Minimum Wage and Unemployment Rate Correlation

Introduction

Reflectively, there are several factors affecting the rate of unemployment. These factors include minimum wage, wage differential, and other market dynamics. In relation to this research, the scope of the paper will concentrate on establishing the relationship between the unemployment rate and minimum wage. The research paper will also provide possible reasons for the positive or negative relationship which will be established. The paper will concentrate on the labor market of the developed countries where a good percentage of the employees are paid the minimum wage as stipulated by the government labor regulatory agencies.

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Theoretical and empirical perspective

Theoretical perspective

Over the years, the minimum wage has been on the rise for several reasons in the developed and the developing labor market. As a result of the increasing minimum wage, organizations have to respond by increasing the salaries in line with the new minimum wage. However, increasing the minimum wage translates into increased cost of labor in companies that have the primary goal of optimal returns from the least possible costs. In response to the increasing minimum wage, a rational agent managing the labor function in a company will have to strike a balance between the laborers and capital to minimize the effects of increasing wages. One of the possible responses to higher wages would be streamlining the labor force by retrenchment to remain with a lean labor as one of the primary factors of production (McConnell and Macpherson 24). From this perspective, it is apparent that the minimum wage increment would negatively affect the unemployment rate as companies respond to the dynamics of increased cost of labor.

Human Capital Theory

Fringe benefits and wage earnings are identified as the main components of compensation summation. However, fringe benefits are apportioned a larger share in the total compensation matrix due to the fact that their influence was experiencing a consistent growth over the last decade in the labor market. These fringe benefits are classified as social security, unemployment compensation and employee’s compensation for every unit of labor given as indicated in the human capital theory. For instance, the wage differentials for different age groups studied average at 5. Since fringe benefits are rarely affected by age, the existing wage differential is negligible. In classification, these fringe benefits assume the form of insurance benefits, paid leave, and legally acquired benefits to a worker for every unit of labor delivered against the revenue realized. Besides these, retirement benefits and savings are included in the summation of the fringe benefits accrued by a worker. An increase in the minimum wage leads to an increase in the benefits. As a result, the unemployment rate may rise as a result of retrenchment as a strategy for managing the rising cost of labor (McConnell and Macpherson 33).

Labor Market Discrimination Theory

Type and form of fringe benefits are never universal. Rather, they are influenced by the type of industry in which labor operates, ration and occupational groups as indicated in the labor market discrimination theory. This is due to the fact that governments and other agencies have introduced laws and regulations aimed at pushing for higher and reliable compensation. In most instances, the blue collar employees have a larger share of the legalities, construed benefits than their counterparts in white collar jobs (McConnell and Macpherson 39).

Job Characteristics Theory

In a bid to extrapolate this relationship, the Job Characteristics/Compensating Wage Differentials theory is a certain reason for the experienced growth over the sample space. Reflectively, the variables interacting within the parameters of this theory are leisure and income within the normal indifference curve. Consequently, the resulting interaction becomes flexible to different bundles of budget constraints that might be present at each level of computation. Further, this theory asserts that indifference curve is a product of various fringe benefits and wage rates that interact simultaneously to yield same utility level for each worker. When all other factors are held constant, higher swing of the indifference curve indicates higher levels of utility. Irrespective of the inclination of the indifference curve, it is apparent that levels of tax advantage determine the resultant fringe benefit accrued as shown in the survey. Specifically, to support this notion, the benefits accrued from pension plans are taxable upon confirmation of receivership by an employee. Besides, the principle, dividends and interest which are part of the summation of pensions, are best achieved through pretax accumulation of the fringe benefits. On average jobs that demand higher skills attract more wages than those that demand low skills (McConnell and Macpherson 41).

Incentive pay theory

The need for intrinsic substitution as a component of the decision science aimed at managing the fringe benefits are peculiar in labor economics. In such case, the foregone alternative would be forfeiting leisure related savings for health and pension needs which are characterized as basic for every worker. The adoption of this thought is influenced by the fact that basic needs are more critical than the secondary needs in the matrix of fringe benefits. Besides, the long term effects of purchasing the basic needs are greater than those opting to acquire secondary needs upfront. Tax advantages to employers, scale of economies, and efficiency are major factors that led to the growth of fringe benefits. Therefore, as fringe benefits increase, the workers’ utility increased in the same ratio. In drawing the curve, the initial assumptions consist in the fact that the market operates within a normal profit margin in total employment and product market as part of the overall compensation effect per worker. Generally, substantial changes for each cluster of wages and benefits are negligible within the ‘employer’s isoprofit curve’. The same relationship functions in the Wage-Fringe optimum. As performance and pay interest in the labor market, there is a proportional relationship between performance and pay for each unit of labor given to a firm (principal) against the compensation offered as explained in the incentive pay theory (McConnell and Macpherson 24).

