1. 1 Instruments and statistics - The response ® in the DPSIR Torstein Bye 1 and Annegrete Bruvoll 2 1 Director Economics, Energy and Environment, Statistics Norway Senior Researcher, Statistics Norway Motivation for the paper A multidimensional/multipurpose statistical system Statistics for policy analysis Multiple instruments in a consistent statistical system Summary and conclusions

2. Motivation – the policy analysis 2 Where E i =pressure f i functional form d i,1…n = driver type n = from driver to pressure = instrument type n p i,1…n = cost/price The use of environmental instruments are motivated from negative externalities – i.e. economic and other human activity harms the environment and economic actors do not take into account these impacts on other actors in their decision making Use of instruments are meant to internalize these negative externalities, cost efficient or not In the statistics then, we should couple statistics on the use of instruments with statistics for the Driving forces and Pressure variables to make proper analysis of the effect of actual and alternative environmental policy possible

3. 3 Motivation – the existing framework The motivation for the development of environmental and economic accounting is the recognition of the linkages between the economy and the environment. (common in DPSIR and SEEA) In the DPSIR environmental statistical work so far most work has been focusing on the D, P, S (and I), and to a less extent on the R? Despite the main focus in this conf? The focus in the D have been on two dimensions (a matrix of industries and commodities) The environmental consequences partly depends on economic activity partly depends on choice of technology – and the use of instruments influence on both – then the statistics should reflect both dimensions (as do policy) This calls for a three dimensional matrix (industries, commodities and technologies). The statistics on instruments, R, that exists has not been linked properly to the statistics of Drivers and Pressure –ref Bruvoll (2009) – presentation yesterday – Bruvoll and Dalen (2009) In principle – setting up a statistical system to cover these aspects is straightforward – in practice it may be more complex (lack of primary statistics) – but still a relevant framework is essential –To see where relevant statistics fits in –To reveal where relevant statistics is missing

4. 4 A multidimensional multipurpose statistical system - Example emissions to air: The Column dimension (first space): –Relevant Commodity dimension (ex: energy by type, waste, other substances ) The Row dimension (second space) –Economic activity by Industry – the SNA – the driving forces The Technology dimension (third space) –(ex: energy and emissions, - heating, processes, transport) A cube of relevant information (ex: use of fuel for transports in industry x) Example of one multipurpose dimension (Energy Balance/Energy Accounts) –Bridging –Aggregation –Transport –Residential/territorial Multipurpose –Drivers –Relevant instruments Figure 1. The three dimensional multipurpose data cube for sector (SN), commodity source (C i ), Purpose (H, P, T) and data type (a ijk ) a ijk - production, energy by purpose, emission coefficients and emission by matrix manipulation

5. 5 Statistics for policy analysis Taxes (ex: taxes per unit of emissions – i.e. tax rates) –The relevant tax rates – discriminatory taxes – exemptions – all nuances –Different from Eurostat env. related taxes - (cfr Bruvoll (2009) – (rates versus revenue) –OECD databank on taxes and subsidies – rates – relevant – need to transform Subsidies (ex: support per unity of energy) – –Transfers, R&D, preferential taxes, price controls, favorable loans –cf transformation to a common unit -the transformation problem Tradable permits (“black certificate”) – per unit –Shadow price and tax – discriminatory, exemptions –National registers for assignment of free allowances (grandfathered?)  The shadow price of the implicit subsidy equals the equilibrium price –The register of traded volumes and values –Net versus gross purchases of permits  Accounting residual –Firm specific assigned amount – less surrendered amount – less verified emissions –= net trade of permits + accepted CDM + accepted JI –Registers of CDM and JI (transformed to unity measures) Green certificate –Obligations on percentage renewable – derive purchases from energy demand –Market price – the subsidy element for producers – times the percentage=tax White certificate –Obligations in percentage – derive purchase from energy demand –Market price – the subsidy element for producers of savings appliances, tax=% p Regulations - shadow prices – the implicit market price- has to be based on analysis

6. 6 Multiple instruments – in a consistent multipurpose statistical system All instruments in a common unit – –Transformation of units The relation between instruments in each cell a= tax per unit –subsidy per unit –permit price/unit –GC price – an % –WC price – and % –s-p-r Matrix manipulation to values and revenues Consistent modeling and analyses Figure 1. The three dimensional multipurpose data cube for sector (SN), commodity source (C i ), Purpose (H, P, T) and data type (a ijk ) For taxes in Norway cf: Bruvoll and Dalen 2009: http://www.ssb.no/english/subjects/01/09/doc_200916_en/doc_200916_en.pdf http://www.ssb.no/english/subjects/01/09/doc_200916_en/doc_200916_en.pdf

7. 7 Summary and conclusions The DPSIR is a perfect framework for: i) Combining statistics for driving forces and pressure variables – but also for statistics on responses – (cf. also SEEA) Statistics in multiple dimensions –Capturing economic activity, –Commodity specific attributes and –Technology –Multiple number of matrixes –Matrix manipulation –Policy along these dimensions Consistency from micro to macro Capturing “all” instruments consistently –Common units From data to policy analysis via modeling –Effect of policy along three dimensions  Pressure variables  Welfare effects  Distribution of costs/welfare effects Figure 1. The three dimensional multipurpose data cube for sector (SN), commodity source (C i ), Purpose (H, P, T) and data type (a ijk )