Student Working
Paper Series

Axe the Tax? An Analysis of the
Effectiveness of BC’s Carbon Tax in
Reducing GHG Emissions

Ashley McDougall

WP 2024 - 01
August 2024
University of the Fraser Valley
Department of Economics
Abbotsford, British Columbia, Canada

Axe the Tax? An Analysis of the Effectiveness of BC’s
Carbon Tax in Reducing GHG Emissions
Ashley McDougall
August 14, 2024
Abstract
This paper evaluates the effectiveness of British Columbia’s carbon tax in reducing greenhouse gas (GHG) emissions. Multiple regression analyses, including difference-in-differences
methods, are conducted using data from Canada’s official greenhouse gas inventory and other
economic data. The results are robust and indicate that the BC carbon tax has not significantly reduced overall GHG emissions, potentially due to contradictory overlapping policies.
Policy recommendations include streamlining environmental policies and advocating for the
renegotiation of the Paris Accord to account for Canada’s forest sinks. This paper highlights
the need for coherent environmental policies to achieve meaningful reductions in GHG emissions for Canada and globally.

Keywords: carbon tax, greenhouse gas emissions, British Columbia, environmental policy,
policy effectiveness.

JEL Codes: H21, H23, H71, Q58.

1

Introduction

The carbon tax is a historically contentious policy and remains a major point of debate in British
Columbia (BC) and across Canada. Although proponents of the carbon tax are confident in
its potential to meet environmental goals, critics argue that it is both ineffective and regressive.
Carbon tax policies are supported by the BC New Democratic Party (NDP) and the federal Liberal
government, and have faced significant criticism from both the BC and federal Conservatives, who
have popularized the ”axe the tax” slogan. The aim of this paper is to analyse the effectiveness of
the carbon tax in reducing greenhouse gas (GHG) emissions.
On July 1, 2008, BC became the first jurisdiction in North America to implement a carbon tax.
The tax was initially set at CA$10 per tonne of GHG emissions, measured in tonnes of carbon
dioxide equivalent (t CO2 eq), with a plan for it to increase until 2012, when it reached CA$30 per
tonne. In April 2022, the tax rate was raised from CA$30 to CA$50 per tonne, and on January 1,
2023, it further increased to CA$65 per tonne. As of April 1, 2024, BC’s carbon tax rate stands
at $80 per tonne. The provincial government’s plan is to continue raising the tax annually, aiming
for CA$170 per tonne by 2030 (Carbon Tax Center, 2024). The BC carbon tax is levied on the
purchase and consumption of fossil fuels, which make up approximately 80% of the province’s
GHG emissions (Ministry of Environment and Climate Change Strategy, 2024).
Prior to the introduction of the BC carbon tax in 2008, environment and climate change had been
polling as the number one concern for British Columbians in 2007. However, in the spring of
2008, gasoline price hikes led to growing public concern about the new policy. Following this, the
opposition BC NDP launched an ”axe the tax” campaign at that time, which resulted in declining
public support for the BC Liberals and the carbon tax policy (Harrison, 2019).
By 2009, in the wake of the global recession, British Columbia’s public opinion had shifted. Opinion
polls at that time revealed that British Columbians had the lowest level of support for a carbon tax
in the country, despite being the only province with such a tax at the time, with just 40% backing
the measure (The Canadian Press, 2009). Today, as the costs of food and housing continue to
rise, nearly half of Canadians now support the elimination of the carbon tax. According to a 2023
1