The unbalance relationship between pay and performance may result in the principal – agent problem which might culminate in under utilization of labor units since the agent (employee) may opt to increase leisure through reduced efforts at work. In order to avoid this unwanted scenario, the theory proposes different forms of incentive compensation, such as royalties, profits, and bonus plans. In most cases, employers control these incentives and limit them as a fraction of the total revenue after factoring the cost of production and each labor unit. When implementing these incentive plans, it is important to concentrate on personal performance bonuses as opposed to team bonuses, which promote a joyride attitude among workers since the process has no specific measure for distributing incentives.

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Empirical evidence

A research was conducted by Neumark, David and Wacher, William to ascertain the relationship between minimum wage and employment (Neumark and Wascher 11). Data for various countries across the world was used to conduct this study. From the research, the authors established that there exists a wide range effect of changes on minimum wage on employment. Further, these results varied across various countries. The study also established that the assumption that the minimum wage reduces the level of employment of low-skilled worker is not correct (Neumark and Wascher 11). The research carried out established that there a negative association between minimum wage and employment level. In the research, 102 entries were used to ascertain the relationship between these two variables. Two thirds of these entries show that there raising the minimum wage has a negative effect on employment (Neumark and Wascher 11). Only eight entries provided a contrary result of a positive relationship between the two variables. The research further indicated that the least-skilled workers will be least affected by the negative relationship between minimum wage and employment. Further, there was no evidence of a positive relationship between employment and minimum wage, especially when the regression analysis was carried using wide range skill group.

The authors pointed out a number of considerations that need to be taken into account when evaluating the relationship between minimum wage and employment. First, longer panel studies that take into account both the country and time variation yields a negative relationship between the two variables. This result is contrary to the result obtained from US data. The study also revealed that labor-labor substitution effect has a significant impact on the relationship between minimum wage and employment especially for low skilled workers. This applies to the group whose employment status and wages are adversely affected by changes in the minimum wage. The research highlighted that employers replace the low-skilled worker with available substitutes as a way of responding to the increases in minimum wages. Therefore, an increase in the minimum wage can cause a total disemployment. In summary, the research established that minimum wage has negative employment effects both in the US and other countries across the world (Neumark and Wascher 11).

Data analysis

The data on minimum wage and unemployment rate in the US will be used to test the relationship between these two variables. Further, a vector of control variable will be introduced in the analysis. The control variable will be time. The data will be divided into two time periods based on recession. Dummy variable will be introduced so that the periods that the country had a recession will be allocated 1 while the periods the country did not have recession will be allocated 0. The data will cover a period of 59 years that is from 1955 and 2013. The data are presented in the table below.

Year Unemployment rate % Current dollars Control variable (time)
1955 4.37 0.75 0
1956 4.13 1 0
1957 4.30 1 1
1958 6.84 1 1
1959 5.45 1 0
1960 5.54 1 1
1961 6.69 1.15 1
1962 5.57 1.15 0
1963 5.64 1.25 0
1964 5.16 1.25 0
1965 4.51 1.25 0
1966 3.79 1.25 0
1967 3.84 1.6 0
1968 3.56 1.6 0
1969 3.49 1.6 1
1970 4.98 1.6 1
1971 5.95 1.6 0
1972 5.60 1.6 0
1973 4.86 1.6 1
1974 5.64 2 1
1975 8.48 2.1 1
1976 7.70 2.3 0
1977 7.05 2.3 0
1978 6.07 2.65 0
1979 5.85 2.9 0
1980 7.18 3.1 1
1981 7.62 3.35 1
1982 9.71 3.35 1
1983 9.60 3.35 0
1984 7.51 3.35 0
1985 7.19 3.35 0
1986 7.00 3.35 0
1987 6.18 3.35 0
1988 5.49 3.35 0
1989 5.26 3.35 0
1990 5.62 3.8 1
1991 6.85 4.25 1
1992 7.49 4.25 0
1993 6.91 4.25 0
1994 6.10 4.25 0
1995 5.59 4.25 0
1996 5.41 4.75 0
1997 4.94 5.15 0
1998 4.50 5.15 0
1999 4.22 5.15 0
2000 3.97 5.15 0
2001 4.74 5.15 1
2002 5.78 5.15 0
2003 5.99 5.15 0
2004 5.54 5.15 0
2005 5.08 5.15 0
2006 4.61 5.15 0
2007 4.62 5.85 4.41
2008 5.80 6.55 4.77
2009 9.28 7.25 5.3
2010 9.63 7.25 5.22
2011 8.93 7.25 5.06
2012 8.08 7.25 4.97
2013 7.35 7.25 4.87

(Source of data – United States Department of Labor 1)

Scatter plots

Scatter diagram seeks to establish if there exists a linear relationship between the two variables plotted. This can be observed by looking at the trend of the scatter plots. The independent variable is plotted on the x – axis while the dependent variable is on the y – axis.

Scatter plot
Scatter plot

The scatter plot does not seem to provide a clear relationship between the unemployment rate and minimum wage in current prices and unemployment rates (Gujarati 23).

Correlation coefficient

The table presented below shows the correlation coefficient.

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Unemployment rate % Minimum wage in Current dollars Control variable
Unemployment rate % 1
Minimum wage in Current dollars 0.3584 1
Control variable 0.0936 -0.1111 1

The table above shows that there is a weak positive relationship between the unemployment rate and minimum wage in current dollars. The value of the coefficient is 0.3584. Also, there is a weak relationship between the unemployment rate and the control variable, that is 0.0936. Further, there is a negative relationship between the minimum wage in current prices and control variable.

