Distributional effects of environmental taxation in Norway

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Distributional effects of environmental taxation in Norway

Calle Kumlin

Master of Philosophy in Economics Number of credits: 30

Department of Economics University of Oslo

May 2021

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Distributional effects of environmental taxation in Norway Calle Kumlin

hhtp://www.duo.uio.no/

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Acknowledgements

Firstly, I would like to thank my supervisor Odd Erik Nygård, who have been helpful, inspiring and enthusiastic from the beginning to the end. Without Odd Erik Nygård, this thesis wouldn’t have been possible.

I would also like to thank Stine Wang Fallang, for your invaluable support and encouragement throughout the process. Lastly, a mention to my daughter Hedda who possibly taken time from my work but at the same time giving back so much more, hopefully she will grow up in a world without a climate problem and therefore doesn’t need to be concerned about distributional effects of environmental taxation.

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Summary

Environmental taxation is a common approach for countries to reduce the emissions of greenhouse gases and shift from a fossil-based economy into a green sustainable economy. The aim of this thesis is to explore and analyse the distributional effects of environmental taxation in Norway and investigate if environmental taxation contributes to economic inequality.

The distributional effects of environmental taxation in Norway is examined with the simulation model LOTTE-Konsum, which is used by policymakers to estimate the distributional effects of changes in indirect taxation. LOTTE-Konsum calculates consumption expenditure for each household based on disposable income and demographics, and determines the budget shares for each household and creates households specific price indices. A dataset consisting of 2.576.693 households and 5.423.505 individuals is constructed, which represent the Norwegian population and the dataset is used to answer the research question. The distributional effects are found through changes in household specific price indices, which is identified by changes in commodity prices due to environmental taxation. The findings are analysed and presented through decile tables and inequality measurements.

The main result of the thesis suggest that environmental taxation overall is regressive in Norway with regressive effects on electricity, gasoline, diesel and oils, liquid fuel, mineral water, soft drinks and beer, and progressive effects on vehicle purchase costs, air passenger costs and wine. The effect on inequality is measured by changes in the Gini coefficient, with a before and after analysis of the coefficient. A distinction is done for environmental taxes closely related to economic theory (Pigouvian taxes) and environmental related taxes which is used in international reporting. The Gini coefficient is decreased with about 0,9% to 0,11% when excluding environmental taxes and about 0,26% to 0,39%

when excluding environmental related taxes. This implies that the introduction of environmental taxation has led to a higher Gini coefficient and increased inequality.

The results also suggest that the regressive impact can be mitigated and in fact made to a progressive impact if the revenues from the taxes are recycled back to the households in population in lump-sum transfers.

JEL classification : D3, H23, Q38, Q48.

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List of tables

Table 1. Studies on distributional effects of environmental taxes... 4 Table 2. Environmental tax bases based on the definition of environmental related taxes. ... 6 Table 3. Overview of environmental taxes according to two definitions. Environmental taxation and environmental related taxes. ... 8 Table 4. Group overview in LOTTE-Konsum and price simulation per commodity group. ... 14 Table 5. Estimated average consumption expenditure for different types of households in the

baseline simulation. ... 20 Table 6. Average reduction in tax burden/consumption expenditure in NOK per decile and

commodity group, presented separately for environmental taxation and environmental related taxation. Equivalence scale: Normalized EU-scale. ... 22 Table 7. Average reduction in tax burden/consumption expenditure in NOK per decile and

commodity group, presented separately for environmental taxation and environmental related taxation. Equivalence scale: Per Capita ... 23 Table 8. Average reduction in tax burden/consumption expenditure as a share of average total consumption expenditure, presented separately for environmental taxation and environmental related taxation. Equivalence scale: Normalized EU-scale.. ... 24 Table 9. Gini coefficient. Baseline coefficient and changes in the coefficient when the environmental tax’s share of the price excluded, based in the two definitions. Equivalence scale: Per capita and EU- scale. ... 25

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List of figures

Figure 1. Revenues of environmental related taxes in 2019, value added tax (VAT) and other indirect taxes. ... 7 Figure 2. Revenues from environmental taxes and environmental related taxes and their share of GDP for Norway in the time period 1995-2019. ... 9 Figure 3. Environmental tax revenue by category as % of TSC (Taxes and social contributions) and GDP in 2019. ... 10 Figure 4. Illustration of the Gini coefficient and the Lorenz curve. ... 18 Figure 5. Change in the Gini coefficient, with the environmental tax share of the price excluded.

Equivalence scale: Per capita and EU-scale. ... 26 Figure 6. Changes in the Gini coefficient per commodity group, with the environmental tax share of the price excluded. Equivalence scale: Per capita and EU-scale. ... 27 Figure 7. Change in the Gini coefficient due to environmental taxation and different lump-sum transfer policies. Equivalence scale: Per capita. ... 28 Figure 8. Direct and cross price elasticity for new vehicles, by vehicle energy technology in Norway 2016. ... 29

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1. Introduction

In line with empirical findings confirming the human impact on the climate change and the rise in temperature due to greenhouse gases, the attention to so-called environmental taxes has increased in OECD- and EU-countries since the 1980 (St.prp. nr. 54, 1998, p. 14) and (European Environment Agency, 2000). These taxes are well justified in line with economic theory and efficiency when regarding (negative) externalities¹. The flip side is the distributional effects. If there is an additional tax on a necessary good, there could be unfortunate distributional effects. The aim of this thesis is to explore and analyse the distributional effects of environmental taxes in Norway and investigate if environmental taxation contributes to economic inequality.

