The Second Generation Model: Data, Parameters, and Implementation

Transcription

1 PNNL The Second Generaton Model: Data, Parameters, and Implementaton Ronald D. Sands 1 Allen A. Fawcett 2 October 2005 Prepared for the Unted States Envronmental Protecton Agency under Contracts AGRDW and AGRDW Jont Global Change Research Insttute, College Park, MD Pacfc Northwest Natonal Laboratory Operated by Battelle for the US Department of Energy 1 Jont Global Change Research Insttute, Pacfc Northwest Natonal Laboratory, Battelle, Unversty of Maryland, 8400 Baltmore Avenue, Sute 201, College Park, MD 20740, USA 2 U.S. Envronmental Protecton Agency, 1200 Pennsylvana Ave. NW (6207J), Washngton, DC 20460, USA. The vews of the authors do not necessarly represent the vews of the U.S. Government or the Envronmental Protecton Agency.

2 LEGAL NOTICE Ths report was prepared by Battelle Memoral Insttute (Batelle) as an account of sponsored research actvtes. Nether Clent nor Battelle nor any person actng on behalf of ether: MAKES ANY WARRANTY OR REPRESENTATION, EXPRESS OR IMPLIED, wth respect to the accuracy, completeness, or usefulness of the nformaton contaned n ths report, or that the use of any nformaton, apparatus, product, or composton dsclosed n ths report may not nfrnge prvately owned rghts; or Assumes any labltes wth respect to the use of, or for damages resultng from the use of, any nformaton, apparatus, process, or composton dsclosed n ths report. Reference heren to any specfc commercal product, process, or servce by trade name, trademark, manufacturer, or otherwse, does not necessarly consttute or mply ts endorsement, recommendaton, or favorng by Battelle. The vews and opnons of authors expressed heren do not necessarly state or reflect those of Battelle. 2

3 I. Introducton Ths document provdes a descrpton of the data, calbraton procedures, behavoral parameters, and other parameters needed to populate the Second Generaton Model (SGM) as of 1 October It s one of a par of documents. The other document s a theoretcal model descrpton of the SGM (Fawcett and Sands, 2005), whch descrbes the status of the SGM as t exsts on 1 October The theoretcal descrpton of the SGM should be read frst as we assume that the reader s famlar wth Fawcett and Sands. Development of data for the Second Generaton Model began n A model base year of 1985 was selected and ntal efforts focused on SGM-USA. To model nternatonal trade n carbon emssons rghts, global coverage was needed. The world was then parttoned nto 13 regons for data collecton: some regons are ndvdual countres whle others are collectons of countres. To populate a computable general equlbrum (CGE) model for all SGM regons, the PNNL modelng group organzed a team of nternatonal collaborators that could provde local nputoutput tables, energy balances, natonal ncome accounts, data on hstorcal nvestment, and local knowledge of nsttutons and markets. It was not possble to create collaboratons for all SGM regons, but nne of the ten largest carbon-emttng countres ncludng both developed and developng countres, accountng for 75 percent of fossl fuel carbon emssons, were developed n collaboraton wth nternatonal nsttutons. At the tme, nothng exsted smlar to the global data sets presently provded by the Global Trade Analyss Project (GTAP). Durng the 1990s, two major nnovatons were ncorporated nto SGM. The frst was a revson of the benchmark nput-output table to provde full consstency wth energy balances. Carbon doxde emssons are ted closely to energy combuston, but the economc nput-output tables dd not provde suffcent nformaton on energy quanttes. The second nnovaton was to allow old vntages of the captal stock to have a lower elastcty of techncal substtuton than new captal: ths provdes a lagged response to a carbon polcy consstent wth the tme requred for turnover of captal stocks. Around the year 2000, the SGM base year was changed from 1985 to Some SGM regons were completely rebult wth the new base year and an ncreased number of producton sectors; some SGM regons were partally rebult, usng scaled nput-output data from the prevous verson. The remander of ths document s dvded nto four sectons whch dscuss the data employed to calbrate the model to reproduce a specfc base year, the calbraton process for transformng data nto model parameters, parameters that govern behavoral responses to changes n the model, and addtonal nformaton that s needed to create and run a model scenaro. The next secton, Secton II, provdes a descrpton of the data used for base-year calbraton, ncludng nputoutput tables, energy balances, and natonal accounts. Secton III descrbes procedures for combnng data sets for nput to SGM. Secton IV descrbes the behavoral parameters that determned model response to changes n relatve prces. Secton V descrbes other elements of model operaton and mplementaton such as populaton projectons, techncal change over tme, treatment of nternatonal trade, and smulaton of a clmate polcy. In addton, three appendces descrbe the relatonshp between SGM regons and geopoltcal regons, background on make and use tables, and the constructon of a commodty-by-commodty hybrd nput-output table for SGM-USA. 3

4 II. Base-Year Data The 13 SGM regons wth a base year of 1990 can be organzed nto three types accordng to ther hstory of data development: (1) regons that are based on 1990 nput-output data and have 15 to 21 producton sectors; (2) regons that use scaled nput-output data from a 1985 base year and have 7 or 8 producton sectors; (3) mnmal models for the remanng regons have 7 or 8 producton sectors, but nput-output tables are not avalable. All regons use 1990 energy balances, ether from the Internatonal Energy Agency (IEA) or from local sources. Table 2.1 summarzes characterstcs of the 13 SGM regons. Table 2.1. Characterstcs of SGM regons wth 1990 base year. Regon number of producton sectors type of constructon source of energy data energy sectors year of nputoutput table USA (USA) 21 rebult 1990 EIA/DOE and 1992 Canada (CAN) 8 scaled 1985 IEA W. Europe (WEU) 8 scaled 1980 IEA Japan (JPN) 17 rebult 1990 JIEE Australa/NZ (ANZ) 8 scaled 1985 IEA former Sovet Unon (FSU) 8 scaled 1985 IEA E. Europe (EEU) 8 mnmal IEA 6 hybrd Chna (CHN) 15 rebult 1990 ERI Inda (IND) 18 rebult 1990 TERI /1990 Mexco (MEX) 7 scaled 1985 IEA S. Korea (KOR) 17 rebult 1990 KEEI Mddle East (MDE) 7 mnmal IEA 5 hybrd Rest of World (ROW) 7 mnmal IEA 5 hybrd Notes: Insttutons provdng energy data nclude: Energy Informaton Admnstraton/U.S. Department of Energy (EIA/DOE); Internatonal Energy Agency (IEA); Japan Insttute of Energy Economcs (JIEE); Energy Research Insttute (ERI) of Chna; Tata Energy Research Insttute (TERI) of Inda; Korea Energy Economcs Insttute (KEEI). Input-output tables were not avalable for the Eastern Europe, Mddle East, and Rest of World regons; a hybrd nput-output table was constructed for each regon usng IEA energy balances and natonal accounts data from the Unted Natons Statstcal Yearbook. The major types of data needed for each SGM regon nclude: economc nput-output tables, energy balance tables, supplemental data on energy consumpton, natonal ncome accounts, and hstorcal nvestment by producton sector. Energy balance tables mght not provde enough nformaton on energy consumpton n energy-ntensve ndustres or on transportaton, so other sources of data on energy consumpton are used for SGM regons wth an extended set of producton sectors. Table 2.2 shows whch producton sectors are present n each SGM regon. 4

5 Table 2.2. Producton sector representaton n SGM regonal modules Producton Sector USA CAN WEU JPN ANZ FSU EEU CHN IND MEX KOR MDE ROW Crude Ol Producton X X X X X X X X X X X X Natural Gas Producton X X X X X X X X X X X X Coal Producton X X X X X X X X X X X X X Coal Products X X X Electrcty Generaton X X X X X X X X X X X X X Petroleum Refnng X X X X X X X X X X X X X Natural Gas Dstrbuton X X X X X X X X X Prmary Agrculture X X X X X X X X X X X Grans X X Anmal Products X X Forest Products X X Other Agrculture X X Food Processng X X X Paper and Pulp X X X X X Chemcals X X X X X Cement, Stone, Clay, Glass X X X X X Iron and Steel X X X X X Nonferrous Metals X X X X Other Industry X X X Durable Manufacturng X Other Manufacturng X Transportaton Passenger Transport X X X X Freght Transport X X X X Ral Transport X Non-ral transport X Everythng Else X X X X X X X X X X X X X Socal Accountng Matrx as an Organzng Tool A convenent way to organze data for a CGE model s wth a socal accountng matrx (SAM). The three major components of a SAM are a use table (or nput table), a make table (or output table) and the natonal accounts. See Appendx B for background on use and make tables and the varous ways they can be combned nto an nput-output table. Input-Output Table An nput-output table can be constructed n ether values or quanttes. Tables publshed by government statstcal agences are n values. However, f all agents pay the same prce for an nput to producton and we know these prces, then quantty nformaton can be recovered. Conversely, f an nput-output table s n terms of quanttes, we can recover the value table by multplyng each row through by ts prce. The general structure of an nput-output table s dsplayed n Fgure 2.1. Each row of the nputoutput table represents an nput to producton, ether an ntermedate nput or a prmary factor, and each column represents an actvty that uses nputs. An nput-output table s usually structured to have the same number of producton actvtes as ntermedate nputs, so that the ntermedate flows matrx s square. 5

6 The fnal demand porton of the nput-output table ncludes columns for personal consumpton C, nvestment I, government consumpton G, exports X, and mports M. Imports are entered as negatve values so that the row sum for any commodty across ntermedate uses and fnal demand s equal to total producton. If the nput-output table s n value terms, then row sums are the total value of producton and column sums for any producton actvty are the total cost of producton. Therefore, a test for consstency s that row sums equal column sums for each commodty, or that the value of producton equals the cost of producton Makers of commodtes fnal demand Commodtes Makers of commodty j Ammount of commodty used by used by makers of commodty j < Commodty C I G X M Total output of commodty Value added K L IBT Value added sold drectly to fnal demand Tot. val. add. Total cost for makers of commodty j Natonal Accounts Fgure 2.1. General structure of a commodty-by-commodty nput-output table Instead of drectly usng nput-output tables as publshed by government agences, we construct specalzed tables for use n energy and clmate polcy analyss that are hybrds of nput-output tables and energy balances. Detals of buldng a hybrd table are provded n Secton III. The man objectve of usng hybrd nput-output tables s to mantan full consstency wth energy balances. 6

