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1
Ullah, Obaid. "The Effect of Remittances on Socio-Economic Condition and Decision Making Process of Rural Families : A Case Study of Peshawar Khyber Pukhunkhuwa Pakistan." Thesis, Södertörns högskola, Institutionen för samhällsvetenskaper, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-28199.
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The objective of the study is to analyze the effect of remittances on socio-economic conditions of rural families in Peshawar, and how remittances change the decision-making process of families. This study examines the effects of remittances on local population in three towns of Peshawar, i.e. Hayatabad, Faqir-Abad and Gulberg-area. The study is basically conducted to see how remittances bring changes in the life of the recipients. The research is quantitative, data was collected through questionnaires. For the research, a sample of 300 respondents was selected from three towns in Peshawar District. The results of the research were interpreted through statistical tools, regression model. The Ordinary least square method (OLS) was used to find out the effect of remittances on health sector and investment made by respondents in the form of purchased property and investment made in establishing their own businesses. Along with that, the simple Logit Model was also used. The result is generalized on linear model with link logit and binomial response. Findings stated that the literacy level of the emigrant’s household positively impacted on children’s probability to move to private education. The results reveals that the recipient invest 4% of their income on investment as a form of business and purchasing property while educated people appears not to be interested in investing money in businesses as they want to continue their jobs. Respondent are not using a large portion of their remittances for health perhaps mostly people are entitled to free services from the government. Remittances changed their standard of living and socio economic affairs of the remittances receiving respondents. According to my demographic information about respondents life, the remittances mostly brings changes in the physical part of people life such as Private Education, Personal transport, new houses, investment in buying properties, more electric appliances, bank balance etc., but culturally people are still conservative and believe in cultural values that have been practices by local population for centuries. Following are some main recommendations that this research has identified, Foreign remittances are improving the socio-economic conditions and decision making of rural families, however, their consumption behavior is not inclined towards investment, they rather prefer to enjoy luxurious household’s equipment. Therefore, it is recommended that these families should utilize their resources in more efficient way, and should go for short and long term investment avenues. Government must design policies in order to educate these families and create awareness among them that will enable them to look for sustainable domestic income, which would help the families in the long run. These families follow the norms and traditions, and they prefer sending their children abroad for earning purposes, which in turn is comparatively less profitable idea as compared to sending these children for higher education purpose.
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Li, Yang. "An Empirical Analysis of Family Cost of Children : A Comparison of Ordinary Least Square Regression and Quantile Regression." Thesis, Uppsala University, Department of Statistics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-126660.
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Quantile regression have its advantage properties comparing to the OLS model regression which are full measurement of the effects of a covariate on response, robustness and Equivariance property. In this paper, I use a survey data in Belgium and apply a linear model to see the advantage properites of quantile regression. And I use a quantile regression model with the raw data to analyze the different cost of family on different numbers of children and apply a Wald test. The result shows that for most of the family types and living standard, from the lower quantile to the upper quantile the family cost on children increases along with the increasing number of children and the cost of each child is the same. And we found a common behavior that the cost of the second child is significantly more than the cost of the first child for a nonworking type of family and all living standard families, at the upper quantile (from 0.75 quantile to 0.9 quantile) of the conditional distribution.
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Ntshobane, Gcobisa. "Capital structure and determinants of capital structure, before, during and after the 2008 financial crisis: A South African study." Master's thesis, Faculty of Commerce, 2021. http://hdl.handle.net/11427/33941.
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This study examines the effects of 2007/8 financial crisis on capital structure determinants of Johannesburg Stock Exchange (JSE) listed companies in South Africa. Data extracted from INET BFA Expert database was analyzed using regression models on the correlation between the leverage and company size, growth, profitability, tangibility, liquidity, non-debt tax shield along with Ordinary Least Squares based on the sample of JSE listed companies for the period of 2004 to 2013. The study examined two industries namely, Real estate and Retail industry. The results show that size, tangibility, profitability and liquidity have significant impact on the capital structure before, during and after financial crisis. Growth results were inconsistent over the period under review, and non-debt tax shield was found to be statistically insignificant. The study also shows that the 2007/8 had statistical significance on the capital structure of the listed companies in South Africa.
