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Context & motivation Evidence on business cycles & CO2 emissions Policy Implications Business Cycles & CO2 Emissions Baran Doda Grantham Research Institute, LSE 26 March 2015 Green Growth and the New Industrial Revolution [email protected] Green Growth and the New Industrial Revolution Context & motivation Evidence on business cycles & CO2 emissions Policy Implications Context & motivation We know relatively little about the relationship between uctuations in GDP and CO2 emissions. The nature of the relationship is important for making sure theoretical models resemble the real world carbon pricing policy instruments in practice [email protected] Green Growth and the New Industrial Revolution Context & motivation Evidence on business cycles & CO2 emissions Policy Implications Context & motivation We know relatively little about the relationship between uctuations in GDP and CO2 emissions. The nature of the relationship is important for making sure theoretical models resemble the real world carbon pricing policy instruments in practice [email protected] Green Growth and the New Industrial Revolution Context & motivation Evidence on business cycles & CO2 emissions Policy Implications Research topic 1. What are the key properties of uctuations in GDP and CO2 emissions in a given country? Cyclical Components 1950 1960 1970 GDP 1980 1990 2000 2010 Emissions .02 emis 0 −.02 −.06 14 13.4 −.04 13.6 14.5 GDP 15 13.8 EMIS 14 15.5 .04 14.2 16 .06 US GDP & Emissions Time Series & Trend Components −.04 −.02 0 gdp .02 2. Is there a systematic relationship between these properties and GDP per capita? (Annual data from 122 countries covering 1950-2011) [email protected] .04 Green Growth and the New Industrial Revolution Context & motivation Evidence on business cycles & CO2 emissions Policy Implications Research topic 1. What are the key properties of uctuations in GDP and CO2 emissions in a given country? Cyclical Components 1950 1960 1970 GDP 1980 1990 2000 2010 Emissions .02 emis 0 −.02 −.06 14 13.4 −.04 13.6 14.5 GDP 15 13.8 EMIS 14 15.5 .04 14.2 16 .06 US GDP & Emissions Time Series & Trend Components −.04 −.02 0 gdp .02 2. Is there a systematic relationship between these properties and GDP per capita? (Annual data from 122 countries covering 1950-2011) [email protected] .04 Green Growth and the New Industrial Revolution Context & motivation Evidence on business cycles & CO2 emissions Policy Implications Business cycle properties of emissions FACT 1: Emissions are procyclical in a typical country. Table FACT 2: Procyclicality of emissions is greater in countries with higher GDP per capita. Table Figure FACT 3: Emissions are cyclically more volatile than GDP in a typical country. Table FACT 4: Cyclical volatility of emissions is greater in countries with lower GDP per capita. Table Figure a [email protected] Figure b Green Growth and the New Industrial Revolution Context & motivation Evidence on business cycles & CO2 emissions Policy Implications Business cycle properties of emissions FACT 1: Emissions are procyclical in a typical country. Table FACT 2: Procyclicality of emissions is greater in countries with higher GDP per capita. Table Figure FACT 3: Emissions are cyclically more volatile than GDP in a typical country. Table FACT 4: Cyclical volatility of emissions is greater in countries with lower GDP per capita. Table Figure a [email protected] Figure b Green Growth and the New Industrial Revolution Context & motivation Evidence on business cycles & CO2 emissions Policy Implications Business cycle properties of emissions FACT 1: Emissions are procyclical in a typical country. Table FACT 2: Procyclicality of emissions is greater in countries with higher GDP per capita. Table Figure FACT 3: Emissions are cyclically more volatile than GDP in a typical country. Table FACT 4: Cyclical