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ethicall investment indonesian grates, Summaries of Law

Institute Pertanian Bogor University (IPBU)Law

lecture notes lecture notes lecture notes lecture notes lecture notes lecture notes

Typology: Summaries

2022/2023

Available from 06/14/2023

eva-agustina 🇮🇩

3 documents

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170

statistically not significant. Regression 4 also has a negative coefficient, signalling data

robustness.

The Debt-to-Equity as well as the Total Assets have a negative, but close to zero coefficient

for the first regression, and a positive, but also close to zero, coefficient for regression 2 to 4.

However, all coefficients are statistically insignificant.

The F-Score is significant on a 1% level for Regression 1 and 4 and on a 5% level for 2 and 3.

This indicates that the regression models provide a better fit to the data than the intercept

model. This leads to the conclusion that the size of a firm does have an influence on the

ethical score.

In summary, the Market Capitalization has a positive impact on the Ethical Score while the

Net Profit Margin has a negative impact. All independent variables show data and time

robustness with the only exception of Net Profit Margin.

The regression model appears to be a better fit than the intercept model only.

Table 36 - Regression Results USA ES

USA_ES

Reg1

t10 → t10

Reg2

t17 → t17

Reg3

t17 → t16

Reg4

tØ10,17 → tØ10,17

Coefficient

p-value

Coefficient

p-value

Coefficient

p-value

Coefficient

p-value

Intercept

-0.7331

0.8362

9.8042**

0.0130

8.5738**

0.0269

3.0773

0.3666

logRevenue

-0.4457

0.7028

-1.1365

0.4346

-0.1227

0.9298

-1.0585

0.3898

logMarketCap

5.3780***

0.0000

2.9531***

0.0014

2.7052***

0.0044

4.5962***

0.0000

log#ofemployees

0.7531

0.4061

-0.4142

0.6641

-0.3425

0.7183

0.3342

0.6954

NetProfitMargin

-4.0228*

0.0985

-3.0393

0.1876

1.6738

0.4658

-2.9024

0.2566

Debt-to-Equity

-0.0142

0.8971

0.0159

0.2156

0.0047

0.3317

0.0190

0.4072

logTotalAssets

-0.4563

0.5403

0.7610

0.3020

0.3531

0.6128

0.1488

0.8156

Industry

0.0591

0.7281

-0.2133

0.1432

-0.1562

0.2839

-0.0894

0.5271

R-Squared

0.2398

0.1237

0.1212

0.2199

F-Score

5.9035***

2.6215**

2.5607**

5.2341***

Significance F

0.0000

0.0145

0.0167

0.0000

Table XY – USA_ES Regression.

The table presents the regression results of the Ethical Score (ES) and the independent variables indicating the size of the firm in the USA.

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%.

Partial preview of the text

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statistically not significant. Regression 4 also has a negative coefficient, signalling data

robustness.

The Debt-to-Equity as well as the Total Assets have a negative, but close to zero coefficient

for the first regression, and a positive, but also close to zero, coefficient for regression 2 to 4.

However, all coefficients are statistically insignificant.

The F-Score is significant on a 1% level for Regression 1 and 4 and on a 5% level for 2 and 3.

This indicates that the regression models provide a better fit to the data than the intercept

model. This leads to the conclusion that the size of a firm does have an influence on the

ethical score.

In summary, the Market Capitalization has a positive impact on the Ethical Score while the

Net Profit Margin has a negative impact. All independent variables show data and time

robustness with the only exception of Net Profit Margin.

The regression model appears to be a better fit than the intercept model only.

Table 36 - Regression Results USA ES

USA_ES Reg

t 10 → t 10

Reg

t 17 → t 17

Reg

t 17 → t 16

Reg

t Ø10,17 → t Ø10,

Coefficient p-value Coefficient p-value Coefficient p-value Coefficient p-value Intercept -0.7331 0.8362 9.8042** 0.0130 8.5738** 0.0269 3.0773 0. logRevenue -0.4457 0.7028 -1.1365 0.4346 -0.1227 0.9298 -1.0585 0. logMarketCap 5.3780*** 0.0000 2.9531*** 0.0014 2.7052*** 0.0044 4.5962*** 0. log#ofemployees 0.7531 0.4061 -0.4142 0.6641 -0.3425 0.7183 0.3342 0. NetProfitMargin -4.0228* 0.0985 -3.0393 0.1876 1.6738 0.4658 -2.9024 0. Debt-to-Equity -0.0142 0.8971 0.0159 0.2156 0.0047 0.3317 0.0190 0. logTotalAssets -0.4563 0.5403 0.7610 0.3020 0.3531 0.6128 0.1488 0. Industry 0.0591 0.7281 -0.2133 0.1432 -0.1562 0.2839 -0.0894 0. R-Squared 0.2398 0.1237 0.1212 0. F-Score 5.9035*** 2.6215** 2.5607** 5.2341*** Significance F 0.0000 0.0145 0.0167 0. Table XY – USA_ES Regression. The table presents the regression results of the Ethical Score (ES) and the independent variables indicating the size of the firm in the USA. 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)

Using the Positive Score (PS) as the dependent variable in the regression, similar results to

the Ethical Score regression results can be found. The Market Capitalization has positive

coefficients for all four regression and is significant on a 1% and 5% level. This indicates that

a high market capitalization has a positive impact on the Positive Score. Furthermore, the Net

Profit Margin is statistically significant on a 5% level with a negative coefficient implying a

negative impact. However, the coefficient is positive for the third regression, while all other

regressions show a negative coefficient for the Net Profit Margin. This could be a signal for a

possible time lag.