Angus Reid poll, 42% of Canadians favor completely abolishing the carbon tax, 25% believe it
should remain at its current rate without further increases, 17% advocate for a reduction over the
next three years, and only 15% support maintaining the current approach (Woodside, 2023).
It’s important to examine the trends of support for the carbon tax in the context of affordability.
When life becomes unaffordable, people are less likely to support or be able to afford extra taxation. The fluctuation in public support for the carbon tax highlights how economic pressures can
influence attitudes towards environmental policies. If individuals are struggling with the cost of
living, they will prioritize financial relief over environmental goals. In April 2022, Canada experienced an inflation rate of 6.8%, the highest in 31 years. A recent survey also revealed that 1 in 5
Canadians are reducing their food intake to cope with increased costs and manage their expenses
(Unifor, 2022). These affordability issues significantly impact support for the carbon tax, as people
facing financial difficulties are less inclined to support additional up-front expenses.
As BC approaches a provincial election in October of 2024, British Columbians must decide which
party to support, with the carbon tax being a central issue in the election. BC’s political parties
offer various perspectives on the carbon tax. The BC NDP and BC Greens support maintaining the
current carbon tax structure with incremental increases, while the BC United supports maintaining
the tax with no increase, and the BC Conservative Party supports eliminating the carbon tax
altogether.
Existing literature provides varying perspectives on the carbon tax. Studies indicate mixed results
on the effectiveness of the BC carbon tax, with some noting insufficient tax rates causing ineffectiveness of the carbon tax in reducing GHG emissions, and others noting a significant decrease in
per capita fuel consumption as a result of a carbon tax policy. In this paper, we find that the BC
carbon tax is not effective in reducing GHG emissions. This is likely due, in part, to the fact that
the potential effectiveness of the carbon tax is being undermined by the presence of a multitude of
conflicting policies, which create mixed signals in the market. With such diverse perspectives on a
controversial subject, the objective of this paper is to provide a timely and well-informed analysis
on whether British Columbia should consider ”axing the tax.”

2

The remainder of this paper is structured as follows: Section 2 offers a review of related literature.
Section 3 reviews the data utilized in the analysis. Section 4 outlines the methodology. Section 5
presents the results of the analysis. Section 6 discusses policy implications and conclusions.

2

Literature Review

The following section reviews literature on carbon tax systems applied in BC, Canada, and globally.

2.1

BC Carbon Tax

Several studies have examined the BC carbon tax for its impacts on GHG emissions and the
economy. Pretis (2022) found that while the tax has reduced transportation emissions, it has not
led to significant reductions in overall GHG emissions, suggesting that current tax rates are unable
to generate a substantial impact. Elgie and McClay (2013) reported a 19% decline in per capita
fuel consumption in BC compared to the rest of Canada, with no adverse effects on economic
growth. Murray and Rivers (2015) noted that the tax, set at C$30 per tonne by 2012, covers a
significant portion of emissions and had reduced them by 5% to 15% at that time. They also note
that some sectors faced economic challenges due to the tax, but overall economic impacts were
minimal. Olale et al. (2019) focus on the impact of BC’s carbon tax on agriculture, finding it
associated with a decline in farm income-to-receipts ratios and increased production costs. This
highlights the need to consider specific sectoral impacts in evaluating carbon tax policies. Sileci
(2023) shows that the BC carbon tax reduced GHG emissions and benefited air quality, but noted
that these benefits were unevenly distributed. The conflicts in these findings suggest that further
analysis is needed to properly evaluate the effectiveness of the BC carbon tax in reducing GHG
emissions.

2.2

Carbon Tax in Canada

Several studies examine the application of a carbon tax in Canada. The study by Snodden and
Tombe (2019) highlights that increasing carbon tax revenues could impact provincial fiscal capacities and the distribution of equalization payments, especially given the uneven distribution of

3

GHG emissions across provinces. The role of the federal backstop in provinces without stringent
carbon pricing further complicates matters, as these revenues are currently excluded from the
equalization formula. In Saskatchewan, a study by Liu et al. (2018) using a Computable General
Equilibrium (CGE) model shows that while a carbon tax reduces GHG emissions, it also contracts
the economy, especially in resource-intensive sectors like coal and petroleum. Future research will
focus on dynamic CGE models and exploring carbon tax revenue recycling mechanisms to optimize
benefits. Mildenberger et al. (2022) find that recycling revenue through lump-sum dividends might
reduce public resistance to carbon taxes; however, their study indicates low public awareness and
significant underestimation of rebate amounts in Canada as well as Switzerland. Accurate rebate
information had limited impact on public support, suggesting that perceptions are influenced by
partisan identities. Harrison (2012) explores the political dynamics of carbon tax proposals in BC
and at the federal level, noting that while BC’s carbon tax succeeded due to economic focus during
a recession, carbon tax proposals generally remain unpopular, highlighting the political risks of
environmental policies broad electoral support.