7 Natonal Accounts Natonal accounts for a country can be compactly dsplayed n a condensed SAM, where the dmensons of accounts for actvtes, commodtes, and prmary factors are reduced to one by aggregaton. Even though the structure of an nput-output table s farly standard across CGE models, the representaton of natonal accounts vares wdely, both n terms of the number of accounts and the detal wthn each account. A condensed SAM showng the structure of natonal accounts n SGM s dsplayed n Table 2.3. Table 2.3. Condensed socal accountng matrx for SGM. Entres n bold are derved drectly from an nput-output table. actvtes actvtes commodtes prmary factors enterprses households government captal rest of world GROSS_OUTPUT commodtes INTERMEDIATE_INPUTS PCONS GCONS INVEST EXPORTS prmary factors VALUE_ADDED enterprses OVA households LABOR DIVIDENDS GTR government IBT CIT PIT+SSTAX captal RE PSAV GSAV NET_BORROWING rest of world IMPORTS where PCONS = personal consumpton GCONS = government consumpton INVEST = gross fxed captal formaton EXPORTS = total value of exports IMPORTS = total value of mports NET_BORROWING = - trade balance DIVIDENDS = ncome from nvestment CIT = corporate ncome taxes RE = retaned earnngs (corporate savngs) PIT = personal ncome taxes SSTAX = socal securty taxes PSAV = personal savngs LABOR = labor ncome GTR = government transfers to households IBT = ndrect busness taxes GSAV = government savngs OVA = other value added (payments to owners of captal) Many of the elements of a condensed SAM can be derved drectly from the nput-output table. Other elements, especally the amounts of varous taxes, requre supplemental nformaton from natonal accounts. A condensed SAM descrbes accountng denttes where the rows represent sources of ncome and columns represent expendtures. For example, the account for households n SGM s wrtten as: LABOR + DIVIDENDS + GTR = PCONS + PIT + SSTAX + PSAV Households receve ncome from labor, dvdends from ownng captal, and government transfers. Household ncome s allocated among consumpton, savngs, and taxes. If we start wth accounts for enterprses, households, government, and captal, the accounts can be arranged to derve the dentty 7

8 PCONS + GCONS + INVEST = LABOR + OVA + IBT + NET_BORROWING or that domestc fnal demand equals natonal ncome plus borrowng. A SAM provdes an accountng snapshot of an economy at one pont n tme. Other data are needed to determne the amount of captal n each vntage durng the model base year. The preferred way to do ths, f data are avalable, s to obtan data on hstorcal nvestment by producng sector and aggregate nto fve-year vntages. Energy Balances Snce the SGM s an energy model as well as an economc model, attenton s pad to mantanng energy balances as the model operates through tme. An energy balance table s used for baseyear calbraton of energy producton and consumpton. An energy balance table s essentally an energy nput-output table n physcal unts. The orgnal unts mght be tons of coal equvalent (Chna), tons of ol equvalent (Internatonal Energy Agency statstcs), or calores (Japan). In the SGM, we convert all energy unts to joules, expressed as ether petajoules 3 (PJ) or exajoules 4 (EJ). The format of a typcal energy balance table s shown n Fgure 2.2. Note that the role of rows and columns s transposed relatve to an nput-output table: the columns contan energy nputs whle the rows contan energy consumpton actvtes. energy nputs (fuels) producton mports exports sources electrcty generaton ol refnng cokng energy transformaton agrculture ndustry transport resdental buldngs commercal buldngs fnal consumpton Fgure 2.2. Structure of typcal energy balance table All SGM regons, wth the excepton of South Korea, produce crude ol, natural gas, coal, electrcty, and refned petroleum. South Korea produces lttle or no crude ol or natural gas. Some regons provde a separate coal products sector (prmarly coke). Most regons nclude a joules joules. 8

9 dstrbuted gas sector. Dstrbuted natural gas s an artfcal sector created n SGM to account for the cost of gas dstrbuton; t s not an actvty n the IEA energy balances. Natural gas s an nput to ths energy transformaton sector; other costs are added for dstrbuton to fnal consumers. Data for the Unted States Here we descrbe the data used to construct a 1990 U.S. nput-output table, 1990 U.S. energy balance table, and a condensed SAM n a format for SGM-USA. Input-Output Table The U.S. Bureau of Economc Analyss (BEA) dstrbutes nput-output accounts for the Unted States at the followng web address. Benchmark transactons tables are avalable for years 1982, 1987, 1992, and We use transactons tables for 1987 and 1992 to construct an nput-output table for SGM-USA. These data are avalable from BEA n the form of use and make tables, wth nformaton on 498 ndustres. See Appendx B of ths document for background on use and make tables and the varous ways they can be combned nto an nput-output table. The followng steps were used to construct a 1990 nput-output table for SGM-USA. Frst, the use and make tables for 1987 and 1992 were aggregated to the SGM set of producton sectors. Second, the use and make tables were nterpolated to year Thrd, the use and make tables were combned nto a commodty-by-commodty table. Ths table for SGM-USA s dsplayed n Appendx C. One ssue wth essentally all economc nput-output tables s that crude ol producton and natural gas producton are treated as a sngle producton sector. We requre these be separate producton actvtes n SGM, and we splt the nput-output data for ths producton sector based on the relatve value of output between crude ol and natural gas. Natonal Accounts Table 2.4 contans the natonal accounts nformaton used to set up SGM-USA n Entres wth a bold label are taken drectly from the U.S. nput-output table. Natonal accounts data are then requred for the followng: corporate ncome taxes, personal ncome taxes, socal securty taxes, government transfers to households, and personal savngs. The remanng entres are determned as resduals to satsfy the accountng constrants that row sums equal column sums. 9

10 Table 2.4. Condensed socal accountng matrx for SGM-USA n Unts are 1990 U.S. dollars. actvtes commodtes prmary factors enterprses households government captal rest of world actvtes GROSS_OUTPUT 9,790,599 9,790,599 commodtes INTERMEDIATE_INPUTS PCONS GCONS INVEST EXPORTS 4,269,660 3,760, , , ,179 10,381,711 prmary factors VALUE_ADDED 5,520,940 5,520,940 enterprses OVA 1,823,076 1,823,076 households LABOR DIVIDENDS GTR 3,248,246 1,068, ,000 5,124,823 government IBT CIT PIT+SSTAX 449, ,500 1,143,300 1,733,418 captal RE PSAV GSAV NET_BORROWING 613, ,300 77,633 47, ,865 rest of world IMPORTS 591, ,112 9,790,600 10,381,711 5,520,940 1,823,076 5,124,823 1,733, , ,112 The relatonshps n Table 2.4 are an abstracton of the U.S. natonal accounts. A full set of natonal accounts would have many more entres, ncludng nterest payments between varous agents. Energy Balances We have two possble sources for energy balances for the Unted States. We could use the U.S. energy balances publshed by the Internatonal Energy Agency, or we could go back to the orgnal source data from the U.S. Energy Informaton Admnstraton (EIA) and construct our own energy balance table 5. We have chosen to develop our energy balances from U.S. DOE/EIA source data. Whle EIA does not publsh an energy balance table, one can construct a table from other data publshed by EIA. Table 2.5 contans such a table, and ths table s used n SGM-USA. Energy consumpton data n Table 2.5 are organzed nto 21 producton sectors for SGM-USA. The three prmary fuels are crude ol, natural gas, and coal. All crude ol goes to the petroleum refnng actvty and s transformed to petroleum products. All natural gas goes to the gas dstrbuton actvty and s consumed by other sectors as dstrbuted gas. Ths dstncton between prmary fuel and dstrbuted fuel provdes a convenent method to account for transformaton and dstrbuton costs; the prce dfferental between prmary and dstrbuted fuels can be large. Most coal goes to electrcty generaton, but some goes to ndustral uses and coke producton. Also note that the energy balance table contans a change n nventory account, whch has no representaton n SGM: ths category s treated as f t were an export n model calbraton. 5 Whle IEA data are derved from DOE/EIA submssons, no full reconclaton s presently avalable. 10

11 Table U.S. energy balances Fuel (petajoules) Crude Natural Refned Dstrbuted Actvty Ol Gas Coal Coke Electrcty Petroleum Gas 1 Ol Producton Natural Gas Producton Coal Producton Coke Producton Electrcty Generaton , ,318 3,041 6 Petroleum Refnng 30, , Natural Gas Dstrbuton 0 19, ,347 8 Grans Anmal Products Forestry Products Food Processng Other Agrculture Paper and Pulp Chemcals ,675 2, Cement, Stone, Clay, Glass Iron and Steel Nonferrous Metals Other Industry ,204 2,842 2, Passenger Transport , Freght Transport , Servces (everythng else) , ,298 Consumpton (prvate) ,326 1,336 4,767 Consumpton (government) Change n Inventory ,612 0 Exports , ,511 0 Imports -13,472-1, ,589 0 TOTAL (domestc producton) 17,462 18,284 23, ,084 31,611 19,454 Data Sources Common to More than One Regon Some of our data sources are used by more than one regon, ncludng energy balances from the Internatonal Energy Agency, and base-year emssons of non-co 2 greenhouse gases. IEA Energy Balances The Internatonal Agency (IEA) publshes energy balances from 1960 through 2003 for countres n the OECD, and from 1971 through 2003 for more than 100 non-oecd countres. Energy balance tables generally have fuels n columns and actvtes (energy producton, transformaton, end-use consumpton) n rows. The IEA tables come n two forms, basc and extended, whch dffer prmarly by the number of columns for fuels. Both tables have data on natural gas and electrcty, but the basc tables aggregate several fuels nto the coal and coal products and petroleum products sectors. Coal and coal products conssts manly of coal, coke, and gases from coal transformaton. Petroleum products conssts of several fuels ncludng motor gasolne, desel fuel, fuel ol, and kerosene. Orgnal unts n the IEA energy balances are tons of ol-equvalent, whch IEA defnes n terms of calores. These data are converted to joules for use n SGM. For the fve countres where SGM was rebult n collaboraton wth researchers n that country, and local energy balances were used nstead of IEA energy balances. 11

12 Non-CO 2 Greenhouse Gases Emssons of the followng non-co 2 greenhouse gases are currently tracked n SGM: CH 4 emssons whch emanate from the producton and dstrbuton of natural gas, mnng of coal, from the rasng of rumnant anmals, the growng of rce, from santary landflls, and from combuston processes (prncpally bomass burnng). N 2 O emssons from combuston processes, fertlzer use, selected natural sources. HFC-23 emssons from the producton of HCFC-22. Short lved HFC emssons from varous uses as substtutes for ozone-depletng substances, ncludng losses from refrgeraton and ar-condtonng equpment, foam blowng, aerosol propellants, cleanng solvents, and fre extngushers. PFC emssons from alumnum and semconductor producton. SF 6 emssons from use n electrcal swtch gear and as a cover gas n magnesum smeltng. In general, the release of CO 2 to the atmosphere s proportonal to the energy content of the specfc fuel by a fxed rato of the energy content of the fuel to the carbon content of that fuel and therefore largely ndependent of the sector or subsector n whch the fossl fuel form s combusted 6. In contrast, emssons of the non-co 2 greenhouse gases are not lmted to fuel use actvtes, and thus ther emssons factors do not represent a stochometrc relatonshp between the output of a sector and actual emssons. In some cases ths s because the relatonshp between emssons and the actual emssons actvty s not stochometrc, n others t s because the actual emssons actvty s much more narrowly defned than the SGM producton sector the emssons are assocated wth. In order to smulate emssons of non-co 2 greenhouse gases, the model calbrates emssons to outsde projectons. Ths s accomplshed through the use of base year emssons factors for each source, and tme dependant adjustment parameters for those emssons factors, that are calbrated to outsde projectons. Regon-Specfc Data Sources We have establshed collaboratons wth nternatonal research nsttutons to assst wth data and model development. At the tme a data set s constructed wth a collaborator, we usually work together at the same locaton for at least two weeks, and sometmes much longer. Table 2.6 provdes a lst of collaboratng nsttutons that helped construct SGM nput data sets. 6 Adjustments are necessary for non-fuel uses of energy products, e.g. plastcs and asphalt. 12