Environmental taxes are something that are widespread in most developed countries. There is a considerable amount of research on the distributional effects of these kinds of taxes. The most common belief, backed by empirical evidence, is that environmental taxes are regressive (Kosonen, 2012) and (European Environment Agency, 2011)². Due to the regressive impact, it is less attractive for policy makers to issue these kind of taxes (West & Williams III, 2004). In the paper “Distributional Implications of Environmental Taxation in Denmark” by Klinge Jacobsen, Birr‐Pedersen, and Wier (2003), the authors investigate the distributional effects of environmental taxes in Denmark. The results from the paper suggest that the majority of environmental taxes are regressive, especially taxes on water, retail containers and CO²emissions, and that taxes on gasoline and registration duties for cars are progressive. West and Williams III (2004) investigate the distributional effect of taxes on gasoline and finds that they are regressive. They suggest that the taxes could be made progressive through a lump-sum transfer. Similar results are found by Barker and Köhler (1998). The regressive effects of environmental taxation can be removed, if the revenues collected from the taxes are used either to redistribute amounts to lower income individual/household groups or used to reduce income taxes. Metcalf (1999) finds that environmental taxes can be designed to have a negligible impact on the income distribution, by using the revenues from the taxation to lower the income and the payroll taxation. According to Larsen and Aasness (2002), the poor and rich households have different ways to solve their transportation needs and therefore are contrasting distributional effects from environment taxes on transport. Through empirical examination the authors find that it is possible to achieve more equality and increase environmental quality with the use of taxes on transport. They use Engel elasticities to calculate the distributional effects of environmental taxes on transport in Norway and find that taxes on gasoline is regressive.

Increasing certain taxes while reducing others will have an impact on the income distribution in the society, under the assumption that the increase and reduction affect different groups (NOU, 2015:15, p. 163). In (NOU, 2015:15, p. 163), the commission’s recommendations on environmental taxation suggest that the cost for driving a car in larger cities will have a significant increase, while the cost in rural areas will not increase as much. Kosonen (2012) goes through empirical research on distributional effects and finds that the environmental taxes have different distributional effects depending on the setting. Taxes on heating and electricity is often found to be regressive, while taxes on transport

1 The motivation and efficiency regarding environmental taxation will be presented in section 2.

2 Meaning that the tax burden is higher for less wealthy households than wealthy households as a proportion of income. The tax is called progressive if the tax burden is higher for wealthy households.

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2 (gasoline and vehicles) can be both progressive or regressive, depending on the characteristics of the country studied.

The research concerning distributional effects of environmental taxation is both interesting, important, and relevant for policies regarding the transition to a sustainable economy. The ambition of this thesis is to complement and increase the knowledge of the distributional effects of environmental taxation in a Norwegian context.

The method for examining the distributional effects of environmental taxation is to use the simulation model LOTTE-Konsum. To examining the effects, the two following steps has been done. Firstly, the environmental taxes in Norway and commodity groups affected by environmental taxation are identified. Secondly, the tax’s share of the price is determined. The distributional effects are presented and investigated through decile tables and by the Gini coefficient. The main result is that environmental taxation is regressive in Norway with the highest burden of environmental taxation on households with low income. The effect on inequality is investigated by a before and after analysis when environmental taxation is excluded. The Gini coefficient is decreased with about 0,9% to 0,11%

when excluding environmental taxes and about 0,26% to 0,39% when excluding environmental related taxes. However, the regressive effect could be mitigated by use of revenues from the taxation. This is investigated through constructed lump-sum transfer policies to the households.

The thesis proceeds as follows. The first and second section provides an introduction to the research regarding distributional effects of environmental taxation, a brief background on the change from a fossil-based economy to a green sustainable economy, and an overview of the extent environmental taxes in Norway. Next, the third section will give information about the empirical strategy used in the thesis. The reader will get a description of the LOTTE-Konsum model and information about how the model will be used to investigate the distributional effects of environmental taxation. The fourth section will disclose the results on distributional effects, presented through, decile tables, and inequality measurements. Section 5 will provide a discussion regarding the validity of the results and in section 6 conclusions will be presented.

2. The transition to a green sustainable economy

2.1 Background

Global warming is something that affects all people in the world today. Either through changes in temperatures, rising sea levels or more frequently incidences of extreme weather, regardless if the problem is human made or not (World Bank, 2014). Global warming has the hardest impact on the poor and vulnerable. Poor countries with lower quality of institutions suffer more deaths from natural disasters than rich countries, and with the expectation that global warming will increase the number of natural disasters such as floods, the problem for poor countries will increase (Kahn, 2005). If the world continues in the same pattern of today, will we consume as if there were three planet earths in 2050 (European Commission, 2020).

Anderegg, Prall, Harold, and Schneider (2010) investigate the expert credibility in climate change and if there is consensus of anthropogenic climate change. They find that 97-98 % of climate researchers support the claim that human activities have an impact on the environment. According to the fifth

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3 assessment report (AR5) by IPCC³, greenhouse gas emission created by economic and population growth are extremely likely to have been the dominant cause of observed increase in temperature since the 1950s (IPCC, 2014, p. 4).

The climate change is researched from a variety of different scientific fields, for example economic research investigating the economic consequences of environmental taxes (as this thesis does) and meteorology research investigating different climate effects of global warming.

There could be said that there is consensus between most of the countries in the world to reduce emission from human activities. In the Paris agreement from 2015, the parties agreed to hold the average temperature increase below 2°C compared with pre-industrial levels, and aim to limit the temperature increase to 1,5°C. To achieve this, the Paris agreement specify a collective emission aim for the parties. Which means that the peak of emissions is reached as soon possible, and thereafter reduce emissions as fast as possible to achieve climate neutrality (United Nations, 2015a) According to the treaty collection of the United Nations there are 191 of 195 parties that have ratified the Paris Agreement (United Nations, 2015b). There have been climate agreements before the Paris Agreement.

The Kyoto protocol is maybe the most comprehensive and was adopted in 1997 and entered into force in 2005. The aim of the protocol was to reduce the anthropogenic emissions of greenhouse gases (IPCC, 2007, p. 83). The use of green taxes (also called environmental taxes) is a key instrument to succeed in reducing emission of greenhouse gases and to create a sustainable economy (Kosonen, 2012).

The fundamental idea and theoretical reasoning behind environmental taxes was first introduced by Arthur Cecil Pigou (Pigou, 1920) and (Kreiser, Lee, Ueta, Milne, & Ashiabor, 2014). Since then, the term Pigouvian taxes are generally been used when indirect taxation is applied to correct for negative externalities in the economy (Sandmo, 1975). The indirect tax is forcing the producer of the negative externality to pay the social cost for the activity (Sandmo, 2018). An example of a Pigouvian tax is tax on gasoline. When using gasoline (i.e. driving a fossil fuel vehicle) carbon dioxide is released into the environment. To correct for this negative externality and make the user accountable for the whole cost (both producing and social cost), a Pigouvian tax can be used. The term environmental taxes (or green taxes) are commonly used when referring to indirect taxes (excise taxes) that address negative externalities on the environment. The aim and purpose of environmental taxes is to encourage a change in consumption and production into a more sustainable economic direction (Kosonen, 2012).