2.3

Carbon Tax Globally

This sub-section reviews carbon tax literature from countries outside of Canada. Fremstad and
Paul (2019) show that while a carbon tax can be a straightforward solution to reducing GHG
emissions, it should be complemented by significant research and development (R&D) to foster new
technologies and address market failures related to pollution. Williams III et al. (2014) estimate the
effects of an initial incidence of a carbon tax across U.S. states, which shows geographic differences
driven by income sources and energy use patterns, with revenue use playing a crucial role in
determining the impact. Another study by Dumortier and Elobeid (2021) assesses the economic
and environmental effects of a U.S. carbon tax on agriculture, finding increased production costs
and altered trade patterns, which lead to a slight global increase in GHG emissions from land-use
changes. Agostini et al. (1992) examine the effects of carbon taxes in OECD-European countries,
highlighting the importance of country-specific coordinated environmental policies to stabilize
emissions, with high tax rates being necessary for significant reductions. Hajek et al. (2019)
evaluate the environmental effectiveness of carbon taxes in the energy industries of selected EU
4

countries, finding that increased tax rates significantly reduce GHG emissions. Carson et al. (2015)
compare the cost of carbon tax policies in China and the U.S., finding that the welfare costs are
lower in developing countries like China than those in developed countries such as the U.S. for
emissions reductions up to 12%.

3

Data

Data on road transportation emissions from Canada’s official GHG inventory was used, which
summarizes anthropogenic GHG emissions by measuring consumption of fuels (excluding the biogenic CO2 emissions from ethanol and biodiesel) by vehicles licensed to operate on roads (Environment and Climate Change Canada , 2024). Data from the following Canadian provinces is
used in the analysis: British Columbia, Alberta, Saskatchewan, Manitoba, Ontario, Quebec, New
Brunswick, Nova Scotia, Newfoundland and Labrador, and Prince Edward Island. GHG emissions
from Canadian territories are too small to influence the analysis and results and therefore are not
included.
Canada’s GHG inventory is developed in accordance with the Enhanced Transparency Framework of the Paris Agreement, using the 2006 Intergovernmental Panel on Climate Change (IPCC)
methodological guidance. GHG emissions are estimated by multiplying activity data, such as the
annual amount of fuel burned, by emission factors, which are average rates of emissions for given
activities. Emissions are reported in kilotons of carbon dioxide equivalents (kt CO2 eq), calculated
by multiplying the emissions of a specific GHG by its global warming potential (GWP). The data
collection principles focus on improving estimates of key categories, enhancing data quality iteratively, and ensuring continuous improvement through regular review and agreements with data
suppliers. The Government of Canada collects data on GHG emissions on an annual basis, which
is submitted to the United Nations on April 15 yearly (Environment and Climate Change Canada
, 2023a).
Gases measured are carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFC), perfluorocarbons (PFC), sulfur hexafluoride (SF6) and nitrogen trifluoride (NF3).
These GHGs trap heat in the atmosphere, creating a greenhouse effect and contributing to the
5

Table I: Descriptive Statistics
Variable
Mean
Standard Deviation Minimum
GHG Emissions (kt CO2 eq) 11,601.54
12,730.85
418.19
GDP (Millions)
$169,052.30 $204,513
$3,683
Population
3,255,801
3,838,380
130,369

Maximum
48,461.59
$874,981
14,842,488

warming of the earth. It is estimated that 80% of GHG emissions globally result from burning
fossil fuels and industrial processes. These emissions contribute to increasing annual temperatures, sea level and precipitation level increases, and increased heat waves. In 2021, approximately
22% of Canada’s GHG emissions came from transport. GHGs have varying GWPs and lifespans.
Methane (CH4) and hydrofluorocarbons (HFC) are considered to be short-lived climate pollutants
that are highly potent. Long-lived pollutants include perfluorocarbons (PFC), sulfur hexafluoride
(SF6) and nitrogen trifluoride (NF3), which remain in the atmosphere for a longer period of time
(Government of Canada, 2024).
Lastly, Statistics Canada data on annual population and gross domestic product (GDP) by province
from 1990 to 2021 was used. Population estimates are recorded annually on July 1 and GDP data
is measured annually in chained 2017 dollars at market prices (Statistics Canada, 2024).
Table I presents descriptive statistics of the data.

