iaere presentation v03b · iaere conference 2016 – working paper presentation enrico botta, univ....
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ENVIRONMENTAL REGULATION AND DIRECTION OF TECHNOLOGICAL CHANGE
IAERE Conference 2016 – Working Paper Presentation
Enrico Botta, Univ. degli Studi di Milano
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The impact of environmental regulation is widely discussed in the literature
The traditional view on environmental polices is opposed to the Hypothesis put forward by Porter and van der Linde
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The Porter’s Hypothesis has been articulated into three more narrowly defined “forms”
• The assumptions of perfect markets with fully rational agents are rejected, as such firms are not operating at the maximum possible efficiency.
Strong version
• Firms will innovate in order to comply with the new regulation in the most cost effective manner.
Weak version
• Flexible environmental policy regimes are more likely to increase innovation and improve company performance.
Narrow version
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• Main studies on green innovation and environmental regulation:
– Jaffe and Palmer (1997) – Johnstone et all (2010) – Rubashkina et al. (2015)
• Limited panel data
• Few studies assessing jointly both market and non-market based regulation.
The narrow and weak version
Impact on green innovation
• ..but what happens to “grey innovation” ? – Aghion et al. (2016)
Impact on grey innovation
?
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– A more stringent environmental regulation should steer innovation away from “polluting” technologies and towards green technologies
– The direction of technological change is affected by the cumulated knowledge stock
– Market based regulation provide dynamic incentives and therefore stimulate higher rates of green innovation
Our main working hypothesis is that the direction of technological change is driven by two key factors
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• Intro • The model
Index
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The following empirical model is developed to test the hypotheses set out above:
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The following empirical model is developed to test the hypotheses set out above:
• a common measure of innovation worldwide and used to mitigate issues with the quality of inventions
• Aggregate into three main groups: green energy technologies, other green technologies and not-environmental related innovation.
Triadic patents
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The following empirical model is developed to test the hypotheses set out above:
• It covers 26 OECD countries over the years 1990-2012. • It combines information on 15 environmental policy (both
market based and not-market based) instruments. • Instruments not related to the energy sector are excluded
OECD index
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The following empirical model is developed to test the hypotheses set out above:
Overall Environmental Regulation of the Energy Industry
Not market-based instr.
FiT Taxes R&D sup ELVs
Market-based instr.
Trading schemes
N.B. information on not energy related regulation instruments has been dropped
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The following empirical model is developed to test the hypotheses set out above:
• The law of motion of knowledge is calculated using the perpetual inventory method (Verdolini & Galeotti, 2011. Coe and Helpman,1995)
• a separate variable for the knowledge stock of each type of technology. Both foreign and domestic knowledge stocks considered
Knowl. stock
know_stocktech,it=innotech,it+(1-δ) * knowstocktech,it-1
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The following empirical model is developed to test the hypotheses set out above:
• GDP per capita
• Liberalization of the energy sector Controls
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Econometric estimation
A. Hausman, Hall and Griliches (HHG)
B. Blundell, Griffith and Van Reenen (PSM)
C. Blundell, Griffith and Van Reenen & IHS (IHS)
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• Intro • The model • Results
Index
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Green patents -‐ HGG
Green patents -‐ PSM
Green patents – PSM & IHS
Grey patents -‐ HGG
Grey patents -‐ PSM
Grey patents – PSM & IHS
EPS 0.138*** -0.00729 0.0367 -0.0808*** -0.0601*** -0.0605*** (0.0516) (0.0521) (0.0564) (0.0280) (0.0232) (0.0231)
log_ksgreen_energy 0.316*** 0.583*** 0.394*** 0.176*** 0.193*** 0.196***
(0.119) (0.152) (0.136) (0.0492) (0.0473) (0.0455)
log_ks_other_green 0.737*** 0.795*** 0.547*** -0.0504 -0.0905 -0.0953 (0.237) (0.225) (0.210) (0.1000) (0.0823) (0.0819)
