The U.S. apparel manufacturing industry includes many reputable firms, but is also believed to include many sweatshop operations. Sweatshop workers often work under sub-minimum wages, excessively long hours, and abusive management. Sweatshop establishments in the United States typically violate several U.S. labor laws. Two they commonly violate are the minimum wage under the Fair Labor Standards Act of 1938 and the ban on hiring illegal immigrants under the Immigration Reform and Control Act of 1986. The purpose of the present research was to estimate minimum penalties that would provide no monetary incentive for the average U.S. apparel manufacturing firm to violate the minimum wage and the ban on hiring illegal immigrants. The minimum per-violation penalties that were estimated to deter violation of the minimum wage are 8 to 28 times the current maximum penalty of $1,000 per violation, and those estimated to deter the hiring of illegal immigrants are 3 to 10 times the current maximum penalty of $10,000 per violation. The estimated penalties are associated with annual probabilities of prosecution ranging from 5% to 15%. The estimated penalties primarily depend on the difference between legal and illegal wage rates. A sensitivity analysis indicated that the estimated penalties are insensitive to the value of the own-price elasticity of production labor demand, which is one of the variables used to calculate the penalties. The results suggest that current federal penalties for violating the minimum wage or the ban on hiring illegal immigrants do not deter infraction of these laws by U.S. apparel manufacturers. / Master of Science

This dissertation is an empirical investigation into the distributive effects of overand under-education, defined as market outcomes such that some workers possess skills over or below those required at their jobs respectively. This type of market failure can arise in assignment and search equilibrium settings, as well as in the presence of asymmetric information regarding workers' performance on the job. The existence of permanent and sizable mismatch rates means that returns to education are depressed for over-educated workers and in ated for under-qualified workers. Thus, irreversible decisions to invest in human capital are made in a context of uncertainty regarding the exact outcomes that might arise. As in the Todaro model, where individuals decide whether to migrate to cities based on the expected values of the available alternatives, workers might decide it is worthwhile to keep investing in education even if the probability of finding appropriate employment is falling. The three chapters of the dissertation are entitled: Skill Mismatch and Earnings: A Panel analysis of the U.S. Labor Market," Earnings Inequality and Skill Mismatch in the U.S: 1973-2003," and Employment and Distribution Effects of Changes in the Minimum Wage." Skill Mismatch and Earnings: A Panel analysis of the U.S. Labor Market This chapter examines the effect on earnings induced by a mismatch between workers' skills and the skills actually required on the job. It uses the Current Population Survey (CPS) for the period 1983-2002. The special re-interview methodology of the CPS is used to create a large panel, so that individual heterogeneity can be controlled for. Skill requirements are estimated by the median education level for each 3-digit occupation in the 1980 census occupational classification. The analysis, including the determination of skill requirements, is conducted for males and females separately. Cross-sectional analysis confirms the findings in the recent literature. Returns to required schooling are higher than the returns to attained education in standard earnings regressions. Also, for workers with similar educational attainment, over-education reduces earnings and under-education increases them. Contrary to what other studies have found, we conclude that these results are confirmed after controlling for individual fixed effects. The chapter also investigates which groups are more exposed to mismatch. I use standard probit analysis with over-education and under-education as the respective dependent variables. Women, service sector, and non-unionized workers appear to have higher probabilities of mismatch. Earnings Inequality and Skill Mismatch This chapter shows that skill mismatch is a significant source of inequality in real earnings in the U.S. and that a substantial fraction of the increase in wage dispersion during the period 1973-2002 was due to the increase in mismatch rates and mismatch premia. Standard human capital earnings regressions that do not decompose the education variable into required, surplus, and deficit years provide biased estimates of the relative importance of education in explaining earnings inequality. In 2000-2002 surplus and deficit qualifications taken together accounted for 4:3 and 4:6 percent of the variance in earnings, or around 15 percent of the total explained variance. The dramatic increase in over-education rates and premia accounts for around 11 and 32 percent of the increase in the coeffcient of variation of log earnings during the 30 years under analysis for males and females respectively. Residual inequality is slightly diminished when the estimating equation allows the prices of surplus, required and deficit qualifications to differ but the well-studied increasing trend of within-group inequality remains otherwise unchanged. Changes in the composition of the labor force are found to be important predictors of increasing residual inequality even when skill mismatch is taken into account. The Distributive Effects of the Minimum Wage: an Effciency Wage Model with Skill Mismatch (co-authored with Peter Skott) This chapter analyzes the effect of changes in the real value of the minimum wage on the wage distribution. Changes in the minimum wage and other labor market institutions affect workers in all groups and empirically appear to be good complement to standard supply and demand arguments in explaining overall inequality. We use an effciency wage model but allow for mismatch between jobs and workers. This framework yields predictions not only on the skill premium but also on the extent of inequality within groups. To keep matters as simple as possible, we assume that high-skill workers can get two types of jobs (good and bad), whereas low-skill workers have only one type of employment opportunity (bad). As long as some matches of high-skill workers and bad jobs are sustained in equilibrium, changes in the exogenous variables will affect not only wages and employment rates but also the degree of mismatch. Thus, this paper shows that `over-education' can be generated endogenously in effciency wage models and that a fall in the real value of the minimum wage can (i) reduce total employment, (ii) lead to a simultaneous decline in both the relative employment and the relative wage of low-skill workers, and (iii) produce a rise in within-group as well as between-group inequality. Evidence from the US suggests that these theoretical results are empirically relevant.