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Gaspard, Guetchine. "FLOOD LOSS ESTIMATE MODEL: RECASTING FLOOD DISASTER ASSESSMENT AND MITIGATION FOR HAITI, THE CASE OF GONAIVES." OpenSIUC, 2013. https://opensiuc.lib.siu.edu/theses/1236.
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This study aims at developing a model to estimate flood damage cost caused in Gonaives, Haiti by Hurricane Jeanne in 2004. In order to reach this goal, the influence of income, inundation duration and inundation depth, slope, population density and distance to major roads on the loss costs was investigated. Surveyed data were analyzed using Excel and ArcGIS 10 software. The ordinary least square and the geographically weighted regression analyses were used to predict flood damage costs. Then, the estimates were delineated using voronoi geostatistical map tool. As a result, the factors account for the costs as high as 83%. The flood damage cost in a household varies between 24,315 through 37,693 Haitian Gourdes (approximately 607.875 through 942.325 U.S. Dollars). Severe damages were spotted in the urban area and in the rural section of Bassin whereas very low and low losses are essentially found in Labranle. The urban area was more severely affected by comparison with the rural area. Damages in the urban area are estimated at 41,206,869.57USD against 698,222,174.10 17,455,554.35USD in the rural area. In the urban part, damages were more severe in Raboteau-Jubilée and in Downtown but Bigot-Parc Vincent had the highest overall damage cost estimated at 9,729,368.95 USD. The lowest cost 7,602,040.42USD was recorded in Raboteau. Approximately, 39.38% of the rural area underwent very low to moderate damages. Bassin was the most severely struck by the 2004 floods, but Bayonnais turned out to have the highest loss cost: 4,988,487.66 USD. Bassin along with Labranle had the least damage cost, 2,956,131.11 and 2,268,321.41 USD respectively. Based on the findings, we recommended the implementation and diversification of income-generating activities, the maintenance and improvement of drains, sewers and gullies cleaning and the establishment of conservation practices upstream of the watersheds. In addition, the model should be applied and validated using actual official records as reference data. Finally, the use of a calculation-based approach is suggested to determine flood damage costs in order to reduce subjectivity during surveys.
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Kronenberg, Kai. "ADVERTISING EFFECTIVENESS ON INTERNATIONAL TOURISM DEMAND IN ÅRE – AN ECONOMETRIC ANALYSIS." Thesis, Mittuniversitetet, Avdelningen för turismvetenskap och geografi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-19249.
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The objective of this study is to estimate advertising effects on international tourismdemand for the leading Swedish winter destination, Åre. The increasing share of foreigninbound tourists in this destination region creates a strong interest by shareholders toidentify the factors responsible for this trend. According to traditional micro-economictheory, economic factors, such as income and price, are considered as main determinantsfor tourism demand (Song and Witt 2000). However, according to advertising theories(Comanor and Wilson, 1974) and previous tourism research (Bhagwat and Debruine, 2008;Divisekera and Kulendran, 2006), this study additionally focuses on the brand awarenessof Åre as perceived by international tourists. More concretely, advertising theoriesdistinguish between the brand and the information function of advertising (Nelson, 1974).The former function follows the idea that advertising increases the level of productdifferentiation to build up a base of loyal customers. By contrast, the information functionimplies that advertising primarily provides information about products in order to increasethe market transparency. Accordingly, in order to estimate the impact of advertisingexpenditures for off- and online channels as well as promotional activities, furtherexplanatory variables, e.g. mega events, are considered in this study (Salman, 2003; Songet al., 2010). By applying ordinary least square (OLS) methods, demand elasticitycoefficients are estimated for each of the sending countries Norway, Finland, Russia,Denmark and the UK. Results show that advertising is the main significant driver oftourism demand from the UK, Russia and Finland, while a comparably weak advertisingleverage can be shown for Denmark and Norway. Interestingly, in contrast to microeconomictheories tested in previous research, income and tourism price levels reveal asbeing less significant drivers for demand in all analysed tourism markets. In turn, theresults provide evidence that the increased usage of online channels most significantlyaffects consumers’ buying behaviour. Finally, with respect to brand image perception,results reveal that the destination of Åre is perceived as a brand by tourists from Denmark.Moreover, for customers from the countries Norway and Finland, Åre indicates a weakbrand perception, while tourists from Russia and the UK don’t perceive Åre as a brand atall. The results gained by this research conducted at the level of the tourism destinationprovide useful hints about the factors influencing travel behaviour of tourists from maininternational markets. The study supports destination managers to appropriately adjustmarketing campaigns according to the predominant level of brand perception in respectivesending countries.KK-Foundation project ‘Engineering the Knowledge Destination’ (no. 20100260; Stockholm, Sweden).