4

Methods

This section outlines the methods used in the analysis. We specifically focus on the application
of four linear regression models, including difference-in-differences techniques. The GHG data,
GDP data, and population data were transformed using logarithms, allowing us to interpret the
estimated coefficients in the regressions as elasticities. The following section details the specific
methodologies used to construct these regression models.
The first regression model tests whether the BC carbon tax is correlated with reducing GHG
emissions in British Columbia. Models 1 and 2 uses a restricted sample, focusing only on BC.
Focusing these analyses on the province with the longest-standing carbon tax allows us to examine
a more extended period of treatment exposure, which allows for a clearer observation of the policy’s

6

long-term effects. Model 1 is specified as:

log GHGt = β0 + β1 CarbonT axt + β2 log GHGt−1 + et

(1)

where CarbonT axt is a binary variable indicating the presence of the BC carbon tax (0 if the
year is < 2008, 1 if the year is ≥ 2008), logGHGt−1 is the logarithm of GHG emissions, lagged
at year t − 1, and et is the error term at year t. The coefficient β1 in equation (1) represents the
elasticity of GHG emissions with respect to the BC carbon tax policy. If β1 is negative, it implies
that the introduction of the BC carbon tax is associated with a reduction in GHG emissions. If
β1 is positive, it suggests that the BC carbon tax is correlated with an increase in GHG emissions.
A zero coefficient would indicate no correlation between the BC carbon tax and GHG emissions.
The magnitude of β1 indicates the strength of this relationship: a larger absolute value means a
stronger impact of the BC carbon tax on GHG emissions, whereas a smaller absolute value means
a weaker impact. The coefficient β2 is lagged logarithmic GHG emissions, which is included to
account for the potential of autocorrelation. Pretis (2022) discusses the need to include the lagged
logarithmic GHG emissions because of the persistence of GHG emissions’ impact on current and
future emission quantities.
The second regression includes additional variables to control for GDP and population size, aiming
to reduce omitted variable bias and provide a more accurate estimate of the BC carbon tax’s effect
on GHG emissions. Equation (2) also uses a restricted sample focusing solely on British Columbia.
As well, the model includes lagged data for GHG emissions, GDP and population to model delayed
effects and enhance the robustness of the analysis. The model is specified as:

log GHGt = β0 + β1 CarbonT axt + β2 log GHGt−1 + γ1 log GDPt−1 + γ2 log P opulationt−1 + et (2)

where logGHGt−1 is the logarithm of lagged GHG emissions at year t for BC, and γ1 log(GDPt−1 )
and γ2 log(P opulationt−1 ) are logarithmic GDP and population, lagged at year t − 1. γ1 is the
7

output elasticity of GHG and γ2 is the population elasticity of GHG. γ1 measures the percentage
change in GHG for every one percentage point increase in GDP in the previous period. γ2 measures
the percentage change in GHG for every one percentage point increase in population in the previous
period.
The estimated effect of the policy in (1) and (2) is correlational only and cannot be considered
causal. To evaluate the causal impact of the BC carbon tax, we employ a difference-in-differences
approach in models 3 and 4. This model compares the changes in GHG emissions over time between
BC (the treatment group) and other provinces (the control group). The model is specified as:

log GHGt = β0 +β1 CarbonT axt +β2 log GHGt−1 +β3 T reatedi +β4 CarbonT axit ×T reatedi +et (3)

where T reatedi is a binary variable indicating the presence of the carbon tax policy (1 if i is BC,
0 if i is not BC) and CarbonT axit × T reatedi is the interaction term and difference-in-differences
(DID) estimator. The coefficient β3 captures the causal effect of the carbon tax policy by comparing
changes in GHG emissions over time between BC (the treatment group) and other provinces (the
control group). This approach helps isolate the impact of the carbon tax from other confounding
factors. The final regression model extends the DID approach by including GDP and population
information to further control for other factors, thereby controlling for omitted variable bias. The
model is specified as:

log GHGit = β0 + β1 CarbonT axit + β2 log GHGi,t−1
+ β3 T reatedi + β4 CarbonT axi t ∗ T reatedi + γ1 log GDPi,t−1 + γ2 log P opulationi,t−1 + et (4)

These four regression models provide a comprehensive framework for analyzing the effectiveness
of the BC carbon tax on reducing GHG emissions.

