The construction industry is one of the largest industries in the United States and has major influence on the nation's economy. While there is information about industry-wide labor productivity, there has been very little specifically aimed at analyzing the key macroeconomic factors such as labor productivity and gross margin of the construction industry as a whole and at fourteen of its sub-sectors. To address these shortcomings, the objectives of this research are threefold: (1) quantify the macroeconomic performance of the industry as a whole and at fourteen of its sub-sectors in terms of labor productivity, gross margin, and labor wages, (2) investigate the relationship among the three key parameters over the study period from 1992 to 2007, and (3) develop a quantifying model that predicts the level of a firms' profit as a function of such parameters. In addition, the paper seeks to further examine the interdependence between gross margin and labor productivity and wages by looking at the construction industry as a whole. First, data were collected from the 1997, 2002, and 2007 U.S. Economic Census reports generated by the U.S. Census Bureau. This raw data had discrepancies because of some missing values in data fields. This problem was then resolved by performing a bi-variate linear regression. Second, a one-way ANOVA and a general linear regression analysis was performed to investigate whether there was a statistically significant relationship among gross margin, labor productivity, and labor wages per construction worker. Third, a quantifying model was developed to predict the value of gross margin as a function of key parameters. Lastly, the proposed model was then validated with actual values of gross margin observed in three states, California, Florida, and Texas. The results of this research clearly indicate that there was no statistically significant relationship between labor productivity and labor wages per construction worker. In addition, it was seen that there was no significant relationship between labor wages and gross margin per construction worker. However, this study proved that there was a statistically significant relationship between labor productivity and gross margin per construction worker, which suggests the importance of labor productivity. The validation study proved the reliability of the proposed model in predicting the value of gross margin, with little deviation. This study concludes that sub-sectors experiencing higher labor productivity resulted in more profits as represented by the level of gross margin. This finding conveys the important fact that as labor productivity improves, firm's profits also increase significantly. It is noticeable to find that the construction industry as a whole had experienced a steady increase in its labor productivity and gross margin over the study period.

Anecdotal descriptions and small studies have reported decreasing reimbursements from Medicare Part D sponsors and commercial third-party payers, resulting in decreased gross margins for independent pharmacies; however, reports are inconclusive regarding which payer more greatly affects independent pharmacies’ financial viability. Using 2006-2009 prescription claims data collected by a pharmacy switching company, the purpose of this study was to calculate and describe estimated reimbursement formulas and mean gross margins to assess the relative impact of these two payer groups. The study evaluated a total of 2,929,696 prescription claims paid for by Medicare Part D sponsors (n = 1,830,896) and commercial third-party payers (n = 1,098,800). The prescriptions were dispensed by 418 Texas independent pharmacies to 192,968 patients aged 65 to 94. Between 2008 and 2009, the median ingredient reimbursement ranged from AWP-17% to AWP-15% for Part D sponsors and from AWP-17.44% to AWP-15% for commercial third-party payers. The median dispensing fee ranged from $1.50 to $2.00 for Part D sponsors and from $1.10 to $2.00 for commercial third-party payers. For all payers, the median dispensing fee and median ingredient reimbursement decreased or was stagnant. Similarly, aggregate percent gross margin (calculated using the payers’ estimates of acquisition cost) decreased for both payer types between 2007 and 2009, with the mean gross margin of 4.0 percent earned for Part D prescriptions being higher than the 3.7 percent earned for commercial third-party prescriptions. In the same timeframe, the mean aggregate percent gross margin ranged from 2.8 percent to 6.0 percent among the five most popular Part D sponsors in the sample, and from 2.4 percent to 5.1 percent among the five most popular commercial third-party payers. The generic dispensing ratio explained a portion of the variance between and among payers. This study shows that significant variation exists in reimbursement formulas and percent gross margin between and among several of the most popular Part D sponsors and commercial third-party payers and supports pharmacy assertions that reimbursements from both payer types are decreasing. Pharmacies can respond to these pressures by being more conscientious of their business’ margins when reviewing contracts and increasing the proportion of generic drugs dispensed. / text

