Quantitative analysis of optimum corrective fuel tax for road vehicles in Bangladesh: achieving the greenhouse gas reduction goal

Abstract This study estimates optimum corrective fuel taxes for Bangladesh and correlates them with climate change policy. First, we use the European road transport emission model (COPERT IV) to precisely estimate the externalities. Second, using the same model, we also estimate the reduction in gre...
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Autor*in:	Kamruzzaman, Mohammad Haider [verfasserIn] Mizunoya, Takeshi [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Vehicle emissions Gasoline tax Diesel tax Corrective fuel tax Welfare gains Bangladesh

Übergeordnetes Werk:	Enthalten in: Asia-Pacific journal of regional science - [Singapore] : Springer Singapore, 2017, 5(2020), 1 vom: 11. Okt., Seite 91-124
Übergeordnetes Werk:	volume:5 ; year:2020 ; number:1 ; day:11 ; month:10 ; pages:91-124

Links:	Volltext

DOI / URN:	10.1007/s41685-020-00173-5

Katalog-ID:	SPR043331076

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245	1	0	\|a Quantitative analysis of optimum corrective fuel tax for road vehicles in Bangladesh: achieving the greenhouse gas reduction goal
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520			\|a Abstract This study estimates optimum corrective fuel taxes for Bangladesh and correlates them with climate change policy. First, we use the European road transport emission model (COPERT IV) to precisely estimate the externalities. Second, using the same model, we also estimate the reduction in greenhouse gas emissions caused by the fuel tax. Finally, we develop a correlation between the fuel tax rate and emissions reduction. Our benchmark calculation of the optimum corrective tax is US$0.94 per gallon for gasoline and US$1.46 per gallon for diesel (in 2016 prices). We find that congestion and accident externalities are the two main fuel tax components for Bangladesh. We also find that the net social welfare gain per year is US$302.11 million and the net revenue gain per year is 3.59% of GDP. The corrective diesel tax reduces fuel consumption by 18.10% and increases fuel efficiency by 12.53%. In the benchmark case, corrective fuel taxes reduce GHG emissions by 5.77%. With the combination of the existing gasoline tax and a diesel tax of US$1.20 per gallon, the country’s greenhouse gas reduction goal can be achieved. Policymakers can use fuel taxes to support climate change policy.
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matchkey_str	article:25097954:2020----::uniaienlssfpiucretvfetxoravhceibnldsahei
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allfields	10.1007/s41685-020-00173-5 doi (DE-627)SPR043331076 (DE-599)SPRs41685-020-00173-5-e (SPR)s41685-020-00173-5-e DE-627 ger DE-627 rakwb eng 300 ASE 300 ASE Kamruzzaman, Mohammad Haider verfasserin aut Quantitative analysis of optimum corrective fuel tax for road vehicles in Bangladesh: achieving the greenhouse gas reduction goal 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study estimates optimum corrective fuel taxes for Bangladesh and correlates them with climate change policy. First, we use the European road transport emission model (COPERT IV) to precisely estimate the externalities. Second, using the same model, we also estimate the reduction in greenhouse gas emissions caused by the fuel tax. Finally, we develop a correlation between the fuel tax rate and emissions reduction. Our benchmark calculation of the optimum corrective tax is US$0.94 per gallon for gasoline and US$1.46 per gallon for diesel (in 2016 prices). We find that congestion and accident externalities are the two main fuel tax components for Bangladesh. We also find that the net social welfare gain per year is US$302.11 million and the net revenue gain per year is 3.59% of GDP. The corrective diesel tax reduces fuel consumption by 18.10% and increases fuel efficiency by 12.53%. In the benchmark case, corrective fuel taxes reduce GHG emissions by 5.77%. With the combination of the existing gasoline tax and a diesel tax of US$1.20 per gallon, the country’s greenhouse gas reduction goal can be achieved. Policymakers