Evaluation with stylized facts
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(2) Content. Fundamental laws and stylized facts. Systematic evaluation of IAMs with stylized facts. Evaluating AMPERE models with stylized facts. Stylized conclusion and outlook.
(3) From fundamental laws to observable deep-order patterns Natural Science: Controlled experiments confirm fundamental laws.. F =G. m1 m2 r2. Example from Newton, 1686. Social Science (and coupled complex systems): Uncontrolled observations suggest some stylized patterns. 1 1 Sch1 Hneg Zneg 1 1 1 1 4 ib a c A B C ↑ W 4 L1 ↓ V 1 Sch1 H 1 Z 9 = R 4 × 3 sch7 H 7 Z 9 Example from Propp, 1928. Definition of stylized fact: Kaldor 1961 (Economic Growth Theory), Buchanan 2012 (Complex Social Systems).
(4) Systematic evaluation of IAMs with stylized facts. Proposal for a community-wide list of stylized facts. Criteria for selection: I. Evaluation value: acceptance, relevance, endogenous and exogenous model results, transperancy. I. Completeness: capturing important system processes and scales. I. Applicability: to a broad class of IAMs of global climate change.
(5) Identifying relevant system processes.
(6) Use of PIRT-Tables PIRT - Phenomena Identification and Ranking Tables. .
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(40) Proposal: List of stylized facts Focus on endogenous and quasi-endogenous model results I. Economic development SF 1: Consumption ∝ economic growth SF 2: Economic growth ∝ investment. I. Energy transition SF 3: Output intensity of final energy ∝ 1/(per capita income) SF 4: Consumption of primary energy per capita ∝ per cap income SF 5: Share of residential sector in FE ∝ 1/per capita income. U-shape relationship for industry share. Service sector share ∝ per capita income. Agriculture is small. SF 6: Increasing share in modern energy technologies, solids decrease at the same time.. I. Energy transition/Climate change SF 7: Trend towards decarbonization.. I. Technological change SF 8: Extent of technology diffusion ∝ duration of tech diffusion SF 9: Spacial acceleration of technology diffusion..
(41) Testing stylized facts in AMPERE models: Two examples.
(42) Testing stylized facts: Consumption and GDP Acemoglu 2: Correlation between consumption and GDP data from PWT 7.0, year: 2000 5. linear regression, slope: 0.89 linear regression, slope: 1.03. log ( per capita consumption ). 4.5. USA JPN EUR USA. ISL GBR CHE NOR BMU AUT NLD CAN AUS GER SWE FRA DNK BEL JPN ITA IRL ARE HKG ESPFIN BHS GRC NZL PLW BRB TWN MLTISR PRT PRI SGP KWT CYPSVN BRN CZEKOR BHR MAC HUN KNAPOLSVK GRD LBN MEX SYC TTO URY EST LTU ARG HRV TUR JAM MHL BLZ CRI LCA BIHTON LVA CUB BRA CHL SAU MKDDOM ATG OMN SLV WSMBGR MUSRUS LBY ROM GTM COL BLR ZAF PAN VEN MYS MNE IRN PER KAZTHA ECU DMA FJI EGY PRY VUT TUN ALB NAM JOR BWA GAB SWZ VCT FSMUKR BOL ARMGEO AZE GUY HND SYR LKA CPV IDN KIR DJI PHL MAR TKMDZA MDA NIC SUR PAK HTI SDN BTN CH2 KGZ MDV MNG CMR INDYEM LSO CHN LAO SENCIVVNM PNG STPKEN MRT KHM TJK BEN UZB TLS IRQ NPL BGDNGA COM GHA TGO GNQ MDG BFA UGA TZA ZMB MLI GMB SLB GIN COG AGO ERI SLE CAF RWA LBR. 4. ROW. LUX. QAT. LAM RUS. 3.5. OAS. MEA. IND CHN. 3. AFR. MOZ NER GNB BDI ETH AFG MWI SOM. 2.5 ZAR. 2. 2. TCD. ZWE. 2.5. 3. 3.5 log( per capita GDP ). 4. 4.5. 5.
