Everyone one should have the right to earn a livable wage, right? No one should be stuck in a job that forces them to work in subhuman conditions for a wage that does not allow them to provide for their families. Not raising the minimum wage will punish those who are the most disadvantaged in our society and keep people living in poverty. These are the concerns raised over the debate to adjust the minimum wage at either the Federal or State levels. Arguments like these are made out of pure emotion without actual data to back them up. The debate often lacks answers to crucial questions like what effect has previous minimum wage increases had, who makes up the majority of minimum wage workers, and how do we determine to what level the minimum wage is determined?
What is the function of the minimum wage?
The minimum wage was implemented as part of the fair standards act during the New Deal. It's intention was to ensure that every employee no matter how unskilled or productive could earn a "decent" wage. It was originally set at twenty-five cents when the law was past in 1938 and is currently $ 7.25. The decent wage was originally set arbitrarily and increased infrequently as a result of cost of living and inflation demands. The changes were rarely made in relation to actual market fluctuations in the labor market and mostly made for political gain. Minimum wage increases are an easy way for a politician to champion a cause that endears them to a large segment of the population who can sympathize. On the surface it seems reasonable to set a floor for the wages that a worker can earn. The rationale came from the horror stories of underage factory workers getting paid very little for excessive amounts of work. But what are the actual effects of minimum wage increases and is public opinion correct?
What happens when the minimum wage increases?
Once the minimum wage is increased very little public scrutiny is given to the results. The politicians make the case, pass the law, and leave analysis to the academics. It is important to look at the results because the issue will never disappear and the country must understand how to make the correct decisions. Research from the Journal of Human Resources examined the effects of a minimum wage increase. The results showed that the group most affected by the change were low income workers who initially saw an increase in their income. The long term effects showed that the low income workers also experienced lower overall employment and total working hours after the wage increase. The data shows that when faced with higher labor costs, employers cut part time and low skill workers first and then scale back the hours of those that remain to minimize the increase operational costs.
Other data shows that there appears to be a correlation between high minimum wages and real unemployment among low income and unskilled workers. Compared with the federal minimum wage (7.25), the states with the highest minimum wages are as follows: California ($8.00), Massachusetts($8.00), Vermont ($8.60), Connecticut ($8.25), Illinois ($8.25), Nevada ($8.25), Oregon ($8.95), and Washington ($9.19). Of these States, only Vermont and Massachusetts fall below the US average for real unemployment rates (U-1,2,3,4,5,6). Real unemployment includes those that are seeking work but have not found employment which includes a large number of minimum wage level workers. These results show a possible link but there are many factors that also affect the unemployment rate along with the minimum wage. The numbers reflect a total unemployment which means that the States with a higher skilled and older workforce will be less affected by the minimum wage fluctuations.
