Project: Bram Edens, Rutger Hoekstra, Daan Zult, Harry Wilting (PBL), Ronghao Wu (intern) Carbon footprints – reconciling academic and statistical work

Overview –Overview work within statistical community –Overview work within academic community –State the problem –Possible solution: SNAC footprint –Conclusions and discussion 2

Overview of footprint calculations at NSI’s and other government agencies NSI/Other Institute Type Country specific IO Years Environmenta l Regions Industries National Statistical Institutes Australian Bureau of Statistics SRIOY2007/ 2008GHG140 Statistics CanadaMRIOY2002&2006GHG4? Statistics DenmarkPartialY2005CO INSEEPartialY2005CO 2 ±1560 DESTATISPartial/ hybridY2007Energy, CO Statistics NetherlandsPartialN2009GHG (4)1760 Statistics SwedenSRION Energy; materials; air emissions 2134 GSO VietnamSRION2005, 2007CO 2 15 Other government agencies PBL Netherlands Environmental Assessment Agency Partial and MRIOY2001GHG (3) and land1357 DEFRAMRIOY CO 2 and GHG4123 International institutes OECDMRIOY 1995, 2000, 2005, 2008, 2009 CO2 (only emissions from fuel combustion) 5718 EurostatSRION pressures264 3

Statistical community –There is wide range of methods being used ‐NSIs often use simpler models –Focus broader than carbon –Clear interest in additional breakdowns ‐Household characteristics such as income –Dissemination practices of the institutes show that the results are not always presented as “official statistics” 4

Overview of MRIO databases that are currently publically available GTAPEXIOBASEWIODEora Acronym Global Trade Analysis Project EXIOPOL: Externality data and input-output tools for policy analysis World Input-Output Database- InstitutePurdue University EXIOBASE: FP6 project (EXIOPOL) led by FEEM Database created by NTNU, TNO, SERI, CML FP7 project lead by the University of Groningen University of Sydney Years 1990, 1992, 1995, 1997, 2001, 2004, 2007 (years are not comparable) Prices of previous year ­- Countries/ Regions (depends on year) 43 (27 EU, 16 non-EU) (95% of the global GDP) 40 (27 EU and 12 non-EU) (80% of world GDP in 2006) 187 Number of industries 57 industries130 industries35 industries industries Environmental data Greenhouse gases (CO2, NO2, CH4) Energy use Land use (split agro- ecological zone) Emissions (56) Materials (96) Land use (15) Water use (14) Energy use / several energy carriers Water consumption Land use Emissions of greenhouse gases Air pollutants Resource use/extraction Generation and treatment of various types of waste Greenhouse gases Air pollution Water use Ecological Footprint 5

Academic work –Difference between MRIOs: ‐Aggregation (industries and/or countries) ‐Construction method: IO based, SUT based, or trade based ‐Assumptions RoW or ITMs ‐Emission data (modeled or not) –Aim of MRIOs ‐Information about global developments ‐No claim to be 100% correct at national level ‐Focus on consistent method (rather than best country data) 6

Carbon footprints for the Netherlands from various MRIO databases 7 Data provided by Glen Peters and Nori Yamano

Carbon footprints for the Netherlands: WIOD and Eora 8

Stating the problem –Growing policy interest in footprints, but no clear answers –MRIOs have set the standard, but outside NSIs capabilities Labour intensive Assumptions –MRIOs vs. official statistics Always inconsistent due to integration/balancing required: Trade asymmetries –Can we reconcile statistical and academic work in area of footprint analysis? 9

A SNAC footprint –Produce a footprint, based on MRIO, that is consistent to official statistics of the Netherlands ‐Single-country National Accounts consistent (SNAC) –Main approach: “Adjust WIOD to be consistent to Dutch data” –Why WIOD? ‐Transparancy ‐Time series availibility –Gain insight why results could be so different 10

Method –Follow WIOD procedure, but overrule with improved Dutch int SUT: ‐Improved allocation of imports/exports to countries: Trade in goods: Bilateral trade data (re-exports and domestic trade) from micro data Trade in services: Trade in services (confidential) ‐National Accounts Used IO database to isolate re-exports Used IO database for valuation layers -> basic prices ‐Expand from 35 to 72 industries (CO2 only) –Balancing using the WIOD procedure but keeping the Dutch data fixed 11

Results: SNAC vs. WIOD 12 –Overall difference in footprint: 4-6% –Mainly due to lower foreign emissions –NL becomes net exporter of emissions Name SNAC- footprintWIODSNAC-footprintWIOD Absolute/PercentageMtCO 2 % % Total Footprint % % Domestic indirect emissions81784% % Domestic direct emissions41403% 40395% Total Domestic % % Total Foreign % % Resident emissions

Results 2: per capita 13 Source: CBS 2013

Results for top 10 countries/regions 14 Source: CBS 2013 –China at 19%: largest foreign emissions followed by Germany –WIOD: 21%

Why do SNAC and WIOD results differ? WIOD intermediate consumption Final consumption expenditure Gross fixed capital formation Changes in inventories and valuables Gross capital formation ExportsTotal use at basic prices use ,091 imports (incl ITM) Total intermediate inputs Taxes less subsidies on products Intermediate Inputs adjusted Value added at basic prices5100 Output at basic prices1,0910 CBS use ,096 imports Total intermediate inputs Taxes less subsidies on products Total intermediate inputs adjusted Value added at basic prices511 Output at basic prices1,096 15

Why do SNAC and WIOD results differ? 2 CBS/WIOD intermediate consumption Final consumption expenditure Gross fixed capital formation Changes in inventories and valuables Gross capital formationExports Total use at basic prices use114%107%96%33%100%79%100% imports85%63%91% 80% Total intermediate inputs104%100%95%100%98% Taxes less subsidies on products45%152%156% Total intermediate inputs adjusted101%103%100%75%104% Value added at basic prices100% Output at basic prices100% 16 Differences due to: Re-exports Valuation layers More detailed information

Conclusions and discussion 1.Shift: uncertainty within MRIO to between MRIOs 2.MRIOs are produced for global questions, a SNAC-footprint is more relevant for national policy makers due to consistency to country statistics 3.SNAC makes a difference! (at least for the Netherlands) 4.MRIO producers could quite easily make a footprint for individual countries using “SNAC-philosophy”; key issue is sharing data 5.Need for enhanced cooperation especially in light of 2008 SNA ‐Between statistical offices ‐Between MRIO producers ‐Statistical and academic community 17