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The dependent variable is the Ethical Score (ES), which is measured as the difference of the Positive Score (PS) and the Negative Score
(NS). The independent variables are defined as follows: the logarithmised revenue [in bn $] (logRevenue), the logarithmised market
capitalization [in bn $] (logMarketCap), the logarithmised number of employees (log#ofemployees), the Net Profit Margin
(NetProfitMargin), the Debt-to-Equity Ratio (Debt-to-Equity), the logarithmised Total Assets [in bn $] (logTotalAssets), and the industry as
a dummy variable.
Regression 1 (Reg1) uses the data from 2010 for both, the dependent and the independent variables. Regression 2 (Reg 2) uses the data for
2017 for both, the dependent and the independent variables. Regression 3 (Reg 3) uses the data from 2017 for the dependent variable and
from 2016 for the independent variables in order to check for a time lag. Regression 4 (Reg 4) uses the average of the data from 2010 and
2017 in order to check the robustness.
*** Significant at 1%, ** Significant at 5%, * Significant at 10%.
Positive Score (PS)
When using the Positive Score as the dependent variable, a very similar picture to the Ethical
Score is depicted. The revenue also has positive coefficients for all four regressions and is
significant on a 1% level for regression one and four, and significant on a 10% level for
regression 2. This indicates that a high revenue has a positive impact on the Positive Score
with data and time lag robustness.
The market capitalization also shows a very similar regression result in comparison to the
Ethical Score regression. All coefficients are under one and positive and only the second
regression, that uses the 2017 data, is significant on a 10% level. This implies that the market
capitalization has a positive impact on the Positive Score but is less significant than the
revenue. The number of employees again has a negative but close to zero coefficient for the
first regression that uses the 2010 data and for the other three regressions has positive
coefficients. It is significant on a 1% level when using the 2017 data and the robustness check
for time lag is significant on a 5% level. The number of employees appears to have a positive
impact on the Positive Score in more recent years and appears to not have that effect earlier.
The Net Profit Margin has all negative coefficients that are close to zero. They are significant
on a 1% level for regression two to four and significant on a 10% level for regression one.
The Net Profit Margin appears to have no to slightly negative impact on the Positive Score.
The same can be found for the Ethical Score. As the results for regression three and four are
similar to one and two, data and time lag robustness can be assumed.
The Debt-to-Equity Ratio regression results for PS are also similar to the ES. The coefficients
are all close to zero and a have a negative sign. The only difference is that the coefficient for
the first regression is significant on a 10% level implying that a high Debt-to-Equity Ratio has
a small, negative impact on the PS. The Total Assets coefficients are also all close to zero
with a negative sign. None of them are statistically significant while the data is robust.