| Column1 | U-1 | U-2 | U-3 | U-4 | U-5 | U-6 |
| Los Angeles County | 6.4 | 5.8 | 10.9 | 11.5 | 12.6 | 20.8 |
| Nevada | 6.4 | 6.3 | 11 | 11.9 | 13.3 | 20.3 |
| California | 6.2 | 5.8 | 10.4 | 11.1 | 12.2 | 19.3 |
| Rhode Island | 6.3 | 6.6 | 10.5 | 10.9 | 11.8 | 17.6 |
| Oregon | 4.2 | 5.1 | 8.9 | 9.1 | 10.1 | 17.2 |
| Washington | 4.3 | 4.7 | 8.3 | 8.7 | 10.1 | 16.9 |
| Michigan | 5.2 | 5 | 9.1 | 9.8 | 11 | 16.6 |
| North Carolina | 5.7 | 5 | 9.2 | 9.6 | 10.7 | 16.3 |
| Florida | 5.4 | 4.9 | 8.4 | 9.3 | 10.1 | 16 |
| Illinois | 5.3 | 4.9 | 8.7 | 9.3 | 10 | 16 |
| Arizona | 3.9 | 4 | 8.2 | 8.8 | 9.8 | 15.9 |
| New York City | 6.6 | 5.5 | 9.4 | 10.3 | 11.4 | 15.8 |
| South Carolina | 5.4 | 4.9 | 9.4 | 10.1 | 11.2 | 15.8 |
| New Jersey | 5.9 | 5.9 | 9.5 | 10.1 | 11 | 15.7 |
| Georgia | 5.4 | 4.4 | 9.1 | 9.9 | 10.7 | 15.7 |
| Mississippi | 5 | 4.4 | 8.9 | 9.4 | 11.1 | 15.1 |
| Maine | 3.9 | 4.4 | 7.7 | 8 | 9.3 | 15 |
| New York | 5.5 | 5 | 8.7 | 9.3 | 10.3 | 14.9 |
| Connecticut | 5.3 | 5.2 | 8.4 | 9 | 9.8 | 14.7 |
| United States | 4.5 | 4.4 | 8.1 | 8.6 | 9.5 | 14.7 |
| Colorado | 4.2 | 4.5 | 8.1 | 8.4 | 9.3 | 14.6 |
| Indiana | 3.9 | 4.6 | 8.3 | 8.6 | 9.3 | 14.2 |
| District of Columbia | 6.1 | 4.3 | 9 | 9.5 | 10.7 | 14.1 |
| New Mexico | 3.9 | 3.4 | 7.1 | 7.5 | 8.8 | 14.1 |
| Idaho | 3.6 | 3.2 | 7.1 | 7.4 | 8.3 | 14 |
| Pennsylvania | 4.3 | 4.7 | 7.8 | 8.3 | 9.2 | 13.9 |
| Delaware | 4.2 | 4.3 | 7.2 | 7.7 | 8.7 | 13.9 |
| Kentucky | 3.9 | 4.3 | 8 | 8.4 | 9.2 | 13.8 |
| Montana | 2.6 | 3.1 | 6.1 | 6.4 | 7 | 13.7 |
| Ohio | 3.7 | 3.8 | 7.2 | 7.7 | 8.6 | 13.6 |
| Alabama | 4.6 | 4.5 | 8 | 8.6 | 9.6 | 13.5 |
| Tennessee | 4.2 | 4.4 | 7.8 | 8.4 | 9.1 | 13.3 |
| West Virginia | 3.9 | 4.1 | 7.4 | 7.9 | 8.5 | 13.1 |
| Wisconsin | 3.5 | 4 | 7.1 | 7.5 | 8.4 | 13.1 |
| Alaska | 3.1 | 4.1 | 7.4 | 8.1 | 8.9 | 13 |
| Arkansas | 3.4 | 3.6 | 7.6 | 7.9 | 8.9 | 13 |
| Massachusetts | 3.7 | 3.9 | 6.7 | 7.2 | 7.9 | 12.9 |
| Hawaii | 3.3 | 3.2 | 6 | 6.4 | 7.5 | 12.8 |
| Missouri | 3.5 | 4.1 | 6.9 | 7.3 | 8 | 12.5 |
| Maryland | 3.9 | 3.8 | 7 | 7.6 | 8.5 | 12.1 |
| Texas | 3.3 | 3.3 | 6.7 | 7.1 | 7.8 | 12.1 |
| Louisiana | 3.9 | 3 | 7.1 | 7.6 | 8.5 | 11.9 |
| Virginia | 3.2 | 2.8 | 6 | 6.5 | 7.3 | 11.7 |
| Minnesota | 2.7 | 3.1 | 5.8 | 6 | 6.9 | 11.7 |
| Utah | 2.7 | 3 | 5.8 | 6.2 | 6.8 | 11.2 |
| New Hampshire | 2.9 | 3.3 | 5.6 | 6 | 6.7 | 11.2 |
| Vermont | 2.1 | 2.9 | 5.1 | 5.4 | 6.3 | 11 |
| Kansas | 2.6 | 2.8 | 5.6 | 5.9 | 6.7 | 10.2 |
| Wyoming | 2.1 | 2.5 | 5.5 | 5.7 | 6.4 | 10 |
| Iowa | 2.3 | 2.6 | 5.1 | 5.3 | 6.1 | 10 |
| Oklahoma | 2.2 | 2.9 | 5.1 | 5.4 | 6.3 | 9.6 |
| Nebraska | 1.7 | 1.9 | 4 | 4.3 | 4.7 | 8.8 |
| South Dakota | 1.4 | 2 | 4.6 | 4.9 | 5.5 | 8.5 |
| North Dakota | 1 | 1.5 | 3.2 | 3.4 | 3.9 | 6.1 |
- U-1, persons unemployed 15 weeks or longer, as a percent of the civilian labor force;
- U-2, job losers and persons who completed temporary jobs, as a percent of the civilian labor force;
