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Ut molestiae libero esse voluptas qui magna eius fugiat aut qui magna voluptatem Est vel, Schemes and Mind Maps of Business Ethics

Institute Pertanian Bogor University (IPBU)Business Ethics

Numquam eaque eos suscipit lorem duis neque vero quia magnam molestias nemo ab quo autem similique laborum

Typology: Schemes and Mind Maps

2021/2022

Available from 06/14/2023

eva-agustina
eva-agustina ๐Ÿ‡ฎ๐Ÿ‡ฉ

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183
insignificant. This might be due to a missing time lag robustness as the data shows robustness
but not time lag robustness. Except that, the Net Profit Margin has also a positive impact on
the Positive Score.
The Total Assets show a negative coefficient for the first regression that is also statistically
significant on a 5% level but all positive coefficients for the other regression. The coefficients
of regression two and four show statistical significance on a 10% level. The 2010 regression
therefore implies a negative impact on the Positive Score, while the 2017 regression shows a
positive impact. Time lag and data robustness is given.
As in the previous regressions for the Ethical Score, the Debt-to-Equity variable for the
Positive Score has all positive coefficients of which none are statistically significant. The
impact of the Debt-to-Equity on the Positive Score is positive.
The only independent variable that has all negative coefficients and therefore objects the
previous results, is again the Market Capitalization. This implies a negative impact of the
market capitalization on the Positive Score. However, none of the coefficients are statistically
significant.
It also has to be mentioned, that the R-Squares values are relatively low and the F-Score is
also significant for the first and fourth regression on a 1% and 5% level.
In summary, the results for the Positive Score are very similar to the results for the Ethical
Score. All independent variables indicate a positive impact of the company size on the Ethical
Score, with revenue, Net Profit Margin, number of employees, and Total Assets having
statistically significant coefficients. The only independent variable that contradicts the
previous results is the market cap, that shows a negative impact on the Positive Score.
Table 43 - Regression Results China PS
CHI_PS
Reg1
t10 โ†’ t10
Reg2
t17 โ†’ t17
Reg3
t17 โ†’ t16
Reg4
tร˜10,17 โ†’ tร˜10,17
Coefficient
p-value
Coefficient
p-value
Coefficient
p-value
Coefficient
p-value
Intercept
4.9634***
0.0000
8.3801***
0.0000
9.6698***
0.0000
6.9470***
0.0000
logRevenue
1.7690**
0.0177
1.1413
0.1821
1.6685*
0.0594
1.8240**
0.0237
logMarketCap
-1.0591
0.2978
-0.4854
0.6025
-1.4833
0.1826
-1.4494
0.1577
log#ofemployees
0.0077*
0.0655
0.0022
0.5680
0.0026
0.5388
0.0034
0.3441
NetProfitMargin
2.9702**
0.0293
1.2189
0.5765
-0.8776
0.4306
2.7046
0.1055
Debt-to-Equity
0.2656
0.2481
0.0692
0.8248
0.1550
0.5901
0.1536
0.5352
logTotalAssets
-0.0033**
0.0358
0.0001*
0.0821
0.0001
0.8772
0.0002*
0.0595
Industry
0.1694
0.2456
0.1418
0.4116
0.1331
0.4439
0.1796
0.2156
R-Squared
0.1892
0.0807
0.0713
0.1523
F-Score
3.3669***
1.2658
1.1082
2.5914**
Significance F
0.0029
0.2749
0.3638
0.0168
pf3

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insignificant. This might be due to a missing time lag robustness as the data shows robustness

but not time lag robustness. Except that, the Net Profit Margin has also a positive impact on

the Positive Score.

The Total Assets show a negative coefficient for the first regression that is also statistically

significant on a 5% level but all positive coefficients for the other regression. The coefficients

of regression two and four show statistical significance on a 10% level. The 2010 regression

therefore implies a negative impact on the Positive Score, while the 2017 regression shows a

positive impact. Time lag and data robustness is given.

As in the previous regressions for the Ethical Score, the Debt-to-Equity variable for the

Positive Score has all positive coefficients of which none are statistically significant. The

impact of the Debt-to-Equity on the Positive Score is positive.

The only independent variable that has all negative coefficients and therefore objects the

previous results, is again the Market Capitalization. This implies a negative impact of the

market capitalization on the Positive Score. However, none of the coefficients are statistically

significant.