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Hu, Yajie. "Exploring Equity and Resilience of Transportation Network through Modeling Travel Behavior: A Study of OKI Region." University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1554212469614412.
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Weng, Lichen. "A Hardware and Software Integrated Approach for Adaptive Thread Management in Multicore Multithreaded Microprocessors." FIU Digital Commons, 2012. http://digitalcommons.fiu.edu/etd/653.
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The Multicore Multithreaded Microprocessor maximizes parallelism on a chip for the optimal system performance, such that its popularity is growing rapidly in high-performance computing. It increases the complexity in resource distribution on a chip by leading it to two directions: isolation and unification. On one hand, multiple cores are implemented to deliver the computation and memory accessing resources to more than one thread at the same time. Nevertheless, it limits the threads’ access to resources in different cores, even if extensively demanded. On the other hand, simultaneous multithreaded architectures unify the domestic execu- tion resources together for concurrently running threads. In such an environment, threads are greatly affected by the inter-thread interference. Moreover, the impacts of the complicated distribution are enlarged by variation in workload behaviors. As a result, the microprocessor requires an adaptive management scheme to schedule threads throughout different cores and coordinate them within cores.
In this study, an adaptive thread management scheme was proposed, integrating both hardware and software approaches. The instruction fetch policy at the hardware level took the responsibility by prioritizing domestic threads, while the Operating System scheduler at the software level was used to pair threads dynami- vi cally to multiple cores. The tie between them was the proposed online linear model, which was dynamically constructed for every thread based on data misses by the regression algorithm. Consequently, the hardware part of the proposed scheme proactively granted higher priority to the threads with less predicted long-latency loads, expecting they would better utilize the shared execution resources. Mean- while, the software part was invoked by such a model upon significant changes in the execution phases and paired threads with different demands to the same core to minimize competition on the chip. The proposed scheme was compared to its peer designs and overall 43% speedup was achieved by the integrated approach over the combination of two baseline policies in hardware and software, respectively. The overhead was examined carefully regarding power, area, storage and latency, as well as the relationship between the overhead and the performance.
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Peres, Ariádine. "Restrições ao crédito e o uso dos recursos financeiros nas empresas brasileiras." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2014. http://hdl.handle.net/10183/98311.