- U-3, total unemployed, as a percent of the civilian labor force (this is the definition used for the official unemployment rate);
- U-4, total unemployed plus discouraged workers, as a percent of the civilian labor force plus discouraged workers;
- U-5, total unemployed, plus discouraged workers, plus all other marginally attached workers, as a percent of the civilian labor force plus all marginally attached workers; and
- U-6, total unemployed, plus all marginally attached workers, plus total employed part time for economic reasons, as a percent of the civilian labor force plus all marginally attached workers.
Although there is an apparent correlation between the real unemployment and minimum wage is is unclear if the minimum wage affects the hiring or the firing of employees. The unemployment numbers do not tell the whole story because each State's economy is unique with differing circumstances that affect the unemployment rate independent of the minimum wage. The make up of the State's demographics and economy play a role in the minimum wage affect. According to the Bureau of Labor Statistics, minimum wage workers are mostly under the age of 25, single, no more than a high school education, and work in the service or hospitality industry. Many other economic circumstances can affect the employment numbers of this demographic including the affluence of the areas, marital status, overall state economy and other unforeseen circumstances. The following graph shows the employment rates in each state for that demographic:
Regardless of the unemployment, an increase in the minimum wage has a tangible effect on the way that employers operate. Many economists agree that there is an inverse relationship between minimum wage and unemployment, especially among low skill and young workers. When the minimum wage increases, it increases the cost on a business that employs minimum and low skill workers. The unemployment demographic distribution in each State with the highest minimum wage is shown below:
| Group | Unemployment Rate | ||||||||
| US | CA | CT | IL | MA | NV | OR | VT | WA | |
| Total | 8.1 | 10.4 | 8.4 | 8.7 | 6.7 | 11.0 | 8.9 | 5.1 | 8.3 |
| Men | 8.2 | 10.4 | 9.1 | 9.0 | 7.5 | 12.0 | 9.3 | 5.4 | 8.4 |
| Women | 7.9 | 10.4 | 7.7 | 8.4 | 5.8 | 9.7 | 8.4 | 4.9 | 8.2 |
| White | 7.2 | 10.1 | 7.8 | 7.7 | 6.4 | 10.7 | 8.7 | 4.9 | 8.3 |
| White, men | 7.4 | 10.1 | 8.1 | 8.2 | 7.1 | 11.7 | 9.0 | 5.1 | 8.2 |
| White, women | 7.0 | 10.2 | 7.3 | 7.3 | 5.7 | 9.5 | 8.2 | 4.6 | 8.3 |
| Black or African American | 13.8 | 17.3 | 14.9 | 16.0 | 12.1 | 16.4 | 18.4 | 17.7 | 14.7 |
| Black or African American, men | 15.0 | 17.8 | 19.1 | 18.1 | 14.5 | 18.4 | 22.6 | 10.5 | 14.3 |
| Black or African American, women | 12.8 | 16.8 | 11.0 | 14.4 | 9.9 | 14.3 | 11.4 | 5.5 | 15.2 |
| Hispanic or Latino ethnicity | 10.3 | 12.7 | 15.7 | 10.2 | 9.8 | 13.6 | 10.0 | 3.1 | 11.2 |
