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Instruments and statistics–the response R in DPRI
by
Torstein Bye and Annegrete Bruvoll1
Statistics Norway
1. Introduction
The use of environmental policy instruments has increased the last decades. This calls for statistics
on the scope and magnitude of such instruments to follow up the policy. Analyses on the
effectiveness of environmental policy calls for detailed statistics on the use of instruments. OECD and
Eurostat aims at gathering comparable statistics for environmental instruments, including
environmental related taxes. As shown in Bruvoll (2010) the present statistics may be flawed with
respect to relevance out of several reasons. Since the instrument portfolio is complex (see Bye and
Bruvoll 2009), a consistent way of measuring is important. Also, the national accounts need
information about all economic transactions. This calls for a systematic way of producing statistics for
a broad set off instruments. This is the authorities response (the R) in the DPSIR (Driver, Pressure,
State, Impact, Response) approach. Consistent statistics over countries on this issue has so far been
more or less neglected or underreported.
NAMEA and SEEA combine statistics for driving forces (through the national account -NA) and
environmental consequences (environmental accounts -EA) which then cover the D, P and I in the
DPSIR approach. The energy account is a link between these two accounts since energy is part of the
input commodity in the NA and a basis for calculation of emissions in the EA. Both the Oslo group
and the London Group have discussed a multipurpose energy accounting system, i.e. a system in
three dimensions (sector, commodity, end use or technology) which allows a simple aggregation to
both energy and national accounts (sector, commodity) and to energy balances (commodity and a
mix of sector and end use). Environmental policy instruments should in theory address
environmental externalities, which often are technology specific, i.e. a framework for statistics on
environmental instruments fits well into these three dimensions; energy types, sectors, and energy
use (process, mobile and stationary use). Besides, in practical policy the introduction of
environmental instruments is often discriminatory, and the discriminatory approach most often
follows these three dimensions too. A joint system for energy, environment, national account and
instruments will then serve all purposes.
In this paper we describe such a multipurpose system and show how it may be extended to cover
also the instrument part. This may seem straight forward but raises some challenges; i) what is an
environmental tax and an environmental subsidy, ii) how do we calculate these instruments, iii) what
is the relevant comparable instrument between countries, i.e. should we produce figures for the
value or prices (tax rates/subsidy rates), iv) some instruments have got more stimulating names (like
green, brown and white certificates), how do we compare them to taxes and subsidies and how do
we calculate them, v) is it meaningful to produce statistics for just one or two instruments and
exclude the rest when comparing among countries? also presents a limited application for Norway
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Torstein Bye – tab@ssb.no - is Director of Economics, Energy and Environment and Annegrete Bruvoll –
agb@ssb.no - is Head of Energy Research at Statistics Norway.
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on environmental taxes and tradable permits in the carbon market, which could be further
developed to include instruments, such as green or white certificates.
2. A multipurpose statistical system for activity, environmental
consequences and instruments
Let us first present the general framework for the production of interlinked statistics on activity
(Driving forces), environmental consequences (Impact and Stress) and Instruments (Response), see
figure 1 in the Appendix (the three dimensional cube).
The first column (sector) describes the preferred industry aggregation level which should be
consistent with the SN2007 coding (which makes it consistent with the National Account). The
detailing of this column should be selected with respect to data availability, Euorostat/UN demand
and analytical purposes. The row (commodity heading), i.e. the Ci‘s , follow the commodity
definitions in the energy accounts – cf. the IRES Manual (which is consistent with SNA), extended to
include non energy relevant activities that create pollution/emissions (waste etc). The third direction
(end use- H,P,T) describes technological activities like heating, production processes and transports
(own transport) that takes place in each of the industries. The elements, aijk represent the a’th
element in sector I, commodity j, and end use k, where a=1,2,…….,m – i.e. represents all m activities
(production in the SNA, energy input coefficients, energy input, energy prices, emission coefficients
for compound n, emissions of compound n, tax rates on compound n, taxes revenues on compound
n, permit price on compound n, value of permit trades on compound n, free allowances of
compound n, subsidies on compound n, subsidy rates on compound n, etc). Generally this allows us
to compute values from volumes and prices (including taxes and subsidies) just by matrix
manipulations.
Now we can produce a set of activity tables. A sector activity and commodity table (from input
output tables in the NA) serves as the point of departure. When national accounts and energy
accounts are consistent, this automatically brings forward the energy account n fixed prices. A matrix
of prices (may differ among consumers) transforms this to physical units, or the other way around,
an energy account in physical units together with energy inputs in value from the national account
produces relevant energy prices. This forms the basis for the calculation of energy related emissions.