8

The parallel trends assumption is crucial to the difference-in-differences analysis. It requires the
assumption that in the absence of the treatment (CarbonTax), the treated and control groups
would have followed the same trend over time. This assumption enables us to attribute any
post-treatment differences in GHG emissions between the groups to the BC carbon tax.

5

Results

5.1

Trends in GHG Emissions

Figure 1 illustrates the annual mean GHG emissions (in kt CO2 eq) for Canadian provinces from
1990-2021. The 1990’s saw steady, but substantial growth in road transportation emissions across
Canadian provinces. During the 1990s, Canada experienced significant urbanization, which had an
impact on GHG emissions from road transportation. As cities expanded outward, urban residents
increasingly moved to suburban areas, which is also referred to as urban sprawl. This shift led to
longer commuting distances and times, as people traveled greater distances between their homes
and workplaces. The reliance on personal vehicles grew due to public transportation infrastructure
in these areas not keeping pace with the population growth, further exacerbating the rise in emissions. The increased vehicular traffic contributed to higher fuel consumption and GHG emissions.
As a result, urbanization during this period was a key factor in the growth in road transportation
emissions in Canada (Rahdari, 2021). From 2000-2010, this trend continued, with GHG emissions
continuing to grow with growing urbanization. There was a dip in GHG emissions in 2008 with the
financial crisis occurring at that time, resulting in less road transportation and therefore less GHG
emissions. Despite this periodic dip, emissions continue to rise from 2008-2010. From 2010 to 2021,
GHG emissions from road transportation continued to rise, though at a slower rate compared to
previous decades. This may be partially due to electric vehicles (EVs) becoming more common,
though they still remain a small proportion of total vehicles in Canada. The COVID-19 pandemic
led to a temporary reduction in road transportation emissions in 2020 due to lockdowns, reduced
economic activity, and changes to road transportation behaviours.
Figure 2 illustrates provincial GHG emissions from road transportation by year. The majority of
provinces exhibit an overall increase in GHG emissions from 1990 to 2021, with some variations
9

Figure 1: Total Annual GHG Road Transportation Emission Trends in Canada, 1990-2021

in the rates of increase. Most provinces show a steady or slightly increasing trend in GHG emissions from 2000 onwards, with some provinces experiencing increases and decreases during this
period.
BC’s emissions show a gradual increase, peaking slightly around 2004-2008 before declining briefly,
possibly temporarily influenced by the implementation of the BC carbon tax in 2008, before a
large increase after the implementation of the BC carbon tax. Emissions in Saskatchewan also
show an increasing trend, peaking around 2015 before a slight decline. Ontario and Quebec are
Canada’s highest GHG emitting provinces, though both display mostly stable emissions with minor
fluctuations. Quebec, in particular, shows a slight decreasing trend. Alberta also consistently
exhibits high GHG emissions, which reflects its significant reliance on fossil fuel industries. Other
provinces such as British Columbia, Manitoba, and Saskatchewan show relatively stable emission
trends over the years, with lower overall emission levels compared to Alberta. Manitoba and
maritime provinces (Manitoba, New Brunswick, Nova Scotia, Newfoundland & Labrador, and
Prince Edward Island) have lower emissions compared to the larger provinces. They exhibit less
pronounced trends, with minor fluctuations over the years.

10

Figure 2: Annual GHG Emissions from Road Transportation by Province, 1990-2021

5.2

Impact of the Carbon Tax on GHG Emissions

The first regression model examines the impact of British Columbia’s carbon tax policy on the
logarithm of GHG emissions. This model also considers the effect of the lagged logarithm of GHG
emissions. As presented in Table 2, column (1), the coefficient for the lagged variable log(GHG)
(0.809) is highly significant at the 1% level (p = 0.000), indicating a strong positive autocorrelation,
where past emissions strongly predict current emissions. The coefficient for CarbonT ax is positive
(0.006) but not statistically significant (p = 0.733), suggesting that the BC carbon tax policy does
not have a significant immediate effect on reducing GHG emissions. The constant term, significant
at the 10% level (1.831), represents the base level of emissions when all other variables are zero. .
The R-squared value of 0.860 indicates that 86% of the variation in GHG emissions is explained
by the model
In the second model, the lagged logarithm of GDP and population are included as additional
variables. The results in Table 2, column (2), show that the coefficient for lagged log(GHG)
remains positive (0.655) and significant (p = 0.000). The CarbonT ax coefficient is negative (0.017) but still not significant (p = 0.527). The coefficients for log(GDP) and log(Population) are