| Hispanic or Latino ethnicity, men | 9.9 | 12.1 | 17.1 | 9.9 | 12.2 | 14.9 | 13.4 | 3.8 | 9.0 |
| Hispanic or Latino ethnicity, women | 10.9 | 13.5 | 14.2 | 10.5 | 7.0 | 11.8 | 23.3 | 3.4 | 14.3 |
| Total, 16 to 19 years | 24.0 | 34.6 | 25.4 | 27.1 | 20.2 | 25.6 | 15.9 | 5.6 | 28.6 |
| Total, 20 to 24 years | 13.3 | 15.9 | 13.4 | 15.0 | 9.2 | 15.2 | 7.9 | 19.8 | 12.0 |
| Total, 25 to 34 years | 8.3 | 10.1 | 9.1 | 7.9 | 6.8 | 11.3 | 8.7 | 12.2 | 7.5 |
| Total, 35 to 44 years | 6.6 | 8.5 | 6.5 | 6.6 | 5.0 | 9.0 | 6.9 | 6.6 | 6.3 |
| Total, 45 to 54 years | 6.2 | 8.3 | 6.9 | 8.0 | 5.5 | 8.6 | 6.9 | 2.4 | 7.8 |
| Total, 55 to 64 years | 5.9 | 8.2 | 6.0 | 6.4 | 6.0 | 9.2 | 4.3 | 4.0 | 6.4 |
| Total, 65 years and over | 6.2 | 9.3 | 7.6 | 4.6 | 6.1 | 11.9 | 21.7 | 2.9 | 8.1 |
| Men, 16 to 19 years | 26.8 | 37.6 | 33.8 | 29.2 | 22.9 | 28.8 | 19.1 | 6.0 | 33.4 |
| Men, 20 to 24 years | 14.3 | 16.1 | 16.3 | 15.9 | 12.2 | 16.7 | 9.0 | 15.6 | 12.8 |
| Men, 25 to 34 years | 8.2 | 9.7 | 10.3 | 8.2 | 8.0 | 12.7 | 9.2 | 8.9 | 8.0 |
| Men, 35 to 44 years | 6.4 | 8.0 | 5.9 | 6.3 | 5.9 | 9.7 | 6.1 | 4.4 | 5.4 |
| Men, 45 to 54 years | 6.2 | 8.4 | 7.2 | 8.7 | 5.9 | 9.8 | 7.3 | 3.7 | 7.4 |
| Men, 55 to 64 years | 6.3 | 9.0 | 6.3 | 7.2 | 6.0 | 9.7 | 4.0 | 3.6 | 6.6 |
| Men, 65 years and over | 6.2 | 9.3 | 7.4 | 4.0 | 6.1 | 10.2 | 24.8 | 3.9 | 9.1 |
| Women, 16 to 19 years | 21.1 | 31.5 | 18.2 | 25.2 | 18.0 | 20.0 | 12.6 | 5.0 | 23.7 |
| Women, 20 to 24 years | 12.1 | 15.6 | 10.4 | 14.1 | 6.0 | 13.5 | 6.5 | 11.2 | |
| Women, 25 to 34 years | 8.4 | 10.8 | 7.7 | 7.6 | 5.6 | 9.7 | 8.2 | 6.8 | |
| Women, 35 to 44 years | 6.8 | 9.1 | 7.3 | 7.0 | 3.8 | 8.3 | 7.7 | 7.4 | |
| Women, 45 to 54 years | 6.2 | 8.1 | 6.7 | 7.2 | 5.2 | 7.3 | 6.5 | 8.3 | |
| Women, 55 to 64 years | 5.6 | 7.3 | 5.8 | 5.6 | 6.0 | 8.6 | 4.7 | 6.2 | |
| Women, 65 years and over | 6.3 | 9.3 | 7.7 | 5.4 | 6.2 | 14.2 | 6.8 | ||
(Data from US Census)
California is particularly bad across the board while Massachusetts and Vermont appear to be outliers once again. The linear regression analysis of the census data shows that education attainment level and median income are significant factors in driving up the minimum wage in these States. Both Vermont and Massachusetts have a population that has attained a higher level of education than the country as a whole. Each State has an economy that is based on education, information, or professional services which are generally higher paying and more secure compared to the service industries. Of the states with the highest minimum wages, both Vermont and Massachusetts have unusually high populations in terms of education and income level, which would mean both states may be more immune to unemployment effects of minimum wage increases. Other factors come in to play when talking about these states because each have unique demographic profiles. Vermont has a large seasonal and retirement residency that affect the overall need for minium wage workers.