Thesis advisor: Christopher Maxwell / This paper aims to measure the impact of increases to Seattle minimum wage from the years 2015 – 2018 on total earnings of the greater Seattle area. My research concentrates on low-wage industries but also touches upon the effect on high wage industries and the overall economy. Also, to ensure continuity of results, models were replicated at the federal level. This question is important because of a modern movement for higher state and city minimum wages. There have been several research papers about this topic already; however many economists have come up with conflicting results. My methods are a combination of previously used methods in an attempt to provide an unbiased analysis. In addition, research that has been released on this topic only covers the initial increases in minimum wage from 2015 – 2016. My research expands on this time frame and analyzes the impact of minimum wage increases from 2015 – 2018. My results show a statistically significant positive impact of minimum wage on total earnings for the greater Seattle area, not just for low-wage industries but also for the overall economy. These results show that a high minimum wage can be beneficial for the economy. / Thesis (BA) — Boston College, 2019. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: Departmental Honors. / Discipline: Economics.

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Given a set of n points on a plane, in the Minimum Weight Triangulation problem, we wish to find a triangulation that minimizes the sum of Euclidean lengths of its edges. The problem has been studied for more than four decades and is known to be incredibly challenging. In fact, the complexity status of this problem remained open until recently when it was shown to be NP-Hard. We present a novel polynomial-time algorithm that computes a 16-approximation of the minimum weight triangulation---a constant that is significantly smaller than what has been previously known. To construct our candidate solution, our algorithm uses grids to partition edges into levels by increasing weights, so that edges with similar weights appear in the same level. We incrementally triangulate the point set by constructing a growing partial triangulation for each level, introducing edges in increasing order of level. At each level, we use a variant of the ring heuristic followed by a greedy heuristic to add edges, finally resulting in a complete triangulation of the point set. In our analysis, we reduce the problem of comparing the weight of the candidate and the optimal solutions to a comparison between the cardinality of the two underlying graphs. We develop a new technique to compare the cardinality of planar straight-line graphs, and in combination with properties due to the imposed grid structure, we bound the approximation ratio. / Master of Science