(43) Testing stylized facts: Consumption and GDP IMAGE, AM3S1. log per capita consumption [$2005 PPP]. 6. 5.5. RUS CHN UKR RSAM STAN SEAS RCAMBRA RUS NAF CEU SAF USA UKR INDIAINDO CAN CHN ME MEX RSAM JAP TURKOR STAN World WEU USAOCE SEAS RSAS RCAM RUS BRA CAN CEUSAF JAP METURMEX UKRNAF INDIA WEU USA OCE INDOKOR CHNWorld RSAM RSAF CAN STAN CEU JAP EAF USA OCE RCAM MEXWAF WEU SAF TUR BRA MERSAS. 5. 4.5 UKR. 4. NAF. SEAS NAF KOR World CAN INDIA RUS OCE CEU INDO RSAF WEU JAP. EAF RSAM MEX RCAM TUR BRA ME SAF. RSAS SEAS CHN RSAF STAN EAF WAF INDO. WAF KOR. World. INDIA. RSAS RSAF. 3.5 EAF. 3. 3. WAF. 3.5. 4 4.5 5 log per capita GPD [$2005 PPP]. 5.5. 6.
(44) Testing stylized facts: Consumption and GDP IMACLIM, AM3S1. log per capita consumption [$2005 GDP]. 6. 5.5 CAN JANZ. USA JANZ FSU RAL EUR USA CHN FSU. 5. CAN. CAN JANZUSAEUR RAL MEA. 4.5. FSUUSA World BRA EUR RAS MEA. BRA. RAS World. MEA CHN IND. RALJANZCAN World CHN BRA EUR MEA. 4. IND. RAS AFR. RAL FSU World AFR. IND. BRA RAS. 3.5. AFR CHN. AFR IND. 3. 3. 3.5. 4 4.5 5 log per capita GDP [$2005 PPP]. 5.5. 6.
(45) Testing stylized facts: Consumption and GDP MESSAGE, AM3S1 5 PAO NAM WEU PAO NAM. log per capita consumption [$2005 PPP]. WEU NAM PAO LAM EEU CPA WEU PAS NAM FSU MEA World. 4.5. LAM PAOCPA EEU WEU FSU PAS SAS World MEA CPA EEU FSU AFR LAM World SAS EEU. 4. MEA PAS. AFR FSU World SAS LAM MEA PAS AFR. 3.5. CPA. SAS. AFR. 3. 3. 3.5. 4 log per capita GDP [$2005 PPP]. 4.5. 5.
(46) Testing SF (extensive): Transition of energy structure Energy transition - structure. projections by REMIND. World - historical data (1800-2000) 100 Grids (electricity, gases, heat, hydro). FE structure [% of total FE]. 80. LIQUIDS. 60. 40. EMF27G1. EMF27G17. 20. 0 1800. SOLIDS (coal, biomass, trad. biomass). 1850. 1900. 1950. EMF27G9. 2000. 2050. EMF27G1 EMF27G17 EMF27G9. 2100.