Who is affected?
To definitively understand the minimum wage effects you have to understand who it affects and what choices are presented to those effected. Individuals with a job that pays the minimum wage are directly affected by any change to the wage level. An increase immediately increases their income and increases their purchasing power. Secondly, those out of work and collecting welfare are affected in that an increase in the minimum wage may make them more likely to take a job since many jobs are more attractive with a higher wage. An increase in the minimum wage forces employers to change the wages that they offer at the lower end of their pay scales. An increase in the minimum wage will create an upward force on many lower level jobs. The employers are directly affected by an increase in the minimum wage because they incur the added cost of employing each minimum wage worker. The customers and shareholders of companies ultimately pay for any added cost of production by the increase in wages.
Although common assumptions believe that an employer will fire workers once the minimum wage increases, there are other options to avoid this circumstance. Employers may choose to cut costs in other ways in order to mitigate the added costs of increased wages. The employer may choose to cut back on hours, benefits, or bonuses. The employers tend to offer lower wages and fewer hours to low skill workers, instead of reduction in the work force. Data from the Journal of Human Resources shows that the net reduction in hours affects workers making up to those earning 1.5 times the minimum wage. The statistical analysis shows that there are small decreases in compensation for higher wage workers in relation to minimum wage workers. The reduction in hours seems to put renewed emphasis on the U-6 unemployment numbers. U-6 measures the unemployment including those who are working fewer than 40 hours a week but seek full employment. If employers cut hours and benefits instead of overall employment, then the youth unemployment numbers would hide the true effects of the minimum wage increase. This assumption reaffirms the correlation shown between the U-6 unemployment and the minimum wage level.
The Department of Health and Human Services released a study in 2009 that confirmed the earlier assumptions that low wage workers are statistically mostly female, educated through no more than high school, caucasian, in their 20's, and single. Given these realities, it can be assumed that a majority of their earning potential and productive employment is ahead of these individuals. Cut backs in hours and benefits adversely affects this highly vulnerable population because they are most likely the only or primary income in their household. The unintended consequences of a minimum wage increase leads to a reduction in benefits that these individuals can not afford. A reduction in hours or employment overall of this population also restricts this population's ability to develop their "human capital".
Human Capital and Indirect Compensation of Minimum Wage Workers:
(Thomas Sowell, Sr Fellow Hoover Institute)
In a healthy economy, most of the workers with specialized skills find work that is comparable to their skill set and low skill workers find entry level (mostly minimum wage work). The low skill workers exercise their social mobility by accumulating human capital. Human capital includes training and skills that they develop on the job which increases their demand (and wages)in the labor market. The skills and training they acquire may or may not be applicable to other jobs but it gives them the ability to climb the wage scale with their employer. In ideal situations, all low skill workers that desire work would be able to find at least some type of minimum wage job to build their human capital. The more skilled workers a labor market has, the greater the productivity and quality of the goods and services produced. This makes society in general better off than they were before. Unfortunately as the labor market loses human capital, productivity decreases and the economy is worse off in comparison. The goal of a health economy is social mobility and enrichment of the society as a whole. Personal improvement is central to that creed and can only be accomplished with ample opportunity. The HHS report shows that over half of the low wage workers surveyed in 2001 found better opportunities and wages just 2 years later (5% found high wage jobs). Increasing the minimum wage may seem to help those most in need but it may take opportunity for so many more who have yet to find employment. Increasing the minimum wage is a step to institutionalizing the minimum wage class where the incentive to move upward is decreased. People are creatures of habit and are sensitive to incentives whether it be against their own interests.