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Este estudo têm como objetivo identificar qual o comportamento de empresas brasileiras de capital aberto com relação à aplicação dos recursos financeiros de seus fluxos de caixa (recursos internos) em investimentos e não investimentos (em fins que não se configuram como um projeto real de investimento) no curto e longo prazo e mostrar como essa questão está relacionado com o grau de restrições financeiras enfrentado pelas empresas. Para alcançar esse objetivo foram estimadas quatro regressões pelo método OLS (Ordinary Least Square / Mínimos Quadrados Ordinários), cada uma delas com uma das variáveis resposta correspondentes aos principais usos de caixa, ou seja, retenção de caixa, investimentos, dividendos e redução do financiamento externo e com as variáveis explicativas dadas pelo fluxo de caixa nos períodos t, t-1 e t-2 e algumas variáveis de controle específicas da firma. Os resultados sugerem que empresas brasileiras restritas e irrestritas se comportam de forma diferente ao receberem um choque positivo em seus fluxos de caixa e que o comportamento das mesmas também difere no curto e no longo prazo. Empresas restritas e irrestritas ao receberem um choque positivo em seus fluxos de caixa, retêm caixa no período contemporâneo e alocam tais recursos intertemporalmente. Empresas restritas investem mais no curto prazo enquanto as irrestritas investem mais no longo prazo. No curto prazo, empresas irrestritas distribuem mais dividendos do que empresas irrestritas e no longo prazo, os coeficientes dos fluxos de caixa não são significativos para nenhum dos grupos. No curto prazo empresas irrestritas reduzem o financiamento externo, enquanto empresas restritas levantam mais financiamentos externos e no longo prazo, esse comportamento se inverte. Dessa forma, fica clara a importância de se considerar o longo prazo bem como as restrições financeiras enfrentadas pelas empresas.This study aim to identify what is the behaviour of Brazilian public companies regarding the use of financial resources of cash flows (internal resources) in investments and not investments (for purposes that are not configured as a real investment project) in the short and long term and show how this is related to the degree of financial constraints faced by firms. To achieve this aim, four regressions were estimated by OLS ( Ordinary Least Square), each with one of the response variables corresponding to the main uses of cash, ie , cash holding, investments, dividends and external finance reduction and the explanatory variables given by the cash flow in periods t , t - 1 and t - 2 and some control variables specific of the firm. The results suggest that restricted and unrestricted Brazilian companies behave differently when they receive a positive shock on cash flows and their behavior also differs in the short and long term. When constrained and unconstrained firms receive a positive impact on cash flows, they retain cash in the contemporary period and intertemporally allocate such resources. Constrained firms invest more in the short term while the unrestricted invest more in the long run. In the short term, unconstrained firms distribute more dividends than unconstrained firms and in the long run, the coefficients of cash flows are not significant for either groups. In the short term unconstrained firms reduce external finance, while constrained firms raise more external finance and in the long term, this behavior is reversed. Thus, it is clear that it matters to consider the long term as well as financial constraints faced by firms.
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Larrabee, Beth R. "Ordinary least squares regression of ordered categorical data: inferential implications for practice." Kansas State University, 2011. http://hdl.handle.net/2097/8850.
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Master of ScienceDepartment of Statistics
Nora Bello
Ordered categorical responses are frequently encountered in many disciplines. Examples of interest in agriculture include quality assessments, such as for soil or food products, and evaluation of lesion severity, such as teat ends status in dairy cattle. Ordered categorical responses are characterized by multiple categories or levels recorded on a ranked scale that, while apprising relative order, are not informative of magnitude of or proportionality between levels. A number of statistically sound models for ordered categorical responses have been proposed, such as logistic regression and probit models, but these are commonly underutilized in practice. Instead, the ordinary least squares linear regression model is often employed with ordered categorical responses despite violation of basic model assumptions. In this study, the inferential implications of this approach are investigated using a simulation study that evaluates robustness based on realized Type I error rate and statistical power. The design of the simulation study is motivated by applied research cases reported in the literature. A variety of plausible scenarios were considered for simulation, including various shapes of the frequency distribution and different number of categories of the ordered categorical response. Using a real dataset on frequency of antimicrobial use in feedlots, I demonstrate the inferential performance of ordinary least squares linear regression on ordered categorical responses relative to a probit model.
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Santos, Levi Alã Neves dos. "Mínimos quadrados ordinários (MQO) na produção científica brasileira: a interdisciplinaridade entre a econometria e as metrias da informação (bibliometria, informetria e cientometria)." Universidade Federal da Bahia, 2017. http://repositorio.ufba.br/ri/handle/ri/25329.