This research aims to identify important factors contributing to a construction firm's profitability and to develop a prediction model which would help in determining the gross margin/profitability of a construction firm as a function of important parameters. All the data used in the research was taken from U.S Census Bureau reports. The novelty of the research lies on its focus at a state level, by dividing states into pertinent clusters and then analyzing the trends in each cluster independently. The research was divided into two phases. Phase 1 of the research focused on identification of the most important factors contributing to gross margin of a construction firm. The variables used were derived from the U.S Census Bureau data. Based on the independent variables and gross margin, all the states were divided into three clusters. Subsequently, a prediction model was developed for each cluster using step-wise backward elimination, thus, eliminating non-significant variables. Results of Model 1 gave impetus to developing Model 2. Model 1 clearly showed that labor productivity was the most important variable in determining gross margin. Model 2 was developed to predict gross margin as a function of single most important factor of labor productivity. Similar to Model 1, states were clustered based on their labor productivity and gross margin values. Prediction model was developed for each cluster. In this study, an excel embedded decision support tool was also developed. This tool would aid the decision-makers to view the state's level of gross margin and labor productivity at a glance. Decision support tool developed was in the form of color-coded maps, each of which was linked to a spreadsheet containing pertinent data. The most important conclusion of the research was that there exists a positive linear relationship between labor productivity and gross margin at a state level in the construction industry. The research also identified and quantified other important factors like percent of rental equipment used, percent of construction work sub-contracted out and percent of cost of materials, components and supplies which affect gross margin.

Master of Science / Department of Agricultural Economics / Vincent R. Amanor-Boadu / This study assessed the farm and farmer characteristics influencing the profitability of broiler chicken farms in Ghana. It used data obtained from the 2015 census of the poultry industry conducted by USAID-METSS in collaboration with Ghana's Ministry of Food and Agriculture and the Ghana National Association of Poultry Farmers. Results show that broiler production in Ghana is operated on a small scale basis with an average number of 1,410 birds. Broiler chicken production is profitable in Ghana with national average gross margin/bird of GHS 9.22 and standard deviation of 8.40. Regression analysis was carried out using Ordinary Least Square method to estimate the effect of farm and farmer characteristics on profitability and also explore regional differences. Results shows that farm income and feed were negative and statistically significant such that a farmer with primary income from broiler chicken production had a decrease in gross margin of GHS 1.24 per bird compared to a farmer with other sources of income; a farmer that increases one unit of own feed production will have a decrease in gross margin of GHS 0.06 per bird. Additionally, regional differences exist such that farms situated in Ashanti, Central, and Eastern had higher gross margin per bird of GHS 3.21, GHS 6.10 and GHS 6.26 respectively compared to farms situated in Brong Ahafo Region. In conclusion, the study shows that both farmer (primary source of income) and farm characteristics (such as regional location and the extent to which feed was prepared on the farm) were important in explaining broiler chicken profitability. Finally, continuous research is recommended to examine the robustness of these factors in explaining profitability.

