The best method for governments to encourage businesses to comply with new legislations and policies is usually through subsidies and incentives. This use of incentives has been applied in the implementation of climate change policies globally. However the incentives are not always available for all industries. This affects the implementation of the climate change agenda across the board.
The United Kingdom and the United States of America are among the biggest contributors to carbon emissions globally. Apart from this, they are also among the biggest economies in their respective regions, Europe and North America. This makes the Carbon Emissions data from these two countries important in the analysis of the global handling of the climate change agenda.
This research paper focuses on the impact that the availability of government incentives has had on the level of carbon emissions in the United Kingdom and the United States of America. The purpose for this research is to compare the impact that the availability of government incentives has had on the level of carbon emissions for the year 2014 in the two countries. This comparison is going to give a picture of the handling of climate change in not only both countries but also their respective regions.
The relationship between the carbon emission and the economic activities of the firms has been one of the most researched topics in last two decades. With increasing in the size and the reach of the firms there has been significant change in the climate also and it has becomes one of the most significant global threat. The carbon emission from the firm, especially from the manufacturing firms has affected the climate and the global temperature is on rise. So, the current research is aimed to examine impact of the incentive provided for the management on the voluntary disclosure of the carbon emission (Behram & Özdemirci 2014; Skaza et al. 2013).
This process is related to the agency theory of the corporate governance. According to the agency theory there is conflict among the stakeholders and the management in the organisation(Wiseman 2012; Duh 2010; M. Jensen & Meckling 1976; Wanyonyi & Tobias 2013). On one hand the management’s main objective is to maximize their compensation, irrespective of the financial performance of the firm. So the managers may such decision which may be good for the short term return but the long term return to the company and its stakeholders are very less (Ghazouani 2013; M. C. Jensen & Meckling 1976; Vergas1 et al. 2015).
On the other hand the stakeholders of the company want to maximize the long term returns. One of the stakeholders of the firms is the government and the local communities, and the return for those stakeholders is the clean and safe environment. So, there is continuous conflict among these stakeholders and the management, which led to the rise of similar problem of agency theory. According to firms wants to produce more and earn higher profit without caring much about the environment. Whereas the government and the local communities want to ensure that the firms are following the environmental guidelines provided by the government of the international organisations.
To ensure that the firms are operating as per the given guidelines the firms are asked to disclose their carbon emission every year. Some firms voluntarily disclose the carbon emission; however some firms do not disclose the actual data. On the basis of the carbon disclosure the disclosure score is determined. Many previous scholars have used this disclosure score as the proxy for the corporate governance also. According to some research, if the firm provide incentives to its managers for complying with the carbon emission guidelines then the managers are expected to work towards reducing the carbon emission. Some previous studies have shown that the carbon emission have declined in some firms where the managers are provided with both cash and kind incentives for reducing the carbon emission. On the other hand if the incentives are not provided than the managers are expected to find other ways to maximize their compensation which may be harmful to the environment, such as usage of low quality raw material, using banned chemicals etc. (KamelMadi et al. n.d.; Najah & Cotter 2010; Reid & Toffel 2009).
So, in the current research the relationship between the incentive for the managers and the carbon disclosure score will be analysed. There has been some previous research in the similar area, however there is no unique conclusion from those research. Some research has shown that increasing the incentive leads to lower carbon emission, whereas some scholars have found that there is no effect of providing incentive. However none of the research has shown negative impact of incentive on carbon emission.
Null hypothesis: The carbon disclosure score is not affected by the incentive provided to the management for climate related issues.
Alternative hypothesis: The carbon disclosure score is affected by the incentive provided to the management for climate related issues.
Theoretical Construct |
Proxy measure (From CDP survey provided) |
Dependent (DV) and Independent (IV). Control Variable (CV), Mediating Variable (MeV) or Moderating Variable (MoV). In a sentence explain why it is a DV, IV, CV, MeV or MoV |
Measurement Scale: Nominal, Ordinal, or Scale (Ratio) |
Voluntary disclosure measures |
Carbon disclosure score |
Dependent variable |
Scale |
Corporate governance |
Incentive provided for management related to climate change issues |
Independent variable |
Ordinal |
Other factors |
Country, GRI |
Control variable |
nominal |
In this research a samples of 60 firms were considered for the analysis and subsequent inferencing. The firms were drawn from two countries; United Kingdom and United States of America. From each of the countries, an equal sample of 30 firms was collected. The research focused on collecting data for the year 2014.
This research focused on firms that came from three industries mainly;
The three industries are a sample from the total number of industries provided in the CDP survey data. The industries above represent a good sample that captures the carbon emissions from both the direct and indirect contributors. Whereas the Aerospace and Defence Industry represents direct contributors, the other two industries; Banks, Diverse Financials and Insurance, and Food and Beverage Processing, represent the indirect contributors.
The research will analyse data from two subsets generated from the CDP survey datasets. These subsets are:
Both subsets will have the same number of observations. They will also have the same number and type of variables.