can use fuel taxes to support climate change policy. Vehicle emissions (dpeaa)DE-He213 Gasoline tax (dpeaa)DE-He213 Diesel tax (dpeaa)DE-He213 Corrective fuel tax (dpeaa)DE-He213 Welfare gains (dpeaa)DE-He213 Bangladesh (dpeaa)DE-He213 Mizunoya, Takeshi verfasserin aut Enthalten in Asia-Pacific journal of regional science [Singapore] : Springer Singapore, 2017 5(2020), 1 vom: 11. Okt., Seite 91-124 (DE-627)87812652X (DE-600)2882268-7 2509-7954 nnns volume:5 year:2020 number:1 day:11 month:10 pages:91-124 https://dx.doi.org/10.1007/s41685-020-00173-5 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-WIW SSG-OLC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 5 2020 1 11 10 91-124
spelling	10.1007/s41685-020-00173-5 doi (DE-627)SPR043331076 (DE-599)SPRs41685-020-00173-5-e (SPR)s41685-020-00173-5-e DE-627 ger DE-627 rakwb eng 300 ASE 300 ASE Kamruzzaman, Mohammad Haider verfasserin aut Quantitative analysis of optimum corrective fuel tax for road vehicles in Bangladesh: achieving the greenhouse gas reduction goal 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study estimates optimum corrective fuel taxes for Bangladesh and correlates them with climate change policy. First, we use the European road transport emission model (COPERT IV) to precisely estimate the externalities. Second, using the same model, we also estimate the reduction in greenhouse gas emissions caused by the fuel tax. Finally, we develop a correlation between the fuel tax rate and emissions reduction. Our benchmark calculation of the optimum corrective tax is US$0.94 per gallon for gasoline and US$1.46 per gallon for diesel (in 2016 prices). We find that congestion and accident externalities are the two main fuel tax components for Bangladesh. We also find that the net social welfare gain per year is US$302.11 million and the net revenue gain per year is 3.59% of GDP. The corrective diesel tax reduces fuel consumption by 18.10% and increases fuel efficiency by 12.53%. In the benchmark case, corrective fuel taxes reduce GHG emissions by 5.77%. With the combination of the existing gasoline tax and a diesel tax of US$1.20 per gallon, the country’s greenhouse gas reduction goal can be achieved. Policymakers can use fuel taxes to support climate change policy. Vehicle emissions (dpeaa)DE-He213 Gasoline tax (dpeaa)DE-He213 Diesel tax (dpeaa)DE-He213 Corrective fuel tax (dpeaa)DE-He213 Welfare gains (dpeaa)DE-He213 Bangladesh (dpeaa)DE-He213 Mizunoya, Takeshi verfasserin aut Enthalten in Asia-Pacific journal of regional science [Singapore] : Springer Singapore, 2017 5(2020), 1 vom: 11. Okt., Seite 91-124 (DE-627)87812652X (DE-600)2882268-7 2509-7954 nnns volume:5 year:2020 number:1 day:11 month:10 pages:91-124 https://dx.doi.org/10.1007/s41685-020-00173-5 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-WIW SSG-OLC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 5 2020 1 11 10 91-124
allfields_unstemmed	10.1007/s41685-020-00173-5 doi (DE-627)SPR043331076 (DE-599)SPRs41685-020-00173-5-e (SPR)s41685-020-00173-5-e DE-627 ger DE-627 rakwb eng 300 ASE 300 ASE Kamruzzaman, Mohammad Haider verfasserin aut Quantitative analysis of optimum corrective fuel tax for road vehicles in Bangladesh: achieving the greenhouse gas reduction goal 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study estimates optimum corrective fuel taxes for Bangladesh and correlates them with climate change policy. First, we use the European road transport emission model (COPERT IV) to precisely estimate the externalities. Second, using the same model, we also estimate the reduction in greenhouse gas emissions caused by the fuel tax. Finally, we develop a correlation between the fuel tax rate and emissions reduction. Our benchmark calculation of the optimum corrective tax is US$0.94 per gallon for gasoline and US$1.46 per gallon for diesel (in 2016 prices). We find that congestion and accident externalities are the two main fuel tax components for Bangladesh. We also find that the net social welfare gain per year is US$302.11 million and the net revenue gain per year is 3.59% of GDP. The corrective diesel tax reduces fuel consumption by 18.10% and