The main objective of this study is to evaluate the economic potential and opportunities for introducing Genetically Modified (GM) cassava that is Cassava Mosaic Virus (CMV) resistant and has improved starch properties in South Africa. The level of cassava production in South Africa is limited and thus a study on a new technology for this crop may seem strange. However, with innovations like the CMV resistance trait or amylose free cassava starch, cassava production in South Africa can possibly become more viable and relatively more profitable than competing crops such as maize and potatoes. Various ex ante economic methods and approaches to assessing economic impacts exist in the subject literature: the partial budget approach, cost benefit analysis, consumer and producer or economic surplus approach and the computable general equilibrium (CGE) or simulation model. For the purpose of this study and due to available data, a simple gross margin analysis was applied to analyse the economic profitability of genetically modified cassava in South Africa in comparison to maize and potato. Due to data limitations, this study relies on a synthesis between secondary information from various studies in other African countries and interviews with experts. The information collected was used to assess the potential for genetically modified cassava in South Africa. Secondary information and interviews with experts were used to provide more insights and information relating to the possible opportunities, constraints, performance of the genetically modified events, and production practices for cassava and other competing crops like maize and potato in the country. The gross margin analysis results show that cassava production is not profitable at farm level for both dryland and irrigation scenarios. However, processing cassava into starch results in higher returns from the higher starch output and quality compared to potato and maize. The starch from cassava has many industrial applications. The scenario analysis for GM cassava and infected cassava at 10%, 20%, 30% and 40% expected yield loss showed that the CMV resistant and amylose free GM cassava provides additional benefits due to its better quality and higher starch yields compared to infected varieties. The higher quality starch yields a higher profit making it even more profitable to produce cassava for starch. The results of interviews with subject experts show that cassava production and utilisation has lagged behind other crops in South Africa and the crop is sparingly and informally traded. An analysis of market constraints showed that there is a strong consumer taste preference for maize and other cereals dominating the starch market. Other factors that have contributed to the lagging behind of cassava in South Africa and other African countries are the post colonial government policies that favoured maize over cassava. Cassava has a number of important traits that present a competitive advantage for cassava as a commercial crop for farmers compared to other crops such as maize and potato. For example, cassava can be grown under difficult environmental conditions and has a wide range of applications ranging from food products to industrial starches. Cassava can be grown as a monoculture crop, unlike maize and potato which require rotation. In addition, the special characteristics of cassava starch present an important alternative to maize, wheat, rice and potato. Cassava flour and starch have unique properties which make them ideal for many applications in the food, textile and paper industries where flour and starch from other crops hold a quasi monopoly. For example, among starch producing plants, cassava has been considered as the highest yield producer (25 to 40 percent higher than potato, rice and maize) and as the most efficient (the highest) converter of solar energy to carbohydrate per unit area. However, despite these advantages, cassava has remained a neglected crop in South African agricultural research and development activities compared to cereals. However, the increasing demand for starch based applications in the food industry and industrial sector and the fact that the industry is searching for a cheaper substitute for cereals present an impressive market growth potential for cassava starch. For example, industries including the paper industry, food industry and textile industry are the main buyers of cassava starch in South Africa. The results from interview discussions show that there are some concerns and questions related to the introduction of GM cassava in South Africa. One of the main concerns was that empirical studies in South Africa have shown that the occurrence of cassava mosaic virus in the country is very low; it has an approximate 2 percent incidence rate. As a result, large scale producers have been able to control CMV through good management practices, natural selection and chemical control. Also, bureaucracy and lack of transparency in the South African genetically modified organism (GMO) regulatory system, especially regarding socio-economic issues consumer perception on GM cassava, may result in an extended delay before contained field trials are conducted in the country. It has also become clear that the two proposed GM events are still relatively far from being commercialisable. Furthermore, the current availability of mutant varieties of conventional cassava varieties that can produce better quality starch with a very low amylose content provide an important alternative to GM cassava. The utilisation of the former tends to be less time consuming and less expensive compared to GM cassava. It is difficult to perform a socio-economic assessment before confined laboratory tests or field trials have been conducted. Further development of the potential product would supply crucial information that is needed for an ex ante socio-economic study. It is clear that this study was conducted far too early as GM technologies are not yet remotely close to being ready for commercialisation. Many basic studies still need to be conducted, including field trials. The South African GMO Act and regulations do not clearly stipulate when a socio-economic study should be conducted, but it is clear that the worth of a study conducted before any confined field trials had been performed would be questionable. Copyright / Dissertation (MScAgric)--University of Pretoria, 2010. / Agricultural Economics, Extension and Rural Development / unrestricted

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / Retail trade modernization in Peru has displaced the traditional retailer as the first option when it comes to shopping. Supermarkets have grown 45% during the last four years and the new convenience stores gather all competitive advantages required by the sector. Industry has adapted to the new Peruvian in order to cover the needs generated by a digital age offering solutions that give timely information, comfort and modernity when acquiring a new product. In 2017, 414,000 grocery stores were counted in Peru, which were forced to adapt and improve their services. This research project aims to come up with a solution to bring the grocery stores into the twenty-first century, and thus, to increase their gross margin and ensure their continuity. A methodology connecting the requirements of the grocery stores that invest the most in the city of Lima to the needs of the mass consumption companies by means of a platform that digitalizes ads at the point of sale driven by digital advertising is presented here. Currently, the product benefits 40 grocery stores in the city with a new customer service channel that allows to increase their sales by 20%.