In research regarding environmental taxation, the term double dividend hypothesis frequently occurs.

The term suggests that are two benefits from environmental taxation; improving the quality of the environment and at the same time improve the economic efficiency (Goulder, 1995). The Norwegian government through the ministry of Finance confirms this point of view. They write that it is possible to abate distortionary taxes with the revenues collected from environmental taxes (Prop. 1 LS, 2020- 2021, p. 62). Bye and Fæhn (2009) investigate the effects of green tax reforms in Norway, and the possibility of a double dividend. They find that it is possible to achieve a double dividend. I.e. both reducing emissions and increasing economic welfare, when issuing green tax reforms. This is possible if the revenue from a CO2 tax is used to reduce a distorted tax, like the payroll tax.

3 The intergovernmental panel on climate Change (IPCC) is the United Nations body for assessing the science related to climate change.

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4 Büchs, Bardsley, and Duwe (2011) does an assessment of empirical studies that investigate distributional effects caused by environmental taxation. They argue that it is likely that a large number of the environmental taxes have an regressive effect but that the effect could be mitigated through several policy actions. Büchs et al. (2011) lists four different scenarios/policy actions. 1) It is highly likely that environmental taxation is regressive if the revenues are not earmarked for direct redistribution to the citizens. 2) It is possible to increase public acceptance for environmental taxes if the revenues are earmarked for improving the quality of the environment. 3) Redistributing the revenues from environmental taxation to the population can reduce the regressive effect. This can be done by reducing other distortionary taxes. 4) Redistributing the revenues from environmental taxation to the population as a lump-sum can also reduce the regressive effect.

An overview of some selected studies on distributional effects of environmental taxes can be seen in table 1. It is worth noting the findings of Brenner, Riddle, and Boyce (2007) in China and Yusuf and Resosudarmo (2015) in Indonesia. Their results show that environmental taxes have a progressive effect, and that is in contrast to the common belief of regressivity. Yusuf and Resosudarmo (2015) and Brenner et al. (2007) explains the contrasting result by the fact that Indonesia and China differ from other countries⁴ where regressivity of environmental taxes has been found.

Table 1. Studies on distributional effects of environmental taxes.

Country Tax Distributional Effect Comments

Denmark (Wier, Jacobsen, Klinge, & Klok, 2005)

CO2 tax, energy. Regressive Examining direct and

indirect effects.

Denmark (Klinge Jacobsen et al., 2003)

Several taxes investigated. Progressive: Gasoline and registration duties for cars.

Regressive: Water, retail containers and CO2 emissions.

Most of the taxes

investigated were found to be regressive.

USA (West & Williams III, 2004)

Gasoline Regressive The effect can be made

progressive with the use of revenues, through lump- sum transfers.

Norway (Larsen & Aasness, 2002)

Transport Progressive, air flights, taxis and cars. Regressive:

Gasoline.

Lower tax rate on buses, bicycles and mopeds reduce inequality.

Ireland (Callan, Lyons, Scott, Tol, & Verde, 2009)

Carbon tax Regressive The effect can be made

progressive with revenue recycling.

Indonesia (Yusuf &

Resosudarmo, 2015)

Carbon tax Progressive The effect can be increased

with the use of lump-sum transfers

China (Brenner et al., 2007) Carbon tax Progressive The effect can be increased with the use of lump-sum transfers.

USA (Metcalf, 1999) Several taxes investigated. Regressive Negligible impact if revenues are used to lower the income and payroll taxation.

Germany (European Environment Agency, 2011)

Several taxes investigated. Regressive Overall benefit for the economy, environment and society.

4 In both papers they define it as industrialised countries.

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Sweden (Ahola, Carlsson, &

Sterner, 2009)

Gasoline Regressive Can be made progressive

with the use of revenues, through a reduction of VAT on food.

2.2 Norway’s climate policy

Norwegian Ministry of Climate and Environment (2018)’s report “Norway’s Seventh National Communication” describes Norway’s climate policy. The climate policy is based on the objectives of the United Nations Framework Convention on Climate Change (UNFCCC), the Kyoto protocol and the Paris agreement. The reports produced by the IPCC is used for scientific understanding regarding the effects of global warming for deciding and developing climate policy. The climate change and emissions of greenhouse gases has been on Norwegian policy agenda since the late 1980’s and Norway’s have a broad set of measures for almost all emission and removals.

The Norwegian government is using a variety of different methods and tools to reduce the climate impact. One of these tools is to apply so called environmental taxes (Norwegian Ministry of Climate and Environment, 2018). In the literature of behavioural economics, it is suggested that earmarking the revenues from environmental taxation could improve the acceptance of environmental taxation (Kallbekken & Sælen, 2011) and (Büchs et al., 2011). The Norwegian policy is not to use earmarking of revenues from environmental taxation, because it has been found to be inefficient to tie up public funds to specific expenditures (NOU, 2015:15, p. 52). OECD (2006) confirms the view that earmarking of environmental tax revenues can create economic inefficiency. The increased revenues from environmental taxation of emissions are used for general reductions in distortionary direct and indirect taxes (NOU, 2015:15, p. 52)

2.3 The extent of environmental taxation in Norway

To be able to give the reader an overview of the extent of environmental taxation in Norway, it’s a necessity to explain what’s included in the term. Braathu (2017) explains that there are two different definitions of environmental taxes. The first is closely related to economic theory and is a type of Pigou tax (explained above), the second one is wider and include environmental related taxes and is used in international reporting of environmental taxes by EU, OECD and UN. The latter definition is ratified in the EU regulation 691/2011 and Eurostat⁵ uses the following definition of environment related taxes

“A tax whose tax base is a physical unit (or a proxy of a physical unit) of something that has a proven, specific negative impact on the environment, and which is identified in ESA⁶ as a tax” (Eurostat, 2013).

Eurostat (2013) gives an overview on what taxes that should be included as environmental related taxes and can be seen in table 2.

5 Eurostat is the statistical office of the European Union

6 European Free Trade Association Surveillance Authority (ESA)

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6 Table 2. Environmental tax bases based on the definition of environmental related taxes.