11

-0.006 and 0.234, respectively, with neither being statistically significant (p = 0.927 and p = 0.482).
The constant term is also not significant (p = 0.944). The R-squared value slightly increases to
0.869, indicating that the inclusion of population and GDP as variables does not substantially affect
the variability of GHG emissions outcomes. Both models suggest that past GHG emission levels
are the strongest predictors of current and future emissions. Despite the CarbonT ax coefficients
being insignificant, it is noteworthy that they are inconsistent between the two models. Model
1 indicates a small positive impact on GHG emissions, while Model 2 indicates a small negative
impact. Model 2’s CarbonT ax coefficient is also inconsistent with the observed increase in GHG
emissions over time, despite the BC carbon tax policy being in place since 2008.

5.3

Difference-in-Difference Regressions

The difference-in-differences (DID) models, 3 and 4, aim to provide a causal estimate of the BC
carbon tax’s impact by including the interaction term CarbonT ax × T reated. Table 2 column (3)
shows that the coefficient for lagged log(GHG) increases significantly to 0.898, which shows that
previous emissions have an even stronger predictive power when the DID variable is introduced.
The CarbonT ax coefficient (-0.002) is negative but still not significant, indicating that the BC
carbon tax does not show a statistically significant impact on emissions reduction. The constant
term is positive and highly significant (0.896). The R-squared value of 0.998 suggests that this
model explains nearly all the variability in greenhouse gas emissions.
The final model shows lagged log(GHG), CarbonT ax, and CarbonT ax × T reated coefficients
which are only slightly different from model 3, showing that incorporating GDP and population
as variables does not have a large effect on GHG outcomes. This points to the conclusion that
the largest indicator for GHG emissions outcomes is past GHG emission levels. Table 2 column
(4) shows that the coefficient for lagged log(GHG) remains very high and significant (0.859),
reinforcing the strong dependence on past emissions levels. The CarbonT ax coefficient (-0.014) is
still not significant. The log(GDP) variable becomes significant at the 10% level (0.086), suggesting
a small but positive impact on emissions. The interaction term CarbonT ax × T reated is negative
but not significant (-0.005), implying that the impact of the BC carbon tax is not significant.
The constant term (1.518) is significant at the 10% level. The model retains an R-squared value
12

Table II: Regression Results
Dependent variable: log(GHGi,t ) 1
2
log(GHGi,t−1 )
0.809*** 0.655***
-10.25
-4.71
CarbonT axi,t
0.006
-0.017
-0.34
(-0.640)
log(GDP ii,t )
-0.006
(-0.04)
log(P opulationi,t )
0.234
-0.71
CarbonT axi,t × T reatedi,t

3
0.898***
-33.99
-0.002
(-0.270)

4
0.859***
-25.17
-0.014
(-1.320)
0.086*
-2.33
-0.088
(-1.52)
-0.003
-0.005
(-0.160) (-0.220)
Constant
1.831*
-0.2
0.896*** 1.518*
-2.45
(-0.070) -3.94
-2.19
Observations
31
31
310
310
R squared
0.86
0.869
0.998
0.998
Notes: *** significant at 1%, ** significant at 5%, * significant at 10%.
of 0.998, maintaining its high explanatory power and further proving the dependence of GHG
emissions on past GHG emissions.

6

Policy Discussion

6.1

Policy Explanations to Regression Results

McKitrick (2016) argues that multiple overlapping environmental policies can lead to inefficiencies
and reduced effectiveness. This perspective is reflected in the regression results and is evident in
analyzing the multitude of policies present in BC which are aimed at reducing GHG emissions.
While the BC carbon tax aims to reduce GHG emissions by making fossil fuel use more expensive,
its effectiveness can be undermined if it is implemented alongside other conflicting policies. McKitrick (2016) highlights that such redundancy can create economic inefficiencies and deadweight
loss without achieving additional environmental benefits.
In addition to the carbon tax, British Columbia and Canada have implemented several other overlapping environmental policies. For instance, the federal government has introduced the Clean Fuel
Standard, which mandates a reduction in the carbon intensity of fuels (Environment and Climate
Change Canada , 2023b). BC has its own Low Carbon Fuel Standard with similar objectives, which