log_ks__grey -0.764*** -0.579** -0.681*** 0.380*** 0.503*** 0.506*** (0.254) (0.266) (0.254) (0.107) (0.106) (0.105)
Lag3.lforei._KS_ge 3.653*** 0.558* 0.739* -0.454* -0.115 -0.119 (0.725) (0.303) (0.420) (0.247) (0.143) (0.143)
Lag3.lforei._KS_go 2.755*** 1.242** 0.870 -0.550 -0.361 -0.366 (0.729) (0.558) (0.603) (0.388) (0.260) (0.259)
Lag3.lforei._KS_grey -6.089*** -1.443** -1.390* 0.697 0.237 0.240 (1.173) (0.279) (0.279)
etcr2_ele -0.104*** -0.0838** -0.0998** -0.00443 0.0333** 0.0330** (0.0392) (0.0414) (0.0412) (0.0183) (0.0139) (0.0139)
lgdp_pc -1.446* 0.591 -0.147 -0.133 -0.395* -0.404* (0.841) (0.449) (0.484) (0.367) (0.226) (0.226)
lPSM 0.0518 0.522** 0.289*** 0.286*** (0.205) (0.223) (0.0742) (0.0726)
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Green patents -‐ HGG
Green patents -‐ PSM
Green patents – PSM & IHS
Grey patents -‐ HGG
Grey patents -‐ PSM
Grey patents – PSM & IHS
EPS_Market 0.0955** 0.0613 0.0873* 0.00866 0.00297 0.00325 (0.0404) (0.0465) (0.0448) (0.0252) (0.0210) (0.0210)
log_ksgreen_energy 0.385*** 0.533*** 0.399*** 0.137*** 0.160*** 0.165***
(0.114) (0.144) (0.124) (0.0472) (0.0459) (0.0442)
log_ks_other_green 0.816*** 0.842*** 0.580*** -0.0329 -0.0616 -0.0651 (0.237) (0.226) (0.206) (0.100) (0.0841) (0.0836)
log_ks__grey -0.844*** -0.654** -0.715*** 0.376*** 0.474*** 0.477*** (0.254) (0.280) (0.252) (0.108) (0.109) (0.108)
Lag3.lforei._KS_ge 3.231*** 0.547* 0.657* -0.346 -0.118 -0.119 (0.719) (0.330) (0.397) (0.245) (0.140) (0.140)
Lag3.lforei._KS_go 2.851*** 1.213** 0.857 -0.622 -0.460* -0.462* (0.741) (0.576) (0.603) (0.394) (0.261) (0.260)
Lag3.lforei._KS_grey -5.775*** -1.444** -1.329* 0.772 0.317 0.316 (1.139) (0.611) (0.706) (0.567) (0.280) (0.280)
etcr2_ele -0.106*** -0.0888** -0.0979** -0.000299 0.0334** 0.0332** (0.0396) (0.0411) (0.0410) (0.0183) (0.0140) (0.0140)
lgdp_pc -0.960 0.622 -0.0985 -0.530 -0.494** -0.502** (0.799) (0.455) (0.468) (0.349) (0.225) (0.224)
lPSM 0.113 0.532** 0.309*** 0.304*** (0.212) (0.219) (0.0743) (0.0727)
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Green patents -‐ HGG
Green patents -‐ PSM
Green patents – PSM & IHS
Grey patents -‐ HGG
Grey patents -‐ PSM
Grey patents – PSM & IHS
EPS_nonmarket 0.0690* -0.0413 -0.0305 -0.0772*** -0.0611*** -0.0616*** (0.0401) (0.0346) (0.0390) (0.0185) (0.0164) (0.0164)
log_ksgreen_energy 0.337*** 0.629*** 0.483*** 0.201*** 0.212*** 0.214***
(0.123) (0.140) (0.142) (0.0494) (0.0477) (0.0457)
log_ks_other_green 0.707*** 0.758*** 0.477** -0.0491 -0.0656 -0.0713 (0.239) (0.220) (0.201) (0.0991) (0.0820) (0.0818)
log_ks__grey -0.741*** -0.570** -0.609** 0.366*** 0.460*** 0.462*** (0.259) (0.252) (0.243) (0.105) (0.106) (0.105)
Lag3.lforei._KS_ge 3.676*** 0.547* 0.605* -0.544** -0.158 -0.168 (0.761) (0.279) (0.353) (0.247) (0.157) (0.160)
Lag3.lforei._KS_go 2.687*** 1.276** 0.878 -0.609 -0.332 -0.340 (0.744) (0.553) (0.575) (0.387) (0.262) (0.263)
Lag3.lforei._KS_grey -5.951*** -1.458*** -1.271** 0.735 0.213 0.220 (1.206) (0.555) (0.639) (0.538) (0.292) (0.295)
etcr2_ele -0.104*** -0.0826** -0.0949** -0.00166 0.0341** 0.0336** (0.0392) (0.0407) (0.0413) (0.0179) (0.0139) (0.0139)
lgdp_pc -1.337 0.573 -0.0762 0.0125 -0.322 -0.331 (0.858) (0.439) (0.446) (0.356) (0.241) (0.241)
lPSM 0.0422 0.467** 0.284*** 0.283*** (0.191) (0.220) (0.0749) (0.0736)
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Green knowledge flows across national boundaries but slower
Grey patents -‐ PSM
Grey patents – PSM & IHS
Grey patents -‐ PSM
Grey patents – PSM & IHS
Grey patents -‐ PSM
Grey patents – PSM & IHS
EPS -0.0493** -0.0506** EPS_market 0.0130 0.0143 EPS_nonmarket -0.0603*** -0.0639***
log_ksgreen_energy 0.105** 0.127*** 0.0817* 0.102** 0.117** 0.139***
log_ks_other_green -0.144* -0.136* -0.0979 -0.0912 -0.137* -0.133* log_ks__grey 0.568*** 0.573*** 0.535*** 0.539*** 0.543*** 0.544*** lforei._KS_ge -0.499* -0.445* -0.442* -0.404* -0.727** -0.729** lforei._KS_go -0.751** -0.694** -0.733*** -0.691*** -0.813*** -0.780*** lforei._KS_grey 0.707* 0.635* 0.666** 0.613** 0.818** 0.779**
etcr2_ele 0.0215 0.0212 0.0211 0.0207 0.0200 0.0182 lgdp_pc -0.186 -0.184 -0.291 -0.291 -0.0296 0.00196
lPSM 0.366*** 0.336*** 0.367*** 0.341*** 0.368*** 0.334***
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• Intro • The model • Conclusion
Index
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• The estimations suggest that environmental policy stringency does drive the direction of technological efforts
• Market and non-market instruments behave differently in relation to type of innovation considered.
• Path dependency.
• Measures to favour inflow of green technology might be a tool to stimulate green innovation when designing more stringent regulations prove to be politically challenging
Three main conclusions
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• Thank you