13 Table 2.6. Collaboratng nsttutons for orgnal versons of SGM (1985 and 1990 base years) Regon Insttuton USA -- Canada Unversty of Vctora, Brtsh Columba W. Europe CIRED, Pars, France Japan Natonal Insttute for Envronmental Studes (NIES), Tsukuba Australa/NZ Australan Bureau of Agrcultural and Resource Economcs (ABARE) fsu Moscow Energy Research Insttute E. Europe -- Chna Energy Research Insttute (ERI), Bejng Inda Indan Insttute of Management, Ahmedabad Mexco Colego de Postgraduados, Montecllo, Mexco S. Korea Korea Energy Economcs Insttute (KEEI) Mddle East -- Rest of World -- Notes: More recently, other nternatonal collaboratons have been establshed. The Federal Unversty of Ro de Janero s developng SGM-Brazl wth an extended number of producton sectors. The Mexcan Petroleum Insttute (IMP) s helpng to update SGM-Mexco to more recent base years and to extend the number of producton sectors. The German Insttute for Economc Research (DIW) n Berln has constructed SGM-Germany wth a base year of Versons of SGM-Japan have been constructed wth base years of 1995 and 2000 for recent analyss of clmate polcy n Japan. Here we descrbe the major data sources used for the four countres, other than the U.S., that have an extended set of producton sectors. Data sources for other SGM regons are descrbed more generally. Japan The orgnal nput-output table for Japan n 1990 contans approxmately 500 producton sectors. PNNL was provded wth an aggregated verson of the nput-output table n a spreadsheet. Japan publshes a tme seres of energy balances n two forms: one n orgnal physcal unts and another wth all fuels converted to common unts of calores. The energy balances are qute detaled n terms of fuels and energy consumpton by ndustry. Chna 1990 Input-Output Table of Japan. Energy Balances n Japan, FY. Energy Data and Modelng Center, Japan Insttute of Energy Economcs. Chna publshes benchmark nput-output tables for 1987, 1992, and 1997, but also provdes a smaller table, wth 33 producton sectors, for The table for 1990 was used to construct SGM-Chna. Chna also publshes energy balances, both n terms of physcal unts such as tons (coal), lters (petroleum products), and cubc meters, but also n common unts of tons of coal equvalent. The same publcaton also provdes supplemental tables on energy consumpton by ndustry 13

14 Inda Input-Output Table of Chna 1990, Department of Balances of Natonal Economy and Offce of Input-Output Survey of State Statstcal Bureau, Chna Statstcal Publshng House. Chna Energy Statstcal Yearbook ( ), Department of Industral and Transportaton Statstcs, State Statstcal Bureau, People s Republc of Chna. Chna Statstcal Yearbook on Investment n Fxed Assets ( ) Chna Statstcal Yearbook 1995, State Statstcal Bureau, People s Republc of Chna. Inda s fscal year runs from Aprl 1 through March 31 and annual data are usually provded on a fscal year bass. The basc source for energy balances and energy consumpton s the TERI Energy Data Drectory and Yearbook, publshed annually by the Tata Energy Research Insttute (TERI) n New Delh. Government of Inda, Input-Output Transacton Tables , Central Statstcal Organzaton, New Delh. Tata Energy Research Insttute, TERI Energy Data Drectory and Yearbook, varous ssues, New Delh. Government of Inda, Annual Survey of Industres, Mnstry of Industry, New Delh. Government of Inda, Natonal Accounts Statstcs, Central Statstcal Organzaton, New Delh. South Korea An aggregated verson of 1990 Korea nput-output table was provded to PNNL n a spreadsheet by the Korea Energy Economcs Insttute. Tme seres of energy balance tables s avalable for South Korea. Yearbook of Energy Statstcs 1998, Mnstry of Commerce, Industry and Energy, Korea Energy Economcs Insttute. Other Regons For fve other SGM regons, we combned nput-output tables wth IEA energy balances to construct hybrd nput-output tables, but only two producton sectors outsde of the energy sectors were ncluded. These regons are: Canada, Western Europe, Australa/New Zealand, the former Sovet Unon, and Mexco. In each case, the collaboratng nsttuton lsted n Table 2.6 provded an nput-output table and natonal accounts data. To provde full global coverage n SGM for smulatons of trade n carbon emssons rghts, three other regons were constructed: Eastern Europe, Mddle East, and Rest of World. These models are based prmarly on 1990 energy balances from IEA, but also use natonal ncome accounts and data on consumer expendture from the Unted Natons Statstcal Yearbook. Value shares n 14

15 producton, especally for captal and labor nputs, were carred over from other SGM regons to complete the nput-output table. Unted Natons Statstcal Yearbook 1995, Unted Natons, New York. These models nclude seven producton sectors: agrculture, everythng else, crude ol producton, natural gas producton, coal producton, electrcty generaton, and ol refnng. The everythng else sector ncludes all economc actvty not n the other sx producton sectors. III. Model Calbraton All SGM regons are calbrated to match base-year energy consumpton, carbon emssons, and economc actvty s the current model base year, and one model dagnostc s the comparson between base-year model output and base-year data. We use the term calbraton to refer to the steps needed to ensure that the model reproduces the base-year nput data set. One of these steps s to construct a balanced hybrd nput-output table so that all uses of a commodty equal the sum of all sources, and that the value of output for any commodty equals the cost of producton. Producton functon techncal coeffcents are calculated n the SGM computer code, and are functons of nput value shares n the benchmark hybrd nput-output table. Another step s to set up nvestment functons for each sector to reproduce base-year nvestment levels. Ths secton descrbes constructon of a benchmark nput-output table, calbraton of base-year nvestment, and organzaton of data n calbraton workbooks. Energy Balances and Input-Output Data Ths secton descrbes the constructon of a benchmark nput-output table for an SGM regon. The prmary motvaton s to provde a strct energy accountng n SGM, whch n turn mproves the representaton of carbon doxde emssons. Three types of data are used: an economc nputoutput table n local currency; an energy balance table, and engneerng parameters and costs for electrc generatng technologes. The result s a hybrd nput-output table. The term hybrd refers to hybrd unts n the model nput data and not model structure. All energy flows are n unts of joules, whle real base-year currency (e.g., 1990 US$) s the unt for other goods. The hybrd nput-output table places no restrctons on the form of producton functons n SGM. Mller and Blar (1985) provde a general descrpton of, and the motvaton for usng, hybrd nput-output tables. The basc dea s that energy rows n the hybrd nput-output table are obtaned drectly from energy balances. Ths requres rebalancng other data n the hybrd nput-output table, but energy quanttes are preserved. Base-year model output wll match base-year energy balances. As the SGM steps through tme, energy markets clear n terms of energy quanttes (joules), ensurng energy balance for all model tme steps. Several enhancements can be consdered. The electrcty producton sector can be dsaggregated nto specfc generatng technologes, resultng n extra columns n the use table. Snce an energy balance table s essentally an energy nputoutput table, t can be descrbed n terms of use and make tables just as one does wth an economc nput-output table. Ths procedure also places a burden on the modeler to consder ways that energy-related costs, such as dstrbuton of natural gas, are handled n the benchmark data set. Other efforts to ncorporate energy balances nto economc nput-output tables nclude Malcolm and Truong (1999), and Rutherford and Paltsev (2000). 15

16 Hybrd Input-Output Table The followng steps are used to create a hybrd nput-output table from an economc nput-output table and an energy balance table. a. Put the economc nput-output table n a format sutable for SGM. Ths nvolves aggregaton across producng sectors and possble converson to a 1990 base year. b. Obtan a 1990 energy balance table, convert unts to joules, and aggregate the energy balance table across fuels to match SGM format. Rearrange actvtes (rows) wthn the energy balance table to match those of the economc nput-output table. c. Transpose the energy balance table so that rows correspond to fuel nputs and columns correspond to energy-consumng actvtes. d. Create a hybrd nput-output table where the energy rows (nputs) come from the transposed energy balance table and all other rows come from the economc nput output-table. Ths table s no longer n value terms but s now consdered to be n quantty terms wth unts of joules for the energy rows and unts of 1990 dollars (or other local currency) for all other rows. e. Fnd a set of prces for all ntermedate nputs that wll rebalance the hybrd nput-output table n value terms. By rebalancng, we mean that the value of output n each producng sector s equal to the total value of nputs. A lnear equaton may be derved for each producng sector, resultng n a system of equatons that can be solved to obtan a prce for each ntermedate nput. It s mportant to note that these prces are derved from the calbraton process and are not hstorcal prces (except for exogenous prces such as for crude ol). Ths reflects a modelng phlosophy that assumed technology characterstcs, represented by the nput-output and energy balance data, should determne relatve prces n the model, and not the other way around. Fnally, create a new hybrd nput-output table n value terms by multplyng all quanttes by ther respectve prces. f. We have the opton of redefnng unts for the non-energy nputs n the hybrd nput-output table. We usually redefne these unts so that prces equal 1.0 n the base year, but energy prces can reman n terms of dollars (or other local currency) per unt of energy. The fnal hybrd nput-output table provdes us wth a representaton of the economy that s completely consstent wth base-year energy balances. Energy producton and consumpton for each fuel wll exactly match the quanttes n the base-year energy balance table. Electrcty Generatng Technologes Electrc power generaton s the largest source of global fossl fuel CO 2 emssons. It s therefore treated n detal. Instead of modelng electrcty generaton as an element wthn a larger aggregate sector or even a sngle producton process, the electrcty generatng sector s splt nto several generatng technologes, ncludng gas-turbne, coal-steam, nuclear, and hydro power. The unt of output s klowatt-hours (kwh), and each generaton process contrbutes kwh to total sector output. Economc nput-output tables contan lttle nformaton on specfc generatng technologes, but energy balances provde nformaton on fossl fuel consumpton and kwh generated. Ths s 16