We then need a matrix of emission factors (whether normalized to fixed price figures in NA or to the
physical units in EA), i.e for each compound like greenhouse gases, sulphur dioxide and NOx etc. For
CO2 this seems trivial since carbon in a process is carbon out of the process in a mix with oxygen.
However, emissions of compounds may be technological dependent since carbon may mix with
dioxygen (CO2), or oxygen (CO) or even hydrogen (CH4). Then our multipurpose cube in figure 1 is
useful. The set of instruments is then perfectly linked to the activity tables which also would ease the
analyses of the effect of instruments.
3. Instruments
The economics literature advocates internalisation of externalities by introducing taxes or tradable
permits. Some externalities are local (a common example is sulphur dioxide although it is also
transboundary to some extent), some are global (greenhouse gases).
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Competing industries are often exempted from instruments out of competitiveness concerns. The
cube helps us set up such exemptions in a consistent way. Exemptions also reduce the effectiveness
of the instruments, which calls for extra instruments, and different variations of regulations,
subsidies, green certificates, white certificates and public support for R&D show up. In Bye and
Bruvoll (2008) we show that certificates are nothing but combinations of taxes and subsidies. Since
the tax and subsidy element is endogenously determined in the market for each instrument,
calculation of such instruments is challenging and needs discussion.
To assess the efficiency of instruments and measure politicians/governments willingness to include
environmental considerations, the tax rates (“price element”) are important to measure. The
revenues equal taxes times the emissions and may hence increase both due to increasing emissons
and increasing taxes. Of course, in double dividend analysis also values matter, but only the relvant
revenues.
Taxes
The authorities would normally be the perfect source for information of the tax rates (determined in
the yearly national budget). Two problems arise; the tax is launched on energy rather than on the
externality, ii) the claimed environmental tax part is either higher or lower than the marginal cost of
abatement – i.e. not all of the tax could be considered an environmental tax, see below. There are
several reasons why we should tax energy, see for instance Bye and Bruvoll (2008b); an
environmental externality is just one of them. Other reasons are to harvest resource rent or
monopoly rent, to pay for infrastructure use (transport, transmission), or simply collect revenue to
the government based on the Ramsey principle (Ramsey 1927). All these reasons are often lumped
together in one tax. The tax elements must be separated when calculating the relevant
environmental tax element. Sandmo (1975) and Bruvoll (2009) argue that the relevant environmental
tax should be compared to the relevant marginal cost of the externality and in optimum to the
relevant marginal abatement cost. Bruvoll (2009) proposes a method to separate these that take
into account marginal cost of funds.
Generally subsidies keep prices below their market value for consumers and above market value for
producers. In UNEP (2004) direct transfers, public R&D, preferential tax treatments, price controls
and loans (with a lower than market interest rate) are included in subsidies. However, to compare
subsidies to taxes we need the subsidy rates, which is a unit annuity of the subsidy of the
investments (the capital cost – CAPEX) plus unit operating costs subsidy (OPEX).
Subsidies are normally launched to investment projects in terms of a specific amount or a lump sum,
to producing facilities based on a production basis (for instance a feed in tariff – i.e. a unit subsidy) or
for facilities that want to save the use of input (energy efficiency projects) on the demand side, either
lump sum or per unit. Lump sum subsidies are normally linked to some kind of volume measures, i.e.
they may be transformed to a unit measure. In practice this measure is complex and some data
transformation process is needed to make the measures comparable in units. Subsidies are normally
directed towards detailed projects, i.e. these data are on matrix form, cf. the cube in figure 1.
The bright side of this is that the public sector will normally establish some kind of a register for the
budgeting and accounting and the following up of such projects. Then the data collection is reduced
to harvesting from public registers while the transformation process may be demanding. A recent
paper by Steinbach et al (2008 b) discusses Environmental taxes in the context of the SEEA manual.
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Permits
Trading of a fixed set of allowances creates a shadow price of the restriction. Generally, a shadow
price equal to a tax produces the same cost efficient environmental output. An advantage to the tax
system is that all prices equal marginal abatement costs and no corrections are necessary cf. the tax
section.
