("2004 Yearbook of Immigration Statistics," 2010) However, when you compare the unskilled immigrant with the skilled immigrants, it is clear that you are seeing a similar kind of scenario occurring. Where, they have lower costs of labor in comparison to those educated native workers. In those situations where the immigrants are unskilled, means that many state and local governments will face increased growth in the population. (Car, 2001) Yet, because the overall level of wages are small, means the revenues that are generated will have a limited impact on the community (as far as the government is concerned). Conversely, those immigrants who are more educated will make a larger contribution to the local economy. This is because their specialized education allows them to work in fields that have the potential for greater contributions, to the community and the government. In this particular case, the contributions that they would make towards the community could be through various innovations. They would benefit the state and local governments by paying higher taxes, for the services they use. The above numbers underscore the frustration that some native workers have, where they feel as if immigrants are keeping the cost of wages low. When the economy is facing different financial challenges, this means that there will be increasing amounts of debate regarding the total contribution of immigrants.
Estimated Regression Model
Regression analysis is when you are analyzing the relationship that exists between two or more variables, in correlation with the dependent variable. In this particular situation, the dependent variable would be how the U.S. economy is affected by the impact of immigration. The two independent variables would be the two groups of immigrants, skilled and unskilled. The general liner model is used to draw a relationship between the two groups of immigrants and their impact on the economy. This is when: you are using different independent variables and correlating it with the dependent variable. In this particular situation, skilled and unskilled immigrants would be the two independent variables, while the economy would be the dependent variable. The methods used to collect and analyze the data were: to take the actual immigration statistics used by the U.S. government. Then, analyze the trend and the positive / negative impact of immigration.
Upon looking at the results from the regression analysis conducted, it is obvious that there is a direct link as to how both skilled and unskilled immigrant workers will affect the economy. Analyzing the different trends that have been occurring, those states and cities that have a high influx of unskilled as well as skilled immigrant workers will see a rise in the unemployment rate and a decrease in labor costs. This is because many of the native unskilled / skilled workers will require more compensation than those of who are immigrants. As a result, the hypothesis that immigrants are making an impact upon the economy is correct. Yet, beneath the surface the impact is both positive and negative. Where, immigrant workers help to keep costs down and the skilled workers have made significant contributions to the community. Conversely, the both groups of immigrants will cause unemployment rates to rise and wages to fall. Together, both elements highlight the trade off that is taking place as a result of immigration. This is underscoring the true effects that immigration is having on the American economy. Where, there are distinct benefits (improved economic growth / lower prices) and drawbacks (unemployment rises / wages fall). This is the true effect of immigration on the U.S. economy.
2004 Yearbook of Immigration Statistics. (2010). Retrieved March 16, 2010 from Office of Immigration Statistics