Energy (including fuel for transport) Energy products for transport purposes Unleaded gasoline, Leaded gasoline and Diesel

Other energy products for transport purposes (e.g. LPG, natural gas, kerosene or fuel oil) Energy products for stationary purposes

Light fuel oil, Heavy fuel oil Natural gas

Coal, Coke Biofuels

Electricity consumption and production District heat consumption and production Other energy products for stationary use Greenhouse gases

Carbon content of fuels

Emissions of greenhouse gases (including proceeds from emission permits recorded as taxes in the national accounts)

Transport (excluding fuel for transport) Motor vehicles import or sale (one off taxes)

Registration or use of motor vehicles, recurrent (e.g. yearly taxes) Road use (e.g. motorway taxes)

Congestion charges and city tolls (if taxes in national accounts) Other means of transport (ships, airplanes, railways, etc.) Flights and flight tickets

Vehicle insurance (excludes general insurance taxes) Pollution

Measured or estimated emissions to air Measured or estimated NOx and SOx emissions

Other measured or estimated emissions to air (excluding CO2) Ozone depleting substances (e.g. CFCs or halons)

Measured or estimated effluents to water

Measured or estimated effluents of oxydisable matter (BOD, COD) Other measured or estimated effluents to water

Effluent collection and treatment, fixed annual taxes Non-point sources of water pollution

Pesticides (based on e.g. chemical content, price or volume)

Artificial fertilisers (based on e.g. phosphorus or nitrogen content or price) Manure

Waste management

Collection, treatment or disposal

Individual products (e.g. packaging, beverage containers, batteries, tyres, lubricants) Noise (e.g. aircraft take-off and landings)

Resources Water abstraction

Harvesting of biological resources (e.g. timber, hunted and fished species) Extraction of raw materials (e.g. minerals,

Source: (Eurostat, 2013).

From now on, the term environmental taxation will denote all types of environmental taxes. However, the term environmental taxes will refer to the Pigouvian type, i.e. the narrow definition, while the term environmental related taxes refer to the wide definition. Statistics Norway collects and presents data on tax revenue for each tax, based on the two different definitions. Revenue collected with regards to environmental taxes and environmental related taxes for 2019 can be seen in the appendix, see

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7 appendix table 1 and appendix table 2. The data in appendix table 2 is used in international reporting to Eurostat, the United Nations and OECD. Figure 1 illustrate a comparison of tax revenue collected from environmental taxation, value added taxes (VAT) and other indirect taxes in 2019, tax revenue presented in million NOK. It can be seen in figure 1 that environmental related taxes share of indirect taxes are 17%, while the share of VAT and other indirect taxes are 69% and 14% respectively. Other indirect taxes include a variety of indirect taxes with tax on alcohol (14 518 Million NOK), stamp duty on real estate transfers (10 310 Million NOK) and tax on tobacco goods (6 313 Million NOK) as the largest contributors of tax revenues.

Figure 1. Revenues of environmental related taxes in 2019, value added tax (VAT) and other indirect taxes. Unit: Million NOK.

Source: (Statistics Norway, 2021a) and (Eurostat, 2021).

Bruvoll (2009) looks at the measurement of environmental taxes. She discuss the differences between environmental taxes that are linked to economic theory and environmental related taxes that are used in international reporting, and the problems with differentiating environmental taxes from fiscal taxes.

Bruvoll (2009) writes that several of the environmental related taxes that are included in international reporting are in fact fiscal and not environmental motivated, and therefore gives misleading results and a false interpretation of the extent of environmental taxes. In the report “En vurdering av særavgiftene”⁷ the authors assesses the excise taxation⁸ in Norway and discuss the motivations for these kinds of taxes (NOU, 2007:8). They find that some taxes that are defined as environmental related taxes in international reporting, mainly are fiscal motivated, examples of this are the “Motor vehicle registration tax” and the “Annual weight based tax on motor vehicles”.

Table 3 presents the environmental taxes (narrow definition) and environmental related taxes (wider definition) that exists in Norway in 2019. It is distinctly clear from table 3 that the two definitions differ, with multiple more tax bases included in the definition of environmental related taxes.

7 An assessment of excise taxes.

8 Environmental taxes are included in term excise taxes.

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8 Table 3. Overview of environmental taxes according to two definitions. Environmental taxation and environmental related taxes.

Type of tax Environmental Environmental related

¬ Tax on coal X

¬ Gasoline tax X X

¬ Diesel tax X X

¬ Road tax on natural gas and LPG X X

¬ Tax on electricity X

¬ Tax on mineral oils X X

¬ Tax on C02 emissions X X

¬ Tax on electricity paid to the Norwegian Energy Fund X

¬ Tax on CO2 emissions in the petroleum sector X X

¬ Natural resource tax X

¬ Imputed tax on emission permits X X

¬ Tax on greenhouse gases HFC and PFC X X

¬ Tax on lubricating oils X X

¬ Marine engine tax X

¬ Tax on pesticides X X

¬ Sulphur tax X X

¬ Environmental tax on disposable beverage packaging –

plastic X X

¬ Environmental tax on beverage packaging – carton X X

¬ Environmental tax on beverage packaging – metal X X

¬ Environmental tax on beverage packaging – glas X X

¬ Tax on NOx emissions, petroleum sector excepted X X

¬ Tax on the final treatment of waste X X

¬ Tax on NOX emissions in the petroleum sector X X

¬ Tax on tricloreten X X

¬ Tax on tetracloreten X X

¬ Tax, fishing fleet X

¬ Tax on control and inspection of aquaculture (fish

farming etc) X

¬ Fishing license X

¬ Research tax fisheries X

¬ Hunting license X

¬ Tax on air traffic passengers X

¬ Anti traffic accident premium paid by enterprises X

¬ Anti traffic accident premium paid by households X

¬ Motor vehicle registration tax X* X

¬ Re-registration tax on motor vehicles X

¬ Tonnage tax (payable by shipping companies) X

¬ Annual weight based tax on motor vehicles X

¬ Annual motor vehicle tax paid by enterprises X

¬ Annual tax, fishing boat register X

¬ Annual tax on motor vehicles paid by households X

¬ Taxes transferred to Svalbard Environmental Fund X

* Imputed NOx and CO2 component

Source: (Statistics Norway, 2021a, 2021b).

