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THE EFFECTS OF AN INCREASING FEDERAL MINIMUM WAGE ON FEDERAL UNEMPLOYMENT AND JOB AUTOMATION LEVELS

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Date Issued:
2018
Abstract/Description:
The industrial revolution was the start of increasing technological advancements that are continuing to grow today. Technology improves accuracy, efficiency and is more productive in comparison to human labor as it does not require breaks and cannot violate any labor laws. With many innovations available today, firms have more options to choose from and can select the relatively cheaper solution. The push for a fifteen-dollar minimum wage affects the firm's options, and the use of technology might increasingly become the more viable choice. This study took data from the years 1993 to 2016 and created two regressions using the unemployment rate and job automation rate as the dependent variables. The independent variables looked at were the year, the population growth rate, the minimum wage, inflation, the gross domestic product growth rate, and the consumer price index. After normality checks and transformations were done two regressions were run, and the models were studied to determine the effects. Both regressions were found to be valid with f-statistics lower than one percent. All the statistically significant variables were retained in the model, and the insignificant variables were omitted to reproduce the regression and check for accuracy. The models with the lower Akaike's information criterion and Bayesian information criterion values were kept and used as the final models. Overall the regressions found that the year and consumer price index had the most substantial effects on the unemployment rate, and the consumer price index had the strongest effect on the automation rate. Limitations on the study include the data available, a possible lag in the effect of the minimum wage, and the possible inaccuracy in using industrial robot installation as a measure for job automation.
Title: THE EFFECTS OF AN INCREASING FEDERAL MINIMUM WAGE ON FEDERAL UNEMPLOYMENT AND JOB AUTOMATION LEVELS.
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Name(s): Krayeski, Kiana, Author
Hofler, Richard, Committee Chair
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2018
Publisher: University of Central Florida
Language(s): English
Abstract/Description: The industrial revolution was the start of increasing technological advancements that are continuing to grow today. Technology improves accuracy, efficiency and is more productive in comparison to human labor as it does not require breaks and cannot violate any labor laws. With many innovations available today, firms have more options to choose from and can select the relatively cheaper solution. The push for a fifteen-dollar minimum wage affects the firm's options, and the use of technology might increasingly become the more viable choice. This study took data from the years 1993 to 2016 and created two regressions using the unemployment rate and job automation rate as the dependent variables. The independent variables looked at were the year, the population growth rate, the minimum wage, inflation, the gross domestic product growth rate, and the consumer price index. After normality checks and transformations were done two regressions were run, and the models were studied to determine the effects. Both regressions were found to be valid with f-statistics lower than one percent. All the statistically significant variables were retained in the model, and the insignificant variables were omitted to reproduce the regression and check for accuracy. The models with the lower Akaike's information criterion and Bayesian information criterion values were kept and used as the final models. Overall the regressions found that the year and consumer price index had the most substantial effects on the unemployment rate, and the consumer price index had the strongest effect on the automation rate. Limitations on the study include the data available, a possible lag in the effect of the minimum wage, and the possible inaccuracy in using industrial robot installation as a measure for job automation.
Identifier: CFH2000424 (IID), ucf:45778 (fedora)
Note(s): 2018-12-01
B.S.B.A.
College of Business Administration, Economics
Bachelors
This record was generated from author submitted information.
Subject(s): unemployment
automation
robots
minimum wage
economic
regression
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFH2000424
Restrictions on Access: public
Host Institution: UCF

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