Poverty rates and minimum wage:
The tax payers ultimately pay for those that can not find work as a minimum wage workers through unemployment insurance, medicaid, and welfare payments. The overall effects on the economy are unclear due to the overall complexity but some educated assumptions can be formed. The idea that raising the minimum wage can lift the poor out of poverty is fundamentally flawed. If that policy was affective, an increase of the minimum wage to 100 dollars an hour would solve most of the poverty in the country. The problem is once the minimum wage is increased it initially gives the workers increased purchasing power. Consequently, the employers have to adjust all of their wages upwards which again momentarily boosts the wages and purchasing power of the employees. Unfortunately, to mitigate the costs, the employer would have to cut back on hours and benefits so greatly they may even need to reduce the workforce and even close shop if the higher wages make the employer go out of business altogether. Over time higher wages creates higher aggregate demand which causes inflated prices of goods and services. As prices increase, the purchasing power of the workers decreases and returns to an equilibrium similar than before except now there is added inflation which is not factored in to minimum wages to begin with. If the supply of goods and services does not keep pace with demand there will be constant upward pressure on prices. Unfortunately in this case the labor cost increases prevent the supply from keeping pace. Without inflation adjustments the minimum wage workers fall further behind. The drawback to automatic wage increases is an automatic inflation factor in the local economy. A proverbial double edged sword.
The poverty rates in the country are largely driven by regional economic factors outside of the minimum wage but it still affects how the local economy functions. If fact, on-the-job training that can be acquired while working in a minimum wage job can equalize some of the education disparity that perpetuates much of the poverty problems in the hardest hit states (note the educational attainment and poverty level correlation). This further emphasizes the need for alternative methods of education and the development of human capital. The more workers that the labor market educates, the more likely to climb out of poverty. The labor market can reach and educate scores more workers, for less cost, and with greater quality than any government jobs program. When the price of this education increases, the economy loses human capital which is crucial to fight poverty.
Some basic economic principles apply to the effects of increasing the minimum wage. The foundation of economics is that there is an inverse relationship between price and demand and a direct relationship between supply and price. In this case if you increase the price of a job (wage) you increase people who want that job but you decrease the supply of employers who are willing to provide that job at that given price. Given that relationship, if an artificial price floor (minimum wage) exists, there will be a shortage of jobs provided (see below).
Philosophically, there are two outlooks when it comes to the minimum wage debate. The supply side says that the minimum wage should be kept low or none at all to keep the cost of production down and thus increasing employment and the development of human capital on a larger scale. The other side states that the wages for the low skill workers need to be increased to boost their purchasing power and thus stimulate the aggregate demand. The problem with stimulating the aggregate demand is it is impossible to know the actual effects since the costs of production would increase immediately and adversely affect production anyway.
As noted previously, there are a multitude of factors that the minimum wage could affect. A quick way to determine if there is a relationship between two variables is to conduct a simple correlation analysis and quantify it with a linear regression. In the case of the minimum wage, since it is artificially determined by the legislature it is almost always the independent variable. The correlation analysis can be used to show that some demographic factors affect the minimum wage. The dependent variables can be the unemployment rate, poverty rate, wealth (GDP), and aggregate numbers of minimum wage workers.
