Inferential Data Analysis For Carbon Emissions Study

Research question and theoretical construct summary

In this section, we are going to focus on inferential data analysis. Statistical test we are going to use here is chi-square. We are going to obtain the cross-tabulation table their respective chi-square test.

From the chi-square test table below gives the relationship between country and the type of industry emitting the carbon, we find that Pearson Chi-Square has value of 459.396^a with degree of freedom 168 and p-value of 0.0001. Likelihood Ratio test has a value of 342.170 with degree of freedom of 168 and p-value of 0.0001. Since the p-value 0.0001

Chi-Square Tests
	Value	df Save Time On Research and Writing Hire a Pro to Write You a 100% Plagiarism-Free Paper. Get My Paper	Asymptotic Significance (2-sided)
Pearson Chi-Square	459.396a	168	.000
Likelihood Ratio	342.170	168	.000
N of Valid Cases	781
a. 164 cells (76.3%) have expected count less than 5. The minimum expected count is .01.

1. Country versus climate integrated into business strategy

The table below shows the cross tabulation between different countries and how they have integrated into their business strategy climate change. Out of possible 781 observations from five countries 702 has adopted the integration of business idea into their business strategy.

Crosstab
Count
	CC2.2 – Is climate change integrated into your business strategy?	Total
Yes	No
country	Canada	85	14	99
China	3	5	8
Germany	57	9	66
United Kingdom	205	14	219
USA	352	37	389
Total	702	79	781

From the chi-square test table below, we find that Pearson Chi-Square has value of 30.304 with degree of freedom 4 and p-value of 0.001. Likelihood Ratio test has a value of 19.326 with degree of freedom of 4 and p-value of 0.001. Since the p-value 0.0001

Chi-Square Tests
	Value	df	Asymptotic Significance (2-sided)
Pearson Chi-Square	30.304a	4	.000
Likelihood Ratio	19.326	4	.001
N of Valid Cases	781
a. 1 cells (10.0%) have expected count less than 5. The minimum expected count is .81.

The table below shows the cross tabulation between the country and carbon emission target. Out of the 781 observations, 576 said they had the emission reduction or renewable energy consumption or production target that was active. 

Crosstab
Count
	CC3.1. Did you have an emissions reduction or renewable energy consumption or production target that was active (ongoing or reached completion) in the reporting year?	Total
Yes	No
country	Canada	55	44	99
China	6	2	8
Germany	48	18	66
United Kingdom	180	39	219
USA	287	102	389
Total	576	205	781

From the chi-square test table below, we find that Pearson Chi-Square has value of 25.033^a with degree of freedom 4 and p-value of 0.001. Likelihood Ratio test has a value of 23.968with degree of freedom of 4 and p-value of 0.001. Since the p-value 0.0001

Chi-Square Tests
	Value	df	Asymptotic Significance (2-sided)
Pearson Chi-Square	25.033a	4	.000
Likelihood Ratio	23.968	4	.000
N of Valid Cases	781
a. 1 cells (10.0%) have expected count less than 5. The minimum expected count is 2.10.

From the chi-square test table below gives the relationship between country and percentage change in carbon emission, we find that Pearson Chi-Square has value of 1682.168^a with degree of freedom 1536 and p-value of 0.005. Likelihood Ratio test has a value of 1041.061with degree of freedom of 1536 and p-value of 1.000. Since the p-value 0.0001

Chi-Square Tests
	Value	df	Asymptotic Significance (2-sided)
Pearson Chi-Square	1682.168a	1536	.005
Likelihood Ratio	1041.061	1536	1.000
N of Valid Cases	781
a. 1917 cells (99.6%) have expected count less than 5. The minimum expected count is .01.

Integrating climate change versus percentage change in metric tons of carbon emission. 

