Eco-env-and Eco revisions
Jambo
eco-env-ii.docxThe Relationship between Economic Growth and Environmental Quality in the USA 2
Milestone Two
The Relationship between Economic Growth and Environmental Quality in the USA
Comments: your work here is mainly a literature review and you should go beyond that. That being said, you should provide empirical evidence not just citing others.
Impacts: Alternative Techniques
Describes alternative techniques that could be used in estimating the same types of economic impacts, but the methods identified are not appropriate for the type of study or the description of the techniques lacks detail
Impacts: Perspectives: Discusses how analyses from alternative perspectives could provide consistent and/or inconsistent information to decision makers, but is lacking in detail or contains inaccurate information
Articulation of Response: Submission has major errors related to citations, grammar, spelling, syntax, or organization that negatively impact readability and articulation of main ideas
Milestone Two
The Results
The study revealed that higher rates of environmental pollution had a negative impact on the employment growth rates in the country. Those results showed whereas the federal government has implemented mechanisms to curb pollution, some states do not implement those policies or have varying policies concerning economic growth and environmental sustainability programs. Higher rates of individual’s pollution and environmental pollution rates were associated negatively with individuals earning growth rates. For instance, for every 10% increase in pollution, the earnings growth rates fell by 0.7% (Goh, 2012). The faults in this result could result from concentrating on air pollution variables and ignoring land and water pollution. Notably, these results reject the first hypothesis, which argued that increased level of pollution leads to a higher rate of earnings and decreased levels of employment in those polluted regions. Regarding the second hypothesis, initial rates of employment did not have any statistical impact on growth rates of pollution. However, the high levels of employment are associated with environmental degradation. These results indicate that employment growth rates might have occurred in both polluted areas and known polluted areas thus giving neutral results. Interestingly, increased rates of earning per worker were associated with reduced rates of environmental pollution (Goh, 2012). This negative correlation could be explained by an argument that increased earning rates led to a demand for the quality environment through an income effect. Similarly, public resources used to sustain the environment must have increased with increase in earning to provide a healthy and clean environment. The results also reveal that employees are more concerned with pollution thus asks for more pay when working in polluted areas than in clean environments. As such, communities that are environmental sensitive should
advocate for high-paying jobs and low pollution intensive companies. Such assumption confirms the second hypothesis that increased earnings encourage low levels of pollution thus improving the quality of the environment. The study also tried to establish the link between job opportunities created and the quality of those jobs. The result revealed that regions with initial higher rates of employment and earnings experienced higher growth rates of job opportunities and earnings indicating faster growth rates in higher paying industries. Perhaps those regions were associated with good social amenities that attracted more investors in those areas.
Analysis of individual industry revealed a partial relationship between increased earning and increased rates of pollutions. The effect of individual pollution rates on employment was negative for retail trade and agriculture but positive for transportation, utility, and communication industry. Such results imply that regions that had lower rates of individual pollution had a better chance of creating job opportunities in retail trade and agriculture industry. On the other hand, areas with higher levels of pollution recorded higher employment growth rates in communication, transportation, and utility industries (Eamets and Philips, 2015). Nonetheless, the general results indicate a reduction in pollution rates were accompanied with increased job opportunities. Those regions that experienced higher job growth rates and higher pollutions rates simultaneously must have ignored environmental sustainability programs at the expense of job opportunities. However, if the goal is to increase job opportunities and foster economic growth rates, the authority must implement programs that protect the environment. The national results from all the regions in the U.S. indicate that areas with initial higher rates of employment and higher growth rates of employment recorded lower levels of pollution in all industries investigated. Furthermore, growth in the agricultural sector was associated with reduced levels of pollution while growth in transportation, communication, and manufacturing industries led to increased rates of population. The reasons for this could be that farmers are more conscious about the environment since it affects the industry directly unlike stakeholders from other industry who might ignore the impact of environmental degradation.
The limitation of this data is that not all regions were considered for the research. Only states with more industries were chosen for the research. The limited data is therefore not a presentation of the whole country. Use of secondary data is also disadvantageous because it is prone to bias and manipulation. Regression analysis technique used in the study assumes that all variables remain unchanged. This assumption is not always correct since the variable is prone to other factors such as trend and education level that are not well discussed in the study as such, the study might have misleading and erroneous results. The use of limited data does not give a clear relationship between the variables in the study (Eamets and Philips, 2015). Moreover, the results kept on changing from region to region. Such results that are not consistent with the hypothesis cannot be relied on. Furthermore, the procedure calls for long and tedious calculations that are boring. Parameter instability resulted in changing of results. The study had to rely on the assumption to make conclusions rather than depending on the analyzed data. Such errors can only be corrected if a future research is carried out and compared to this one. Moreover, the data used in the research and regions covered should be increased to obtain a nationalistic image. Future results should use different questions and hypothesis. The null hypothesis should also be included in the future to verify the results obtained.
References
Anselin, L. (2012). Under the hood issues in the specification and interpretation of spatial regression models. Agricultural Economics, 27(3), 247-267.
Eamets, R., & Philips, K. (2015). Job Creation and Job Destruction in Estonia: Labor Reallocation and Structural Changes. Discussion Paper, Institute for the Study of Labor.
Forni, M., & Reichlin, L. (2010). The generalized dynamic factor model: Identification and estimation. Review of Economics and Statistics, 82(4), 540-554.
Goh, C. (2012). Exploring the impact of climate on tourism demand. Annals of Tourism Research, 39(4), 1859-1883.
Hanley, N., & Wright, R. E. (2011). Choice Modelling Approaches: A Superior Alternative for Environmental Valuation?. Journal of economic surveys, 15(3), 435-462.
Nondo, C., & Fletcher, J. (2009). An empirical analysis of the interactions between environmental regulations and economic growth. West Virginia University Libraries.
.