increases fuel efficiency by 12.53%. In the benchmark case, corrective fuel taxes reduce GHG emissions by 5.77%. With the combination of the existing gasoline tax and a diesel tax of US$1.20 per gallon, the country’s greenhouse gas reduction goal can be achieved. Policymakers can use fuel taxes to support climate change policy. Vehicle emissions (dpeaa)DE-He213 Gasoline tax (dpeaa)DE-He213 Diesel tax (dpeaa)DE-He213 Corrective fuel tax (dpeaa)DE-He213 Welfare gains (dpeaa)DE-He213 Bangladesh (dpeaa)DE-He213 Mizunoya, Takeshi verfasserin aut Enthalten in Asia-Pacific journal of regional science [Singapore] : Springer Singapore, 2017 5(2020), 1 vom: 11. Okt., Seite 91-124 (DE-627)87812652X (DE-600)2882268-7 2509-7954 nnns volume:5 year:2020 number:1 day:11 month:10 pages:91-124 https://dx.doi.org/10.1007/s41685-020-00173-5 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-WIW SSG-OLC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 5 2020 1 11 10 91-124
allfieldsGer	10.1007/s41685-020-00173-5 doi (DE-627)SPR043331076 (DE-599)SPRs41685-020-00173-5-e (SPR)s41685-020-00173-5-e DE-627 ger DE-627 rakwb eng 300 ASE 300 ASE Kamruzzaman, Mohammad Haider verfasserin aut Quantitative analysis of optimum corrective fuel tax for road vehicles in Bangladesh: achieving the greenhouse gas reduction goal 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study estimates optimum corrective fuel taxes for Bangladesh and correlates them with climate change policy. First, we use the European road transport emission model (COPERT IV) to precisely estimate the externalities. Second, using the same model, we also estimate the reduction in greenhouse gas emissions caused by the fuel tax. Finally, we develop a correlation between the fuel tax rate and emissions reduction. Our benchmark calculation of the optimum corrective tax is US$0.94 per gallon for gasoline and US$1.46 per gallon for diesel (in 2016 prices). We find that congestion and accident externalities are the two main fuel tax components for Bangladesh. We also find that the net social welfare gain per year is US$302.11 million and the net revenue gain per year is 3.59% of GDP. The corrective diesel tax reduces fuel consumption by 18.10% and increases fuel efficiency by 12.53%. In the benchmark case, corrective fuel taxes reduce GHG emissions by 5.77%. With the combination of the existing gasoline tax and a diesel tax of US$1.20 per gallon, the country’s greenhouse gas reduction goal can be achieved. Policymakers can use fuel taxes to support climate change policy. Vehicle emissions (dpeaa)DE-He213 Gasoline tax (dpeaa)DE-He213 Diesel tax (dpeaa)DE-He213 Corrective fuel tax (dpeaa)DE-He213 Welfare gains (dpeaa)DE-He213 Bangladesh (dpeaa)DE-He213 Mizunoya, Takeshi verfasserin aut Enthalten in Asia-Pacific journal of regional science [Singapore] : Springer Singapore, 2017 5(2020), 1 vom: 11. Okt., Seite 91-124 (DE-627)87812652X (DE-600)2882268-7 2509-7954 nnns volume:5 year:2020 number:1 day:11 month:10 pages:91-124 https://dx.doi.org/10.1007/s41685-020-00173-5 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-WIW SSG-OLC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 5 2020 1 11 10 91-124
allfieldsSound	10.1007/s41685-020-00173-5 doi (DE-627)SPR043331076 (DE-599)SPRs41685-020-00173-5-e (SPR)s41685-020-00173-5-e DE-627 ger DE-627 rakwb eng 300 ASE 300 ASE Kamruzzaman, Mohammad Haider verfasserin aut Quantitative analysis of optimum corrective fuel tax for road vehicles in Bangladesh: achieving the greenhouse gas reduction goal 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This study estimates optimum corrective fuel taxes for Bangladesh and correlates them with climate change policy. First, we use the European road transport emission model (COPERT IV) to precisely estimate the externalities. Second, using the same model, we also estimate the reduction in greenhouse gas emissions caused by the fuel tax. Finally, we develop a correlation between the fuel tax rate and emissions reduction. Our benchmark calculation of the optimum corrective tax is US$0.94 per gallon for gasoline and US$1.46 per gallon for diesel (in 2016 prices). We find that congestion and