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Analisa a produção científica brasileira (artigos nacionais, artigos internacionais, anais de eventos e livros) através dos Mínimos Quadrados Ordinários (MQO). Para tanto, discorre sobre o percurso histórico e de aplicação das metrias que a Ciência da Informação (CI) vem construindo, desde a mais primordial de todas, a bibliometria, oriunda da biblioteconomia, passando pelas visões modernas como a cienciometria até a informetria. Explica como a econometria constrói o seu modelo de análise, que é utilizado para pesquisas na economia e, ao mesmo tempo, reflete como esse método pode ser trazido para as metrias da informação. Explica e expõe o método de estimação por MQO para a análise de regressão, que é a proposta desta tese. Pesquisa aplicada descritiva com abordagem quantitativa com procedimentos baseados no tipo de pesquisa estudo de caso do levantamento de dados a partir do Portal do Plano Tabular do CNPq do ano de 2010. Os critérios para delineamento da pesquisa foram aprofundados, na revisão de literatura, em referências tanto da área da CI quanto da bibliometria, estatística e econometria. Este estudo, metodologicamente, conta com a abordagem conceitual da bibliometria e da CI em busca de teorias aplicáveis aos estudos em MQO e a aplicação empírica do MQO se aproxima da concepção econométrica. A tese conclui que a utilização de técnicas de análises das funções de regressão construída por meio de MQO possibilita a criação de um modelo de previsão da produção científica brasileira. Esse modelo é construído a partir da correlação e determinação detectada entre o número de doutores e a produção científica destes em cada estado do Brasil. Com a aplicação de estratégias econométricas (índice de correlação, índice de determinação, forma funcional de curva de regressão e cálculo dos parâmetros da função por MQO), foi possível construir um modelo de previsão.
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Chu, Ka Lok 1975. "Inequalities and equalities associated with ordinary least squares and generalized least squares in partitioned linear models." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=85140.
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The motivation for this thesis is the paper by Paul L. Canner [The American Statistician, vol. 23, no. 5, pp. 39--40 (1969)] in which it was noted that in simple linear regression it is possible for the generalized least squares regression line to lie either entirely above or entirely below all of the observed data points.Chapter I builds on the observation that in Canner's model the ordinary least squares and generalized least squares regression lines are parallel, which led us to introduce a new measure of efficiency of ordinary least squares and to find conditions for which the total Watson efficiency of ordinary least squares in a partitioned linear model exceeds or is less than the product of the two subset Watson efficiencies, i.e., the product of the Watson efficiencies associated with the two subsets of parameters in the underlying partitioned linear model.
We introduce the notions of generalized efficiency function, efficiency factorization multiplier, and determinantal covariance ratio, and obtain several inequalities and equalities. We give special attention to those partitioned linear models for which the total Watson efficiency of ordinary least squares equals the product of the two subset Watson efficiencies. A key characterization involves the equality between the squares of a certain partial correlation coefficient and its associated ordinary correlation coefficient.
In Chapters II and IV we suppose that the underlying partitioned linear model is weakly singular in that the column space of the model matrix is contained in the column space of the covariance matrix of the errors in the linear model. In Chapter III our results are specialized to partitioned linear models where the partitioning is orthogonal and the covariance matrix of the errors is positive definite.
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Rosopa, Patrick. "A COMPARISON OF ORDINARY LEAST SQUARES, WEIGHTED LEAST SQUARES, AND OTHER PROCEDURES WHEN TESTING FOR THE EQUALITY OF REGRESSION." Doctoral diss., University of Central Florida, 2006. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/2311.