17 supplemented by engneerng cost data wth enough nformaton to construct a levelzed cost, n dollars per MWh or mlls per kwh, of electrcty by generatng technology. These data nclude the purchase prce of captal (dollars per klowatt), energy effcency (as a percentage or as a heat rate), plant factor (fracton of hours n a year that plant s operated), and operaton and mantenance cost (mlls per kwh). Engneerng and costs data for electrc generatng technologes n SGM-USA are dsplayed n Table 3.1. Table 3.1. Engneerng cost assumptons for electrcty generaton subsectors n SGM-USA. Some of the generatng technologes (natural gas combned cycle, pulverzed coal, coal IGCC) are avalable wth or wthout carbon doxde capture and storage (CCS). natural gas coal renewables sngle Parameter unt ol cycle NGCC PC IGCC nuclear hydro wnd Operatng n model base year? yes yes no yes no yes yes no Economc assumptons fuel prce $/GJ nterest rate percent 10% 10% 10% 10% 10% 10% 10% 10% Captal cost purchase cost of captal $/kw ,150 1,401 1,000 1,000 1,200 plant factor percent 20% 40% 75% 75% 75% 75% 75% 20% captal lfetme years nterest plus deprecaton percent 11.7% 11.7% 11.7% 11.7% 11.7% 11.7% 11.7% 11.7% levelzed captal cost mlls/kwh Fuel cost effcency percent 32% 36% 50% 32% 41% fuel cost per kwh mlls/kwh Operatons and mantenance cost mlls/kwh Levelzed cost per kwh (total) mlls/kwh CCS operatonal n base year? no no no capture effcency percent 90% 90% 90% CO2 captured kg-co2/kwh captal cost $/kg-co2/h O & M cost mlls/kg-co energy requred kwh/kg-co Notes: Engneerng and cost assumptons n ths table, especally wth respect to CCS technologes, are generally consstent wth Davd and Herzog (2000). Adjustments were made to the fuel effcency of exstng technologes to mantan compatblty wth base-year energy balances. Durng the base year, we are constraned to mantan consstency between electrcty data n the energy balance table and engneerng descrptons of generatng technologes, especally wth respect to generatng effcency. If they are not consstent, then ether the energy balances or engneerng data are adjusted to make them consstent. Heat rates mpled by the energy balances are a broad average over generatng plants of all vntages and scales of generaton. Engneerng data typcally represent a modern plant wth a specfc generatng capacty. We usually do not modfy data from the energy balance tables: a change n one element of the table requres a change somewhere else n the table to mantan balance. A full hybrd use table, n quantty terms, s descrbed n Fgure 3.1. A use table allows for more actvtes than there are nputs to producton; n ths case there are fve ways to generate electrcty n the base-year use table, but there s only one electrcty nput to other consumpton or producton actvtes. All elements of the hybrd nput-output table (or more accurately, a 17

18 hybrd use table) n Fgure 3.1 are nterpreted as quanttes. Each row, or nput, has an assocated prce whch s used to convert the table to values. commodtes crude ol natural gas coal coke electrcty refned petroleum dstrbuted gas other ndustres ol producton gas producton coal producton joules real dollars coke ol-fred electrcty gas-fred coal-fred joules nuclear real dollars hydro petroleum refnng gas dstrbuton actvtes other ndustres joules real dollars consumer fnal demand government nvestment joules exports real dollars mports factors land labor captal real dollars real dollars real dollars Fgure 3.1. Structure of hybrd use table. Energy rows are n joules; non-energy rows are n unts of real local currency, n ths case dollars. Electrcty generaton technologes are represented as ndvdual columns. Base-Year Calbraton of Investment The SGM operates n fve-year tme steps and keeps track of captal stocks n fve-year vntages. Durng each tme perod, the model converts nvestment for each producng sector nto a captal stock, wth the captal stock defned to be fve year s worth of nvestment. Each type of captal stock has a specfed lfetme, typcally four tme perods or 20 years. At the end of the captal stock lfetme, the captal s retred and no longer used. Captal stocks are operated across ther lfetme wth no decrease n techncal effcency. The SGM nvestment structure has two stages. The frst stage allocates new captal across producton sectors wthn a model tme step, where each producton sector produces a unque product and s assocated wth a unque prce. The second stage allocates sector-level nvestment to subsectors wthn a sector, where each subsector represents a dfferent way to produce the product for that sector. Electrcty generaton s the only producton sector n SGM wth subsectors; each subsector represents a dfferent generatng technology. Sector Level Investment Sector-level nvestment n SGM s governed by one of two nvestment algorthms, ether an nvestment accelerator functon or an output accelerator functon. The functonal form s descrbed n detal n the SGM theory document (Fawcett and Sands, 2005). The level of nvestment depends on several parameters, ncludng an expected proft rate. Investment functons are calbrated n the base year so that (1) calculated nvestment by sector matches hstorcal nvestment by sector; and (2) the expected proft rate equals 1. The prmary nvestment 18

19 calbraton parameter s an nvestment wedge, a sector-specfc adder to the SGM nterest rate. For each sector durng calbraton, the nvestment wedge s adjusted untl the expected proft rate equals 1. 7 The key determnant of nvestment n SGM s the expected proft rate, or rate of return to new captal. If the expected proft rate equals 1, dscounted returns from an nvestment just cover the purchase cost of the captal good. If prce expectatons are myopc (the standard case), an expected proft rate equal to 1 reduces to the condton that prce receved equals levelzed unt cost. The SGM s calbrated so that the expected proft rate equals 1 for each producton sector n the base year. The condton that the expected proft rate equals 1 can be wrtten as fac j p j q P x N 1 j = 1 K K p x = 1 (1a) where P k s the purchase prce of the captal good. The left-hand-sde of equaton (1a) s the expected proft rate; the numerator s the sum of dscounted revenues less varable costs, assumng that future prces are the same as current prces; the denomnator s expendture on captal. The numerator contans a factor, shown n equaton (1b) that sums and dscounts over the lfetme of the captal stock. fac j = T = r j (1b) Equatons (1a) and (1b) show the dependency of the expected proft rate on a sector-specfc nterest rate and on the captal stock lfetme. When preparng data for an SGM nput fle, a calbraton worksheet replcates the calculaton of the expected proft rate for each producton sector n the base year. The role of the nvestment calbraton worksheet s to search over the nvestment wedge untl the base-year expected proft rate equals 1. Therefore, the sector-specfc nvestment wedge s an nvestment calbraton parameter ncluded n the model nput fle. In general, the nvestment wedge vares across producton sectors. Under some condtons, however, nvestment wedges are the same. Investment wedges are the same f two condtons are met: (1) the rato of other-value-added, from the nput-output table, to the quantty of captal n the most recent vntage, s the same and; (2) both types of captal have the same lfetme. Subsector Investment Electrcty generaton s the only SGM sector wth subsectors. Each subsector represents a technology for generatng electrcty. Investment s allocated across generatng technologes accordng to levelzed unt cost (mlls per kwh), wthn a nested logt structure. Each nest has a parameter (lambda) that governs the rate that nvestment shares change n response to changes n levelzed cost. Ths parameter s set exogenously, but another parameter, assocated wth each 7 Wth myopc prce expectatons, an expected proft rate equal to 1 can be shown to be the same as the zero-proft condton where prce = unt cost (Fawcett and Sands, 2005). 19

20 technology (b), s adjusted n the calbraton worksheet so base-year electrcty generaton matches hstorcal data. share = b C j b j λ C λ j (2a) Some SGM regons use an alternatve method for calculatng nvestment shares by subsector. Ths s based on the subsector expected proft rate. In ths case, a subsector-specfc nvestment wedge becomes the nvestment calbraton parameter. s, j, t λ ( E, j, t) ( Eπ kt,,) = π k λ (2b) Each generatng technology, or subsector, has ts own set of captal vntages and operates just lke any other producton actvty n SGM once the quantty of captal for the most recent vntage has been determned. The SGM calbraton workbook contans an engneerng cost descrpton of each technology, from whch the levelzed cost s calculated. SGM-USA contans a large set of electrcty generatng technologes, ncludng carbon doxde capture and storage (CCS). Some of the technologes are actve n the SGM base year, whle others become actve durng later tme steps. Captal Stock Data To start the SGM n ts base year, we requre nformaton on captal stocks by vntage for each producton sector and subsector. Wth a 1990 base year and a captal lfetme of 20 years, we requre four captal stocks whch equal nvestment durng the tme perods , , , and The followng steps are used to create captal stocks for a regon. a. Obtan hstorcal tme seres of nvestment data for each producng sector. b. Ft an exponental curve to the nvestment data for each producng sector. Ths smoothes the effects of recessons or other temporary devatons from a long-term trend. Ths also provdes a way to extrapolate data backwards n tme f the hstorcal seres of nvestment s not long enough to create all of the needed captal stocks. c. Convert nvestment data to real 1990 currency (e.g., 1990 U.S. dollars) usng a tme seres of GDP deflators. d. Sum nvestment by sector across each fve-year tme perod to create captal stocks wth unts of 1990 currency. Fgure 3.2 provdes an example of annual nvestment data avalable for papermakng and paper products sector n Chna. An exponental lne s ft to the hstorcal data for Chna to smooth out the effects of a recesson around The exponental ft also allows us to extrapolate nvestment data backwards to before 1980 when annual nvestment data by sector s not avalable. The smoothed data are summed over fve-year ntervals to create captal stock vntages. 20

21 mllon yuan (1990 yuan) Fgure 3.2. Annual nvestment: paper makng and paper products n Chna If hstorcal data by producton sector are not avalable for a regon, t s not dffcult to construct a seres of captal stocks consstent wth other-value-added data n the nput-output table. One needs only to back out the amount of captal, n the most recent vntage, that s consstent wth other-value-added, equpment lfetme, and the model nterest rate. After that, an assumed rate of declne n the captal stock, from new to old vntages, s used to construct old vntages of captal. Organzaton of Calbraton Workbooks Data for each SGM regon are assemble n two calbraton workbooks, one for creatng the hybrd nput-output table, and the other for all other nput data and calbraton of the nvestment functon. We refer to the frst calbraton workbook as the Hybrd Table Workbook and the second workbook as the Master Calbraton Workbook. Hybrd Table Workbook Worksheets wthn the Hybrd Table workbook have the followng general organzaton. Energy balances. The workbook starts out wth several worksheets contanng energy balances. The frst worksheet contans orgnal energy balances n orgnal unts. Subsequent worksheets convert unts to joules, then aggregate sectors and actvtes to those n SGM, and then brng n supplemental energy consumpton data f needed. Hybrd. Ths worksheet combnes energy balances wth economc nput-output table to create a hybrd nput-output table, usng the methods descrbed earler n Secton III. The fnal result, an nput-output table fully consstent wth base-year energy balances, s then coped from ths worksheet to the Accounts sheet n the Master Calbraton workbook. 21