From the chi-square test table below gives the relationship between integrating climate change in business strategy and percentage change in carbon emission, we find that Pearson Chi-Square has value of 302.560^a with degree of freedom 384 and p-value of 0.999. Likelihood Ratio test has a value of 238.929with degree of freedom of 384 and p-value of 1.000. Linear-by-Linear Association has a value of 157 with a degree of freedom of 1 and p-value of 0.692. Since the p-value 0.999>0.05 at 95% confidence level, we can say that there is no significant relationship integrating into business strategy the climate change and percentage change in carbon emission. 

Chi-Square Tests
	Value	df	Asymptotic Significance (2-sided)
Pearson Chi-Square	302.560a	384	.999
Likelihood Ratio	238.929	384	1.000
Linear-by-Linear Association	.157	1	.692
N of Valid Cases	781
a. 753 cells (97.8%) have expected count less than 5. The minimum expected count is .10.

Relationship between country and type of industry emitting carbon

The table below gives the additional information on the relationship between integrating into business strategy the climate change and percentage change in the emission of carbon. It gives the Pearson’s correlation coefficient and Spearman correlation coefficient. The Pearson correlation coefficient has value of -0.014 and asymptotic standardized error of 0.019. The Spearman correlation coefficient has value of 0.044 and asymptotic standardized error of 0.036

Symmetric Measures
	Value	Asymptotic Standardized Errora	Approximate Tb	Approximate Significance
Interval by Interval	Pearson’s R	-.014	.019	-.396	.692c
Ordinal by Ordinal	Spearman Correlation	.044	.036	1.227	.220c
N of Valid Cases	781
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null hypothesis.
c. Based on normal approximation.

 Emission reduction target versus percentages change of carbon emissions 

From the chi-square test table below gives the relationship between emission reduction target and percentage change in carbon emission, we find that Pearson Chi-Square has value of 420.388^a with degree of freedom 384 and p-value of 0.097. Likelihood Ratio test has a value of 493.288with degree of freedom of 384 and p-value of 0.0001. Linear-by-Linear Association has a value of 0.0 with a degree of freedom of 1 and p-value of 0.988. Since the p-value 0.097>0.05 at 95% confidence level, we can say that there is no significant relationship between carbon emission target and percentage change in carbon emission.

Chi-Square Tests
	Value	df	Asymptotic Significance (2-sided)
Pearson Chi-Square	420.388a	384	.097
Likelihood Ratio	493.288	384	.000
Linear-by-Linear Association	.000	1	.988
N of Valid Cases	781
a. 758 cells (98.4%) have expected count less than 5. The minimum expected count is .26.

The table below gives the additional information on the relationship between emission reduction target and percentage change in the emission of carbon. It gives the Pearson’s correlation coefficient and Spearman correlation coefficient. The Pearson correlation coefficient has value of 0.001 and asymptotic standardized error of 0.046. The Spearman correlation coefficient has value of 0.163 and asymptotic standardized error of 0.036 

Symmetric Measures
	Value	Asymptotic Standardized Errora	Approximate Tb	Approximate Significance
Interval by Interval	Pearson’s R	.001	.046	.015	.988c
Ordinal by Ordinal	Spearman Correlation	.163	.036	4.599	.000c
N of Valid Cases	781
a. Not assuming the null hypothesis.
b. Using the asymptotic standard error assuming the null hypothesis.
c. Based on normal approximation.

 Industry type versus the percentage change of carbon emission 

From the chi-square test table below gives the relationship between country and percentage change in carbon emission, we find that Pearson Chi-Square has value of 16209.768^a with degree of freedom 16128 and p-value of 0.323. Likelihood Ratio test has a value of 3527.574 with degree of freedom of 16128 and p-value of 1.000. Since the p-value 0.323

Chi-Square Tests
	Value	df	Asymptotic Significance (2-sided)
Pearson Chi-Square	16209.768a	16128	.323
Likelihood Ratio	3527.574	16128	1.000
N of Valid Cases	781
a. 16548 cells (100.0%) have expected count less than 5. The minimum expected count is .00.

Hypothesis testing 

H₀: Integration of climate change in business strategy has no significant relationship with carbon emission reduction.