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When testing for the equality of regression slopes based on ordinary least squares (OLS) estimation, extant research has shown that the standard F performs poorly when the critical assumption of homoscedasticity is violated, resulting in increased Type I error rates and reduced statistical power (Box, 1954; DeShon & Alexander, 1996; Wilcox, 1997). Overton (2001) recommended weighted least squares estimation, demonstrating that it outperformed OLS and performed comparably to various statistical approximations. However, Overton's method was limited to two groups. In this study, a generalization of Overton's method is described. Then, using a Monte Carlo simulation, its performance was compared to three alternative weight estimators and three other methods. The results suggest that the generalization provides power levels comparable to the other methods without sacrificing control of Type I error rates. Moreover, in contrast to the statistical approximations, the generalization (a) is computationally simple, (b) can be conducted in commonly available statistical software, and (c) permits post hoc analyses. Various unique findings are discussed. In addition, implications for theory and practice in psychology and future research directions are discussed.Ph.D.
Department of Psychology
Sciences
Psychology
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Shulga, Yelena A. "Model-based calibration of a non-invasive blood glucose monitor." Digital WPI, 2006. https://digitalcommons.wpi.edu/etd-theses/58.
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This project was dedicated to the problem of improving a non-invasive blood glucose monitor being developed by the VivaScan Corporation. The company has made some progress in the non-invasive blood glucose device development and approached WPI for a statistical assistance in the improvement of their model in order to predict the glucose level more accurately. The main goal of this project was to improve the ability of the non-invasive blood glucose monitor to predict the glucose values more precisely. The goal was achieved by finding and implementing the best regression model. The methods included ordinary least squared regression, partial least squares regression, robust regression method, weighted least squares regression, local regression, and ridge regression. VivaScan calibration data for seven patients were analyzed in this project. For each of these patients, the individual regression models were built and compared based on the two factors that evaluate the model prediction ability. It was determined that partial least squares and ridge regressions are two best methods among the others that were considered in this work. Using these two methods gave better glucose prediction. The additional problem of data reduction to minimize the data collection time was also considered in this work.
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Haddad, Khaled. "Design flood estimation for ungauged catchments in Victoria ordinary & generalised least squares methods compared /." View thesis, 2008. http://handle.uws.edu.au:8081/1959.7/30369.
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Thesis (M.Eng. (Hons.)) -- University of Western Sydney, 2008.A thesis submitted towards the degree of Master of Engineering (Honours) in the University of Western Sydney, College of Health and Science, School of Engineering. Includes bibliographical references.
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Amir, Daban. "Kenyas export till samtliga handelspartner - påverkande faktorer? : En empirisk analys på makronivå med tillämpning av gravitationsmodellen." Thesis, Örebro universitet, Handelshögskolan vid Örebro Universitet, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-35622.
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Tidigare studier visar att ökad handel spelar en tydlig roll för ett lands ekonomiska tillväxt. Genom att träda in på den globala marknaden öppnas många möjligheter för ökad handel och nya arbetstillfällen. Utrikeshandeln är betydelsefull för små öppna ekonomier som till exempel Kenya och bör utgöra en stor del av landets BNP. I och med detta är det viktigt att studera vilka faktorer som påverkar ett lands utrikeshandel. Syftet med uppsatsen är att undersöka vilka faktorer som påverkar Kenyas export. Analysen visar att handelspartnernas BNP har en betydande påverkan på Kenyas export. Det geografiska avståndet har en negativ påverkan på Kenyas utrikeshandel. De regionala handelsavtalen har som förväntat en positiv påverkan på exporten.
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Craver, Gerald A. "A Comparison of Ordinary Least Squares and Instrumental Variables Regression for High Intensity Disease Management Evaluation." VCU Scholars Compass, 2008. http://scholarscompass.vcu.edu/etd/4513.
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Purpose: Disease management (DM) programs are typically evaluated using study designs that are susceptible to selection bias and other internal validity threats because participants are often allowed to self-select into the programs. As a result, DM evaluation results are usually biased because researchers are unable to control for preexisting differences between the DM participants and non-participants. Linden and Adams (2006) offer an instrumental variables (IV) regression procedure as a means of deriving unbiased estimates of DM program effectiveness. However, IV regression relies upon the existence of one or more variables (or instruments) that produce considerable variation in the program participation variable, but have no direct effect on the outcome variable. Linden and Adams argue that participant three-digit zip codes meet these criteria and can be used as instruments in IV regression.