22 Input-output table. The workbook ends wth one or more worksheets contanng the economc nput-output table. If the nput-output table s already formatted for the SGM, then only one worksheet s needed. However, some further adjustments are usually needed. For example, almost all nput-output tables combne crude ol and natural gas producton nto a sngle sector. These are dsaggregated n SGM nto separate producton sectors. Master Calbraton Workbook Worksheets wthn the Master Calbraton workbook have the followng general organzaton. INPUT_DATA. Ths worksheet contans all the data needed to run an SGM regon, organzed n blocks of data that can be read by the SGM executable. Data n ths worksheet are lnked to other worksheets n the master calbraton workbook. The workbook contans a macro that wrtes ths worksheet to a separate Comma-Separated-Value (CSV) fle that the SGM can read drectly. Accounts. Ths worksheet ncludes an nput-output table and data on natonal ncome accounts. Some natonal accounts data can be obtaned from the nput-output table, but other data must be entered separately. The worksheet also calculates tax rates from the natonal accounts data. Investment. All of the SGM nvestment equatons are duplcated n ths worksheet so that they can be calbrated to match actual nvestment n the base year. Each nvestment equaton has a calbraton parameter, whch s the sector-specfc dscount rate adder (called the nvestment wedge ). The worksheet uses Excel s Solver tool to fnd the dscount rate where the expected proft rate equals 1 for that sector. Use table. The worksheet contans an expanded verson of the nput-output table, wth the electrcty sector dsaggregated nto the varous generatng technologes actve n the base year. Electrcty. Ths worksheet contans engneerng cost data on all of the electrc generatng technologes used n SGM, whether actve n the base year or not. Engneerng data generally come n unts such cents per klowatt-hour or dollars per klowatt, and these are scaled n SGM to the level of a hypothetcal plant. For technologes that operate n the base year, the sze of the hypothetcal plant s determned by base year generaton n the U.S. For technologes that wll become actve after the SGM base year, the sze of the hypothetcal plant s typcally 1,000 megawatts. Fnally, data by hypothetcal plant are converted to a form that can be placed drectly n the use table as a column for each technology. Captal. Ths worksheet contans the amount of captal n each vntage for each producton actvty n the model base year. The unts are real base-year currency (e.g., real 1990 dollars). Populaton. Ths worksheet contans populaton projectons, for both male and female, by fve-year tme step and by fve-year age cohort. IV. Behavoral Parameters Several types of behavoral parameters govern model response to changes n relatve prces. Ths secton covers the followng types of elastctes n SGM: prce elastcty of demand, ncome 22

23 elastcty of demand, substtuton elastcty n producton, savngs supply, and labor supply. In addton, a separate parameter governs the rate that one electrcty technology can substtute for another. We also smulate mtgaton opportuntes for non-co 2 greenhouse gases wth exogenous margnal abatement cost curves. Even though several sources on elastctes were revewed, modeler s judgment plays a sgnfcant role n settng behavoral parameters. There s never a perfect match between the behavoral parameters requred by SGM, and those publshed elsewhere n econometrc studes. Reasons for dfferences nclude: (1) functonal form; (2) treatment of short-run and long-run dynamcs; (3) aggregaton of producton sectors; (4) aggregaton of nputs to producton; (5) estmaton methodology; and (6) adequacy of data used for estmaton. Ths secton documents the actual parameters used n SGM-USA, sources that have nfluenced these parameters, some of the reasonng behnd our judgment, and what we have learned from lmted senstvty analyss. However, the range of elastctes presented n these sources s very wde and they cannot by themselves determne pont estmates for use n SGM. As the SGM s desgned for analyss of alternatve clmate polces, we are partcularly nterested n parameters that determne model response to changes n prces of energy. Therefore, ownprce elastctes of demand for energy goods should be n a range that s supported by the lterature on energy demand. Each CES producton functon n SGM has only one free elastcty parameter, the elastcty of substtuton. Smlarly, each consumer demand equaton n SGM has only one free elastcty parameter. These parameters are set so that the mpled own-prce elastctes of demand for energy are n a plausble range. Model response to a carbon prce s the combned effect of all behavoral parameters, and ths s tested wth a seres of constant-carbon-prce experments. Examples of such prce experments are found n Sands (2004). Key References The followng references revew the lterature on estmates of prce and ncome elastctes of demand for energy and have been used to nsure that behavoral parameter values are wthn the range found n the open lterature: Edmonds (1978), Boh (1981), and Dahl (1993). We have also looked at Ballard et al. (1985) for gudance on the savngs supply elastcty. Recently, staff at Resources for the Future (RFF) asssted wth a survey on energy prce and ncome elastctes for the U.S. and other countres. Ths ncludes household gasolne consumpton n the US (22 studes), electrcty consumpton n US households and ndustry (14 studes), nternatonal gasolne consumpton (6 studes), nternatonal electrcty consumpton (7 studes), and nternatonal petroleum products (3 studes). 8 When SGM-Japan was developed, an effort was made to fnd Japanese data sources on elastctes. One of these, Tokutsu (1994) provdes estmates of substtuton elastctes usng a nested CES producton functon and hstorcal nput-output tables as data. Ths functonal form had three nputs at the top nest: labor, materals, and a captal-energy composte. Although not a perfect match to SGM, the estmates provded gudance for SGM. Elastctes used n the frst 8 The RFF survey provded more recent estmates of energy demand elastctes, ncludng US studes by Branch (1993); Hsnanck and Kyer (1995); Kayser (2000); Taher (2002); and Kamershcen and Porter (2004). Internatonal studes nclude Eltony (1996); Banaszak, Chakravorty, and Leung (1999); Halversen and Larsen (2001); Bjorner, Togeby, and Jensen (2001); Bjorner and Jensen (2002); Gately and Huntngton (2002); and Cooper (2003). 23

24 verson of SGM-Japan are documented n Hbk and Sands (1996). We lack strong gudance as to how elastctes should vary across regons, so elastctes are set to be the same or nearly the same across SGM regons. However, we have conducted a senstvty analyss usng SGM-Inda to see how a doublng of the substtuton elastcty n producton affects response to a carbon prce. Ths has a dramatc effect on the carbon prce needed to meet any partcular emssons target. Consumer Prce and Income Elastctes We frst wrte out the functonal form of the SGM consumer demand system to show the relatonshp between elastctes and demand system parameters. Consumer ncome and prce elastctes are functons of parameters (exponents) n the consumer demand functons, as descrbed by equatons (3a) and (3b). All prces and ncome n equaton (3a) are normalzed by the prce of the numerare good to enforce homogenety of degree zero n prces and ncome. Equaton (3b) ensures that all ncome s expended. x β γ P Y 1 = α (3a) PN PN Γ where P N s the prce of the numerare good and Γ = n = 1 β + 1 γ 1 P Y α (3b) PN PN Elastctes can be wrtten as a functon of the β and γ parameters and the value share S. The own-prce elastcty of demand s ε = β (1 S ) S (4) Note that the own-prce elastcty of demand approaches β as the value share goes to zero. The cross-prce elastcty of demand s ε j = S j ( β j +1) (5) The ncome elastcty of demand s ε m = 1+ γ S γ n k = 1 k k (6) If the value share s small, then the β beta parameter s a good approxmaton of the own-prce elastcty of demand. Values of these parameters, and ther mpled elastctes are provded n Table 4.1. All of the cross prce elastctes are very small wth ths functonal form. Prmary fuels are not consumed drectly, only ndrectly through other products, and therefore elastcty parameters are not requred. 24

25 Table 4.1. Consumer prce and ncome elastctes n SGM-USA parameters elastctes Producton Sector value share beta gamma own-prce cross-prce ncome 1 Crude Ol Producton 0 2 Natural Gas Producton 0 3 Coal Producton 0 4 Coke Producton 0 5 Electrcty Generaton 1.79% Petroleum Refnng 0.15% Natural Gas Dstrbuton 0.60% Grans 0.01% Anmal Products 0.09% Forestry Products 0.05% Food Processng 6.15% Other Agrculture 0.54% Paper and Pulp 0.45% Chemcals 1.89% Cement, Stone, Clay, Glass 0.12% Iron and Steel 0.00% Nonferrous Metals 0.00% Other Industry 11.20% Passenger Transport 1.82% Freght Transport 1.22% Servces (everythng else) 73.91% The parameters n Table 4.1 reflect a constrant on our consumer demand system that, for any par of equatons, the sum of beta and gamma must be equal. Ths constrant s needed to satsfy the Slutsky symmetry condtons. It doesn t matter what beta and gamma sum to, so we mght as well choose zero. From equaton (6), t can be seen that any constant added to each gamma parameter wll cancel. Therefore, only the beta parameters can be set ndependently, and they determne both the own-prce and ncome elastctes. The ncome elastcty always turns out to be approxmately the same magntude as the own-prce elastcty, but of opposte sgn. Substtuton Elastctes for Producers There s a smple relatonshp between the substtuton elastcty and the own-prce elastcty of demand for a non-nested CES producton functon. x p ε = = σ ( S 1) (7a) p x If the nput value share s small, then the own-prce elastcty of demand n equaton (7a) s approxmately the same as the substtuton elastcty, wth a reversal n sgn. Ths holds for any nput to producton and s helpful because we can use estmates of the own-prce elastcty of demand for energy to nform the choce of substtuton elastcty. The cross-prce elastcty of demand s gven n equaton (7b). If the value share of nput j s small, then the cross-prce elastcty s also small. x p = (7b) j ε j = σs j p j x 25

26 Subscrpts for producton sectors have been suppressed n equatons (7a) and (7b), but all substtuton elastctes for SGM-USA are shown n Table 4.2, along wth the nput value shares for energy goods. In most cases, the value share of energy nputs s small, so the elastcty of substtuton provdes a good approxmaton for the own-prce elastcty of demand, wth a change of sgn. Table 4.2. Value shares of energy nputs and substtuton elastctes n producton for SGM-USA nput value shares substtuton elastcty Producton Sector coal electrcty refned ol natural gas long-run short-run 1 Crude Ol Producton 0.0% 0.0% 0.0% 0.0% Natural Gas Producton 0.0% 0.0% 0.0% 0.0% Coal Producton 0.0% 0.0% 0.0% 0.0% Coke Producton 23.5% 0.0% 0.0% 0.0% Electrcty Generaton 14.4% 7.8% 4.8% 6.1% Petroleum Refnng 0.0% 0.0% 6.9% 0.0% Natural Gas Dstrbuton 0.0% 0.0% 0.1% 51.0% Grans 0.0% 0.4% 1.9% 2.7% Anmal Products 0.0% 1.1% 0.5% 0.0% Forestry Products 0.0% 0.2% 0.6% 0.4% Food Processng 0.0% 0.5% 0.1% 0.7% Other Agrculture 0.0% 0.4% 1.4% 1.1% Paper and Pulp 0.2% 1.6% 0.4% 1.6% Chemcals 0.3% 1.9% 2.5% 4.4% Cement, Stone, Clay, Glass 0.5% 6.3% 0.2% 3.3% Iron and Steel 0.0% 2.8% 0.2% 3.4% Nonferrous Metals 0.0% 2.1% 0.1% 2.4% Other Industry 0.0% 0.6% 0.5% 0.5% Passenger Transport 0.0% 0.4% 39.1% 0.0% Freght Transport 0.0% 0.0% 9.0% 0.0% Servces (everythng else) 0.0% 0.5% 0.0% 0.2% The very low substtuton elastctes for electrcty generaton n Table 4.2 ndcate that each electrcty generaton technology s modeled as very close to a fxed-coeffcent technology. However, another parameter governs the rate that nvestment s allocated among new vntages of captal for these technologes. Technology Shft The electrcty sector n SGM s actually a collecton of producton processes that represent dfferent ways of generatng electrcty. A parameter n the logt sharng mechansm, that determnes the nvestment share of generatng technologes, governs the rate that nvestment n one technology can substtute for another as relatve costs change. From equaton (2a) t can be shown that share C share j C j λ = (8) C share C j share j Therefore, the lambda parameter n equaton (2a) s as an elastcty that governs the rate that relatve nvestment shares change n response to changes n relatve unt cost. 26