It also has to be mentioned, that the R-Squares values are relatively low and the F-Score is

also significant for the first and fourth regression on a 1% and 5% level.

In summary, the results for the Positive Score are very similar to the results for the Ethical

Score. All independent variables indicate a positive impact of the company size on the Ethical

Score, with revenue, Net Profit Margin, number of employees, and Total Assets having

statistically significant coefficients. The only independent variable that contradicts the

previous results is the market cap, that shows a negative impact on the Positive Score.

Table 43 - Regression Results China PS

CHI_PS Reg

t 10 โ†’ t 10

Reg

t 17 โ†’ t 17

Reg

t 17 โ†’ t 16

Reg

t ร˜10,17 โ†’ t ร˜10,

Coefficient p-value Coefficient p-value Coefficient p-value Coefficient p-value Intercept 4.9634*** 0.0000 8.3801*** 0.0000 9.6698*** 0.0000 6.9470*** 0. logRevenue 1.7690** 0.0177 1.1413 0.1821 1.6685* 0.0594 1.8240** 0. logMarketCap -1.0591 0.2978 -0.4854 0.6025 -1.4833 0.1826 -1.4494 0. log#ofemployees 0.0077* 0.0655 0.0022 0.5680 0.0026 0.5388 0.0034 0. NetProfitMargin 2.9702** 0.0293 1.2189 0.5765 -0.8776 0.4306 2.7046 0. Debt-to-Equity 0.2656 0.2481 0.0692 0.8248 0.1550 0.5901 0.1536 0. logTotalAssets -0.0033** 0.0358 0.0001* 0.0821 0.0001 0.8772 0.0002* 0. Industry 0.1694 0.2456 0.1418 0.4116 0.1331 0.4439 0.1796 0. R-Squared 0.1892 0.0807 0.0713 0. F-Score 3.3669*** 1.2658 1.1082 2.5914** Significance F 0.0029 0.2749 0.3638 0.

The table presents the regression results of the Positive Score (PS) and the independent variables indicating the size of the firm in China. The dependent variable is the Positive Score (PS), which is the sum of all negative scores in the screening. 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 (Reg 1) 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%.

Negative Score (NS)

When the Negative Score is applied as the dependent variable, no independent variable has a

statistically significant influence. Counterintuitively, the coefficients for revenue are all

positive, same as for ES and PS, while the coefficients for market cap are all negative, again

the same as for ES and PS. This implies that the revenue has a positive and the market cap has

a negative impact on the Negative Score, as well as the Ethical Score and the Positive Score.

The number of employees and the Debt-to-Equity have all positive coefficients, implying a

positive impact on the Negative Score.

The Net Profit Margin has all negative score indicating a negative impact on the Negative

Score. The Total Assets have negative coefficients for the first and third regression and

positive coefficients for the second and fourth. However, the coefficients are all close to zero.

The R-Square is also relatively low. However, the F-Score is never significant in contrast to

the ES- and PS-regressions.

In summary, none of the independent variables show statistically significant coefficients. The

coefficient signs are, counterintuitively, similar to the results for the ES and PS regression.

Revenue, number of employees, and Debt-to-Equity show positive signs, market cap and Net-

Profit-Margin show negative coefficients and Total Assets show mixed signs.

Table 44 - Regression Results China NS

CHI_NS Reg

t 10 โ†’ t 10

Reg

t 17 โ†’ t 17

Reg

t 17 โ†’ t 16

Reg

t ร˜10,17 โ†’ t ร˜10,

Coefficient p-value Coefficient p-value Coefficient p-value Coefficient p-value Intercept 0.9417*** 0.0025 1.2620** 0.0169 1.667** 0.0233 1.1854*** 0. logRevenue 0.2408 0.2193 0.3287 0.2901 0.3907 0.2192 0.3554 0. logMarketCap -0.2725 0.3131 -0.3860 0.2562 -0.4107 0.3060 -0.4306 0. log#ofemployees 0.0015 0.1784 0.0000 0.9979 0.0004 0.7760 0.0006 0. NetProfitMargin -0.3460 0.3346 -0.3225 0.6846 -0.3857 0.3378 -0.3556 0. Debt-to-Equity 0.0373 0.5406 0.0355 0.7682 0.0402 0.6986 0.0230 0. logTotalAssets -0.001 0.7812 0.0000 0.9977 -0.0001 0.7520 0.0000 0.