Correlation Analysis:
1. Min Wage vs. Income
A correlation analysis shows that there is a positive relationship between a State's minimum wage. This means that the higher the median income of an area pushes up the minimum wage. This is a logical result because generally higher incomes reflect higher costs of living in a given area. The R squared term is .21. This means that 21 percent of the variation in the minimum wage is explained by the variations in the median wage. This number is less significant on its own, but becomes important when compared to the R squared terms of the other variables.
2. Min Wage vs. GDP
The relationship between the minimum wage and the state GDP is slightly positive. The relationship is so faint that it is not significant because the R squared term is .0015 and the correlation coefficient is .00000008 which means there is virtually no correlation between the two variables. this result is not that surprising since GDP is affected by so many factors and minimum wage only affects a fraction of the aggregate workforce.
3. Min Wage vs. Education
The US Census divides education attainment in to three categories to compare states. The three categories are high school, undergraduate, and post graduate education attainment. The minimum wage has a positive correlation with the percentage of the population with at least a high school education. The high school variable has a R squared value of .19 (or it explains 19 percent of the variation of the minimum wage level). The slope of the best fit line is .30 which determines the degree by which the correlation exists. The R squared value for the college level education is .17 with a slope of .17 as well. The R squared value for the post graduate statistic is .10 with a slope of .21. These numbers suggest that the strongest indicator of the minimum wage is the percentage of the population with at least a high school education. This correlation is much larger than the GDP predictor and larger than the income predictor.
4. Min Wage vs. Unemployment
The correlation between the Minimum Wage level and the overall unemployment is extremely small if existent at all. Although the slope shows a strong negative correlation strength, the R squared value is .0049 which barely registers as a correlation and any tend is most likely chance. The unemployment for each minority group follows the same trend and shows little to no correlation.
5. Min Wage vs. Poverty rate
Central to the argument of a higher wage is its presumed effect on the poverty rate. The correlation analysis shows that there is a small correlation between the two variables with an R squared term of .09 and a negative slope of 21. The caveat to this result is that the areas with higher minimum wages tent to be more affluent and thus have lower poverty rates to begin with. Since the correlation is small but not insignificant, any conclusions must be mitigated.
6. Min Wage vs. Percent of population working at the minimum wage
The correlation between these two variables yields an R squared term of .09 and negative slope of nearly negligible degree. This like the unemployment numbers should be noted but their effect should be mitigated in the overall analysis.
7. Min Wage vs Welfare distributions
The correlation between the percentage of the population receiving welfare and the minimum wage is small but large enough to show some significance. The R squared term is .11 and the slope is 63 which means the correlation is strongly positive but again with a small R squared term, the correlation is limited.
Regression Analysis:
A regression analysis of the minimum wage data shows that any affect on the poverty rate and unemployment are nil and any correlation is by chance. A coefficient shows the percentage of the dependent variable (y) is described by the dependent variable (x). In relation to the poverty rates, the coefficient of the minimum wage level is .0021 with a high probability the correlation is by chance. In relation to the unemployment rates, the minimum wage date show little significance and mostly based on chance than an actual relationship between the variables.
Conclusions/Discussion:
The date remains somewhat muddled after the analysis. The only conclusive data seems to indicate that the affluence of an area indicates the minimum wage level. This follows that assumption that the cost of living is usually higher in areas of significant affluence. Second, the data shows that there appears to be a small correlation between the minimum wage rate and the number of people receiving welfare distributions. Outside of those conclusions, the results are open to interpretation.
Minimum wage policy is a sensitive issue since it involves the most economically vulnerable members of our society. Given the affects on business and the needs of the individual there is a fine line regarding the correct solution. Because the overall affects of increases are muted as related to there effects on the unemployment and poverty rates, there is some wiggle room for policy makers. There are limits to any positive effects of a minimum wage increase. If you increase it too far, you reduce the workforce from what it otherwise would have been. The problem is, no single person knows that economic sweet spot that maximizes the positive effects of such a policy. Only can the market dictate what that economic sweet spot based on the prevailing wages. The dangers of institutionalizing such decisions lead to artificially high minimum wages that lower overall employment among vulnerable groups and create inflation. Given that the minimum wage rate has very little correlation to the poverty rate and unemployment numbers it is dangerous to increase arbitrary price levels on the economy with little benefit.