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9 2.3.1 Revenues of environmental taxation as a measure

Figure 2 can give the reader an understanding of the extent of environmental taxation in Norway in the period 1995 to 2019. The figure presents the total revenue collected from environmental taxation based on the two definitions of taxation and their share of GDP. The figure reveals a general trend of increasing revenues from environmental taxation and a general decreasing trend for revenues as share of GDP. Revenues as share GDP based on the narrow definition have remained relatively steady in the period 2012 to 2019 but have decreased overall during the period.

The average degree of revenues as share of GDP based on environmental related taxes for OECD countries have been relatively steady in the period 1995 to 2017 (OECD, 2019). Eurostat (2020a) finds an average decrease (from 2,5% to 2,4%) of the revenues based on environmental related taxes relative to GDP in the period 2002 to 2018.

Figure 2. Revenues from environmental taxes and environmental related taxes and their share of GDP for Norway in the time period 1995-2019. Unit: Million NOK.

Source: (Statistics Norway, 2021a, 2021b, 2021c) and author’s calculations.

Eurostat collects and presents environmental related tax revenues for EU-members and some additional European countries that aren’t members of the EU. Figure 3 display environmental related tax revenue per country and category as percentage of TSC (Taxes and social contributions) and GDP in 2019. One takeaway from the figure is that energy taxation clearly dominates the share of TSC, and that taxation of transport is the second largest category for most of the countries.

Environmental taxation as share of TSC and GDP can be used as an indicator of trends and for comparison between countries (Eurostat, 2013) and (OECD, 2019). It can be seen in figure 2 that Norway has a relatively low share of environmental related taxation relative to TSC and GDP in comparison to other European countries in 2019. Howbeit, environmental taxes as share of TSC and GDP can be a challenging measure to draw conclusion from (OECD, 2019). A high share of the two measures doesn’t automatically mean that a country has a high interest of improving the quality of environment and the change to a more sustainable economy (Eurostat, 2013). Below are some examples of how the measures could be understood.

0,00%

0,50%

1,00%

1,50%

2,00%

2,50%

3,00%

3,50%

4,00%

0 10 000 20 000 30 000 40 000 50 000 60 000 70 000 80 000 90 000

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Environmental taxes Environmental related taxes

Environmental taxes part of GDP Environmental related taxes part of GDP

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• An increase of the share of TSC or GDP can imply that a country is increasing the tax rates and issuing new taxes to improve the quality of environment, but it is also possible that the increase is due to a higher emissions or as a rise in consumption of products with a negative environmental impact (Eurostat, 2013).

• A country has an interest for improving the quality of the environment. However, the country has already come a long way towards a more sustainable economy and consequently has low emissions of greenhouse gases. The revenues share of TSC and GDP are therefore low (OECD, 2019).

• A country has an interest for improving the quality of the environment. However, the country is using other measures and tools to improve the quality of the environment and the change to a more sustainable economy. E.g. environmentally friendly technologies such as solar and wind power can reduce the revenues from environmental related taxes, and consequently reduce the measure (OECD, 2019).

• The country’s level of TSC and GDP will affect the measure. The share of TSC and GDP will be smaller, if the country is a welfare state and has a generally high tax level and the country is productive and has a high GDP. This comes from how the measure is constructed. If the denominator is large relative to the numerator, the measure will be small.

𝑅𝑒𝑣𝑒𝑛𝑢𝑒𝑠 𝑓𝑟𝑜𝑚 𝑒𝑛𝑣𝑖𝑟𝑜𝑛𝑚𝑒𝑛𝑡𝑎𝑙 𝑟𝑒𝑙𝑎𝑡𝑒𝑑 𝑡𝑎𝑥𝑒𝑠

𝑇𝑆𝐶 and 𝑅𝑒𝑣𝑒𝑛𝑢𝑒𝑠 𝑓𝑟𝑜𝑚 𝑒𝑛𝑣𝑖𝑟𝑜𝑛𝑚𝑒𝑛𝑡𝑎𝑙 𝑟𝑒𝑙𝑎𝑡𝑒𝑑 𝑡𝑎𝑥𝑒𝑠 𝐺𝐷𝑃

Figure 3. Environmental tax revenue by category as % of TSC (Taxes and social contributions) and GDP in 2019.

Source: (Eurostat, 2020b).

An additional challenge is how to measure the “performance” and efficiency of an environmental tax.

One way of evaluating environmental taxes is to investigate the decrease in emissions of greenhouse gases, but it’s difficult to know how much a certain tax contributed to the decrease and not all environmental taxes has an aim to reduce emissions of greenhouse gases directly⁹ (Kreiser et al., 2014).

9 E.g. fees and taxes on plastic bags, beverage containers, water pollution etc.

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3. Data and methodology

The simulation model LOTTE-Konsum is developed by the Research Department at Statistics Norway, and is used for examining the distributional effects of indirect taxation. The model is therefore well suited for answering the research question raised in this thesis

The basic concept and theoretical background of LOTTE-Konsum will be presented in section 3.1. In section 3.2, the empirical strategy will be presented.

3.1 LOTTE-Konsum

This part is mainly based on the paper «LOTTE-Konsum- en mikrosimuleringsmodell for fordelingsvirkninger av indirekte skatter¹⁰» (Nygård & Aasness, 2013).

LOTTE-Konsum is part of the LOTTE model system, that consists of the models LOTTE-Konsum, LOTTE- Skatt and LOTTE-Arbeid. LOTTE-Skatt is a tax-benefit model consisting of all households in Norway and is used to analyse the tax revenue consequences and distributional effects of changes in the personal income tax and the wealth tax (direct taxes). The LOTTE-Konsum consists of the same households and uses input on disposable income from LOTTE-Skatt.

Firstly, the LOTTE-Konsum model calculates consumption for each household, based on disposable income and demographics (number of adults and children). Secondly, the model determine consumption for each commodity group in the model and calculates budget shares for each household in a reference year. This imputation process relies on both macro data (from the national account) and microeconomic studies based on the Households Expenditure Survey. The change¹¹ in tax burden/consumption expenditure for households and individuals due to indirect taxation ¹² can be estimated based on consumption data from LOTTE-konsum.