Co-channel interference limits the capacity of cellular systems, reduces the throughput of wireless local area networks, and is the major hurdle in deployment of high altitude communication platforms. It is also a problem for systems operating in unlicensed bands such as the 2.4 GHz ISM band and for narrowband systems that have been overlaid with spread spectrum systems. In this work we have developed model-based techniques for the demodulation of co-channel MSK signals. It is shown that MSK signals can be written in the linear model form, hence a minimum variance unbiased (MVU) estimator exists that satisfies the Cramer-Rao lower bound (CRLB) with equality. This framework allows us to derive the best estimators for a single-user and a two-user case. These concepts can also be extended to wideband signals and it is shown that the MVU estimator for Direct Sequence Spread Spectrum signals is in fact a decorrelator-based multiuser detector. However, this simple linear representation does not always exist for continuous phase modulations. Furthermore, these linear estimators require perfect channel state information and phase synchronization at the receiver, which is not always implemented in wireless communication systems. To overcome these shortcomings of the linear estimation techniques, we employed an autoregressive modeling approach. It is well known that the AR model can accurately represent peaks in the spectrum and therefore can be used as a general FM demodulator. It does not require knowledge of the exact signal model or phase synchronization at the receiver. Since it is a non-coherent reception technique, its performance is compared to that of the limiter discriminator. Simulation results have shown that model-based demodulators can give significant gains for certain phase and frequency offsets between the desired signal and an interferer. / Master of Science

Computational fluid dynamics (CFD) modeling was used to predict the gas-solid hydrodynamics of fluidized beds. An Eulerian-Eulerian multi-fluid model and granular kinetic theory were used to simulate fluidization and to capture the complex physics associated therewith. The commercial code ANSYS FLUENT was used to study two-dimensional single solids phase glass bead and walnut shell fluidized beds. Current modeling codes only allow for modeling of spherical, uniform-density particles. Owing to the fact that biomass material, such as walnut shell, is abnormally shaped and has non-uniform density, a study was conducted to find the best modeling approach to accurately predict pressure drop, minimum fluidization velocity, and void fraction in the bed. Furthermore, experiments have revealed that all of the bed mass does not completely fluidize due to agglomeration of material between jets in the distributor plate. It was shown that the best modeling approach to capture the physics of the biomass bed was by correcting the amount of mass present in the bed in order to match how much material truly fluidizes experimentally, whereby the initial bed height of the system is altered. The approach was referred to as the SIM approach. A flow regime identification study was also performed on a glass bead fluidized bed to show the distinction between bubbling, slugging, and turbulent flow regimes by examining void fraction contours and bubble dynamics, as well as by comparison of simulated data with an established trend of standard deviation of pressure versus inlet gas velocity. Modeling was carried out with and without turbulence modeling (k-ϵ), to show the effect of turbulence modeling on two-dimensional simulations. / Master of Science

A sign pattern is a matrix whose entries are from the set $\{+, -, 0\}$. This thesis contains problems about refined inertias and minimum ranks of sign patterns. The refined inertia of a square real matrix $B$, denoted $\ri(B)$, is the ordered $4$-tuple $(n_+(B), \ n_-(B), \ n_z(B), \ 2n_p(B))$, where $n_+(B)$ (resp., $n_-(B)$) is the number of eigenvalues of $B$ with positive (resp., negative) real part, $n_z(B)$ is the number of zero eigenvalues of $B$, and $2n_p(B)$ is the number of pure imaginary eigenvalues of $B$. The minimum rank (resp., rational minimum rank) of a sign pattern matrix $\cal A$ is the minimum of the ranks of the real (resp., rational) matrices whose entries have signs equal to the corresponding entries of $\cal A$. First, we identify all minimal critical sets of inertias and refined inertias for full sign patterns of order 3. Then we characterize the star sign patterns of order $n\ge 5$ that require the set of refined inertias $\mathbb{H}_n=\{(0, n, 0, 0), (0, n-2, 0, 2), (2, n-2, 0, 0)\}$, which is an important set for the onset of Hopf bifurcation in dynamical systems. Finally, we establish a direct connection between condensed $m \times n $ sign patterns and zero-nonzero patterns with minimum rank $r$ and $m$ point-$n$ hyperplane configurations in ${\mathbb R}^{r-1}$. Some results about the rational realizability of the minimum ranks of sign patterns or zero-nonzero patterns are obtained.