accident externalities are the two main fuel tax components for Bangladesh. We also find that the net social welfare gain per year is US$302.11 million and the net revenue gain per year is 3.59% of GDP. The corrective diesel tax reduces fuel consumption by 18.10% and increases fuel efficiency by 12.53%. In the benchmark case, corrective fuel taxes reduce GHG emissions by 5.77%. With the combination of the existing gasoline tax and a diesel tax of US$1.20 per gallon, the country’s greenhouse gas reduction goal can be achieved. Policymakers can use fuel taxes to support climate change policy. Vehicle emissions (dpeaa)DE-He213 Gasoline tax (dpeaa)DE-He213 Diesel tax (dpeaa)DE-He213 Corrective fuel tax (dpeaa)DE-He213 Welfare gains (dpeaa)DE-He213 Bangladesh (dpeaa)DE-He213 Mizunoya, Takeshi verfasserin aut Enthalten in Asia-Pacific journal of regional science [Singapore] : Springer Singapore, 2017 5(2020), 1 vom: 11. Okt., Seite 91-124 (DE-627)87812652X (DE-600)2882268-7 2509-7954 nnns volume:5 year:2020 number:1 day:11 month:10 pages:91-124 https://dx.doi.org/10.1007/s41685-020-00173-5 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-WIW SSG-OLC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_266 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 5 2020 1 11 10 91-124
language	English
source	Enthalten in Asia-Pacific journal of regional science 5(2020), 1 vom: 11. Okt., Seite 91-124 volume:5 year:2020 number:1 day:11 month:10 pages:91-124
sourceStr	Enthalten in Asia-Pacific journal of regional science 5(2020), 1 vom: 11. Okt., Seite 91-124 volume:5 year:2020 number:1 day:11 month:10 pages:91-124
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Vehicle emissions Gasoline tax Diesel tax Corrective fuel tax Welfare gains Bangladesh
dewey-raw	300
isfreeaccess_bool	true
container_title	Asia-Pacific journal of regional science
authorswithroles_txt_mv	Kamruzzaman, Mohammad Haider @@aut@@ Mizunoya, Takeshi @@aut@@
publishDateDaySort_date	2020-10-11T00:00:00Z
hierarchy_top_id	87812652X
dewey-sort	3300
id	SPR043331076
language_de	englisch
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author	Kamruzzaman, Mohammad Haider
spellingShingle	Kamruzzaman, Mohammad Haider ddc 300 misc Vehicle emissions misc Gasoline tax misc Diesel tax misc Corrective fuel tax misc Welfare gains misc Bangladesh Quantitative analysis of optimum corrective fuel tax for road vehicles in Bangladesh: achieving the greenhouse gas reduction goal
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topic_title	300 ASE Quantitative analysis of optimum corrective fuel tax for road vehicles in Bangladesh: achieving the greenhouse gas reduction goal Vehicle emissions (dpeaa)DE-He213 Gasoline tax (dpeaa)DE-He213 Diesel tax (dpeaa)DE-He213 Corrective fuel tax (dpeaa)DE-He213 Welfare gains (dpeaa)DE-He213 Bangladesh (dpeaa)DE-He213
topic	ddc 300 misc Vehicle emissions misc Gasoline tax misc Diesel tax misc Corrective fuel tax misc Welfare gains misc Bangladesh
topic_unstemmed	ddc 300 misc Vehicle emissions misc Gasoline tax misc Diesel tax misc Corrective fuel tax misc Welfare gains misc Bangladesh
topic_browse	ddc 300 misc Vehicle emissions misc Gasoline tax misc Diesel tax misc Corrective fuel tax misc Welfare gains misc Bangladesh
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title	Quantitative analysis of optimum corrective fuel tax for road vehicles in Bangladesh: achieving the greenhouse gas reduction goal
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title_full	Quantitative analysis of optimum corrective fuel tax for road vehicles in Bangladesh: achieving the greenhouse gas reduction goal
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author_browse	Kamruzzaman, Mohammad Haider Mizunoya, Takeshi
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title_sort	quantitative analysis of optimum corrective fuel tax for road vehicles in bangladesh: achieving the greenhouse gas reduction goal
title_auth	Quantitative analysis of optimum corrective fuel tax for road vehicles in Bangladesh: achieving the greenhouse gas reduction goal