Household specific price indices are used to evaluate the effects of changes in tax burden/consumption expenditure for households. More precisely, the Laspeyres price index is used to construct household specific price indices. Laspeyres index can be written as ^{∑ 𝑝}¹^∗𝑞⁰

∑ 𝑝₀∗𝑞_𝑜

,

where p stands for prices and q stands for quantity. The Laspeyres index is measuring relative change in consumption expenditure based on the reference situation (the baseline situation 𝑝₀) and behavioural changes are therefore not considered. The index is still a good approximation for small changes in price.

The Laspeyres price index can be used as an approximation to the true change in cost of living. A price increase on a certain commodity, will have different impacts depending on the budget shares of the commodity for a given household. Wealthy households will generally have a smaller budget share on food than less wealthy households and will therefore be less affected of a tax increase on food. The budget share of certain goods can also vary with the household’s composition, e.g. households with children can have different preferences than households without children.

10 Translated to English “LOTTE-Konsum, a microsimulation model for distributional effects of indirect taxes”

11 Behavioural changes are not taken into account.

12 An environmental tax is an indirect tax.

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12 A dataset consisting of 2.576.693 households and 5.423.505 individuals is constructed by LOTTE- Konsum¹³ with household specific information about income, consumption expenditure, household size and budget shares for each commodity group. The dataset is used for examining the distributional effects of environmental taxation.

An alternative method to examine the distributional effects is to use observed consumption for each household based on expenditure surveys. However, the annual samples of expenditure surveys are small, which means a lot of uncertainty, and expenditure surveys is characterized by measurement noise in the data (NOU, 2007:8, p. 183). Underlying consumer patterns is found through econometrics studies to be extremely stable over time, or only change slowly and this knowledge is implemented in the LOTTE-Konsum model (Nygård & Aasness, 2013).

Equivalence scales

The use of equivalence scales is an common approach to adjust for different compositions and sizes of the households and take economics of scale into account (Atkinson, 1995). The consumption needs for a household doesn’t increase proportionally with an additional member, if two adults are in one household, the need for electricity or housing space isn’t doubled. OECD-scale, EU-scale and Square root scale are three commonly used equivalence scales. Per capita¹⁵ and a normalized EU-scale will be used in the examination of the distributional effect of environmental taxation. The two equivalence scales (per capita is a type of equivalence scale) are chosen due to authenticity. Statistics Norway used the same two scales in the state budget for 2021 when examining the effects of changes in indirect taxation.

EU-scale

The first adult in the household is given a value of 1 and the next has a value of 0,5, while children get a value of 0,3 each. E.g. a household of two adults and three children needs 2,4 times higher income than a household with only one adult to achieve the same economic standard of living. Nygård (2019) explains that a normalized equivalence scale can be used to adjust the discrepancy between average actual change in taxes and the average change when using equivalence scales. The sum of average change is significantly larger than the actual, when using equivalence scale and there exists significant economies of scale for households (Nygård & Aasness, 2013). An illustrative example of the use and calculation can be found the appendix.

3.2 Empirical strategy

The strategy for examining the distributional effects is firstly to identify commodity groups affected by environmental taxation in the LOTTE-Konsum model. A detailed explanation of how the identification is done will be presented in the next section 3.2.1. Secondly, to determine the tax’s share of the price, which will be used for the model simulation. I simulate changes in tax burden/consumption

13 The dataset represents the Norwegian population.

15 Per capita = Per person. Thus, no adjustment for different compositions or sizes of households.

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13 expenditure for households/individuals in a scenario where the environmental tax’s share of the price of certain commodities is removed, i.e. a constructed situation where environmental taxes do not exist. Two different simulations will be executed, one with environmental taxes (the narrow definition), and one with environmental related taxes (the wider definition).

The distributional effect of the price changes (due to environmental taxation) will be examined and presented through decile tables, and by inequality measurements for both definitions of environmental taxation. The deciles tables will be ranked by gross income per household member and give information about the average change in tax burden/consumption expenditure per commodity group. The average change per decile is displayed in NOK and as a share of total consumption expenditure, where the latter is used to investigate regressivity and progressivity. The assumption is that consumers bear the full burden of the taxation, and therefore bear the full burden of the change in price. The Gini coefficient will be used to measure and compare the effect of environmental taxation on inequality. A description of the Gini coefficient is presented in section 3.2.2, and an explanation of how the coefficient is implemented to answer the research question is presented in section 3.2.3.

3.2.1 Identification of environmental taxes in the model and tax’s share of the price The LOTTE-Konsum model consists of 30 commodity groups that are affected of indirect taxation in Norway (Nygård & Aasness, 2013). The 30 groups can be seen in table 4. Obviously, not all commodities are levied environmental taxation (not directly at least) and a selection must be done. The commodity groups with bold text in table 4 will be used in the simulation and the change in price per commodity group and is also presented.

The main source for identification of the tax’s share of the price¹⁶ is the document «Grunnlag for Finansdepartementets beregninger av skatter og avgifter i statsbudsjettet for 2018»¹⁷, the document contains information about the calculations done be the Ministry of Finances of taxes and fees in the state budget for 2018 (Finansdepartementet, 2017). Finansdepartementet (2017) have calculated the excise tax part of the price on different commodities. The Ministry of Finances information and my own calculations will be used in the simulation for price changes.

The price of each commodity group is equal to 1 in the baseline situation and most taxes examined are subject to VAT¹⁸. New price per commodity group is calculated be the following formula:

New price = 1 – (Environmental tax’s share of the price∙(1+VAT rate))

To examine the distributional effects of environmental taxation the following is done:

The new prices per commodity group are entered into datasets constructed by LOTTE-Konsum to create new price indices per household. Table 4 display new prices per commodity group when environmental taxation is removed, which is used to determine new price indexes per household. In the reference situation the price index for each household is equal to 1 and lower than 1 when removing the environmental tax from the price.

16The pre-tax price is assumed to be constant for simplicity.

17 It is the latest version released from the Ministry of Finance.

18 The motor vehicle registration tax and the re-registration tax are not subject to VAT.

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14 Table 4. Group overview in LOTTE-Konsum and price simulation per commodity group. Price

scenario 1 display simulation prices for environmental taxation and price scenario 2 display simulation prices for environmental related taxation.