Methods: To test the feasibility of their IV regression procedure, a series of ordinary least squares (OLS) and instrumental variables (IV) regression models were used to evaluate the effects of a high intensity Medicaid diabetes DM program on annual diabetes-related costs, emergency department visits, and hospital days. Program participation was the endogenous variable and age, gender, and propensity scores were the exogenous variable. Standard statistical tests were performed to assess the quality and validity of the IV regression models and zip code instruments.
Results: The study found that using propensity scores as covariates in the regression models appeared to offer a viable means of controlling for potential overt biases. However, the statistical tests performed to assess the quality and validity of the IV regression procedure using recipient three-digit zip codes as instruments indicated that it may not be appropriate due to various issues such as multicollinearity, lack of significant differences between the IV and OLS regression models, and weak instrument bias.
Conclusions: While the results of the present study do not support the use of participant three-digit zip codes as instruments in IV regression, the quality of the results obtained using this procedure may depend on the specific sample that is used in the analysis. Researchers may thus still wish to consider this procedure when evaluating DM programs because different samples may yield different results.
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Krueger, Justin Michael. "Parameter Estimation Methods for Ordinary Differential Equation Models with Applications to Microbiology." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/78674.
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The compositions of in-host microbial communities (microbiota) play a significant role in host health, and a better understanding of the microbiota's role in a host's transition from health to disease or vice versa could lead to novel medical treatments. One of the first steps toward this understanding is modeling interaction dynamics of the microbiota, which can be exceedingly challenging given the complexity of the dynamics and difficulties in collecting sufficient data. Methods such as principal differential analysis, dynamic flux estimation, and others have been developed to overcome these challenges for ordinary differential equation models. Despite their advantages, these methods are still vastly underutilized in mathematical biology, and one potential reason for this is their sophisticated implementation. While this work focuses on applying principal differential analysis to microbiota data, we also provide comprehensive details regarding the derivation and numerics of this method. For further validation of the method, we demonstrate the feasibility of principal differential analysis using simulation studies and then apply the method to intestinal and vaginal microbiota data. In working with these data, we capture experimentally confirmed dynamics while also revealing potential new insights into those dynamics. We also explore how we find the forward solution of the model differential equation in the context of principal differential analysis, which amounts to a least-squares finite element method. We provide alternative ideas for how to use the least-squares finite element method to find the forward solution and share the insights we gain from highlighting this piece of the larger parameter estimation problem.Ph. D.
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Forslind, Fanni. "The Effect of Immigration on Income Distribution : A Comparative Study of Ordinary Least Squares and Beta Regression." Thesis, Uppsala universitet, Statistiska institutionen, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-433098.
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The purpose of this study is to estimate the relationship between income inequality and immigration in Sweden. To do so, data from the data base Kolada with observations from all 290 municipalities in Sweden is used. As a proxy for income distribution the Gini coefficient is used and as a proxy for immigration the share of foreign born of working age is used. The model also controls for income tax, education level and unemployment level. The dependent variable the Gini coefficient is bounded by a unit interval and it is therefore not possible to simply run a linear regression. Such a model could potentially predict outside the interval. To properly estimate the relationship two approaches are made. Firstly a model is estimated with Ordinary Least Squares (OLS) after the dependent variable is transformed on to the real line through log-odds. Then a model is estimated using beta regression. The study concludes that there is a statistically significant positive correlation between income inequality and immigration in Sweden. The OLS estimated model shows that a 1 unit increase in immigration, on average increases the log-odds of 0.28336 units, ceteris paribus. Beta regression provides perhaps more intuitive results. If immigration increases with 1% the income inequality increases with on average 0.1046%, ceteris paribus. Because of the easier interpretation, among other things, beta regression is determined to be a better estimation method in this study.