The revenue has all positive coefficients, indicating a positive impact of a high revenue on the

Positive Score. The coefficients, however, are not statistically significant.

The number of employees, the Debt-to-Equity, as well as the Total Asset have all coefficients

close to zero with mixed signs and no statistical significance.

The F-Score is statistically significant for all four regression on a 1% level. Just like the

regression results for the Ethical Score, this implies that the regression models provide a

better fit to the data than the intercept model.

All results show data robustness and time delay robustness except Net Profit Margin.

In summary, the results are very similar to the Ethical Score regression results. The Market

Capitalization has a positive impact on the Ethical Score while the Net Profit Margin has a

negative impact. All independent variables show data and time robustness with the only

exception of Net Profit Margin. The regression model appears to be a better fit than the

intercept model only.

Table 37 - Regression Results USA PS

USA_PS Reg

t 10 → t 10

Reg

t 17 → t 17

Reg

t 17 → t 16

Reg

t Ø10,17 → t Ø10,

Coefficient p-value Coefficient p-value Coefficient p-value Coefficient p-value Intercept -0.5335 0.8762 11.6854*** 0.0013 10.6308*** 0.0028 4.1542 0. logRevenue 1.0045 0.3742 0.7844 0.5545 1.6485 0.1957 0.8640 0. logMarketCap 4.4631*** 0.0000 2.3583*** 0.0050 2.0554** 0.0171 3.8204*** 0. log#ofemployees 0.9251 0.2914 -0.6284 0.4707 -0.5152 0.5520 0.2668 0. NetProfitMargin -4.6803** 0.0472 -3.0536 0.1473 1.1082 0.5963 -3.4084 0. Debt-to-Equity -0.0703 0.5069 0.0040 0.7334 0.0023 0.5952 -0.0029 0. logTotalAssets -0.3975 0.5809 0.2228 0.7403 -0.1639 0.7967 -0.1586 0. Industry 0.0985 0.5490 -0.1720 0.1956 -0.1296 0.3295 -0.0488 0.

ethicall investment indonesian grates, Summaries of Law

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statistically not significant. Regression 4 also has a negative coefficient, signalling data

robustness.

The Debt-to-Equity as well as the Total Assets have a negative, but close to zero coefficient

for the first regression, and a positive, but also close to zero, coefficient for regression 2 to 4.

However, all coefficients are statistically insignificant.

The F-Score is significant on a 1% level for Regression 1 and 4 and on a 5% level for 2 and 3.

This indicates that the regression models provide a better fit to the data than the intercept

model. This leads to the conclusion that the size of a firm does have an influence on the

ethical score.

In summary, the Market Capitalization has a positive impact on the Ethical Score while the

Net Profit Margin has a negative impact. All independent variables show data and time

robustness with the only exception of Net Profit Margin.

The regression model appears to be a better fit than the intercept model only.

Table 36 - Regression Results USA ES

t 10 → t 10

t 17 → t 17

t 17 → t 16

t Ø10,17 → t Ø10,

Positive Score (PS)

Using the Positive Score (PS) as the dependent variable in the regression, similar results to

the Ethical Score regression results can be found. The Market Capitalization has positive

coefficients for all four regression and is significant on a 1% and 5% level. This indicates that

a high market capitalization has a positive impact on the Positive Score. Furthermore, the Net

Profit Margin is statistically significant on a 5% level with a negative coefficient implying a

negative impact. However, the coefficient is positive for the third regression, while all other

regressions show a negative coefficient for the Net Profit Margin. This could be a signal for a

possible time lag.

The revenue has all positive coefficients, indicating a positive impact of a high revenue on the

Positive Score. The coefficients, however, are not statistically significant.

The number of employees, the Debt-to-Equity, as well as the Total Asset have all coefficients

close to zero with mixed signs and no statistical significance.

The F-Score is statistically significant for all four regression on a 1% level. Just like the

regression results for the Ethical Score, this implies that the regression models provide a

better fit to the data than the intercept model.

All results show data robustness and time delay robustness except Net Profit Margin.

In summary, the results are very similar to the Ethical Score regression results. The Market

Capitalization has a positive impact on the Ethical Score while the Net Profit Margin has a

negative impact. All independent variables show data and time robustness with the only

exception of Net Profit Margin. The regression model appears to be a better fit than the

intercept model only.

Table 37 - Regression Results USA PS

t 10 → t 10

t 17 → t 17

t 17 → t 16

t Ø10,17 → t Ø10,