13

also imposes a credit-based emissions trading system. Additionally, there are various subsidies and
incentives for renewable energy projects, electric vehicles, and energy efficiency improvements at
both the provincial and federal levels. The Greenhouse Gas Industrial Reporting and Control Act
in BC requires large industrial emitters to meet specific emissions targets or pay into a technology
fund (Province of British Columbia, 2024). These overlapping policies lead to regulatory confusion
and administrative burdens for businesses. They may also result in double counting of emissions
reductions or conflicting signals about the most effective ways to reduce GHG emissions. Addressing these overlaps requires careful policy coordination to ensure that the combined impact of these
measures maximizes environmental benefits without imposing unnecessary economic costs.
Low adoption of electric vehicles (EVs) is another example of an inefficiency created through the
use of overlapping policies. Despite significant subsidies and incentives, EV adoption remains limited, suggesting that existing policies promoting their adoption may not be effectively designed
to achieve lower GHG emissions, which is the intended outcome. The conflicting results observed
in our regression models further highlight the need for a more streamlined approach to environmental policy. For example, while Model 1 suggests an association between the BC carbon tax
and increased GHG emissions, Model 2 shows a reduction in GHG emissions when GDP and population are accounted for. However, the coefficients for the CarbonT ax variable in both models
are not statistically significant. This inconsistency points to potential issues with policy overlap,
reinforcing McKitrick’s argument for more targeted and efficient policy design. Table 3 shows
Electric and Non-Electric vehicle registration in Canada from 2017-2022, including EV registration growth. Since 2019, growth in EV registration has been declining, while year-to-year demand
for non-electric vehicles has maintained stable growth between 2018-2022. This further highlights
the lack of efficiency when multitude of environmental policies are implemented.
Another key element of the policy explanation for these results is the issue of inadequate funding
for public transit investments. Canada could increase public transit ridership through targeted
investments in transit operations, housing density near transit, and incentives for faster transit
services. These measures could cut 65 million tonnes of carbon emissions from 2024 to 2035.
However, current public transit is underutilized due to unreliable services and lack of adequate
14

Table III: Electric Vehicle Registration in Canada, 2017-2022
2017
2018
2019
2020
2021
Non-electric
3,268,655 3,327,929 3,381,707 3,369,266 3,512,196
Electric
48,789
59,210
79,823
101,311
134,331
Percentage of EV to
1.50%
1.80%
2.40%
3.00%
3.80%
total M.V.R.
EV growth year-to-year
19%
33%
27%
27%
Non-electric growth
2%
2%
0%
4%
year-to-year

2022
3,615,356
173,594
4.80%
26%
3%

funding. Despite significant federal investment in transit infrastructure, insufficient funding for
day-to-day operations leaves many buses idle (Environmental Defence, 2024). Investing adequately
into transit services is crucial for improving ridership, reducing GHG emissions, and making public
transit a viable climate solution.

6.2

Policy Recommendations

In order for environmental policies to be effective, BC and the rest of Canada should adopt a
more streamlined approach. McKitrick’s argument for reducing policy overlap and redundancy
is particularly important here. Multiple overlapping policies can lead to inefficiencies, increased
financial burdens, and economic inefficiencies without necessarily providing environmental benefits.
Instead, focusing on a single, well-targeted policy can generate more productive and substantial
outcomes, while also being less burdensome on consumers and the economy.
If a carbon tax is to be implemented, it should be the only environmental policy targeting GHG
emissions. This would allow for a clearer signal in the market, reducing confusion and enabling
businesses and consumers to make better decisions that are less burdened by a multitude of policies.
By concentrating resources and efforts on one policy, be it the carbon tax or another policy, its
effectiveness can be maximized and would ensure that it sufficiently creates reductions in emissions.
This focused approach is more likely to yield better environmental and economic results.
Pretis (2022) argues that carbon pricing at current rates alone is insufficient for major GHG
emission reductions. The absence of a statistically significant effect of carbon taxes on aggregate
emissions is likely due to the tax being too low to prompt changes, given the varied GHG emissions
elasticities across sectors. Pretis also argues that carbon taxes are not the only way to reduce
15

