E STIMATION RESULTS FOR E UROPEAN OIL AND GAS COMPANIES

The estimated results for European oil and gas companies are summarized in Table 7. We see that all models are statistically significant at the 1% level, except for the TGI estimation of model 2. The R² values are consistent with the US results, where the within variation for estimations on ROA containing TGI is generally higher than the ones containing DGI, except for model 5. In general, the results show several interesting and significant effects from the key variables. As with the US results, all estimated effects are ceteris paribus.

Table 7: Europe Estimation Results – Fixed Effects

Model 1 includes only the control variables. We see that the coefficients for company size and the leverage ratio are not statistically significant, which indicates these two variables do not affect the financial performance of European oil and gas companies. This is different from both the estimations found in the US data and from previous studies where these effects have been confirmed several times, even if there has been little consensus around the sign of the coefficients (see e.g., Bagirov & Mateus, 2019; Lin et al., 2019). However, the two control variables involving the oil price are both significant. The coefficient of oil price is significant at the 1% level and has a positive coefficient of 6.981. This means that when Brent crude oil price increases by 1%, ROA is expected to increase by 0.070 percentage point on average in the same year. The coefficient of the dummy variable of the 2014 and 2015 oil crisis is significant at the 1% level and has a value of -9.262. Thus, European oil and gas companies’

ROA was on average 9.262 percentage points lower than normal during the oil crisis. The result is consistent with previous studies where shocks on the oil price are found to have a significant impact on company financial performance in the European oil and gas industry (Bagirov &

Mateus, 2019).

In model 2 including DGI, we see that the estimation result of the coefficient of DGI is positive and significant at the 1% level. When including the control variables in model 3, the coefficient of DGI becomes insignificant. However, it becomes again significant in models 5 and 6 when including the interaction term with oil price. For the model including TGI, we see that the coefficient of TGI is insignificant in model 2 and becomes significant in the estimations in model 4, which adds the quadratic term of TGI.

Model 3 adds the key variables of the green innovation scores. The estimation result shows that the level of the previous year’s DGI has a negative effect on financial performance, while TGI has a positive effect. However, both estimated coefficients are insignificant, which implies that green innovation has no linear effect on European oil and gas companies’ financial performance.

Model 4 adds the quadratic term to explore if there is any proof of a curvilinear effect. The estimation result shows that there is no significant curvilinear relationship between DGI and

ROA. However, the coefficient of TGI is negative and significant at the 5% level, while the coefficient of its quadratic term is positive and significant at the 5% level. The two variables are jointly significant at the 10% level. The result shows that there is a curvilinear U-shaped relationship between total green innovation and ROA, with a turning point of !_%∗.''"^."#$ ! = 53.11.

In other words, TGI has a negative increasing effect on ROA. This means that when TGI is lower than 53.11, the effect of one additional unit of TGI on financial performance is negative but when the score becomes higher than 53.11, the effect turns positive. The U-shaped relationship shows that European oil and gas companies should either not invest in green innovation at all or invest sufficient funds in green innovation practices to gain financial benefits.

Model 5 includes an interaction term of oil price and the key variables. The result shows that the coefficient of DGI has a positive effect on ROA, which is 0.457 at the 10% significance level. The coefficient of interaction term of DGI and oil price is -0.114 and significant at the 10% level. However, the joint significant test of these two variables is insignificant. The result indicates that there exists a weak moderating effect of oil price on the relationship between the disruptive green innovation and the oil and gas companies’ financial performance, where an additional percentage increase in oil price will lower the positive effect of the previous year’s DGI on ROA. The coefficients for TGI and its interaction term have the same sign as DGI.

However, the estimates are not statistically significant, and we cannot confirm a moderating relationship between the oil price and the European oil and gas companies’ total green innovation efforts.

Model 6 acts as a robustness check and it adds all the independent variables used in the previous five models, including both quadratic terms of the green innovation variables and the interaction term of oil price and green innovation. For DGI, the results are consistent with previous results from model 5. The coefficient of the interaction term is -0.112 and significant at the 10% level.

The estimates for TGI show that the coefficient of the quadratic term is positive with a magnitude of 0.009 and is significant at the 10% level. This result is also consistent with what

we previously obtained from Model 4. The joint significant test of the three independent variables shows that TGI, the quadratic term of TGI, and the interaction term of TGI and Brent crude oil price, are jointly significant at the 5% significance level.

For the European companies, we do not find any significant linear effect of green innovation on the oil and gas companies’ financial performance. This includes both sustained and disruptive innovation efforts. The results show a U-shaped curvilinear relationship between TGI and ROA. These findings have previously been identified by Trumpp and Guenther (2017), which argue companies must make a minimum level of commitment to green innovation before the positive effects on financial performance start to show. Therefore, we confirm hypotheses 1 and 2, as we find that there is an effect of green innovation on the financial performance of European oil and gas companies and that the relationship is curvilinear with a negative increasing effect. We also find some evidence for a moderating effect of oil price on the relationship between disruptive green innovation and financial performance for European companies. The estimation results suggest that when oil price increases, the effect of disruptive green innovation on financial performance decreases. As previous literature suggests, high oil prices might dampen the fall when investing in disruptive innovation projects, making companies more likely to take risky investment decisions (Rassenfoss & Henni, 2015). The results show no significant interaction effect between TGI and oil price. This makes sense as companies’ investment activities in continuous improvements of products and processes, is a means to survive in the short term and more based on day to day operations. Thus, we also confirm hypothesis 3 for European companies, which conclude that there is a moderating effect of oil price on the relationship between green innovation and financial performance.