Level: Intermediate
Ondina Sevilla-Rovirosa, Graduate Student and Small Business Owner, Oklahoma State University
The pay gap between top executives and the average American worker continues to widen. Additionally, the gender pay gap has narrowed, but women only earn 85% of what men earn. Experts debate if higher compensations could positively impact the firm’s performance and maximize its value. Therefore, it is worth analyzing the factors that companies are considering to determine the salaries of top executives.
The original dataset of 2,646 executives from 250 selected U.S. companies was gender unbalanced. I used a synthetic replication method to balance the data. Then, I ran, analyzed, and compared a decision tree, a stepwise regression, eight different neural networks, and an ensemble model. Finally, a surrogate model was used to explain the best neural net model.
From the 18 initially selected variables of companies and executives, I found that only Total Assets, Number of Employees, and Years Executive in CEO Position had a significant contribution to Salary.
Surprisingly gender had an insignificant effect on the salaries of top executives. Nevertheless, predominantly what affected Salaries was the size of the firm (Assets and Employees), followed by a lower contribution from the number of years the executive has been in the CEO position.
Auto-generated transcript...
Speaker | Transcript |
| ondinasevilla@gmail.com | My name is Ondina Sevilla and my poster is about salary gaps in corporate America, specifically how do the company and executive characteristics influence compensations. |
| Something with a little introduction, the pay gap between top executives and the average American worker continues to widen. |
| Also the gender pay gap has narrowed, but women only earn 85% of what men earn. Even experts debate if higher compensations could positively impact the firm's performance and maximize its value. |
| So it is worth it to analyze the factors that companies are considering to determine the salaries of top executives. I made two questions for this research. |
| Are...is there a salary gap for top female executive in US companies? |
| And does the company's size influence executives' salaries? |
| So for this research, I collected a data set of 2046 from top executives from 250 selected US companies, such as Halliburton, Southwest Airlines, Starwood Hotels, Sherwin-Williams and others. |
| Then I applied a synthetic replication method in SAS to obtain a gender balance database and used 12 companies and six executive variables, being salary by input variable. |
| The technique used was predictive modeling. I analyzed and compared in JMP Pro 15 a decision tree, stepwise regression, eight different neural networks and ensemble model. |
| And outlier... |
| oh, a salary percentage year per year variable was excluded from from...for the first analysis and then I included it to compare. However, the rules are adjusted for error and the outer absolute error were higher with the outlier. |
| So, |
| I'm going to show you here |
| the model, the different models that I ran without the outlier and the neural networks comparison. So from all these models, the lowest |
| root average squared error without the outlier was the number eight neural network. |
| These ...this neural net has 4 inputs |
| two hidden layers, eight double neurons, with a TanH function. |
