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A Stepping-Stone? An Analysis of How the Minimum Wage Impacts the Wage Growth of Individuals in Monopsonistic Industries
Date: 2022-01-01
Creator: Levi McAtee
Access: Open access
- Do minimum wage increases serve as stepping-stones to higher-paying jobs for low-pay workers? This paper analyzes the impact of state minimum wage policy on the one-year wage growth rates of individuals across the wage distribution and whether that impact changes for individuals in highly monopsonistic industries. I review the recent literature on the disemployment effect, the impact of the minimum wage on wage growth rates, the nature of monopsonistic industries, and the relationship between the minimum wage and monopsony power. I offer theoretical reasons why the minimum wage may impact the wage growth rates of individuals in monopsonistic industries differently than it impacts those of individuals in competitive industries. I then re-estimate Loprestiās and Mumfordās (2016) panel fixed effects model to determine how the effect of a minimum wage increase depends nonlinearly on the size of the increase. Using data from 2005-2008, Lopresti and Mumford found that small minimum wage increases have a significant negative impact on wage growth rates, while large minimum wage increases have a significant positive impact. Using data from 2016-2019, I find similar results. As my primary empirical contribution, I test whether individuals in highly monopsonistic industries experience minimum wage changes differently than individuals in more competitive industries. I find monopsony power in the form of high labor immobility primarily impacts the wage growth rates of high-pay workers and does not influence how low-pay workers experience minimum wage changes. Finally, I recommend policymakers impose larger minimum wage increases to avoid impeding the wage-growth of low-pay workers.
Sensitivity Analysis of Basins of Attraction for Gradient-Based Optimization Methods
Date: 2022-01-01
Creator: Gillian King
Access: Open access
- This project is an analysis of the effectiveness of five distinct optimization methods in their ability in producing clear images of the basins of attraction, which is the set of initial points that approach the same minimum for a given function. Basin images are similar to contour plots, except that they depict the distinct regions of points--in unique colors--that approach the same minimum. Though distinct in goal, contour plots are useful to basin research in that idealized basin images can be inferred from the steepness levels and location of extrema they depict. Effectiveness of the method changes slightly depending on the function, but is generally defined as how closely the basin image models contour information on where the true minima are located, and by the clarity of the resulting image in depicting well-defined regions. The methods are tested on four distinct functions which were chosen to assess how each method performs in the presence of various challenges. This project ranks the five methods for their overall effectiveness and consistency across the four functions, and also analyzes the sensitivity of the methods when small changes are made to the function. In general, less sensitive and consistently effective methods are more applicable and reliable in applied optimization research.