emissions and that other measures like command-and-control approaches and mandated efficiency
improvements can significantly lower emissions.
Another viable policy solution may be for Canada to advocate for a renegotiation of the Paris
Accord to account for its large forest sinks. Research shows that forest-related emissions reported
in national inventories may be lower than global estimates, due to differences in how anthropogenic
forest carbon sinks are counted. For instance, Canada’s National Inventory Report shows a discrepancy between actual forestry-related emissions and reported figures. While carbon emissions from
wildfires are considered natural, carbon removals from commercially mature forests are deemed
anthropogenic. This inconsistent reporting approach can lead to an emissions account that is not
truly reflective of Canada’s emissions (Bysouth et al., 2024).
Canada’s forests, especially its boreal forests, are crucial carbon sinks, absorbing significant amounts
of greenhouse gases and playing an important role in the global carbon balance. These forests are
a major contributor to climate mitigation by sequestering more carbon than they emit, which
helps offset emissions globally (Harris et al., 2021). This raises important questions about whether
Canada, with its considerable natural carbon sinks, should bear the same burden of climate mitigation through policies like the carbon tax, which impose direct costs on consumers and the
economy. Instead, greater responsibility should be placed on nations that are larger polluters, as
they contribute more substantially to global carbon emissions. Renegotiating the Paris Accord to
recognize the unique contributions of heavily forested nations like Canada could lead to a more
effective global strategy for addressing climate change, one that accurately reflects each country’s
carbon balance and directs responsibility towards the major emitters.
The health and management of Canada’s carbon sinks are critical for maintaining the environmental benefits they provide. There is a need for further research on the emissions of unmanaged forests
in order to better understand and accurately account for carbon dynamics and potential carbon
sinks in unmanaged forests. These forests play a crucial role in carbon emissions and deficits, yet
they are often excluded or underrepresented in national inventories. Recognizing their contribution
is important in order to create a more accurate and comprehensive picture of a country’s carbon

16

balance, particularly for a nation like Canada with extensive unmanaged forests. Furthermore,
other countries with significant forest cover, such as Brazil, Russia, and countries in central Africa
share similar challenges and opportunities with large forests (Harris and Gibbs, 2021). These
nations could become key allies for Canada in advocating for a renegotiation of the Paris Accord. This collaboration could aim to ensure that the carbon sinks provided by large, forested
areas is properly acknowledged within international climate agreements. These countries can push
for an international framework that more accurately reflects the contributions of forested nations
to global carbon sequestration. This approach would recognize a more equitable distribution of
responsibilities in combating climate change.

7

Summary and Conclusion

This paper analyzes the effectiveness of the BC carbon tax in reducing GHG emissions. Data
from Canada’s official GHG inventory, along with provincial population and GDP data, were
analyzed using multiple regression models and difference-in-differences techniques. The findings
reveal that the BC carbon tax has not significantly reduced overall GHG emissions, likely due to
contradictory overlapping policies and insufficient tax rates. We examine possible solutions for the
future direction of environmental policy in BC and the rest of Canada.
The study highlights the mixed impact of the carbon tax, with some models indicating a slight
positive or negative correlation with GHG emissions, but none showing significant results. Policy
recommendations include streamlining environmental policies to reduce overlap and focusing on
a single, well-targeted measure like an appropriately set carbon tax. As well, we suggest that
Canada should advocate for a renegotiation of the Paris Accord to account for its vast forest sinks.
We also emphasize the need for further research on unmanaged forests’ emissions in Canada, as
well as other densely forested countries.
This paper contributes to existing carbon tax literature by providing an analysis of the BC carbon
tax’s effectiveness. Through highlighting the inconsistencies and limited impact of the carbon
tax, the study contributes to the ongoing debate on the best ways to approach to environmental
policy in Canada by showing the BC carbon tax to be statistically ineffective. These findings
17

highlight the importance of policy coherence and clarity of direction in the market when it comes to
environmental and carbon pricing policy. Future research should explore the benefits of employing
only a single environmental policy as well as the potential benefits of renegotiating the Paris Accord
to recognize forest sinks accurately. This approach could lead to more effective climate policies
globally.

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