volatility of emissions is greater in countries with lower GDP per capita. Table Figure a [email protected] Figure b Green Growth and the New Industrial Revolution Context & motivation Evidence on business cycles & CO2 emissions Policy Implications Business cycle properties of emissions FACT 1: Emissions are procyclical in a typical country. Table FACT 2: Procyclicality of emissions is greater in countries with higher GDP per capita. Table Figure FACT 3: Emissions are cyclically more volatile than GDP in a typical country. Table FACT 4: Cyclical volatility of emissions is greater in countries with lower GDP per capita. Table Figure a [email protected] Figure b Green Growth and the New Industrial Revolution Source: World Bank (2014) Context & motivation Evidence on business cycles & CO2 emissions Policy Implications What are the facts good for? Implications for xed instruments: Carbon tax =⇒ emissions uncertainty Emissions trading system =⇒ cost uncertainty Improving instrument performance Indexed regulation [email protected] Green Growth and the New Industrial Revolution Context & motivation Evidence on business cycles & CO2 emissions Policy Implications What are the facts good for? Implications for xed instruments: Carbon tax =⇒ emissions uncertainty Emissions trading system =⇒ cost uncertainty Improving instrument performance Indexed regulation [email protected] Green Growth and the New Industrial Revolution Context & motivation Evidence on business cycles & CO2 emissions Policy Implications How to price carbon in good times...and bad! Two broad policy implications: 1) Making the stringency of regulation responsive to economic uctuations can decrease overall burden of regulation. 2) Whatever instrument is chosen to price carbon, it should apply to as large a group of emitters as possible. Linking previously independent ETSs can mimic responsive regulation and lead to overall gains. However, country-specic gains are not assured. [email protected] Green Growth and the New Industrial Revolution Context & motivation Evidence on business cycles & CO2 emissions Policy Implications How to price carbon in good times...and bad! Two broad policy implications: 1) Making the stringency of regulation responsive to economic uctuations can decrease overall burden of regulation. 2) Whatever instrument is chosen to price carbon, it should apply to as large a group of emitters as possible. Linking previously independent ETSs can mimic responsive regulation and lead to overall gains. However, country-specic gains are not assured. [email protected] Green Growth and the New Industrial Revolution Context & motivation Evidence on business cycles & CO2 emissions Policy Implications How to price carbon in good times...and bad! Two broad policy implications: 1) Making the stringency of regulation responsive to economic uctuations can decrease overall burden of regulation. 2) Whatever instrument is chosen to price carbon, it should apply to as large a group of emitters as possible. Linking previously independent ETSs can mimic responsive regulation and lead to overall gains. However, country-specic gains are not assured. [email protected] Green Growth and the New Industrial Revolution Context & motivation Evidence on business cycles & CO2 emissions Policy Implications Conclusions Business cycle properties of emissions dier across countries. Climate change policy design and performance can be improved by conditioning policy on business cycle uctuations cross-country dierences in business cycle properties of emissions other country characteristics [email protected] Green Growth and the New Industrial Revolution Business Cycles & CO2 Emissions Baran Doda Grantham Research Institute, LSE 26 March 2015 Green Growth and the New Industrial Revolution Email: [email protected] Table: Cyclicality of emissions Mean Std. Dev. Min Max Sample ρ̄ey 0.297∗∗∗ 0.244 −0.305 