27 Table 4.3. Technology shft parameters n SGM-USA nest between peak, baseload, and renewable technologes elastcty (λ) -3.0 among baseload fossl fuels -1.5 among renewables -1.5 between fossl technology wth and wthout CCS In the nest where a fossl generatng technology competes wth the correspondng technology wth CCS, the elastcty s set very hgh (n absolute value) so that CCS receves no nvestment wth a zero carbon prce. Other elastctes are selected manly on the bass of senstvty analyss: determnng elastctes that can reproduce hstorcal shares of electrcty generaton wthout movng the calbraton parameters b n equaton (2a) too far away from 1. Labor and Savngs Supply The supply of labor, personal savngs, and retaned earnngs (corporate savngs) are all determned by equatons wth a smlar functonal form. Each equaton has three free parameters, whch allow calbraton to base-year data, but also allow the user to set an upper bound and the supply elastcty. These parameters are summarzed n Table 4.4. Table 4.4. Supply functon parameters. Numercal examples are from SGM-USA. Equaton SGM defnton Base-year rate Upper bound Elastcty labor supply labor partcpaton rate s total maxmum labor employment dvded by workng partcpaton rate s set age populaton (ages 15-64) to 0.8 base year labor partcpaton rate (from 1990 data) equals can be set to any desred elastcty n model base year; however, wage rate ncreases relatve to all other prces over tme and labor partcpaton rate approaches upper bound personal savngs supply personal savngs rate s the rato of personal savngs to (personal ncome plus government transfers less personal ncome taxes) base year rate (from 1990 data) equals maxmum savngs rate s set to 0.4 can be set to any desred elastcty wth respect to nterest rate; presently set to 0.4 retaned earnngs (corporate savngs) retaned earnngs rate s the rato of retaned earnngs to (payments to owners of captal less corporate ncome taxes) base year rate (from 1990 data) equals maxmum retaned earnngs rate s set to 0.8 can be set to any desred elastcty wth respect to nterest rate; presently set to 0.7 The behavor of labor supply over tme s drven manly by the observaton that wages ncrease faster over tme than any other prce n the model, whch drves the labor partcpaton rate to ts upper bound. The labor supply elastcty can be set to any desred value n the base year, but the elastcty s drven to zero as the labor partcpaton rate approaches ts upper bound. The personal savngs supply elastcty s taken from the standard case assumpton of Ballard et al. (1985). The corporate savngs supply elastcty s set hgher prmarly for model stablty: to clear the captal market wthout large varaton n the nterest rate. 27

28 The SGM also has a land supply functon, whch s used n some SGM regons but not n others. 9 It has the same functonal form as the supply functons n Table 4.4, so the user can set an upper bound on the amount of agrcultural land, and can set the elastcty of land supply wth respect to the land prce. The nvestment accelerator functon n SGM has several parameters, ncludng a base rate that represents an antcpated ncrease n nvestment for each sector, all else beng equal. The base rate for SGM-USA s presently set at 1.2, whch mples a 20% ncrease n nvestment over fve years, or 3.7% per year. The other two parameters n the nvestment accelerator functon are exponents on the expected proft rate and on the rato of present to past workng age populaton. Both of these exponents are set to 1. Prce Response for Mtgaton of Non-CO 2 Greenhouse Gas Emssons Emssons reductons for non-co 2 greenhouse gases are accomplshed n two ways n the model. As s the case wth CO 2 emssons, emssons of non-co 2 gases can be reduced by lowerng output from the assocated producton sectors. The second mechansm for non-co 2 emssons reductons s the use of exogenous margnal abatement cost curves. In the presence of a carbon polcy that apples to non-co 2 greenhouse gases, emssons from any partcular source wll be reduced as output from the assocated sector falls, and emssons wll be further reduced by an amount ndcated by the margnal abatement cost curve for that source at the prevalng carbon prce. The U.S. EPA provded, through the Stanford Energy Modelng Forum, a set of margnal abatement cost (MAC) curves for varous emssons actvtes. DeAngelo et al. (2005), DelHotal et al. (2005), and Ottnger et al. (2005), descrbe these margnal abatement cost curves. These MAC curves are mplemented n the model as the percentage reducton n emssons that can be acheved for any gven carbon prce. For a complete descrpton of the equatons used for mplementng the non-co 2 greenhouse gas margnal abatement cost curves n the model, see the companon SGM theory document (Fawcett and Sands, 2005). V. Model Implementaton The SGM contans many other parameters, n addton to behavoral parameters, that affect model operaton. Ths ncludes parameters coverng technologes, government, nternatonal trade, and smulaton of a clmate polcy. Ths secton starts out by descrbng two of the key drvers that determne future scenaros: populaton and techncal change. The secton also provdes a general descrpton of model characterstcs determned by varous swtches, or varables n the model nput fle that are set to ether zero or one. Populaton data The SGM uses populaton data from the Internatonal Data Base (IDB), avalable on the US Census Bureau web ste ( The Internatonal Data Base s a collecton of nternatonal data sources, and can be downloaded to a personal computer. The data used n SGM were extracted n 2000 from the IDB. Populaton data are avalable by country and fve-year age cohort. These are all read nto the SGM as data but and used to 9 SGM-USA does not have a land market at ths tme. 28

29 calculate workng age populaton defned as all resdents between 15 and 64 years of age. Fgure 5.1 provdes a plot of total populaton projectons for some of the larger SGM regons and OECD countres combned bllon people Rest of World Mddle East Inda 2 Chna 1 E. Europe and fsu OECD Fgure 5.1. Populaton projectons used by SGM. OECD ncludes the followng SGM regons: Unted States, Western Europe, Japan, Australa/New Zealand, S. Korea, Mexco. Source: U.S. Census Bureau, Internatonal Data Base. Technology Each vntage of captal stock n SGM s assocated wth a producton functon durng the tme step the captal stock s created. Techncal coeffcents assgned at that tme do not change throughout the lfe of that vntage of captal. However, newer captal can be more effcent than old, and the SGM has a large set of effcency parameters to nfluence the tme path of economc output and energy consumpton. Each nput to the producton functon has an assocated effcency parameter. For energy nputs, ths s analogous to an Autonomous Energy Effcency Improvement (AEEI) parameter. A separate exogenous techncal parameter s avalable for the varous forms of energy, as well as labor, and all other nputs to producton. Further, the rate of change of ths parameter can be vared durng each SGM tme step. All captal stocks n SGM are constructed wth four vntages whch, along wth a fve-year tme step, mply an equpment lfetme of 20 years. Ths four-vntage lmt s actually an artfact of the way the SGM was orgnally coded n Fortran, and wll be relaxed n any new verson of SGM. Although 20 years may be a representatve lfetme for some types of captal, t s too short for others, especally electrcty generatng plants. 29

30 Investment wthn the electrcty generatng sector s allocated across generatng technologes ether by levelzed cost or, n the case of nuclear and hydro, as an exogenous amount of nvestment. The reasonng behnd settng the amount of hydro capacty exogenously s that new hydro resources are lmted, especally n the U.S, and t s better to model hydro capacty on a scenaro bass rather than beng drven by changes n relatve prces. A smlar reasonng apples to nuclear power. There are so many other factors besdes prce affectng nuclear capacty that t s better to treat nuclear capacty on a scenaro bass. The followng generatng technologes are avalable n the SGM base year of 1990: ol-fred, natural gas sngle cycle, pulverzed coal, hydro, and nuclear. After the base year, advanced technologes are avalable ncludng natural gas combned cycle, coal ntegrated gasfcaton combned cycle, wnd, and fossl technologes wth carbon doxde capture and storage. The model user controls whch tme step each new technology becomes avalable. At that tme, new technologes compete wth old for a share of nvestment n electrcty generaton. Government The government n SGM has two prmary roles: to collect and dsperse revenues, and to consume goods and servces. The dfference between all government revenues and expendtures s government savngs, and ths s set exogenously. Government savngs s set n the model base year to match natonal accounts data, but can be vared by the model user n later model tme steps. Therefore, the tme path of government savngs could be set to brng savngs or borrowng to zero over tme. Tax rates (personal ncome tax, corporate ncome tax, socal securty tax, and ndrect busness taxes) are fxed over tme, and are calculated from the benchmark SAM. Base year data for government n SGM are an aggregate of local, state, and federal governments. As a consumer of goods and servces, government demand functons are fxed-coeffcent, where the coeffcents are determned by the benchmark SAM. Internatonal Trade and Foregn Exchange Rates Each SGM regon can be thought of as a small open economy, where some goods are traded and some are not, and each regon faces an exogenous balance of payments constrant. However, the SGM s confgured for endogenous nternatonal trade n only a few goods. The model user can set whch goods are tradable and must supply an exogenous prce path for these goods. For all SGM regons these goods nclude crude ol, natural gas, and the numerare good ( everythng else ). Some regons also treat coal as tradable. For other goods, the amount of trade s fxed at base-year quanttes n all model tme steps and a domestc prce s computed endogenously durng model operaton to clear the market. From a theoretcal pont of vew, these goods behave as non-tradables. Any combnaton of SGM regons can be combned nto a market tradng carbon emssons rghts; the prce of carbon permts s determned endogenously wthn ths market. Exchange rates are needed when a regon faces exogenous prces for crude ol, natural gas, or tradable carbon permts. These foregn exchange rates are set to base-year market exchange rates and are fxed over tme. Even when SGM regons are combned for trade n carbon emssons rghts, each regon stll treats world prces of crude ol and natural gas parametrcally. Ths reflects the dea that one regon, the Mddle East, s a prce setter for crude ol and natural gas, but we don t explctly model ths prce-settng behavor. 30