Code Description Price scenario 1 Price scenario 2

001 Food items, sugar exempted 1,000 1,000

002 Sugar items, chocolate, etc. 1,000 1,000

03A Coffee, tea, cocoa 1,000 1,000

03B Mineral water, soft drinks 0,951 0,951

03C Liquor 0,996 0,996

03D Wine 0,989 0,989

03E Beer 0,963 0,963

4 Tobacco 1,000 1,000

12 Electricity 1,000 0,738

13A Liquid fuel 0,783 0,783

13B Solid fuel 1,000 1,000

14A Other operating expenses, car, etc. 1,000 1,000

14B Gasoline, diesel and oils 0,509 0,509

21 Clothing and shoes 1,000 1,000

22 Other commodities 1,000 1,000

25 Leisure equipment 1,000 1,000

30 Vehicle purchase costs 0,920 0,827

41 Furniture, etc. 1,000 1,000

42 Electric household items 1,000 1,000

50 Housing 1,000 1,000

60 Other services 1,000 1,000

61 Insurance services 1,000 1,000

62 Health care services 1,000 1,000

63 Health care items 1,000 1,000

66 Norwegians consumption abroad 1,000 1,000

75 Road transport 1,000 1,000

76 Air passenger costs ^1,000 ^0,944

77 Railway, tram, etc. 1,000 1,000

78 Boat and ferry 1,000 1,000

79 Postal and telecommunications serv. 1,000 1,000

Source: Statistics Norway, LOTTE-Konsum and author’s calculation of the price change.

A brief description of identified environmental taxes and price change per commodity group will now follow.

Group 03B, 03C, 03D and 03E. Environmental tax on beverage packaging

Commodities in these groups are levied an environmental tax on beverage packaging. The basic excise tax is in 2021 NOK 1,27 per beverage. There is also additional tax on packaging when using plastic, cardboard, glass and metal, the additional tax amount can be dropped if the return rate reach a certain level of recycling (Prop. 1 LS, 2020-2021, p. 318). Finansdepartementet (2017) calculate that the environmental tax on beverage packaging to be 3% of the price. It is assumed that Ministry has used an average price over the different beverages, which makes the share high for some beverages and

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15 low for others, the tax share on the price on soft drinks should be higher than tax share on the price on liquor for example. Due to this, it is estimated that the tax share on the price separately on every group. The following price reduction will be simulated in the model; 03B (Mineral water, soft drinks):

4,9%, 03C (Liquor): 0,4%, 03D (Wine): 1,1% and 03E (Beer): 3,7%.

Group 12. Electricity

Electricity consumption in Norway is levied an excise tax. The standard tax rate in 2021 is 0,17 NOK per kWh and the reduced rate is 0,05 NOK per kWh for industries, the purpose of the tax is both to generate revenue and to reduce the use of electricity (Prop. 1 LS, 2020-2021, p. 216-217). In the simulation the price will be reduced by 26%, the reduction is based on the calculations of the ministry of Finance from 2017 (Finansdepartementet, 2017). The tax on electricity is not identified as an environmental tax, but as an environmental related tax, which is used in international reporting. Bruvoll (2009) discuss the tax in a Norwegian setting and suggests that the tax doesn’t correct any negative externalities and therefore should not be defined as an environmental related tax.

Group 13A. Liquid fuel

This category is levied environmental taxation to correct negative externalities and contains Liquefied petroleum gas (LPG), paraffin, lubricating oils, medium oil (including heating gas oil), heavy oil (including marine diesel oil and bunker oil). A simulation of a price change in this category is somewhat more complicated than for example in situation with the beverage packaging tax, where there is a specific consumption good with a price to alter. For simplicity, the approach is to use the calculations from Ministry of Finance from 2017 for the change in price without the environmental taxation.

According to Finansdepartementet (2017), the tax on CO2 emission and tax on mineral oils share of the price is 20%, and 12% for the tax on CO2 emission on Natural Gas and LPG.

Group 14B. Gasoline, diesel and oils

This category contains gasoline and diesel. They are both levied two different excise taxes to price the external cost of driving, the emission of greenhouse gases is priced with the CO2 tax and the road traffic tax is used for pricing the external cost of driving, through for example accidents or reduction in air quality (NOU, 2015:15, p. 69). The numbers from the Ministry of Finance from 2017 will be used when simulating the price change in LOTTE-Konsum. Finansdepartementet (2017) calculate that the tax on CO2 emission and road traffic tax share of the price is, 38% for diesel and 42% for gasoline.

Group 30. Vehicle purchase costs

This category contains costs regarding motor vehicles in Norway, and includes vehicle purchases, lubricate oil and re-registration tax on motor vehicles. The motor vehicle registration tax is levied on the purchase of a vehicle in Norway, electric cars are exempted and hybrid cars are partly exempted from the tax (Norwegian Ministry of Climate and Environment, 2018). The purpose of the tax is to generate revenue and to stimulate environmentally friendly vehicles. Lubricate oil is levied a tax on CO2 emission and a tax on mineral oils and the excise taxes share of the price is 20%

(Finansdepartementet, 2017). As illustrated in table 2 the re-registration tax on motor vehicles is not included in environmental taxation (the narrow definition) and the tax has not been found to have significance environmental importance (NOU, 2015:15, p. 69). The reason to examine this tax is because it is included in the definition used in international reporting of environmental related taxation. The simulation on this group will differ, based on the two different definitions of

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16 environmental taxation. Finansdepartementet (2017) calculate that the motor vehicle registration tax share of the price is 25% and the re-registration tax equals 4% of the price. The simulation based on the definition environmental related taxes will be executed through a price change with regards to the motor vehicle registration tax, the lubricate oil tax and the re-registration tax. The simulation based on the environmental taxation (the narrow definition) is different from the wider definition due to a modification of the motor vehicle registration tax and entirely exclude the re-registration tax on motor vehicles. The reduction in price of motor vehicles is 12% instead of 25% when regarding the motor registration tax and is calculated by only using the CO2 and NOx share of the tax.

Group 76. Air passenger costs

Flight tickets is levied an excise tax in Norway. The tax has two different rates, 76,5 NOK for destinations within Europe and 204 NOK for other destinations in 2020. The purpose of the tax is to generate revenue, but it can also have an environmental effect by reducing the demand for flights (Prop. 1 LS, 2020-2021, p. 234). The price of flight tickets will be reduced with 6% in the simulation, the reduction is based on the calculations of the ministry of Finance from 2017 (Finansdepartementet, 2017). The tax is not defined as an environmental tax, but as an environmental related tax.

