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revision_eco_env-i.docxThe Relationship between Economic Growth and Environmental Quality in the USA 2
Milestone One
The Relationship between Economic Growth and Environmental Quality in the USA
Comments: This is a very good research topic. You said "A regression analysis was conducted to examine the impacts of environmental pollution on economic development and vice versa"
Please keep it as it is but make sure you defined clearly the independent and dependent variables.
Note: highlighted you work or your revision
Milestone One
Introduction
The relationship between economic growth regarding job opportunities, market, income, and environmental quality have generated controversy for a long time. Is economic growth compatible with environmental quality? What impact do increased job opportunities and income have on an environment is a particular industry? How does condition of the environment influence the location of a firm, its expansion, and the economic growth of a community? Some economists have argued that greater development of the economy encourages pollution of the environment. In contrasts, some pundits believe too much resource in protecting the environment inhibit economic growth and promote loss of jobs (Acs and Armington, 2014). Neutralists believe economic growth should be tied to environmental sustainability programs to avoid a rift between capitalistic-economists and environmentalists. The debate is necessitated by the lack of significant empirical proof on how the quality of the environment is affected by economic growth and increased income for families.
This study evaluates the relationship between economic activities and environmental quality. One of the main hypotheses tested is whether communities with greater recorded rates of pollution encountered slower rates of employment but increase earnings for the employed individuals. High levels of earning would illustrate reduced levels of labor supply hence the need to compensate the remaining employees for the risks associated with pollution. The assumption is that higher levels of pollution impacts employment rates negatively due to risks such as respiratory diseases related to polluted air (Acs and Armington, 2014). Moreover, clean environment attracts skilled laborers thus a firm access them at a lower cost. Additionally, the costs of production are lower in regions with the clean environment because cleaner environment limits levels of sick leaves and increase employee’s productivity.
The second hypothesis argues that increased earning and reduced levels of employment reduces the levels of pollution leading to right environmental conditions in the country. The common hypothesis is that environmental quality and earning are related positively because an increase in earning encourages an increase in environmental mitigations programs that safeguards the interests of the environment (Stern, 2014). On the other hand, an increase in levels of employment encourages environmental degradation because of the scale effect. The said scale effect is a reflection of increased levels of economic activity in a particular region, holding constant the production techniques as well as the composition of final output. The second hypothesis assumes there is a positive relationship between pollution growth rates and employment. However, this is an assumption and hopes to prove it against the result of this study.
This study tries to determine if employment and income growth rates affect the rates of pollution in a given area and if pollution growth rates affected growth rates of employment and earned in the same region. This research examines various industries among them is manufacturing, agriculture, communication, transportation, utilities, services and retail trade. Notably, factors that determine the location of an industry and its expansion have baffled researchers and policymakers for a long time. The location and development of business have often been affected by tax rates, availability of labor, political manipulation, and the cost related to work, and opinions of trade unions (Stern, 2014). Though the impact of unionization, wages, energy price, and human capital are well studied, the impact of quality of life and environmental factors that influence the location of industries are rarely considered. Environmental regulations that advocate for clean water, clean air, and sound disposal of waste products have introduced a new dimension in the location and growth of industries as well as economic activity in general. Economists believe stringent environmental regulations programs inhibits growth and expansion of industries. Growth inhibition is encouraged by over taxation and increased the cost of sustaining the environment as provided in those environmental sustainability programs. The three primary variable affecting the growth and expansion of manufacturing firms are labor, tax, and environmental regulations in that order.
Alfred Weber developed a theory of industrial location in which he argued that the cost of transporting the raw material to the firm and the cost of transporting the finished product to the market determines the location of industries. The theory is popularly known as the location triangle theory. The theory argues for the location of a company between the supplier and the market to minimize the cost of transportation (Stern, 2014). The theory factored in the weight of raw material and the finished product. As such, if an investor were to choose between the market and point of supply, they would opt for a point from which the weight of materials transported is less. For instance, if finished products were lighter than raw materials, then the industry would be located near to the supplier since to minimize the cost of transportation. Weber’s model was more applicable during the industrial revolution period. However, the current industries are influenced by other variables other than the cost of transport. Nonetheless, in the event of locating industry that deals with heavy raw materials such as iron, coal, and aluminum, Weber’s theory come to play because the cost of transport may influence the profitability of the company. Even so, the evolving forces of market and globalization have introduced other variables such as environmental regulations laws that affect the location of industry.
Methodology and Data
A regression analysis was conducted to examine the impacts of environmental pollution on economic development and vice versa. The regression model established by Johansson (2000) facilitates the controlling of endogenous variables that influence economic growth, earnings, and pollution rates. Explanatory variables for employment growth rate are labor force, market characteristics, access to markets, electric and land prices, monetary and regulatory variables, environmental conditions and infrastructure, and urbanization measured that is measured by metro dummy (Li and Liu, 2015). The explanatory variables encompassed in the equation for earning growth rate are features of workers such as education level, gender, race, age, labor market condition, housing costs, unemployment benefits, environmental conditions, and social amenities. The environmental pollution growth rates variable entails formal regulations, population density, education, firm size, and the level of urbanization. Data on employment and earning was obtained from Regional Economic Information System and the U.S. Bureau of Economic Analysis. Data on per-worker environmental pollution rate was constructed from Environmental Impact Data, Rosebank Research and Statistical Analysis, and Department of Commerce. The data contain general information on land, air, sound, and land pollution. The rates of pollution per worker were obtained by dividing the total volume of pollution by the number of employees in that region. Notably, the majority of data used for this research is secondary data obtained from reliable sources. The data was preferred because it could be obtained quickly and cheaply. Moreover, the data could be quantified to aid in econometric analysis.
References
Li, X., & Liu, X. (2015). Foreign direct investment and economic growth: an increasingly endogenous relationship. World development, 33(3), 393-407.
Stern, D. I. (2014). The Rise and Fall of the Environmental Kuznets Curve. World development, 32(8), 1419-1439.
