. 2023; 15(1):831. https://doi.org/10.3390/su15010831
Chicago/Turabian StyleSamusevych, Yaryna, Serhiy Lyeonov, Artem Artyukhov, Volodymyr Martyniuk, Iryna Tenytska, Joanna Wyrwisz, and Krystyna Wojciechowska. 2023. "Optimal Design of Transport Tax on the Way to National Security: Balancing Environmental Footprint, Energy Efficiency and Economic Growth" Sustainability 15, no. 1: 831. https://doi.org/10.3390/su15010831
APA StyleSamusevych, Y., Lyeonov, S., Artyukhov, A., Martyniuk, V., Tenytska, I., Wyrwisz, J., & Wojciechowska, K. (2023). Optimal Design of Transport Tax on the Way to National Security: Balancing Environmental Footprint, Energy Efficiency and Economic Growth. Sustainability, 15(1), 831. https://doi.org/10.3390/su15010831