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© Copyright 1998 by the Wyoming Department of Employment, Research & Planning
This research shows that the top 20 percent of wages are increasing at a faster rate than the bottom 20 percent of wages. In Wyoming, the distribution of wages was studied to see at which rate the wages increased over a five-year period. The following are the questions this article will attempt to answer for the Equality State:
Data
The Wyoming Department of Employment collects the data used in this analysis. Every employer has to report wages paid each quarter for all employees covered by Unemployment Insurance. Excluded from this data are federal employees, self-employed individuals and most agriculture employees. Employer records include information such as employees' social security numbers, wages earned and quarters worked, and the Standard Industrial Classification (SIC) code of the firm. The wage records file is then merged with the driver's license file and matched up by social security number to obtain the gender and age data for each case in the file. In this analysis, the last five years of wage records available (1992-1996) were used. In order to eliminate extreme outliers at the bottom, continuous and full-time employment was assumed. Continuous employment, defined by Wayne M. Gosar(1) and Brett Judd(2) in previous studies, is working three or more quarters in one year. Full-time employment is defined as working 35 hours or more in a week. Since the actual hours the employees worked was unavailable, the minimum an employee would have to earn receiving minimum wage of $4.25/hour and working 35 hours a week was calculated. Since only quarterly wage data was available, this amount had to be multiplied by 13 weeks per quarter. A full-time employee then had to earn a minimum of $5,802 in 3 quarters or $7,735 if they worked four quarters in a year. Employees who earned less or worked fewer quarters were excluded from the database. This reduced the database for each year from approximately 270,000 to 140,000 records.
Comparison of Wage Growth
Quintiles were used to determine the bottom and top 20 percent of wages. A quintile is one of the points dividing a frequency distribution into five parts, each containing one fifth of the total number of observations. Over the last five years, the bottom quintile increased by only $40 (0.4%). This is below the inflation rate. Looking at Table 1 and Figure 1, wages in the years 1995 and 1996 actually decreased. On the other hand, the top quintile increased by $5,668 (10.7%) over the last five years (see Table 2 and Figure 2). There was never a decrease in wages in the top quintile over the five-year period. The growth rate varied from a high of 3.4 percent from 1992 to 1993 to a low of 1.6 percent from 1994 to 1995.
Comparison by Gender
When comparing the bottom and top quintiles by the split in males and females, approximately half of the wage earners in any of the five years at the bottom quintile are females. Looking at the top quintile, only about 12.5 percent are females (see Table 3). The good news is that the number of females in the bottom has declined from 50.9 to 48.7 percent and females in the top increased from 11.6 to 13.6 percent.
This finding is really not surprising since past research by Gregg Detweiler and Brett Judd(3) has established that females earn less than males in Wyoming. There is a difference in the way that wages for both genders grew over the past five years.
The growth rate for females over the 1992-1996 time period shows that females wages grew at a slower rate than males. The gap is smaller at the bottom than at the top. Females wages at the bottom grew only 0.4 percent while males wages over the same time period increased by 0.7 percent, a difference of 0.3 percent. The mean for females wages was higher than the mean for males wages in the bottom quintile (see Figure 1 and Table 1). The difference is about $130 per year. The mean ages for both genders show that females are on the average three years older than males. Some of the differences in the wages may be explained with the higher experience level due to the likelihood of being in the workforce longer. There is a completely different picture when comparing the top quintiles. Females earn about $8,000 less per year than males and their wages grew by only 7.2 percent while males wages grew by 10.4 percent, a difference of 3.2 percent. Again looking at ages, do females earn less because they are younger and are therefore more likely to have less experience? The data show that females are older than males, even though the difference is only about six months.
Comparison by Industry
Most of the wages in the bottom quintile came from Services (average 37.9%) and then Retail average 28.6%; see Table 4). Most of the wages in the top quintile came from Mining (average 34.1%), Services (average 22.9%), and Transportation, Communications, & Public Utilities (TCPU; average 13.0%; see Table 5).
Do any industrys wages increase at a faster rate than any other? There are definite differences between the industries when it comes to wage increases, especially in the top quintile. There are also large differences that can be observed by gender.
The largest increase in wages for males in the bottom quintile over the five-year period was in Wholesale Trade (1.5%), followed by Services (1.3%) and TCPU tied with Construction (1.2%). There were only two industries where the wages declined for males. These were in Finance, Insurance, & Real Estate (FIRE; -0.9%) and Public Administration (-1.0%). Females, on the other hand, had declines in wages in six out of ten industries. The largest declines were in Mining and Wholesale Trade (-2.6%). The largest wage increase was found in TCPU (1.5%). This industry also had a high increase for males. TCPU, therefore, had the highest increase for all employees. Wages declined in four industries for all employees at the bottom quintile. The largest decrease was in FIRE, which showed a decrease in wages for both genders (see Table 6 and Table 7).
The top quintile for males showed no decrease in wages for any industry over the five-year period. Four of the ten industries showed wage increases of more than ten percent. FIRE (18.1%), which showed declining wages for both genders at the bottom, was the winner here for males. TCPU (12.6%) followed, then Mining (11.5%) and Agriculture (10.6%). The lowest increase for males was in Public Administration (4.9%). The data for females showed a completely different picture. Three industries showed declining wages. These were Agriculture (-5.2%), TCPU (-14.4%) and Retail Trade (-2.3%). A two-digit increase was only seen in two industries, Construction (20.1%) and Mining (11.9%). In looking at the wage increases for all employees, the numbers are similar to the males'. This is due to the fact that females are underrepresented in the top quintile. The same four industries that showed increases above ten percent showed increases above ten percent for all employees. No industry showed a decline in wages (see Table 6). Another observation can be made when looking at the changes over the past five years. When we look at the bottom quintile for both genders, we can see erratic ups and downs in wages for many industries. In the top quintile, we see much smoother lines that are steadily increasing for males and all employees. Females, on the other hand, showed more ups and downs especially in Wholesale Trade, Retail Trade, Construction and TCPU. In TCPU, a very curious drop in wages occurred from 1992 to 1993. In 1992, females earned an average of $55,997 per year, which was actually higher than what males earned. The wages dropped to $45,179 in 1993, which was well below what males earned. An interesting development was also seen in Public Administration for the top quintile. Here females' wages caught up to the males from 1992 to 1993 and stayed almost equal, while in the bottom quintile they actually earned more than males.
Conclusion
One conclusion that can be drawn from this research is that the top 20 percent of wages are increasing faster than the bottom 20 percent of wages. Another conclusion is that both genders are not equal as far as wages in the Equality State. The mean wages for females in the bottom quintile are higher but the difference is very minimal while the mean wages for females in the top quintile is much lower than those for males. This gap is visible over almost every industry. When it comes to an increase in wages, females in the bottom 20 percent actually took a cut in wages in most industries and in the top 20 percent the wages for females increased at a much slower rate than for males. The only highlight was that the number of females in the top 20 percent was increasing.
Further research should be conducted to look for signs other than discrimination that would account for those differences in wage rate growth. For example, do females have a lower level of education than males? Tenure or occupation within the industry could also play a role in explaining the differences in pay increases.
Carola Cowan is a Senior Statistician, specializing in Covered Employment and Wages (ES-202) with Research & Planning.
1 Wayne M. Gosar, Tracking Job Changers in Wyomings Economy, July 1996.
2 Brett Judd, "The Wyoming Wage Record Classification System," Wyoming Labor Force Trends, March 1998.
3 Gregg Detweiler and Brett Judd, "The Relation of Age and Gender to Employment in Wyoming: Parts One and Two," Trends, May and June 1996.
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