0.824 Full (N=122) ρ̄ey 0.260∗∗∗ 0.229 −0.305 0.725 Restricted (N=89) Notes: A bar over a variable indicates a sample mean. The null hypothesis that ρ̄ey is equal to zero tested against a two-sided alternative in each case, where * implies p<0.10, ** implies p<0.05, and *** implies p<0.01. Table: Cyclicality of emissions across countries Value Sample ρ(ρey , GDPpc2009 ) 0.327∗∗∗ Full (N=122) ρ(ρey , GDPpc2009 ) 0.359∗∗∗ Restricted (N=89) Notes: The null hypothesis that ρ(ρey , GDPpc2009 ) is equal to zero tested against a two-sided alternative in each case, where * implies p<0.10, ** implies p<0.05, and *** implies p<0.01. Table: Volatility of emissions Mean Std. Dev. Min Max σ̄e 0.078 0.064 0.018 0.358 σ̄y 0.029 0.018 0.006 0.109 σ̄rel 3.040∗∗∗ 2.492 0.701 17.221 σ̄e 0.068 0.051 0.018 0.285 σ̄y 0.023 0.011 0.009 0.081 σ̄rel 3.082∗∗∗ 2.197 1.019 15.258 Notes: Sample Full (N=122) Restricted (N=89) A bar over a variable indicates a sample mean. In the last row of each panel the null hypothesis that σ̄rel = 1 is tested against the alternative that σ̄rel > 1, where * implies p<0.10, ** implies p<0.05, and *** implies p<0.01. Table: Volatility of emissions across countries Value Sample ρ(σe , GDPpc2009 ) −0.220∗∗ Full (N=122) ρ(σe , GDPpc2009 ) −0.316∗∗∗ Restricted (N=89) ρ(σrel , GDPpc2009 ) −0.203∗∗ Full (N=122) ρ(σrel , GDPpc2009 ) −0.235∗∗ Restricted (N=89) Notes: The null hypothesis that a given correlation coecient is equal to zero is tested against a two-sided alternative in each case, where * implies p<0.10, ** implies p<0.05, and *** implies p<0.01. 1 Figure: Procyclicality of emissions increases with GDP per capita (Fact 2) BIH RUS LTU KGZ CHN BRA ALB .5 PER GEO Cyclicality (ρey) NGA IDN MKD MOZ PHL PAK MDG UZB DOM IRQ POL KAZ THA URY MYS HUN BGR SVN BEL GBR AUT FRA ITA DEU AUS TWN CHE PRT CIV MLI TZA MDA GTM TJK AGO DZA TKM ZAF BHR LKA BFA UGA ZWE BOL ECU KHM ETH COL SAU OMN IRN TUN BGD TTO VENQAT ARE LCA SEN SWE NOR BRB MAR NER HKG SYR SDN VNM MLT −.5 CMR 6 LUX SGP DNK JOR IND GHA ISL CAN KOR ISR NLD NZL FINIRL ESP GRC CRI MWI ZMB 0 LVA CYP KWT ARM CZE ARG CHL SVK MEX JAM YEMMMR EGY COD EST BLR HRV AZE TUR UKR KEN USA JPN ROU 8 Log GDP per capita in 2009 (GDPpc2009) Note: 3−letter country codes in red denote members of the full but not the restricted sample. Regression line drawn for the full sample. 10 .4 Figure: Volatility of emissions decreases with GDP per capita (Fact 4) ARE .3 QAT KHM .2 OMN SGP GEO KWT TTO SAU AGO BHR BFA BIH NGA TJK ETH LCA IRQ SEN MDG .1 CIV NER TZA COD ZMB ZWE MWI MLI KEN UGA BGD GHA ALB SYR KGZ YEM JAM ARM SDNDZAMDA ECU CHN VNM MLT BRB MOZ MMR LKA DOM URY TKM CRI BOL FIN VEN EST IDN CYP EGY ISL LTU DNK JOR THA MAR MYS ISR GTM PER AZE BGR CHE HKG UKR PHL ROU IRL SWE LVACHL TUN TWNAUT NOR KAZ SVK MKD KOR UZB NLD ESPNZL TUR BEL FRA PRT JPN HUN ARG GRC MEX COL BRA CZE SVN HRV POL BLR ITA DEUGBR ZAF AUS USA CAN RUS PAK IND 0 Volatility (σe) IRN CMR 6 8 Log GDP per capita in 2009 (GDPpc2009) Note: 3−letter country codes in red denote members of the full but not the restricted sample. Regression line drawn for the full sample. 10 LUX Relative volatility of emissions decreases with GDP per capita (Fact 4) 20 Figure: 10 CMR TZA SGP ARE TTO BHR LCA KHM LKA 5 BFA JAM MDG ETH SEN CIV BGD COD NER ZMB MWI ZWE KEN MLIUGA SAU QAT IRN ECU BRB NOR GTM MLT DNK FRA EGY VNM SWE FIN MMR ALBGEO BEL CRI OMN CHE AUT MAR IRL UZB CHN NLD MOZ COL DOM PHL URY JPN IDN SYRTHAMYS KGZ DZA ARM KWT ESPISR TWN ISL AUS BGR PRT VEN GRC ITA ZAF SDN MDA PAK MKD HUN DEUGBR TKM ROUPER TUN CZE CAN HKG NZL KAZ SVK USA BIH JOR BRA MEX CHL SVN TUR ESTKOR CYP POL UKR ARG LTU IND HRV LVA AZE RUS BLR BOL TJK NGA AGOGHA IRQ 0 Relative volatility (σrel) 15 YEM 6 8 Log GDP per capita in 2009 (GDPpc2009) Note: 3−letter country codes in red denote members of the full but not the restricted sample. Regression line drawn for the full sample. 10 LUX