How should managers choose between improvements in revenue and gross margin rate, when both contribute to overall profitability? Many finance managers face this question when balancing their companies’ targets and goals. Prior studies show that companies’ stock returns respond to both metrics, especially when they are consistent with each other, which I replicate in my sample. I predict that the relative strength of responses to revenue and gross margin percentage depends on industry growth. I find that the market’s response to revenue growth is greater in high revenue growth than low revenue growth industries. I also argue that the market responds more positively to gross margin rate changes in low growth industries, but the differences are statistically insignificant.In a second study, I apply the theory to the generic pharmaceutical industry where revenue growth is slower. I expect a higher focus on gross margins or pricing when barriers to entry are lower. The Department of Justice and State Attorney Generals sued generic pharmaceutical companies for violating the antitrust laws and manipulating drug prices (consolidated as the multi-district litigation case 2724), making the industry less attractive. I study the pricing changes around the lawsuits and how they affected the likelihood of generic drug manufacturers staying vs. leaving the industry. I also analyze the disparate impact of the lawsuit on large vs. small and medium manufacturers, as the lawsuits listed many large manufacturers as defendants. / Business Administration/Accounting

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O estudo consistiu de dois experimentos com o objetivo de avaliar o efeito metabólico, custos e viabilidade econômica de dietas com diferentes fontes nitrogenadas e teores proteicos. No primeiro experimento avaliou-se o efeito de dois teores de proteína bruta (PB) (130 e 148g/kg de MS) e duas fontes nitrogenadas (farelo de algodão 38 e grão de soja cru integral) na dieta de vacas leiteiras com cana de açúcar como volumoso, sobre as frações nitrogenadas do leite, balanço de nitrogênio e perfil metabólico. Foram utilizadas 12 vacas da raça Holandesa com 155 (±65) dias em lactação, agrupadas em três quadrados latinos 4x4 contemporâneos, com período experimental de 21 dias, sendo 14 dias para adaptação às dietas e os sete últimos para a realização das coletas. As vacas foram alojadas em baias individuais e alimentadas ad libitum. As amostras de leite para análise do balanço nitrogenado e frações nitrogenadas foram coletadas no 15° dia de cada período. O consumo e balanço de nitrogênio foram maiores para vacas alimentadas com dietas com 148 g PB/kg de MS. Por outro lado, vacas alimentadas com dietas contendo farelo de algodão apresentaram maior excreção de nitrogênio no leite do que vacas alimentadas com grão de soja cru integral. A relação entre caseína e proteína verdadeira no leite foi maior em vacas alimentadas com grão de soja cru integral. Houve interação entre fonte nitrogenada e teor de PB da dieta sobre as concentrações de nitrogênio ureico no leite (NUL) e nitrogênio não proteico (NNP). A concentração de NUL foi maior em vacas alimentadas com farelo de algodão e com maior teor de PB, em contrapartida houve menor excreção de NUL em vacas alimentadas com grão de soja com maior teor proteico. Não houve efeito das dietas sobre os teores de proteína do leite, nitrogênio não caseinoso (NNC), caseína e proteína do soro. Conclui-se que o uso de dietas com 130g de PB/Kg na MS não altera o balanço de nitrogênio e de composição do leite de vacas leiteiras em comparação com teores de 148g/Kg de PB na MS, e resultam em menor excreção de nitrogênio no ambiente. No segundo experimento foram calculados os custos e margens