The Norwegian electric car policy

The Norwegian government exercise an ambitious policy to reduce emissions in the transport sector, with especially strong incentives for electric cars and must therefore be mentioned when regarding distributional effects of environmental taxation. Electric cars are exempted from the motor vehicle registration tax, VAT, road usage tax and have a reduced road traffic insurance tax²⁰ (Meld. St. 1, 2020- 2021, p. 117 and p.128). There is also incentives for hybrid electric cars, in the form of reduced motor vehicle registration tax and exemption from the road usage tax (Norwegian Ministry of Climate and Environment, 2018, p. 108). Fjørtoft and Pilskog (2020) examines the statistics on sales of new electric cars in 2019 and finds an overweight of buyers with high income. They sort households in 10 deciles by income from the lowest to the highest, and finds that the 10^th decile (the top 10% of the households) purchased 37% of the new electric cars and that decile 1-5 (the bottom half of the households) purchased 10%. Fjørtoft and Pilskog (2020) compares the benefits for electric car buyers (11 billion NOK exempted in value added tax and motor vehicle registration tax) with child benefit and cash-for- care benefit (together 18 billion NOK), and conclude that the Norwegian electric car policy had important distributional effects in 2019.

It is likely that the price of commodity group 30 (vehicle purchase costs) is affected by the Norwegian policy of incentivizing the use of electric cars. Unfortunately, it is challenging to both incorporate changes in simulation prices due to environmental taxation (lower price) and subsides (higher price) and get a meaningful result. This is partly because of the setup in LOTTE-Konsum. The problem is that the costs of buying a fossil fuel car and electric car are included in the same commodity group and LOTTE-Konsum only operates on simulation of price changes per commodity group, not within a group.

A possible approach for enabling the electric and hybrid car’s benefits in the model simulation is to

20 Electric cars have been exempted from the road traffic insurance tax but from 2021 electric cars are levied road traffic insurance tax on the same level as a motorcycle.

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17 decide their share²¹ of the car fleet. By using the information, it is possible to estimate the price effect of the benefits and the environmental taxes for the whole commodity group. A weakness of the approach is the increased complexity of estimating the price change and therefore a possible decrease of the precision, when regarding several different benefits and taxes on the three types of vehicles. As this thesis examining the distributional effects of environmental taxation, the subsidies of electric and hybrid cars or other similar environmentally friendly subsides are not taken into consideration.

Group 75. Road transport

It is likely that costs regarding road transport is affected of environmental taxation. For example, in the form of a higher price of taxi and buss services due to environmental taxes on road use or gasoline.

However, it is challenging to find evidence of environmental taxes levied directly on the costs in the commodity group and therefore difficult to estimate the price effect. The price of group 75 is for that reason not altered and consequently not used for investigating the distributional effects of environmental taxation.

3.2.2 The Gini coefficient and the Lorenz curve

The Gini coefficient is a widely used measure to display the extent of inequality. The coefficient measures inequality based on income (or some other chosen variable) distribution, where a Gini value of 0 represents absolute equality and a Gini coefficient of value 1 represents absolute inequality (Sen

& Foster, 1997). The Gini coefficient is based on the Lorenz curve, which is illustrated in figure 4 below.

On the horizontal axis the population is arranged in deciles based on income (or some other distribution), from the lowest to the highest, and the vertical axis presents the cumulative percentage of income. The straight diagonal line represents absolute equality and the Lorenz curve (the line below the straight line) represents the income distribution in a population. The Gini coefficient is the area (the grey area) between the Lorenz curve and the straight diagonal line, if the Lorenz curve is a straight diagonal line, then there is absolute equality in the population and the Gini coefficient is equal to 0.

The Gini coefficient is defined as one-half of the relative mean difference, which is defined as the arithmetic average of the absolute values of differences between all pairs of income (Sen & Foster, 1997).

21 I.e. deciding the share of fossil cars, electric cars and hybrid cars in the car fleet

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18 Figure 4. Illustration of the Gini coefficient and the Lorenz curve.

Source: Illustration made by the author.

3.2.3 Implementation of the Gini coefficient

To examine environmental taxation’s impact on inequality, the approach is to do a before and after examination of the Gini coefficient. This is done by calculating the Gini coefficient without environmental taxation and compare it with the Gini coefficient calculated with the taxes are included.

The output variables: Consumption expenditure, price index, household size and budget share per commodity group from the simulation in the LOTTE-Konsum model is used to calculate the Gini coefficient. The Gini coefficient is calculated on the distribution of consumption expenditure, with per capita and EU-scale as equivalence scales. To use income or consumption expenditure when examining differences in living standard and inequality, is an investigated theme. Cutler and Katz (1992) and Slesnick (1993) make arguments suggesting that consumption expenditure to be more accurate than income in a theoretical perspective. Brewer and O'Dea (2012) and Meyer and Sullivan (2003) measure living standards and inequality with both income and consumption expenditure, and finds evidence suggesting that households with low income under-report their income. Consumption generally experience smaller fluctuations than income, and there is reason to believe that consumption is as good indicator of living standards and inequality as income (Benedictow, Hussein, & Aasness, 2000).

Meyer and Sullivan (2003) favours the use of consumption due to the closer link between living standard and consumption when investigating the effects of benefits and transfer programmes.

The Gini coefficient will be approached in three different ways. Firstly, and the main focus is to measure the change in the coefficient when all environmental taxes are excluded in the price.

The change is found by taking the difference between Gini based on ^𝑇^𝑖

𝑆𝑃𝐼 _𝑖 and Gini based on ^𝑇^𝑖

𝑅𝑃𝐼 _𝑖 . Where T is consumption expenditure, SPI is the simulation price index for each household, RPI is the price index for the reference situation for each household and i is consumption units in the population²². In the reference situation the price index (𝑅𝑃𝐼 _𝑖) will be equal to 1 and the simulation

22 Per capita scale: One consumption unit equals one individual. EU-scale: The consumption units are adjusted according to the scale.

Distributional effects of environmental taxation in Norway