On the other side of the coin, minimum wages are largely exempt from inflation indexing and can actually be lower then they need to be in some cases. Although each State economy is hard to compare due to the wildly differing make ups, it is clear that indexing the minimum wage may be a successful structure that makes sure the minimum wage does not fall behind other wages.
The human capital payment can not be forgotten in this debate. Education and training available to minimum wage workers is invaluable and should not be pushed aside and needs to be in the conversation when discussing the minimum wage levels. Education is at a premium in the highly competitive job market and must be acknowledged in the compensation debate.
John F. Kennedy famously said in relation to the economy that "A rising tide lifts all boats" and that is the case with the minimum wage. So long as the economy is allowed to expand mostly unencumbered, many earning the minimum wage today will exercise their economic mobility to earn a livable (or more) wage in the future years. This can not happen if we have government officials making arbitrary decisions on the economy because it is up to chance as to if they made the correct decision and created the favorable incentives. Although it is better for the sake of the economy at large to leave the minimum wage alone, it may be feasible to index it to inflation but refrain from further arbitrary adjustments.
Research and Cited Works:
State Economy Statistics:
http://www.bls.gov/eag/eag.wv.htm#eag_wv.f.4
Demographics of minimum wage workers:
http://www.bls.gov/cps/minwage2011.htm
http://www.bc.edu/research/agingandwork/publications/us_publications.html
Who Are minimum wage workers
http://aspe.hhs.gov/hsp/09/lowwageworkers/rb.shtml
Median state incomes:
http://www.census.gov/hhes/www/income/data/statemedian/
Origin of the minimum wage law:
http://www.dol.gov/oasam/programs/history/flsa1938.htm
How companies respond to minimum wage increases:
http://www.washingtonpost.com/blogs/wonkblog/wp/2013/02/14/why-economists-are-so-puzzled-by-the-minimum-wage/
Changes in state minimum wage:
http://www.dol.gov/whd/state/stateMinWageHis.htm
http://www.nytimes.com/2012/04/21/opinion/what-are-the-effects-of-raising-the-minimum-wage.html?_r=0
http://www.heritage.org/research/testimony/the-economic-effects-of-the-minimum-wage
http://economix.blogs.nytimes.com/2010/03/10/did-the-minimum-wage-increase-destroy-jobs/
Human Capital and economic growth
http://www.jstor.org/sici?sici=0022-3808%28199010%2998%3A5%3CS12%3AHCFAEG%3E2.0.CO%3B2-L
http://www.jstor.org/stable/3559021
http://cms.bsu.edu/-/media/WWW/DepartmentalContent/MillerCollegeofBusiness/BBR/Publications/WageEmploy.pdf
Break down of minimum wage workers:
http://www.bls.gov/cps/minwage2011.htm
http://www.bls.gov/cps/minwage2011.pdf
http://www.bls.gov/lau/#tables
State profiles for State unemployment rates
http://www.bls.gov/lau/table14full11.pdf
http://www.bc.edu/content/dam/files/research_sites/agingandwork/pdf/publications/states/Washington.pdf
http://www.aecf.org/~/media/Pubs/Initiatives/KIDS%20COUNT/Y/youthandworkpolicyreport/kidscountyouthandwork.pdf
Demographic data (poverty, employment, etc)
http://www.statehealthfacts.org/profileind.jsp?cat=1&sub=6&rgn=49
http://www.calmis.ca.gov/file/lfmonth/Calmr.pdf
Education data by state:
http://www.census.gov/compendia/statab/2012/tables/12s0233.pdf
Approximate US population by year:
http://www.multpl.com/united-states-population/table
http://www.census.gov/popest/estimates.html
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