totais de dietas com cinco fontes nitrogenadas principais (ureia, farelo de soja, farelo de algodão, grão de soja cru integral e farelo de glúten de milho) e cinco teores proteicos (130, 145, 148, 157 e 160 g/kg de MS) com cana de açúcar como volumoso para vacas em lactação. Os dados foram provenientes de três estudos conduzidos com a finalidade de coleta de dados produtivos e respostas metabólicas. A análise econômica foi realizada com base nos preços históricos deflacionados (corrigidos do efeito da inflação) praticados durante o período 2002 a 2012, e no cálculo dos custos de alimentação, em função do consumo de alimento, da produção de leite e do teor de proteína bruta no leite. Dietas com cana de açúcar com teor proteico de 14,5% com ureia como fonte nitrogenada principal apresentaram a maior margem bruta (diferença entre a receita da venda do leite e do custo da dieta) com valor médio anual de R$1,85.vaca-1.dia-1. A dieta com 14,8% de PB com grão de soja cru integral apresentou a menor margem bruta de R$ 2,16.vaca-1.dia-1. / The study consisted of two experiments to evaluate the N balance and economical analysis of diets with different nitrogen sources and crude protein levels. On the first experiment it was evaluated the effect of two crude protein (CP) levels (130 e 148 g/kg DM) and two nitrogen sources (cottonseed meal 38% and whole raw soybean) in diets of dairy cows using sugar cane as forage on nitrogen in milk, nitrogen balance and metabolic parameters. Twelve Holstein cows with 155 (±65) days in lactation were distributed into three contemporary 4x4 Latin squares, with experimental period of 21 days, 14 days for diet adaptation and the remaining seven days for sampling. The cows were housed in individual pens and fed ad libitum. Milk samples for nitrogen balance and milk nitrogen fractions analysis were collected on the 15th day of each experimental period. Nitrogen intake and nitrogen balance were higher for the cows fed diets with 148 g CP/kg DM. However cows fed diets with cottonseed meal had higher nitrogen excretion in milk than cows fed diets with whole raw soybean. The casein: true milk protein ratio was higher in cows fed diets with whole raw soybean. There was interaction between the nitrogen source and the diet CP content on the milk urea nitrogen and non-protein nitrogen. Milk urea nitrogen was higher in cows fed diets with cottonseed meal and higher CP concentrations, however lower milk urea nitrogen was observed in cows fed diets with whole raw soybean and higher CP concentration. The concentration of crude protein, noncasein protein, casein and whey protein in milk did not differ between diets. In conclusion the use of low concentrations of protein (130g/Kg in MS) does not affect the performance of dairy cows and provides lower excretion of nitrogen in the environment. On the second experiment, the costs and the gross margin were calculated for diets formulated with five nitrogen sources (urea, soybean meal, cottonseed meal, whole raw soybean and corn gluten meal) and five protein levels (130, 145, 148, 157 e 160 g/kg DM) using sugar cane as forage. Performance data were obtained from three experiments conducted previously. Economical analysis were performed based on historical prices adjusted for the effect of inflation during the period between 2002 and 2012 and based on the feed costs, cow intake, milk prodution and milk protein levels. The higher gross margin (difference between the income from milk sale and diet costs) were obtained for 145 g/kg of CP in DM diets and urea as main nitrogen source, with mean of R$1,85.vaca-1.dia-1. The lower gross margin were observed in the 148 g/kg of CP in DM diet and whole raw soybean as nitrogen source, with mean of R$ 2,16.vaca-1.dia-1.

