TY - JOUR
T1 - Corrigendum to “Induced innovation in clean energy technologies from foreign environmental policy stringency?” (Technological Forecasting & Social Change (2019) 147 (198–207), (S0040162518305894), (10.1016/j.techfore.2019.07.006))
AU - Herman, Kyle S.
AU - Xiang, Jun
N1 - Publisher Copyright:
© 2019 Elsevier Inc.
PY - 2020/2
Y1 - 2020/2
N2 - The authors regret and apologize for a data collection error for several variables in Table 1, which occurred while the lead author was compiling the data. The authors have re-estimated the three models in Table 1 based on the corrected data, and the corrected results are reported next to the original results in the table below. In short, corrections are made for discussing the regression results of control variables in section 4.2. Based on the corrected data, domestic environmental market-policies are statistically significant in all three models rather than only in the third model. While institutional quality demonstrates a puzzling finding in the original table (i.e., negative and statistically significant coefficients), it now becomes statistically insignificant. Likewise, after changing from negative to positive, electricity production from renewable energy now becomes consistent with the expectation. On the other hand, the high technology exports variable switches from positive to negative, and fossil fuel consumption changes from negative to mostly insignificant. Moreover, R&D expenditure is now negative and statistically significant. The results of these three variables are both surprising and interesting. Since country fixed effects are not estimated in Table 1, the Stata command xi: xtreg, i.year, fe presented in the original article needs to be dropped. Finally, due to some missing observations, two countries are not included in the analysis. In conclusion, despite of these changes based on the corrected data, the findings of our main variable foreign environmental market-policies hold strongly. The authors would like to apologize for any inconvenience caused.
AB - The authors regret and apologize for a data collection error for several variables in Table 1, which occurred while the lead author was compiling the data. The authors have re-estimated the three models in Table 1 based on the corrected data, and the corrected results are reported next to the original results in the table below. In short, corrections are made for discussing the regression results of control variables in section 4.2. Based on the corrected data, domestic environmental market-policies are statistically significant in all three models rather than only in the third model. While institutional quality demonstrates a puzzling finding in the original table (i.e., negative and statistically significant coefficients), it now becomes statistically insignificant. Likewise, after changing from negative to positive, electricity production from renewable energy now becomes consistent with the expectation. On the other hand, the high technology exports variable switches from positive to negative, and fossil fuel consumption changes from negative to mostly insignificant. Moreover, R&D expenditure is now negative and statistically significant. The results of these three variables are both surprising and interesting. Since country fixed effects are not estimated in Table 1, the Stata command xi: xtreg, i.year, fe presented in the original article needs to be dropped. Finally, due to some missing observations, two countries are not included in the analysis. In conclusion, despite of these changes based on the corrected data, the findings of our main variable foreign environmental market-policies hold strongly. The authors would like to apologize for any inconvenience caused.
UR - http://www.scopus.com/inward/record.url?scp=85075972610&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85075972610&partnerID=8YFLogxK
U2 - 10.1016/j.techfore.2019.119858
DO - 10.1016/j.techfore.2019.119858
M3 - Comment/debate
AN - SCOPUS:85075972610
SN - 0040-1625
VL - 151
JO - Technological Forecasting and Social Change
JF - Technological Forecasting and Social Change
M1 - 119858
ER -