Regression results

When coming up with the regression model, it is necessary to separate between dependent and independent variables. This section carries out a simple regression analysis to establish the relationship between the unemployment rate and minimum wage (Gujarati 23). Further, a control variable will be introduced to reduce the effect of spurious results (Neumark and Wascher 11).

Simplified regression equation Y = b0 + b1X1 + b2X2 + µ

  • Y = Unemployment rate
  • X1 = Minimum wage
  • X2 = control variable
  • µ = error term

The theoretical expectations are b0 and b2 can take any value while b1 > 0.

Regression results

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.382747683
R Square 0.146495789
Adjusted R Square 0.116013495
Standard Error 1.487462383
Observations 59
ANOVA
Df SS MS F Significance F
Regression 2 21.26666949 10.63333474 4.805931 0.011851101
Residual 56 123.9024831 2.21254434
Total 58 145.1691525
Coefficients Standard Error t Stat P-value Lower 95%
Intercept 4.836899175 0.427648893 11.31044476 4.37E-16 3.9802155
Minimum wage 0.303108222 0.100829961 3.006132503 0.003955 0.101121539
Control variable 0.460334455 0.423197847 1.087752355 0.281364 -0.387432704

The regression equation in this case is Y = 4.8369 + 0.3031X1 + 0.4603X2. The positive coefficient of 0.3031 shows that the two variables move in the same direction. Thus, an increase in minimum wage by one unit will result in a 0.3031 increase in unemployment. Also, it can be observed that there is a positive relationship between the unemployment rate and the control variable.

Test of significance

A two tailed t-test will be used to test the significance of the explanatory variable. The test will be carried out at 5% level of significance. The hypothesis is stated below.

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  • Null hypothesis: Ho: Xi = 0
  • Alternative hypothesis: Ho: Xi ≠ 0

The null hypothesis implies that the variable is not a significant determinant of movements in the minimum wage. The null hypothesis will be rejected if the value of t-calculated is greater than the value of t-tabulated or if the p-value is less than α=0.05. The t-statistics for minimum wage is 3.00613, while the p-value is 0.003955. Since the p-value is less than α=0.05, reject the null hypothesis and conclude that minimum wage is a significant determinant of the unemployment rate (Gujarati 23). The t-statistics for the control variable is 1.08775, while the p-value is 0.281364. Since the p-value is greater than α=0.05, do not reject the null hypothesis and conclude that the control variable is not a significant determinant of the unemployment rate.

F – Test of the regression models

The overall significance of the regression model can be analyzed using an F – test. The test will be carried out 5% significance level.

  • Null hypothesis H0: β0 = β1
  • Alternative hypothesis H1: βj ≠ 0, for at least one value of j

The null hypothesis implies that the overall regression line is not significant. The alternative hypothesis implies that overall regression line is significant. From the regression results, the value of f-calculated is 4.8059 while the value of significance f is 0.01185. Therefore, value of f-significance is less than α = 0.05. This shows that the overall regression line is significant. The coefficient of determination (R2) is 14.65%. It indicates that the regression model is weak because the independent variable explains only 14.65% of the variations in stock movement. This regression analysis shows that there exists a positive relationship between the unemployment rate and minimum wage. Thus, if the minimum wage is increased, then the unemployment level will increase. Therefore, there is a positive relationship between the unemployment rate and minimum wage (Gujarati 23).

Conclusion

The paper carried out an analysis of the relationship between unemployment rates minimum wage payments. The analysis focused on the labor market in the US because a good percentage of the employees are paid the minimum wage as stipulated by the government labor regulatory agencies. The analysis also shows that minimum wage is a significant determinant of unemployment rate and that the overall regression line is significant as indicated by the t-test and f-test. However, the coefficient of determination is small. This implies that there is a weak relationship between these variable. From an economic point of view, it means that minimum wage weakly affects unemployment rate. The regression results above are consistent with the empirical evidence discussed in the previous section. The empirical evidence established that there a negative association between minimum wage and employment level. This research was carried out across various countries. The same result was obtained when the US data were used. The results show that increasing minimum wage increases unemployment rate. This shows that it has an adverse effect on employment rate. Further, the use of control variable shows that there is a positive relationship between recession and unemployment rate. Thus, during recession, the unemployment rate increases.

Works Cited

Gitis, Ben. How Minimum Wage Increased Unemployment and Reduced Job Creation in 2013. Web.

Gujarati, Damodar. Econometrics by Example. USA: Palgrave Macmillan, 2014. Print.

McConnell, Campbell, and David Macpherson. Contemporary Labor Economics. London, UK: McGraw-Hill Education, 2013. Print.

Neumark, David and William Wascher. “Minimum Wages and Employment.” Foundations and Trends in Microeconomics 3. 1 (2007): 1 – 182. Print.

United States Department of Labor. Databases, Tables & Calculators by Subject. 2014. Web.

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