This thesis is addressed to the theoretical controversy which revolves around the explanation of the higher unemployment rates that prevailed after 1957 . The debate that has been generated concerning the causes of this unemployment problem is usually referred to as the "structural" versus "deficient-demand" debate. An attempt is made to present a representative view of both sides of the debate as well as a critical evaluation of both positions. Care is taken to keep both positions separated for each leads to entirely different policy recommendations. A more general theoretical structure is presented which will be useful in analyzing the relevance of structural unemployment. Finally, the controversy is analyzed in terms of current economic development.

The purpose of this study is to study future trends in student enrollment, according to age , sex, grades, and school levels, for different geographic areas, and teacher demand for the elementary and secondary levels of school in Utah from 1970 to the year 2000. For the secondary level information is also given for student enrollment according to different subject areas and the future demand of teachers for these subject areas. Projections were prepared for single calendar years from 1970 to the year 2000. The projections for the school children were based on total population projections for the state, prepared at the Department of Sociology, Utah State University. Census data and school enrollment data were used to obtain information for future trends . The component method of population projection was used to project the total population for the state and the enrollment-ratio method was used to project the school population. With 98 percent of the school-age population, (5-17 years of age), now enrolled in school, future increases or decreases in the school population would mainly come from changes in fertility or migration. The general findings of this study for the period 1970-2000, show an increase of 50,398 students, (16 percent), and 2,124 teachers, (17 percent). Elementary student population increased by 30,599 students and 1,293 teachers, whereas the secondary school population increased by 19,799 students, and 831 teachers. The majority of students are concentrated wi thin four counties: Davis, Salt Lake, Utah, and Weber. In 1970 these counties comprised 77 percent of the school population and projected by the year 2000 to 82 percent.

The goal of this study is to investigate the predictive ability of less data intensive but widely accepted methods to estimate mobility and reliability measures. Mobility is a relatively mature concept in the traffic engineering field. Therefore, many mobility measure estimation methods are already available and widely accepted among practitioners and researchers. However, each method has their inherent weakness, particularly when they are applied and compared with real-world data. For instances, Bureau of Public Roads (BPR) Curves are very popular in static route choice assignment, as part of demand forecasting models, but it is often criticized for underperforming in congested traffic conditions where demand exceeds capacity. This study applied five mobility estimation methods (BPR Curve, Akcelic Function, Florida State University (FSU) Regression Model, Queuing Theory, and Highway Capacity Manual (HCM) Facility Procedures) for different facility types (i.e. Freeway and Arterial) and time periods (AM Peak, Mid-Day, PM Peak). The study findings indicate that the methods were able to accurately predict mobility measures (e.g. speed and travel time) on freeways, particularly when there was no congestion and the volume was less than the capacity. In the presence of congestion, none of the mobility estimation methods predicted mobility measures closer to the real-world measure. However, compared with the other prediction models, the HCM procedure method was able to predict mobility measures better. On arterials, the mobility measure predictions were not close to the real-world measurements, not even in the uncongested periods (i.e. AM Peak and Mid-Day). However, the predictions are relatively better in the AM and Mid-Day periods that have lower volume/capacity ration compared to the PM Peak period. To estimate reliability measures, the study applied three products from the Second Strategic Highway Research Program (SHRP2) projects (Project Number L03, L07, and C11) to estimate three reliability measures; the 80th percentile travel time index, 90th percentile travel time index, and 95th percentile travel time index. A major distinction between mobility estimation process and reliability estimation process lies in the fact that mobility can be estimated for any particular day, but reliability estimation requires a full year of data. Inclusion of incident days and weather condition are another important consideration for reliability measurements. The study found that SHRP2 products predicted reliability measures reasonably well for freeways for all time periods (except C11 in the PM Peak). On arterials, the reliability predictions were not close to the real-world measure, although the differences were not as drastic as seen in the case of arterial mobility measures.

Lightweight thermal paper (LWTP) is a noteworthy import commodity with wide usage and large import value in the United States. In this study, the trade pattern and market dynamics of the LWTP import market in the U.S. has been examined based on almost ideal demand system. The results revealed that both the trade volume and import source of LWTP had changed during last decade. Competition relationships were found among major suppliers in both the short run and long run, and the long-run competition is stronger than that in the short run. The repeal of restriction on conducting countervailing investigation against non-market economy temporarily stimulated the import of LWTP products from China, but the following antidumping/countervailing investigation and the corresponding punitive duties generated trade depression effect on the imports. In addition, positive trade diversion effect was found on German products, which raises doubt on the effectiveness of this trade remedy policy.

While Malawi’s Farm Input Subsidy Program (FISP) has been the focus of numerous studies on the impacts of subsidies on farm-household income, yields, fertilizer use and adoption, there still has not been much empirical work quantifying the program’s effects on maize supply and demand. In this study, we use the econometric framework proposed by Roberts and Schlenker (2013) to identify the effect of FISP on maize production as well as supply and demand price elasticities in Malawi. We use national aggregate data and find that the program has increased aggregate maize supply. Our results show that FISP has had an aggregate effect across years of about 3,746,870 metric tons from 2006-2013. We also find that the program has increased farmers’ responsiveness to changes in fertilizer prices. However, our estimates suggest that higher prices lead to higher quantities of fertilizer demanded, a relationship that is not consistent with economic theory.