The two countries were selected to represent the Country variable. This variable will be a Control Variable in this research. United Kingdom and United States of America present good study cases for this research for the following reasons:
The following variables are present in the two subsets:
In this research, only three variables will be considered for the data analysis. These variables are:
In order to determine whether this research can be used to give a general view of the climate change situation globally, we observe it from two aspects. Firstly, we consider the aspect of the choice on the sample of industries. The three selected industries: Aerospace and Defence, Banks, Diverse Financials and Insurance, and Food and Beverage Processing, are industries that by extension can be said to represent all the general sector in business. The sample represent the following sectors: Security, Transport, Finance and Agriculture. This hence implies that the analysis from the data in this research can be considered applicable for all the industries and sectors of business.
Secondly, we consider the aspect of the choice of location of the firms. This research focuses on the firms in United Kingdom and United States of America. These countries represent the biggest contributors to carbon emissions globally, hence we can conclude that the analysis is applicable for the world’s biggest contributors to carbon emissions. However, the two countries come from only two geographical regions of the world; that is North America and Europe. Other regions such as South America, Africa, Middle East, Asia and the Pacific Countries are left out of the sample. This could present bias in case generalization is applied to the findings of the research for all regions.
UK CARBON EMISSIONS SUBSET
The frequency analysis of the Corporate Governance variable is represented in Table 1: Source SPSS and Table 2: Source SPSS below:
Table 1: Source SPSS shows that the Corporate Governance variable had a sample size of 30, with the entire sample being valid with no missing values. Table 2: Source SPSS shows that of the sample of 30, 23 represent firms for which incentive has been provided. This was percentage equivalent to 76.7%. 7 of the 30 represent firms for which incentive has not been provided, percentage equivalent to 23.3%.
The descriptive analysis of the Carbon Emission Disclosure Score variable is represented in Table 3: Source SPSS below:
Table 3: Source SPSS shows that the Carbon Emission Disclosure Score variable had valid sample size of 30. The highest Carbon Emission Score with respect to percentage reduction was 47% (-47). The lowest Carbon Emission Score with respect to percentage reduction was -37% (37). The average Carbon Emission Score with respect to percentage reduction was 9.7340% (-9.7340). The standard deviation of Carbon Emission Score with respect to percentage reduction was 17.09939.
The normality analysis of the Carbon Emissions Score, considering Corporate Governance as a factor is represented in Table 4: Source SPSS and Table 5: Source SPSS below:
Table 4: Source SPSS represents information on the cases in the UK Carbon Emissions subset data. The cases had no missing values, with 23 cases represent firms for which incentive has been provided, percentage equivalent to 76.7% while 7 of the 30 represent firms for which incentive has not been provided, percentage equivalent to 23.3%.
In Table 5: Source SPSS the firms for which incentive has been provided have the following statistics: Range = 84, Interquartile Range = 13.6, Skewness = -0.017 and Kurtosis = 1.927.
In Table 5: Source SPSS also, the firms for which incentive has not been provided have the following statistics: Range = 36, Interquartile Range = 25.20, Skewness = -0.112 and Kurtosis = -2.222.
The graphical analysis for the Corporate Governance Variable is represented in the plot in Figure 1: Source SPSS below:
Source SPSS gives the proportion for firms for which incentive has been provided and firms for which incentive has not been provided. The graphical analysis show that firms for which incentive has been provided are more than firms for which incentive has not been provided.
The description of the dependent variable in terms of the independent variable is represented in the plot in Figure 2: Source SPSS below:
Figure 2: Source SPSS shows that the data from firms for which incentive has been provided is skewed to the left with a lot of the data points occurring between the 0 mark and -15 mark. This data has five outliers; 24, 9, 21, 18 and 4.
Figure 2: Source SPSS also shows that the data from firms for which incentive has not been provided is skewed to the left with a lot of the data points occurring between the -7 mark and -35 mark. This data has no outlier data points.
For the analysis represented in Figure 2: Source SPSS the five outlier data points can be omitted from the subset. The outliers represent 16.67% of the entire sample therefore can be easily removed without affecting the analysis in the research.
USA CARBON EMISSIONS 2014 SUBSET
The frequency analysis of the Corporate Governance variable is represented in Table 6: Source SPSS.
Source SPSS shows that the Corporate Governance variable had a sample size of 30, with the entire sample being valid with no missing values. Table 7: Source SPSS shows that of the sample of 30, 29 represented firms for which incentive has been provided. This was percentage equivalent to 96.7%. 1 of the 30 represented firms for which incentive has not been provided, percentage equivalent to 3.3%.
The descriptive analysis of the Carbon Emission Disclosure Score variable is represented.
Source SPSS shows that the Carbon Emission Disclosure Score variable had valid sample size of 30. The highest Carbon Emission Score with respect to percentage reduction was 37% (-37). The lowest Carbon Emission Score with respect to percentage reduction was -3.99% (3.99). The average Carbon Emission Score with respect to percentage reduction was 9.1517% (-9.5121). The standard deviation of Carbon Emission Score with respect to percentage reduction was 10.74260.