31 Clmate Polcy and Prce Expectatons Carbon polcy can be smulated domestcally or as one that ncludes nternatonal trade n carbon emssons rghts. A domestc polcy can ether be confgured wth an exogenous tme path of carbon prces, or wth an exogenous tme path of carbon emssons targets. In the case of emssons targets, a carbon prce s computed wthn SGM to clear the domestc carbon market. For a polcy wth nternatonal trade n emssons rghts, two or more SGM regons are lnked together n a carbon market and emssons rghts are allocated across the regons. The model user must set the ntal allocaton of emssons rghts for each regon and tme step. Because each regon faces an exogenous balance of payments constrant, nternatonal purchases of carbon emssons rghts are pad for wth ncreased exports, or reduced mports, of other tradable goods. Carbon prces are appled upstream on prmary fuels: crude ol, natural gas, and coal. Therefore, households and government do not see the carbon prce drectly n ther purchases, but only ndrectly through secondary fuels: electrcty, refned petroleum, and dstrbuted gas. Revenues from the carbon polcy are collected by the government and dstrbuted as a lump sum to consumers. A companon SGM theory document (Fawcett and Sands, 2005) descrbes an elaborate expected proft rate calculaton that can n prncple capture expectatons on future prces, especally energy and carbon prces. Although ths feature of prce expectatons has yet to be used wth any applcaton of SGM, we have been able to explot the vntage structure of SGM to approxmate the dynamcs of carbon prces that are known ahead of tme. For example, say that n 2010 you know that a carbon prce wll be mposed n year 2015 and beyond. Therefore, any captal equpment bult n 2010 wll operate durng part of ts lfetme wthout a carbon prce and part of ts lfetme wth a carbon prce. Durng model operaton we apply a carbon prce n 2010 that s an nterpolaton between the zero carbon prce n 2005 and the known carbon prce n Thus, captal equpment constructed n 2010 reflects an average carbon prce faced durng ts lfetme. System Equatons and Order of Calculaton For each SGM regon, the solver fnds prces that clear markets for nontradable goods, prmary factors of producton, and carbon emssons rghts. Gven these prces, all other model unknowns can be calculated, ncludng allocaton of captal across producng sectors and expendture for government and a representatve household. Ths dffers somewhat from what one would fnd n a typcal CGE model, where the solver would provde tral values for a larger set of core unknowns as shown n Table 5.1. Allocaton of captal would be determned by enforcng zero-proft condtons, and expendture for government and households would be determned through an ncome balance equaton. Instead of an ncome balance equaton, SGM determnes government and household expendture through a careful sequence of calculatons. Once the solver provdes a tral set of prces, the nvestment functons determne the level of actvty n each producng sector. Then derved demands for all nputs to producton are calculated, as well as ndrect busness taxes and drect taxes on prmary factors. Government revenues are calculated, and they help determne government transfers to households. Ths provdes enough nformaton to calculate household expendture. Ths procedure works well for upstream clmate polces, but may not be able to resolve smultanetes between government and households n other scenaros. In that case, the 31

32 obvous remedy s to allow the solver to resolve such smultanetes wth an ncome balance equaton. Table 5.1 Core unknowns and system equatons for a sngle-regon open economy Unknowns SGM Equatons Typcal CGE Equatons prces of nontradables market clearng market clearng rentals of prmary factors market clearng market clearng allocaton of captal across producton sectors (for constantreturns-to-scale producton) nvestment functon (nvestment n each producng sector s a functon of the rate of return, but rates of return are not equalzed across producng sectors) zero-proft condtons (captal s allocated across producng sectors to equalze rates of return) government and household expendture prce of domestc emssons permts determned wth a specfc sequence of calculatons (nvestment, producton, government revenue, government transfers, household ncome) market clearng ncome balance market clearng The numerare good n all SGM regons s the large servces or everythng else sector. Ths provdes the SGM wth some element of prce stablty over tme and helps the user nterpret model output. Tunng to Match a Target Scenaro Some SGM regons are also tuned to roughly match external projectons on energy consumpton and economc output, usually from an offcal government source, from the present to 2020 or beyond. Ths s especally true of SGM-USA, where the Annual Energy Outlook, publshed by the U.S. Energy Informaton Admnstraton, provdes projectons to We use a sequental procedure for baselne calbraton of gross domestc product (GDP), electrcty generaton, and fossl fuel consumpton. Varous techncal parameters are avalable n SGM to nfluence the tme path of model output, especally autonomous tme trends governng the effcency of nputs n producton processes. The frst step n baselne tunng s to match GDP projectons by adjustng an autonomous labor effcency mprovement parameter. The second step s to match projectons of electrcty generaton, n unts of klowatt-hours, by adjustng an autonomous electrcty effcency mprovement parameter n all model actvtes that use electrcty. Thrd, the mx of fossl fuels wthn electrcty generaton s adjusted by varyng the tme path of the cost to produce electrcty usng ol, natural gas, or coal. Fourth, fossl fuel consumpton outsde of electrcty generaton s adjusted usng fossl fuel effcency mprovement parameters n all model actvtes that use fossl fuels. These adjustments n effcency and cost parameters are not ndependent, so the baselne calbraton process s repeated at least once. 32

33 Model Dagnostcs We have developed a set of dagnostcs to test model operaton and to nsure that the model as encoded does n fact conform to the model as theoretcally descrbed n Fawcett and Sands (2005). The two most mportant dagnostc tests are that (1) we can re-create the base-year benchmark data set, and (2) that all of the model s natonal accountng constrants hold n each tme step. 1. Re-create the benchmark data set. As the model s solved n ts base year, we should be able to match the base-year SAM to any desred level of accuracy. Ths s a comprehensve test of all model calbraton procedures, ncludng calculatng techncal coeffcents for all producton functons and consumer demand equatons. 2. Balance of payments dagnostc. Each SGM regon faces an exogenous balance of payments constrant. Ths s mposed as an exogenous captal flow for each regon that affects the level of funds avalable for domestc nvestment. Durng model operaton, trade n crude ol, natural gas, and the numerare sector are all determned endogenously. When we sum the value of net mports across all goods, we should get a trade balance equal to the exogenous captal flow. If not, t usually ndcates that at least one account n SGM s not balanced. Ths s a rather severe test of the model s accountng structure, ncludng whether Walras Law s satsfed. The balance of payments dagnostc s expressed algebracally as pz = D (9a) Where z s the net mport of good, p s the market prce of good, and D s the defct n the balance of payments on goods and servces. Equaton (9a) can be arranged as ( x y ) p = D (9b) or px = D + p y (9c) where x s consumpton of good and y s net output (gross output less that used n other producton processes) of good. For a closed economy, D = 0, and equaton 9b s smply Walras Law. Thus, equaton 9b s smply the generalzaton of Walras Law to an open economy. Equaton 9c reveals that the balance of payments dagnostc s equvalent to the condton that expendture across all consumpton goods s equal to natonal ncome plus exogenous borrowng. Ths relatonshp can also be descrbed n terms of the natonal accounts. In Secton II, we used the accounts n a condensed SAM to derve the dentty PCONS + GCONS + INVEST = LABOR + OVA + IBT + NET_BORROWING or that domestc fnal demand equals natonal ncome plus borrowng. 33

34 References Ballard, C., D. Fullerton, J. Shoven, and J. Whalley A General Equlbrum Model for Tax Polcy Evaluaton. Unversty of Chcago Press. Banaszak, S., U. Chakravorty, and P.S. Leung Demand for ground transportaton fuel and prcng polcy n Asan Tgers: a comparatve study of Korea and Tawan. Energy Journal 20 (2): Bjorner, T.B., and H.H. Jensen Interfuel substtuton wthn ndustral companes: an analyss based on panel data at company level. Energy Journal 23 (2): Bjorner, T.B., M. Togeby, and H.H. Jensen Industral companes demand for electrcty: evdence from a mcropanel. Energy Economcs 23: Boh, D Analyzng Demand Behavor: A Study of Energy Elastctes. Resources for the Future, Johns Hopkns Unversty Press. Branch, E.R Short run ncome elastcty of demand for resdental electrcty usng consumer expendture survey data. Energy Journal 14 (4): Cooper, J.C.B Prce elastcty of demand for crude ol: estmates for 23 countres. OPEC Revew (27):1-8. Dahl, C A Survey of Energy Demand Elastctes n Support of the Development of the NEMS. Prepared of the Unted States Department of Energy. Davd, J. and H. Herzog The Cost of Carbon Capture, n: Proceedngs of the Ffth Internatonal Conference on Greenhouse Gas Control Technologes (CSIRO Publshng, Collngwood, Australa). DeAngelo, B., F. C. de la Chesnaye, R. H. Beach, A. Sommer and B. C. Murray Methane and Ntrous Oxde Mtgaton n Agrculture, Energy Journal (submtted). Delhotal, K.C., F. de la Chesnaye, A. Gardner, J. Bates, and A. Sankovsk Mtgaton of Methane and Ntrous Oxde Emssons from Waste, Energy and Industry, Energy Journal (submtted). Edmonds, J.A A Gude to Prce Elastctes of Demand for Energy: Studes and Methodologes. (ORAU/IEA-78-15(R)), Oak Rdge Assocated Unverstes, Oak Rdge, TN. Eltony, M.N Demand for gasolne n the GCC: an applcaton of poolng and testng procedures. Energy Economcs 18: Fawcett, A. and R. Sands The Second Generaton Model: Model Descrpton and Theory. Pacfc Northwest Natonal Laboratory, PNNL Gately, D., and H.G. Huntngton The asymmetrc effects of changes n prce and ncome on energy and ol demand. Energy Journal 23 (1):

35 Halvorsen, B., and B.M. Larsen The flexblty of household electrcty demand over tme. Resource and Energy Economcs 23 (1):1-18. Hbk, A., and R.D. Sands. December Estmatng the Impact of a Carbon Tax Usng the Second Generaton Model of Greenhouse Gas Emssons for Japan, n Global Warmng, Carbon Lmtaton, and Economc Development, A. Amano ed. Center for Global Envronmental Research, Natonal Insttute for Envronmental Studes, Tsukuba, Japan. Hsnanck, J.J., and B.L. Kyer Assessng a dsaggregated energy nput. Energy Economcs 17 (2): Kamerschen, D.R., and D.V. Porter The demand for resdental, ndustral, and total electrcty, Energy Economcs 26: Kayser, H.A Gasolne demand and car choce: estmatng gasolne demand usng household nformaton. Energy Economcs 22: Malcolm, G., and T.P. Truong. November The Process of Incorporatng Energy Data nto GTAP. GTAP Techncal Paper. Mller, Ronald E., and Peter D. Blar Input-Output Analyss: Foundatons and Extensons. Prentce-Hall, Inc., Englewood Clffs, New Jersey. Ottnger, D., D. Godwn and J. Harnsch Estmatng Future Emssons and Potental Reductons of HFCs, PFCs and SF6, Energy Journal (submtted). Rutherford, T.F., and S.V. Paltsev. February GTAP-Energy n GAMS: The Dataset and Statc Model. Workng Paper No , Department of Economcs, Unversty of Colorado at Boulder. Sands, R.D Dynamcs of Carbon Abatement n the Second Generaton Model. Energy Economcs 26 (4): Scheehle, E. and D. Kruger Global Anthropogenc Methane and Ntrous Oxde Emssons, Energy Journal (submtted). Taher, A.A Energy prce, envronmental polcy, and technologcal bas. Energy Journal 23 (4): Tokutsu, Ichro, Econometrc Analyss of the Structure of Producton. Sobunsha publshng (n Japanese). 35

