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))

Kyle S. Herman, Jun Xiang

Research output: Contribution to journalComment/debatepeer-review

Abstract

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.

Original languageEnglish (US)
Article number119858
JournalTechnological Forecasting and Social Change
Volume151
DOIs
StatePublished - Feb 2020

All Science Journal Classification (ASJC) codes

  • Business and International Management
  • Applied Psychology
  • Management of Technology and Innovation

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