Sediment oxygen demand (SOD) and nutrients releases from the bottom sediments of a water body are important parameters to be included in studies of water quality processes. Two methods to measure SOD, in situ and at laboratory, were applied at Eckie’s Pond on late spring of 2015. Based upon preliminary results, which showed greater values for the in situ method, some modifications of procedures and equipment were made to improve the measurements. Another set of measurements were made on June of 2016, however their results were not conclusive to establish a correlation between these methodologies. As a result of this research, three standard operating procedures (SOP) have been established to measure SOD at shallow waters, first in situ, second at laboratory, and a third SOP to analyze nutrients and metals by using a spectrophotometer.

Inventory control problems constitute one of the most important research problems due to their connection with real life applications. Naturally, real life is full of uncertainty so are the most of the inventory problems. Unfortunately, it is a very challenging task to manage inventories effectively especially under uncertainty. This dissertation mainly deals with single-item, periodic review, and stochastic dynamic inventory control problems particularly on replenishment cycle control rule known as the (R, S) policy. Contribution of this thesis is multiold. In each chapter a particular research question is investigated. At the end of the day, we will be showing that non-stationary (R, S) policies are indispensable not only for its cost efficiency but its effectiveness and practicality. More specifically, the non-stationary (R, S) policy provides a convenient, efficient, effective, and modular solution for non-stationary stochastic inventory control problems.

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The first essay explores the demand for M1, M3 and broad money (BM) and economic uncertainty in Australia over the period 1976:2-2008:4. The results suggest that we have evidence of cointegration between money, economic activity, interest rate and price for the pre-deregulation sub-period. The long-run equilibrium relation is confirmed for post-regulation and for the entire sample once we augment the traditional money demand equation with measure of economic uncertainty. Once we account for uncertainty, the breakdown of the cointegration relationship between real money balance and economic activity disappear and our money demand equation better explain the overshooting of M3 during 1984. Our result has an implication on reopening an important policy question on the viability of framing monetary policy around monetary aggregate. The second essay investigates the impact of financial liberalization on consumption and GDP growth volatility and assess why such impact may differ across countries. We have strong evidence that liberalization is associated with lower consumption growth and output growth volatility. Our result confirms that the initial level of inequality and initial level of financial development help to explain heterogeneity across countries. Countries with better financial development benefit from reduction in consumption growth variability. On the other hand, countries with high initial level of inequality do experience an increase in consumption growth volatility. Overall, after controlling for institutional quality, macroeconomic reform and conflict, our result supports the negative association between financial liberalization and consumption growth volatility in subsequent periods. One possible implication of our result is that an effort to improve financial development and promote redistribution policy that reduces the level of inequality, help countries to reap the potential benefit of liberalization. The third essay presents a two-period model of money-in-the-utility-function to investigate the impact of ant-money laundering policy on crime. Our two- period model reveals that an increase in labor wage in legal sector unambiguously decrease the labor hours allocated for illegal sector by increasing the opportunity cost for illegal activities. However, the crime-reducing impact of anti-money laundry regulation and the probability of the agent to be caught require both parameters should be above some threshold. This threshold is a function of the marginal rate of substitution of `dirty' money for consumption and the responsiveness of illegal income to the policy parameter. Higher threshold implies the need for tougher anti-money laundry regime. Therefore, the marginal rate of substitution between `dirty' money and consumption, and the elasticity of illegal income to the policy parameter are the key in governing the formulation of the anti-money laundry policy.

The main objective of this study was to evaluate the effects of the changes in total nondurables expenditures, prices, and demographics on the U.S. aggregate demand for clothing categories and shoes. In particular, this study focused on identifying and parameterizing the effects of such changes. To this purpose, a demand system for two clothing categories, shoes, and other nondurable commodities for the U.S. was estimated using aggregate time-series data sets (1929-1994), and a second-stage budgeting model was developed and estimated. The basis for the demand model was the Almost Ideal Demand System model, which was modified to account for the demographic effects. Demographic variables included in the final model were age distribution of the U.S. population (median age and variance), proportion of non-White population in the total U.S. population, and labor force participation rate of U.S. women. The main data sources were documents published by the Bureau of the Census, Bureau of Labor Statistics, and Bureau of Economic Analysis in the U.S. Department of Commerce. The results indicate that the total nondurables expenditures is a significant variable in determining consumers' nondurables expenditure allocation on clothing categories and shoes. The estimated total expenditure elasticities suggest that the clothing categories and shoes are expenditure elastic, ranging from 1.1019 to 1.4944. Most own and cross prices appear to be significant variables in determining the consumer budget allocations for clothing categories and shoes. The median age and non-White population variables evidence as significant variables that affect the U.S. aggregate nondurables expenditure allocation on men’s and boys’ clothing and on shoes. Women’s labor force participation rate evidences as a significant variable that affects the U.S. aggregate nondurables expenditure allocation on women’s and children’s clothing. The estimated own-price elasticities of demand for clothing categories and shoes indicate that all the clothing categories and shoes are inelastic (i.e., -0.3908 to -0.9175). The estimated crossprice elasticities of clothing categories, shoes and other nondurable goods show substitution and complementary relationships between the categories. The demand elasticities with respect to the demographic variables were also estimated. / Ph. D.