H₁: Integration of climate change in business strategy has significant relationship with carbon emission reduction.

Chi-Square Tests
	Value	df	Asymptotic Significance (2-sided)
Pearson Chi-Square	302.560a	384	.999
Likelihood Ratio	238.929	384	1.000
Linear-by-Linear Association	.157	1	.692
N of Valid Cases	781
a. 753 cells (97.8%) have expected count less than 5. The minimum expected count is .10.

 The above table shows the chi-square test between integrating climate change into business strategy. The p-value from the table of the Pearson Chi-Square is 0.999. At 95% confidence level, 0.999>0.05. We therefore fail to reject the null hypothesis and conclude that integration of climate change into business strategy has no significant relationship with carbon emission reduction. 

The main objective of the study was to identify if there could be statistical significance relationship between the integrating climate change business strategies and carbon emission reduction. Carbon dioxide is one of the greenhouse gasses which contribute to global warming and eventually causing the climate change. The only way to prevent the effects of climate change is to reduce as much as possible the emission of carbon into the atmosphere. Much of the carbon released in the atmosphere is emitted as a result of majorly the human activities, especially the big manufacturing firms hence our study. To reduce the carbon emission, it is solely in the hand of both the regulators and the firm’s management to ensure that carbon emitted is reduced. One of the ways the firms can do this, from the findings is to integrate climate change into the business strategy and bringing into play the management incentives.  

Integrating climate change and emission reduction target

By business integrating climate change as their business strategy, the main objective of that particular business is to ensure their objectives are achieved including the one for climate change. A strategy is something which the life of a business depend on, without it they cannot succeed. Therefore this calls for not just integrating it just as a strategy but also implementing those strategies. Some strategies have worked while some haven’t worked. Studying the different types of strategies which other firms has put in place across the world can help in spreading the idea and help the firms which have not implemented them to do so. There is the need for both the governments of specific countries and the international organizations to come out and put awareness concerning climate change to the firms which have not implemented those strategies. The government also has the power to enforce some strategies to different firms. Putting it a must that for a firm to operate they must integrate and implement climate change in their business strategy this will help great time.

One of the study variable was management incentives on employees. This has quite work well in some countries. By offering benefits to employees so that they can help the firm to achieve its objectives can be very effective. Though this comes in handy with integrating into the business strategy the issue of climate change, management incentive can help in the general implementation. Firms should be encouraged to adopt this for the people who have not adopted sine it can help to achieve carbon emission free.

On studying on how integrating climate change business strategy, our main expectation was to find how this has contributed majorly, but our hypothesis is saying there is no significant relationship between integrating climate change in business strategy and carbon emission reduction. This might be as a result of putting everything in place but not implementing the idea into real action. Some of the countries has no proper strategies to ensure that climatic change strategies are enforced into action. Some firms might also lack the good will for the reduction of carbon emissions. With reduced carbon emitted less global warming, hence no climate change. 

There are some limitations faced during the study.

Poor implementation. There are many firms according to the study who have integrated climate change in their business strategy, but we still find that this do not have greater effect on the carbon emission has it should be. From individual countries it has worked therefore it can work anywhere.

Irrelevant strategies. There are some strategies put in place by some firms across the world which are related to climate change, but doesn’t necessarily address the climate change. This may lead to many people saying that they have integrate strategies to curb carbon emission, but in real sense they don’t work.

Inadequate government intervention on the implementation of the climatic change strategies. The government may be reluctant on their side in ensuring that these strategies are put in place for effective carbon emission. This can lead to many firms saying they have integrated the strategies but still no effect on the reduction of carbon emission.

The further research should be conducted on how different firms are implementing the strategies they have put in place to reduce the carbon emission. This will help in sharing ideas across the world on how proper implementation can be done.

Another research can look into the different strategies different firms are adopting to ensure reduction of carbon emission. This will also help to share the ideas to curb carbon emission.

Finally research on how the different governments are ensuring that carbon emission reduction policies are followed and met by different operating firms.