abstract	Abstract This study estimates optimum corrective fuel taxes for Bangladesh and correlates them with climate change policy. First, we use the European road transport emission model (COPERT IV) to precisely estimate the externalities. Second, using the same model, we also estimate the reduction in greenhouse gas emissions caused by the fuel tax. Finally, we develop a correlation between the fuel tax rate and emissions reduction. Our benchmark calculation of the optimum corrective tax is US$0.94 per gallon for gasoline and US$1.46 per gallon for diesel (in 2016 prices). We find that congestion and accident externalities are the two main fuel tax components for Bangladesh. We also find that the net social welfare gain per year is US$302.11 million and the net revenue gain per year is 3.59% of GDP. The corrective diesel tax reduces fuel consumption by 18.10% and increases fuel efficiency by 12.53%. In the benchmark case, corrective fuel taxes reduce GHG emissions by 5.77%. With the combination of the existing gasoline tax and a diesel tax of US$1.20 per gallon, the country’s greenhouse gas reduction goal can be achieved. Policymakers can use fuel taxes to support climate change policy.
abstractGer	Abstract This study estimates optimum corrective fuel taxes for Bangladesh and correlates them with climate change policy. First, we use the European road transport emission model (COPERT IV) to precisely estimate the externalities. Second, using the same model, we also estimate the reduction in greenhouse gas emissions caused by the fuel tax. Finally, we develop a correlation between the fuel tax rate and emissions reduction. Our benchmark calculation of the optimum corrective tax is US$0.94 per gallon for gasoline and US$1.46 per gallon for diesel (in 2016 prices). We find that congestion and accident externalities are the two main fuel tax components for Bangladesh. We also find that the net social welfare gain per year is US$302.11 million and the net revenue gain per year is 3.59% of GDP. The corrective diesel tax reduces fuel consumption by 18.10% and increases fuel efficiency by 12.53%. In the benchmark case, corrective fuel taxes reduce GHG emissions by 5.77%. With the combination of the existing gasoline tax and a diesel tax of US$1.20 per gallon, the country’s greenhouse gas reduction goal can be achieved. Policymakers can use fuel taxes to support climate change policy.
abstract_unstemmed	Abstract This study estimates optimum corrective fuel taxes for Bangladesh and correlates them with climate change policy. First, we use the European road transport emission model (COPERT IV) to precisely estimate the externalities. Second, using the same model, we also estimate the reduction in greenhouse gas emissions caused by the fuel tax. Finally, we develop a correlation between the fuel tax rate and emissions reduction. Our benchmark calculation of the optimum corrective tax is US$0.94 per gallon for gasoline and US$1.46 per gallon for diesel (in 2016 prices). We find that congestion and accident externalities are the two main fuel tax components for Bangladesh. We also find that the net social welfare gain per year is US$302.11 million and the net revenue gain per year is 3.59% of GDP. The corrective diesel tax reduces fuel consumption by 18.10% and increases fuel efficiency by 12.53%. In the benchmark case, corrective fuel taxes reduce GHG emissions by 5.77%. With the combination of the existing gasoline tax and a diesel tax of US$1.20 per gallon, the country’s greenhouse gas reduction goal can be achieved. Policymakers can use fuel taxes to support climate change policy.
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title_short	Quantitative analysis of optimum corrective fuel tax for road vehicles in Bangladesh: achieving the greenhouse gas reduction goal
url	https://dx.doi.org/10.1007/s41685-020-00173-5
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up_date	2024-07-03T17:59:16.311Z
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Quantitative analysis of optimum corrective fuel tax for road vehicles in Bangladesh: achieving the greenhouse gas reduction goal

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Vorhandene Bände

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