O objetivo do trabalho foi realizar uma análise econômica e de risco em sistemas integrados de produção agropecuária (SIPA) e de bovinos de corte de ciclo completo na Campanha Meridional do Rio Grande do Sul, região sul do Brasil, por um modelo de simulação. O modelo foi desenvolvido e operado em planilhas dinâmicas do Microsoft Excel®. O trabalho foi dividido em duas etapas, na primeira, foi realizada uma identificação e análise dos riscos existentes na produção de bovinos de corte e SIPA. Na segunda, foi realizada uma análise econômica e uma avaliação dos riscos de três sistemas de produção. Como resultado da primeira etapa, os principais fatores de risco na bovinocultura foram, condições climáticas, custo de produção, capacidade de investimento e gestão da propriedade. Na SIPA foram identificados novos ricos, como a produtividade da soja (Glycine max) e desconhecimento da atividade. No entanto, do total dos riscos considerados mais importantes, metade deles estão presentes nas duas atividades. Na segunda etapa, foram estabelecidos três sistemas de produção, bovinocultura de corte de ciclo completo (SBC), bovinocultura de corte de ciclo completo associado com leasing de uma área para soja (SLS) e bovinocultura de corte de ciclo completo com o cultivo de soja pelo próprio pecuarista (SCS). O sistema que apresentou maior margem bruta foi o SLS (R$ 223,57/ha) comparado aos outros dois sistemas (SBC: R$ 138,11/ha; SCS: R$ 149,62/ha). O SCS apresentou o maior risco entre os sistemas, devido a maior amplitude de resultados na margem bruta. A produtividade média da pecuária foi similar nos sistemas SBC e SLS (129,55 e 131,74 kg PV/ha/ano). Com exceção da produtividade da soja que foi o principal risco no SBS, todos os outros estiveram ligados as fontes de risco de mercado. Conclui-se que os produtores rurais percebem o SIPA com maior risco do que a bovinocultura. Em ambos os casos, o risco de produção é o que apresenta o maior número de fatores com alto risco de ocorrência e, portanto, deve receber especial atenção pelos produtores rurais. O que foi consolidado quando se concluiu que o melhor sistema foi o SLS por apresentar melhor margem bruta e menor risco que o SCS, e este último foi o que apresentou o maior risco, no entanto, os riscos que mais influenciaram a variação da margem bruta foram os de mercado e não os de produção. / The aim of this study was compare the economic and risk analysis on an integrated crop-livestock (ICLS) and a cycle complete beef cattle systems in the Campanha Meridional of Rio Grande do Sul, Brazilian Southern Region, through a simulation model. The simulation model was developed and operated through Microsoft Excel® dynamic worksheets. The research was divided in two stages, in the first, an identification and analysis of the existing risks in the production of beef cattle and ICLS was carried out. In the second, an economic and risk analysis of the three production systems. Because of the first stage, the main risk factors in beef cattle farming were climatic conditions, production cost, investment capacity and farm management. In the ICLS there were changes such as soybean yield (Glycine max) and lack of knowledge of the activity. However, of the total risks considered most important, half of them were present in both activities. In the second stage, three production systems were established, cycle complete beef cattle (SBC), cycle compete beef cattle associated with leasing of a soybean area (SLS) and cycle compete beef cattle with the cultivation of soybean by the owner (SCS). The system with the highest gross margin was SLS (R$ 223.57/ha) compared to the other two systems (SBC: R$ 138.11/ha; SCS: R$ 149.62/ha). The SCS presented the highest risk among the systems, due to the greater range of gross margins. The average productivity of livestock was similar in the SBC and SLS systems (129.55 and 131.74 kg PV/ha/year). Except for soybean yield that were the main risk at SCS, all others were linked to market risk sources. It is concluded that farmers perceive the SIPA with greater risk than beef cattle systems. In both cases, production risks are the one that presents the highest number of factors with high risk of occurrence and, therefore, should receive special attention. This was consolidated when we concluded that SLS presented a better gross margin and a lower risk than the SBC, and the latter was the one that presented the highest risk. However, the risks that most influenced the gross margin variation were the market, not the production.