36 A. Correspondence between SGM Regons and Countres Indvdual countres are lsted below for SGM regons wth more than one country. Australa/NZ: Australa and New Zealand Western Europe: Belgum, Denmark, Fnland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, Netherlands, Norway, Portugal, Span, Sweden, Swtzerland, Unted Kngdom, Turkey former Sovet Unon: Azerbajan, Armena, Belarus, Estona, Georga, Kyrgyzstan, Kazakhstan, Latva, Lthuana, Moldova, Russa, Tajkstan, Turkmenstan, Ukrane, Uzbekstan Eastern Europe: Bulgara, Czech Republc, Hungary, Poland, Romana, Slovena, Slovaka, Serba, Macedona, Croata, Bosna and Herzegovna Mddle East (and North Afrca): Algera, Bahran, Egypt, Gaza Strp, Iran, Iraq, Israel, Jordan, Kuwat, Lebanon, Lbya, Morocco, Oman, Qatar, Saud Araba, Syra, Tunsa, Unted Arab Emrates, West Bank, Yemen Rest of World: other Asa, sub-saharan Afrca, Latn Amerca and Carbbean (except Mexco), Pacfc Islands B. Background on Use and Make Tables Some countres, ncludng the Unted States, provde nput-output data n the orgnal use and make tables. A use table (or nput table) can be combned wth a make table (or output table) to form a sngle nput-output table. Use tables are convenent f there s more than one producton process (or actvty) to create a product. An example n SGM s the electrcty producton sector, wth multple generatng technologes. Make tables are convenent f there are jont products from a producton process. Even though SGM currently has no jont products, t may stll be useful to organze data ths way. A good example s combned heat and power (CHP). Energy balance tables usually have enough nformaton on ths jont product to construct an energy make table. Technques for manpulatng use and make tables can be appled to energy balances as well as economc nput-output data. Methods for Combnng Use and Make Tables Use tables contan one column for each ndustry, wth each row showng the amount of each commodty purchased n a gven year. Make tables contan one row for each ndustry, showng the amounts produced of each commodty. Therefore, use tables have dmensons of commodtyby-ndustry and make tables are ndustry-by-commodty. Because of jont producton, output by ndustry s dfferent than output by commodty, and row sums do not equal column sums n the use or make tables. There are at least four ways to combne use and make tables nto a sngle nput-output table where row sums match column sums. We can create ether commodty-by-commodty or ndustry-by-ndustry tables. Further, each of these two types of tables can be constructed usng commodty-based or ndustry-based technology assumptons. None of ths would be necessary f 36

37 each ndustry produced only one commodty. In that case the make table would be dagonal, provdng no new nformaton beyond the use table. Commodty-Based Technology. Each commodty s produced usng the same value shares of nputs, regardless of what ndustry produced the commodty. Industry-Based Technology. A commodty s produced usng nput value shares that are an average across the ndustres producng t. The assumpton of commodty-based technologes s dffcult to work wth because a matrx nverson s requred, often yeldng negatve nput-output coeffcents. Computaton of nputoutput tables usng the assumpton of ndustry-based technologes s much smpler, wth no negatve coeffcents. For the SGM, we have constructed commodty-by-commodty nput-output tables usng the assumpton of ndustry-based technologes. (Ths s the same way that the Indan government combnes ts use and make tables.) Commodty-by-commodty tables are preferred because the unts of output are pure, and not a mx of commodtes. Each column n the resultng nput-output table s actually a hypothetcal ndustry that produces just one commodty. The use table was post-multpled by a normalzed make table to obtan a commodty-by-commodty nput-output table. Constructng a Commodty-by-Commodty Table Let U be a commodty-by-ndustry use matrx wth the same number of columns as ndustres. Let g be a vector of producton values by ndustry. V s an ndustry-by-commodty make matrx. An nput-output table based on ndustry technology s created usng the matrx equaton T = Ug ˆ 1 V where $g s a dagonal matrx wth the elements of g on the dagonal and zeros everywhere else. Some notaton wll be set up to show why ths works. Let be the value share of nput n the output of ndustry k, whch s equal to the element n the -th row and k-th column of a normalzed use matrx Ug $ 1. Let v kj be an element of the ndustry-by-commodty make matrx V. s an ndex that runs through all nputs, ncludng value added. k s an ndex for ndustres and j s an ndex for outputs. Indvdual elements of the nput-output table are gven by where t j t j = k s k v kj s the amount of nput used n the producton of output j. Let k be any ndustry that produces some of output j. Then v kj s k s the amount of output j produced by that ndustry. The amount of nput requred by ndustry k s gven by s k v kj. Do the same for all ndustres that produce any of output j and sum to get the total amount of nput used n the producton of output j. 37

38 Fnal-demand vectors reman unchanged by these calculatons, and can be appended to the derved nput-output table. Note that ths procedure wll work even f there are more ndustres than commodtes. Postmultplyng by a normalzed make table s a way to convert nformaton categorzed by ndustry to a commodty categorzaton. Ths can be appled to all nput rows of the use table as well as energy consumpton data where the rows are fuels and the columns are ndustres. C. US Hybrd Input-Output Table Tables C.1, C.2, and C.3 provde the commodty-by-commodty US nput-output table used n SGM-USA. The table s splt nto three sectons for readablty: columns 1-10, columns 11-21, and the fnal demand columns. Ths table s n value terms wth unts of mllon 1990 US dollars. Table C.1 contans addtonal nformaton, n the far left column, that can be used to convert the energy rows from values to energy quanttes. If values n the energy rows of the table (mllon dollars) are dvded by the energy prces n the far left column (dollars per ggajoule), then energy quanttes can be derved (petajoules). Table C.1. US hybrd nput-output table (columns 1-10) n 1990 US dollars. $ per GJ Crude Ol N. Gas Coal Coke Electrcty Ref. Petr. Dst. Gas Grans + Anm. Prd. Forestry Crude Ol , Natural Gas , Coal , Coke Electrcty , , Refned Petroleum ,559 9, , Dstrbuted Gas , ,439 1, Grans ,089 22, Anmal Products , Forestry Products Processed Food , Other Agrculture ,094 4,014 1,951 Paper and Pulp Chemcals , , Cement, Stone, Clay, Glass Iron and Steel Non-ferrous Metals Other Industry 18 1,096 1,148 2, ,848 2,828 4,577 2,673 2, Passenger Transport , Freght Transport , ,738 6, ,144 3, Servces (everythng else) 21 9,551 10,000 2, ,939 14,188 6,214 12,340 11, Labor va1 9,789 10,249 8,412 2,000 26,285 9,046 9,740 1,561 3,928 1,183 Captal (other value added) va2 15,436 16,162 5, ,043 9,251 16,356 23,083 9,885 1,794 IBT (ndrect busness taxes) va3 2,058 2,155 2, ,218 6,837 4,495 2,220 1, Total 40,059 41,943 22,611 3, , ,330 92,962 57,315 89,443 7,516 38

39 Table C.2. US hybrd nput-output table (columns 11-21) n 1990 US dollars. Food Proc. Other Ag. Paper Chemcals Cement + Iron, Steel NF Metals Other Ind. Passenger Freght ETE Crude Ol Natural Gas Coal Coke , Electrcty 5 3, ,668 9,516 7,201 3,589 2,271 24,674 1, ,167 Refned Petroleum , , ,989 69,830 22,137 2,368 Dstrbuted Gas 7 2, ,969 11,227 1,916 2,158 1,301 10, ,980 Grans 8 19, Anmal Products 9 69,394 1, Forestry Products , Processed Food 11 61, , , ,638 Other Agrculture 12 12,116 8, , ,334 Paper and Pulp 13 11,813 1,330 56,484 4,612 1, , ,157 Chemcals 14 3,981 4,405 9,785 65,850 2,551 1,321 1,568 62, ,028 Cement, Stone, Clay, Glass 15 4, ,123 7,139 1, , ,681 Iron and Steel , , Non-ferrous Metals ,584 19,542 42, Other Industry 18 21,774 2,607 13,908 18,188 5,728 7,467 6, ,492 6,531 14, ,184 Passenger Transport 19 2, ,477 1, ,351 12,357 6,260 32,293 Freght Transport 20 8,964 1,040 7,106 8,083 4,165 2,887 2,408 35,871 3,707 35,514 30,290 Servces (everythng else) 21 46,575 8,938 23,341 41,715 6,798 12,698 11, ,937 26,392 46,233 1,137,363 Labor va1 51,466 17,885 43,107 50,293 17,473 17,071 11, ,626 40,371 75,956 2,179,061 Captal (other value added) va2 55,597 22,000 30,415 58,979 10,576 5,231 3, ,289 11,847 36,366 1,143,283 IBT (ndrect busness taxes) va3 9,077 1,177 2,067 3, ,806 5,595 6, ,702 Total 385,188 72, , ,955 67,610 73,035 62,278 2,280, , ,990 5,399, Table C.3. US hybrd nput-output table (fnal demand) n 1990 US dollars. C fd1 G fd2 I fd3 X fd4 M fd5 Total Producton Crude Ol ,905 40,059 Natural Gas ,895-3,818 41,943 Coal , ,611 Coke , 538 Electrcty 5 68,185 15, ,711 Refned Petroleum 6 5,635 1, ,171-19, ,330 Dstrbuted Gas 7 22,780 3, ,962 Grans , ,315 Anmal Products 9 3, ,595 89,443 Forestry Products 10 2,011-1, ,516 Processed Food ,708 8, ,758-20, ,188 Other Agrculture 12 20,560 1, ,257-9,169 72,040 Paper and Pulp 13 17,104 3,754 2,935 15,707-18, ,874 Chemcals 14 71,841 12,348 1,261 39,115-32, ,955 Cement, Stone, Clay, Glass 15 4, ,446-7,578 67,610 Iron and Steel ,028-11,174 73,035 Non-ferrous Metals ,504-9,350 62,278 Other Industry , , , , ,603 2,280,611 Passenger Transport 19 69,193 11,874 1,684 28,404-8, ,523 Freght Transport 20 46,444 7,374 3,180 27, ,990 Servces (everythng else) 21 2,807, ,812 57, ,006-77,462 5,399,882 Total 3,799, , , , ,773 39