(47) Testing SF (intensive): Transition of energy structure data from ENERDATA and PWT 6.3 1. share of solids in final energy consumption. BDI COD BTN COD NPL BDI BTN BTN TZA BDI TZA MOZ BDI MOZ TZA NPL COD NER BTN NPL NPL TZA LAO NGA MOZ NER NGA LAO NGA NER NER NGA LAO. XYZ 1990. VNM MOZ HTI ZMB KEN ZWE ZWE HTI SDN MDG CHN KEN SDN ZMBZWE KEN ZMB SWZ ZWE KEN ZMB HTI LAO VNMLKA MWI HTI SDNCHN MDG SDN GTM SWZ MWI IND MWI MWI SWZ SWZ. 0.8. XYZ 1995 XYZ 2000 XYZ 2005. MDGVNM MDG BGD LKA HND IND CHN GTM LKA BWA GTM HND LKA IND SLV CHN IND BGD PAK IDN SEN VNM BWA. 0.6. FJI GTM PHL BWA PAK IDN SLV ZAF HND SEN PAK ZAF SEN BGD FJI IDNSLV CUB IDN CUB POL ZAF FJI BIHALB BWA MUS SLV MNG CRI TUR ZAF PHL COL MNG. SEN HND BGD PAK. 0.4. THA. CZE. BRA CUB. BOL DOM ALB PHL PAN POLBRA FJICOL BRA PER PHL DOM CHL POL MUS GEO TUR SVK TUR KAZ. 0.2. 0. LUX. BOLGEO THA BRA URY KAZ CZE CUB CHL COL LVA PER PAN BIH SVK LVA LVATUR CZE POL THA PAN PER THA KAZ PER FIN AFG MNG PAN KOR CHL FIN MRTBOL BIH FIN COL MRT BIH URY PRT CHL EST IRL MKD DOM BOL UKR UKR CRI SVK MNG CZE FIN AFG SVK PRT UKR AUT AFG MKD DOM ROU MRT KGZ EST SWE SRBCRI SWE URY SWE SWE DEU AUT ROU ESTBGR ALB HUN AUT URYTWN TUN BGR LTU GEO LTU BEL JPN AUT AFG TUN TUN NZL PRT AUS NZL AUS MKD MYSEST TWN ROU MAR JPN MUS GRC FRATWN AUS SVN TWN NZL TUN BGR JPN JPN LTU KOR KOR KOR NZL ALB ESP RUS MAR KGZ JAM ROU HRV MEX HUN GRC PRT MEX JAM JAM FRA SVN IRL BEL SVN AUSNOR MUS CRIMEX MYS BGR BEL MYS FRA FRANOR GRCGBR RUS MAR MYS SVN JAM MEX DEU MDA DEU ESP LBNMKD DEU BLRHUN RUS DNK EGY CAN KGZEGY LBN LBN USA BEL BLR HRV RUS CAN CAN MDA CAN DNK GRC HRV BLR HRV IRL GBR ARG HUN CYP DNK MDAEGY DNK CHE LBN ESP MAR CHE CHE USACHE ARG ARG ESP CYP EGY ITA NLD ITA NLD ISL NLD GBR VEN ITA ITA ARG ISL UZB GBR NLD DZA DZA CYP ISL VEN CYP DZADZA VEN IRN IRN IRN IRN HKG UZB UZB HKG HKG UZB ARM MAC ISR MAC MAC ISR SGP ISR SGP ARM AZE ARM SYR ISR SYR SYRAZE AZE SYR SGP. 0. 20000. LUX. NOR NOR HKG IRL USA ISL. USA. MAC AREARE SGP. ARE. LUX LUX ARE. 40000 per capita GDP [$2005 PPP]. 60000. 80000.