To cover the permit instrument we need two sets of cubes (figure 1)– one for the initial assignment
of free allowances in volumes (implies also a value transfer – volume times the market price –i.e. a
subsidy) and a second for a following up on the economic and volume exchanges through the trading
of emission permits in the “market” (see below). The assigned amount of allowances may be
collected from public registers, this could be divided into grandfathered permits, and other free
emissions (for instance for new facilities). A supplement could be surrendered emissions, if the firm
out of some reason used less than what was assigned and was not allowed to sell abundant
allowances in the market. The “verified” emissions follow from the basic figure 1.
The second part of this table covers the trade of permits – both volumes and values. This comprises
domestic trade and international trade. The international trade involves trade on a market and trade
through CDM and JI. Principally, it should be possible to gather data from the permit exchange on a
firm basis, however since this is supranational trade this is probably not possible. The question then
is whether we need gross trade or net trade in our statistics, or if net trade figures is sufficient.
We may derive the net trade from an accounting matrix – the firm specific assigned amount less the
surrendered amount, and the verified emissions should equal the net trade of permits. Besides, all
CDM and JI projects must be formally accepted by the authorities on a firm basis, i.e. there should be
a register that could provide the data. From the accounting matrix and the register information of
CDM and JI we then may deduct the net trade on the exchange on a firm basis.
Green certificates
A saying is that a dear child has many names, this also applies to green certificates (and all the other
certificates). Some call the green certificate market an electricity certificate market. The instrument
as such, however, may evolve to other markets as for instance the gasoline market and then may be
named a bio fuel market, etc. Bye (2003) also shows that this instrument is nothing but a
combination of a tax (the consumer is obligated by law to purchase a certificate (paper in a derivative
market) in a proportion to his energy consumption) and a subsidy (a green producer gets a
marketable certificate per unit for free when he produces by a green technology). As this instrument
is a combination of a subsidy and a tax, it should be treated likewise statistically. The authorities
must approve which technologies are green and specify the number of certificates to the firms
applying the green technologies. Hence, public registers should exist that could then provide
statisticians with the data on volumes (the volume for the consumer is a share of his energy
consumption per definition). The market is also unitary, i.e. the equilibrium price of the certificate
forms directly the price for both the producer and the consumer (as a share of the price).
White certificates
The white certificate market is a market for obligated savings. The require that consumers to save a
certain share of energy. The costs vary over consumers, and consumers can trade saving certificates
based on marginal cost and achieve the total saving target at a minimum cost. As for the green
certificate market, the white certificate market is also noted in a register. Since it is not reasonable to
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imagine that all actors actually participate in the trade of energy savings, cf. the principal agent
assumption, this eases the data collection. Each agent (for instance a distribution company for
electricity) has to verify the savings and the cost for each principal (consumer), i.e. the exact
information we need for our statistics.
Regulation
Regulations are normally set up on a firm specific level, and the authority registers both regulated
and verified outcome. Statistics could be based on these registers. However, when it comes to
prices, data has to be based on firm specific information about unit cost of the regulation, which we
assume would be produced in cooperation with the authority.
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References
Bruvoll, A. (2009): On the measurement of environmental taxes, Discussion Paper 599, Statistics
Norway.
Bye (2003): On the Price and Volume Effects from Green Certificates in the Energy Market. Discussion
paper 351, Statistics Norway
Bye, T., and A. Bruvoll: (2008a): Multiple instruments to change energy behaviour: The emperor’s
new clothes? . Energy Efficiency 1(4), 373-386.
Bye, T. and A. Bruvoll (2008b): Taxing energy – why and how? The present policies across western
countries . RAPP 2008/28, Statistics Norway,
http://www.ssb.no/english/subjects/01/03/10/rapp_200828_en/
Eurostat (2001): Environmental taxes – A statistical guide. Methods and Nomenclatures.
Luxembourg, Office for Official Publications of the European Communities, 2001.
Bøhringerand Rosendahl (2009) Green Serves the Dirtiest. On the Interaction between Black and
Green Quotas, Discussion paper 581, Statistics Norway
Amundsen og Bye (2010): Multiple instruments in energy and climate change policies. The interplay
between a green and a white certificate market. Paper to the IAEE European conference in Vilnius,
August 2010
Winsnes Moe (2010): Interplay between a white and a black certificates. Master thesis at University
of Life Sciences, Ås, Norway, Spring 2010
Appendix
Figure 1. The three dimensional multipurpose data cube for sector (SN), commodity source (Ci),
Purpose (H, P, T) and data type (aijk)