The normality analysis of the Carbon Emissions Score, considering Corporate Governance as a factor is represented in Table 9: Source SPSS and Table 10: Source SPSS below:
Table 9: Source SPSS represents information on the cases in the UK Carbon Emissions subset data. The cases had no missing values, with 29 cases representing firms for which incentive has been provided, percentage equivalent to 96.7% while 1 of the 30 represented firms for which incentive has not been provided, percentage equivalent to 3.3%.
In Table 10: Source SPSS the firms for which incentive has been provided have the following statistics: Range = 40.99, Interquartile Range = 13.61, Skewness = -1.022 and Kurtosis = 0.270.
In Table 10: Source SPSS also, the firms for which incentive has not been provided have their statistics omitted since the data only has 1 observation. Carbon Emissions Disclosure Score is constant when Corporate Governance = No.
Figure 3: Source SPSS gives the proportion for firms for which incentive has been provided and firms for which incentive has not been provided. The graphical analysis show that firms for which incentive has been provided are more than firms for which incentive has not been provided.
The description of the dependent variable in terms of the independent variable is represented in the plot in Figure 4: Source SPSS below:
Figure 4: Source SPSS shows that the data from firms for which incentive has been provided is skewed to the left with a lot of the data points occurring between the -5 mark and -15 mark. This data has one outlier on data points 29.
Figure 4: Source SPSS also shows that the data from firms for which incentive has not been provided is only one observation. The skewness is not available for the data from firms for which incentive has not been provided. The data has no outliers.
For the analysis represented in Figure 4: Source SPSS the one outlier data point can be omitted from the subset. The outlier represent 3.45% of the entire sample therefore can be easily removed without affecting the analysis in the research.
COMPARISON OF ANALYSIS RESULTS
COUNTRY |
CORPORATE GOVERNANCE (Availability of Incentives) |
CARBON EMISSIONS (Percentage Reduction in Emissions for 2014) |
|||
Yes |
No |
Mean % |
Skewness |
Outliers |
|
UK |
23 |
7 |
9.7340 |
-0.112 |
5 |
USA |
29 |
1 |
9.1517 |
-1.022 |
1 |
CONCLUSION |
Incentives are available to more firms in the USA compared to the UK. |
More firms lack access to the incentives in the UK compared to the USA. |
On average, reduction in carbon emissions was slightly higher in the UK compared to the reduction in the USA. |
Data in both subsets was skewed to the left, with the data from the USA firms being more skewed than the data from the UK. |
The data from the UK subset had more outliers as compared to the data from the USA subset. |
Table 11: Comparative Analysis
The measurement of the Dependent Variable (Carbon Emission Disclosure Score Variable) is on the ratio scale while the measurement of the Independent Variable (Corporate Governance Variable) is on the ordinal scale.
Therefore, the most appropriate statistical test for the testing of the hypothesis of this research would be a T-Test. This is going to be achieved by carrying out a Logistic regression of the Corporate Governance Variable on the Carbon Emission Disclosure Variable.
The following assumptions will be made for the Statistical Test using Logistic Regression (Galit, et al., 2018):
The statistical test in this research will be carried out for both the UK Carbon Emissions 2014 subset and the USA Carbon Emissions 2014. In both tests the impact of Corporate Governance and Carbon Emissions Score will be measured and the hypothesis tested. After this, the two results will be compared to evaluate where the impact is more between the United Kingdom and the United States of America, and by extension between Europe and North America.
References
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Duh, M., 2010. APPLYING AGENCY THEORY AND THE RESOURCE-BASED VIEW IN EXPLAINING PERFORMANCE DIFFERENCES BETWEEN FAMILY AND NON-FAMILY BUSINESSES, Maribor.
Galit, S., Peter, B. C., Inbal, Y., Patel, N. R., & Kenneth, L. C. (2018). Data Mining for Business Analytics (1st ed.). New Delhi: John Wiley & Sons, Inc.
Ghazouani, T., 2013. Capital Structure through the Trade-Off Theory:Evidence from Tunisian Firm. International Journal of Economics and Financial Issues,, 3(3), pp.625–636.
Jensen, M. & Meckling, W., 1976. Theory of the Firm: Managerial Behavior, Agency Cost and Ownership Structure. Journal of finance and economics, 3, pp.305–360.
Jensen, M.C. & Meckling, W.H., 1976. Theory of the firms: managerial behavior, agency costs and ownership structure. Journal of Financial Economics, 3, pp.881–890.
KamelMadi, H., ZuainiIshak & AbdulManaf, . Author links open the author workspace.Nor Aziah, The Impact of Audit Committee Characteristics on Corporate Voluntary Disclosure.
Najah, M.M. & Cotter, J., 2010. Are climate change disclosures an indicator of superior climate change risk management?, Queensland.
Reid, E. & Toffel, M., 2009. Responding to public and private politics: corporate disclosure of climate change strategies. Strategic Management Journal, 30(11), pp.1157–1178.
Skaza, J., Student, E. & University, B., 2013. The Relationship between Economic Growth and Environmental Degradation: Exploring Models and Questioning the Existence of an Environmental Kuznets Curve, Smithfield.
Vergas1, N., Cerqueira1, A. & Brandão1, E., 2015. The Determinants of the Capital Structure of Listed on Stock Market Nonnancial Firms: Evidence for Portugal, Porto.
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