(48) Testing SF (intensive): Transition of energy structure AM3S1 AFR EAF. REMIND 2100 REMIND 2070 REMIND 2040 REMIND 2010 POLES 2100 POLES 2070 POLES 2040 POLES 2010 MESSAGE 2100 MESSAGE 2070 MESSAGE 2040 MESSAGE 2010 IMAGE 2100 IMAGE 2070 IMAGE 2040 IMAGE 2010 IMACLIM 2100 IMACLIM 2070 IMACLIM 2040 IMACLIM 2010. 0.8 RSAF. share of solids in final energy. SSAF IDT WAF. EAF. 0.6. AFR. SASCHN CHN INDIA NDECHN IND CHN. CHN. AFR CPA. 0.4. CHN. SAF AFR RCAM SEAS OAS KOR SSAF IDT EAF TUR CHN RJAN IDT BRA RASIA NDE BRA CEAM IDT World MIEA IDT USA CHN COR JPN World OAS INDPAS INDIA RJAN RSAM INDIA OCIS IDT RSAMJAP WRD World TUR IDT RASIA IDT OCIS IDT BRA TUR IDT UKR WRD World WAF WRDUKR World IDT RSAS CPA LAM USA WRD IDT World World IND EEU COR RSAS EU15 IDT RSAM EU12 IDT EU12 IDT JAP IND ROW CEAM IDT RUS UKR SSAF IDT OCIS IDT CEU RJAN TUREU12BRA IDT AFR SAS EU15 IDT CHN CAN RCAM AFR World CAN CHN RCEU IDT SAF CHN INDIA KOR EU12 IDT JPN RCAM SSAF IDT MIEA IDTIDT RCEU IDT CEURSAFWorld EEU TUR RASIA IDT JPN BRA RCEU IDT EU15 NDE RUS WAF TUR SAF OCIS IDT PAS LAM EEU RSAS TUR COR World World JAP MEX IND JPN CEAM IDTNOAF IDT EEU EAF CEAM IDT IND RCEU IDT WEU World CAN World COR KOR RCAM FSU CHN RSAM TUR RUS CAN KOR SEAS CPA CEU LAM RJAN RAS World USA NOAF IDT BRA NAFRSAM JAP FSU INDO RASROWE PAS JANZPAO CEU World INDO IDT JPN PAS CAN JANZ ROWRSAF RASSAS PAOLAM BRA MEXSAFROWE IDTCHN PAO World RUSOCE STAN PAO World RAS NOAF IDT EUR ROWE IDT NDE BRA MEX SEAS AFR OCE JANZ BRA OCE MEX JPN FSUMEA STAN AFR AFR USA LAM UKR BRABRA FSU JPN USA JPN RSAM World IDT EUR RSAM NAF WEUFSU RUS AFR MIEA OAS FSU BRA RUS CAN NAM EU15 IDT CHN CAN FSU AFR RUS RUS INDO EUR ROWE IDT WEU SEAS WEU ROW ROW JANZ RUS STAN IND NAM RSAM OCE RUSWEU NAFUSA USA USA USA World NAF SAS NAM NOAF IDT CAN CHN LAM STAN USA EUR USA RAL LAM RUS OAS LAM USA NAM MEA ME RAL CAN EURUSAWEU RUS USA World RAL WEUEUR RAL MEA USA USA CAN INDCAN MEA MEA ME WEU ME AFR ME CPA EUR CAN EUR MEA MEA MEA MIEA IDT MEA MEA MEA MEA FSU. 0.2. 0. CHN. RSAF RSAS INDO WAF RASIA IDT. 0. 50000. 1e+05 1.5e+05 per capita GDP [$2005 PPP]. 2e+05.
(49) Testing SF (intensive): Transition of energy structure AM3S1 AFR EAF. REMIND 2100 REMIND 2070 REMIND 2040 REMIND 2010 POLES 2100 POLES 2070 POLES 2040 POLES 2010 MESSAGE 2100 MESSAGE 2070 MESSAGE 2040 MESSAGE 2010 IMAGE 2100 IMAGE 2070 IMAGE 2040 IMAGE 2010 IMACLIM 2100 IMACLIM 2070 IMACLIM 2040 IMACLIM 2010. 