Study On Carbon Emissions And Incentives Provided To Companies In USA

Literature Review

The world is highly devastated with the emission of carbon and that is the reason for the climatic changes across the globe. Thus, it is of utmost importance to reduce the emissions of carbon and green-house gases. The management of several companies have provided incentives to the companies if they are successful in reducing the carbon emissions. The carbon emissions are also dependent on the countries. Thus, the main aim of this study is to evaluate whether the companies receiving incentives are emitting lesser carbon than the companies that do not receive any incentives.

The emission of carbon dioxide along with other greenhouse gases have been increasing gradually. This increase in the emissions is responsible for the global warming and as a result of which, massive climatic changes can be observed across the globe. Thus, urgent actions need to be taken to reduce the emissions of carbon as well as other greenhouse gases by the companies. Different nations have called upon different agreements which can be acting as the major stakeholders and helping the companies to come up with different strategies which will be helpful in the reduction of the emissions. These strategies can also be integrated into the economic production of the companies so that their objectives as well as their goals can be achieved (Cui, et al.  2014, p. 1049). Thus, within different countries, it is required by different companies to integrate in the processes of their productions, technologies so that the green economy can be achieved (Dietz, 2009, p. 18454). It can be said from various analyses and researches that some companies have experienced a reduction in the emission of carbon dioxide which is much higher than some other companies. Most of the firms overemphasize the economic growth of the company at the cost of the emission of carbon (Wei, et al. 2013, p. 27).

Therefore, from the discussions, it is clear that there is a target for the reduction of carbon by the companies which they are unable to meet and there are various reasons behind that. These reasons include the overemphasis of the economic growth at the cost of emission of carbon, missing data in the reporting of emission of carbon and its effects, lack of the support from the stakeholders all these have resulted in the less reduction of carbon emissions by the companies (Druckman, et al. 2011, p. 3579).

The dependent variable in this research is the percentage change in the emission of carbon dioxide.

The independent variable considered for this study is the incentives provided by the management to different companies. The answers to this variable are categorical denoting Yes and No.

The control variable considered in this study is the country which will be considered for performing this study. For this study, the chosen country is USA.

The null and alternate hypothesis required for this study that can be framed from the conceptual model is described as follows:

Null Hypothesis: There are no such difference between the emissions of carbon by the American firms that provide incentives and that do not produce incentives.

Dependent Variable

Alternate Hypothesis: There are significant differences between the emissions of carbon by the American firms that provide incentives and that do not produce incentives.

In order to conduct the analysis, a sample of 293 companies in USA has been considered. The reduction in the carbon for these companies have been noted and the incentives provided by these firms or not are also illustrated. The dataset had information on a lot of companies across the world, but there were a lot of missing values in the dataset. At first, all the USA companies has been selected and the missing values has been eliminated from the dataset thus reducing the sample size to 293 companies across USA. The missing values were obtained in the dataset as some of the companies were not willing to share their information regarding the emission of carbon. Thus, to make the analysis robust, the missing values are omitted from the dataset.

In order to understand the nature of the data obtained, a descriptive statistical analysis has been conducted on the data extracted on the 293 USA companies. These companies have been selected randomly from the list of all the USA companies. As already discussed, the independent variable is whether the companies are providing incentives to the customers and the dependent variable is the percentage change in the emission of carbon dioxide by the companies. It can be seen very clearly from the analysis conducted that most of the companies have been producing incentives on reaching the target of reduction in the emission of carbon. Thus, among the 293 selected companies, it can be seen very clearly that 206 companies have been provided with incentives by the managements on achieving the set target of reduction in the emissions which comprise of 70.3 percent of the population. Similarly, 86 companies on the other hand has been observed not to be receiving incentives from the management of the companies. This non receiving companies form almost 29.4 percent of the population. It can also be seen from the table that 1 out of the 293 selected companies did not disclose their information. Thus, from here, it can be said that a very little proportion of the companies are not interested in disclosing the information regarding the incentives received form the management or not. The data is summarized and tabulated in table 1 and illustrated graphically in figure 1.

Figure 1: Histogram showing the number of companies receiving incentives

The next descriptive analysis has been conducted in order to provide some insight to the dependent variable of the study, which is the percentage change in the emission of carbon by different companies. This variable considered as the dependent variable is a continuous and a numerical variable. Thus, descriptive statistics summary has been conducted with the help of appropriate statistical techniques in order to understand the nature of the data in the variable.

Table 2 gives the information and the results of the descriptive statistical analysis. It can be seen from the table that the average change in percentage of the carbon by the companies is -2.63 percent, which is a negative amount indicating that in most of the firms, there has been a reduction in the emission of carbon from the previous years and the reductions in the emissions has dominated the non-reductions in the 86 other firms. On the other hand, it can be seen clearly from the results that the median percentage change in the carbon emission has also been found to be negative (- 3.5 percent). This indicates that in 50 percent of the firms, the change in carbon emission is more than – 3.5 percent, which indicates that in most of the firms there has been a reduction in the emission of carbon. Thus, there must be outliers present in the data which is affecting the mean measure. In other words, there are some companies which have been emitting carbon a lot higher than the previous years and thus the reduced companies are not being affected by this information. Moreover, it can also be seen from the standard deviation value that the deviation in the data is extremely high and the values are not at all close to the average percentage change in carbon emission. The value of skewness shows that the data on percentage change in the emission of carbon by the companies is skewed positively. That is, more companies have reduced the emission, while lesser companies have increased the emission.

The hypothesis stated above in the hypothesis section can be tested with the help of necessary inferential statistical techniques. In this case, the data present can be divided into two different groups, one is the group of companies that receive incentives and the other is the group of companies that do not receive incentives. The test will be conducted on the difference in the average percentage change in the reduction of carbon emission between these two groups of companies. This test can be conducted with the help of independent sample t-test, which is the most appropriate test to be used for testing the difference in the means of two groups.

References

Cui, L.B., Fan, Y., Zhu, L. and Bi, Q.H., 2014. How will the emissions trading scheme save cost for achieving China’s 2020 carbon intensity reduction target?. Applied Energy, 136, pp.1043-1052.                                                        

Dietz, T., Gardner, G.T., Gilligan, J., Stern, P.C. and Vandenbergh, M.P., 2009. Household actions can provide a behavioral wedge to rapidly reduce US carbon emissions. Proceedings of the National Academy of Sciences, 106(44), pp.18452-18456.

Druckman, A., Chitnis, M., Sorrell, S. and Jackson, T., 2011. Missing carbon reductions? Exploring rebound and backfire effects in UK households. Energy Policy, 39(6), pp.3572-3581.

Wei, M., Nelson, J.H., Greenblatt, J.B., Mileva, A., Johnston, J., Ting, M., Yang, C., Jones, C., McMahon, J.E. and Kammen, D.M., 2013. Deep carbon reductions in California require electrification and integration across economic sectors. Environmental Research Letters, 8(1), p.014038.

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