0.8 RSAF. share of solids in final energy. SSAF IDT WAF. EAF. 0.6. AFR. SASCHN CHN INDIA NDECHN IND CHN. CHN. AFR CPA. 0.4. CHN. SAF AFR RCAM SEAS OAS KOR SSAF IDT EAF TUR CHN RJAN IDT BRA RASIA NDE BRA CEAM IDT World MIEA IDT USA CHN COR JPN World OAS INDPAS INDIA RJAN RSAM INDIA OCIS IDT RSAMJAP WRD World TUR IDT RASIA IDT OCIS IDT BRA TUR IDT UKR WRD World WAF WRDUKR World IDT RSAS CPA LAM USA WRD IDT World World IND EEU COR RSAS EU15 IDT RSAM EU12 IDT EU12 IDT JAP IND ROW CEAM IDT RUS UKR SSAF IDT OCIS IDT CEU RJAN TUREU12BRA IDT AFR SAS EU15 IDT CHN CAN RCAM AFR World CAN CHN RCEU IDT SAF CHN INDIA KOR EU12 IDT JPN RCAM SSAF IDT MIEA IDTIDT RCEU IDT CEURSAFWorld EEU TUR RASIA IDT JPN BRA RCEU IDT EU15 NDE RUS WAF TUR SAF OCIS IDT PAS LAM EEU RSAS TUR COR World World JAP MEX IND JPN CEAM IDTNOAF IDT EEU EAF CEAM IDT IND RCEU IDT WEU World CAN World COR KOR RCAM FSU CHN RSAM TUR RUS CAN KOR SEAS CPA CEU LAM RJAN RAS World USA NOAF IDT BRA NAFRSAM JAP FSU INDO RASROWE PAS JANZPAO CEU World INDO IDT JPN PAS CAN JANZ ROWRSAF RASSAS PAOLAM BRA MEXSAFROWE IDTCHN PAO World RUSOCE STAN PAO World RAS NOAF IDT EUR ROWE IDT NDE BRA MEX SEAS AFR OCE JANZ BRA OCE MEX JPN FSUMEA STAN AFR AFR USA LAM UKR BRABRA FSU JPN USA JPN RSAM World IDT EUR RSAM NAF WEUFSU RUS AFR MIEA OAS FSU BRA RUS CAN NAM EU15 IDT CHN CAN FSU AFR RUS RUS INDO EUR ROWE IDT WEU SEAS WEU ROW ROW JANZ RUS STAN IND NAM RSAM OCE RUSWEU NAFUSA USA USA USA World NAF SAS NAM NOAF IDT CAN CHN LAM STAN USA EUR USA RAL LAM RUS OAS LAM USA NAM MEA ME RAL CAN EURUSAWEU RUS USA World RAL WEUEUR RAL MEA USA USA CAN INDCAN MEA MEA ME WEU ME AFR ME CPA EUR CAN EUR MEA MEA MEA MIEA IDT MEA MEA MEA MEA FSU. 0.2. 0. CHN. RSAF RSAS INDO WAF RASIA IDT. 0. 50000. 1e+05 1.5e+05 per capita GDP [$2005 PPP]. 2e+05.
(50) To do: Stylized fact about a brain’s capacity to process information within a 20 min talks??? Stop here..
(51) Testing stylized facts: Investments and GDP Dosi SF data from PWT 7.0, year: 2005 5 QAT. linear regression, slope: 1.09, correlation coefficient: 0.96 linear regression, slope: 0.98, correlation coefficient: 0.97 ISL KWT NOR AUS SGPARE MAC BHS HKG CHEUSA IRL BHR BEL CAN DNK KOR JPN AUT SYC ESPFIN BMU TTO SVN ITA BRB TWNFRASWE NLD NZL GRD OMN GBR SAU BRN PRT ISRGRC GER KNA EST CZE ATG MHL CYPMLT PRI LVAHRVSVK HUN LBN LCA BWA GNQ CHL KIR PLW GAB MYSMEX LTU IRN POL MDV CRI JAM THA MUS KAZ BGR BTN JOR CHN CH2 ARG RUS TUR LBY BLZ DZA URY BLR VEN SRBROM VCT ECUCOL ZAF ALB TUN TON PAN DMA AZE BRA CPV BIH PERMKD DOM IRQ MARFSM NAM VUT GTM MNE MRT UKR GEO ARM SLV LKA MNG HND VNM IDNSYR FJI IND YEM GUYEGY WSM PRY LAONIC SWZ STP MDA SEN UZB DJIPHL SDN COG BOL AGO PNG PAK BGDZMB GMB GHA NPL TCD KHMCMR LSO CUB GIN TZA BEN TKM SLB MLI MWI AFG KGZ UGAKEN TLS HTI BFA MDG ERI NER TGO COM ETH RWA CIV TJK NGA MOZSLE SOM. 4 log ( per capita investment ). LUX. USA JPN EUR. SUR. ROW. CHNMEA RUS LAM OAS. 3. IND. AFR. 2. GNB ZAR. BDI LBR. CAF. ZWE. 1. 2. 2.5. 3. 3.5 log ( per capita GDP ). 4. 4.5. 5.
(52) Testing stylized facts: Investments and GDP EMF27G1, year: 2020 4 linear regression, slope: 0.86, correlation coefficient: 0.95 log ( per capita ESM investments ). 3.5 USA. 3 ROW RUS MEA. 2.5. EUR JPN. CHN. LAM OAS IND. 2 AFR. 1.5. 1. 3. 3.5. 4 log ( per capita GDP ). 4.5. 5.
(53) Testing stylized facts: Development of FE/cap over population FE/POP vs POP MEA historic aggregate EMF27G1 EMF27G9 EMF27G17 QAT. 600. per capita Final energy consumption [GJ]. 200 150. 500. 100 400. 50 0. 0. 0.2. 0.4. 0.6. 300. 200. 0.8. OMN TJK GEO SYR KAZ YEM DZA AZE ISR LBN LBY UZB SAU ARM JOR TUN IRN KWT BHR MAR EGY TKM ARE KGZ. 100. 0 0.0001. 0.001. 0.01 Population [billions]. 0.1. 1.
(54) Testing stylized facts: Development of FE/cap over GDP/cap FE/POP vs GDP/POP EUR 350. 300 per capita Final energy consumption [GJ]. historic aggregate EMF27G1 EMF27G9 EMF27G17 ROU GRC DEU AUT BGR MLT SVK LUX ITA LTU FRA EST CYP LVA GBR SVN IRL BEL POL FIN SWE HUN DNK PRT NLD ESP CZE ANT. 1970 - 2100. 250. 200. 150. 100. 50. 0. 0. 20000. 40000 per capita GDP [ PPP D 2005 ]. 60000. 80000.
(55) Testing stylized facts: Distribution dynamics of PE intensity.
(56) Testing stylized facts: Substitution of energy technologies Primary energy consumption, Fisher-Pry plot, EMF27G17 world, data from BP 2011, Smil, and WEO 2. 10. oil, own, BP 2011 coal, own, BP 2011 gas,own, BP 2011 nuclear, own, BP 2011 hydro, own, BP 2011 oil, Smil coal, Smil gas, Smil nuclear, Smil hydro, Smil biofuels, Smil oil, WEO coal, WEO gas, WEO nuclear, WEO hydro, WEO biofuels, WEO coal, EMF27G1 oil, EMF27G1 gas, EMF27G1 nuclear, EMF27G1 biofules, EMF27G1 hydro, EMF27G1 wind, EMF27G1 solar, EMF27G1 geothermal, EMF27G1. 1. 10. 0. 10. f/(1-f). -1. 10. -2. 10. -3. 10. -4. 10. -5. 101800. 1900. 2000 years. 2100. 2200.
(57) Testing stylized facts: Distribution dynamics of carbon intensity Dynamic distribution of carbon intensity of FE 0.07. 0.04 Efficiency Mix Supply. 0.03. 0.06 0.05 0.04. 0.02. 0.03 2010. 0.01. 2040. 0.02 0.01. 0 -200. -100. 0. 100. 200. 0 -200. -100. 0. 100. 200. 0.03. 0.08. 0.025 density. 0.06 0.02 0.04. 0.015 2070. 2100. 0.01. 0.02 0.005 0 -200 -100 0 100 200 deviation from average / average in 2005. 0 -200. -100. 0. 100. 200.
(58) Stylized outlook - What can be done should be done Possible ex-ante using stylized facts to evaluate IAMs of global climate change: I. educated opinion formation about future developments. I. systematic questioning of model behavior (incl. model inter-comparison). I. community list of stylized facts could serve as a criteria for model quality. Only possible ex-post validating forecasting power: Marquardt 1981 citing O’Neills 1975 I. 2005 Establishing first Marsian mines. I. 2040 100 000 people living on Mars.
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