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Nevarez, Martinez Deyanira. "Identifying Housing Patterns in Pima County, Arizona Using the DEYA Affordability Index and Geospatial Analysis." The University of Arizona, 2015. http://hdl.handle.net/10150/576108.
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When the Fair Housing Act of 1968 was passed 47 years ago, the United States was in the midst of the civil rights movement and fair housing was identified as a pillar of equality. While, progress has been made, there is much work that needs to be done in order to achieve integration. As a country, the United States is a highly segregated country. It is important to understand the factors that contribute to this and it is important to understand the relationships that exists between them in order to attempt to solve the problem. While the legal barriers to integration have been lifted choices continue to be limited to families of color that lack the resources to live in desirable neighborhoods. The ultimate goal of this study is to examine the relationship between the impact of individual indicators and housing patterns in the greater Tucson/Pima county region. An affordability index, the DEYA index, was created to determine where affordability is at its highest. The index includes different weights for foreclosure, Pima County spending on affordable housing, the existence of Pima County general obligations bond affordable housing projects, land value and inclusion in the community land trust. Once this was determined a regression analysis was used to determine the relationship between affordability and individual factors that may be affecting integration. The indicators used were broken down into 3 categories: the categories were education, housing and neighborhoods and employment and economic health.
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Anderson, Cynthia 1962. "A Comparison of Five Robust Regression Methods with Ordinary Least Squares: Relative Efficiency, Bias and Test of the Null Hypothesis." Thesis, University of North Texas, 2001. https://digital.library.unt.edu/ark:/67531/metadc5808/.
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A Monte Carlo simulation was used to generate data for a comparison of five robust regression estimation methods with ordinary least squares (OLS) under 36 different outlier data configurations. Two of the robust estimators, Least Absolute Value (LAV) estimation and MM estimation, are commercially available. Three authormodified variations on MM were also included (MM1, MM2, and MM3). Design parameters that were varied include sample size (n=60 and n=180), number of independent predictor variables (2, 3 and 6), outlier density (0%, 5% and 15%) and outlier location (2x,2y s, 8x8y s, 4x,8y s and 8x,4y s). Criteria on which the regression methods were measured are relative efficiency, bias and a test of the null hypothesis. Results indicated that MM2 was the best performing robust estimator on relative efficiency. The best performing estimator on bias was MM1. The best performing regression method on the test of the null hypothesis was MM2. Overall, the MM-type robust regression methods outperformed OLS and LAV on relative efficiency, bias, and the test of the null hypothesis.
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Cook, Finnie B. "Globalization, Migration and the U.S. Labor Market for Physicians: The Impact of Immigration on Local Wages." [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0003279.
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Can, Mutan Oya. "Comparison Of Regression Techniques Via Monte Carlo Simulation." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/3/12605175/index.pdf.
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The ordinary least squares (OLS) is one of the most widely used methods for modelling the functional relationship between variables. However, this estimation procedure counts on some assumptions and the violation of these assumptions may lead to nonrobust estimates. In this study, the simple linear regression model is investigated for conditions in which the distribution of the error terms is Generalised Logistic. Some robust and nonparametric methods such as modified maximum likelihood (MML), least absolute deviations (LAD), Winsorized least squares, least trimmed squares (LTS), Theil and weighted Theil are compared via computer simulation. In order to evaluate the estimator performance, mean, variance, bias, mean square error (MSE) and relative mean square error (RMSE) are computed.
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Razzaghi, Hesham M. "Spatial Analysis of Alcohol-related Injury and Fatal Traffic Crashes in Ohio." University of Dayton / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1493979849390008.
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Karlsson, Jonas. "Public Opinion on Tobacco, Alcohol, and Sugar Policy and its Economic Implications in Sweden : A study on sociodemographic factors’ effects on health policy attitudes of Swedes." Thesis, Internationella Handelshögskolan, Jönköping University, IHH, Nationalekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-48515.
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Using paired samples t-tests, this study examines attitudes toward government intervention to decrease the consumption of tobacco, alcohol, and sugar to improve public health in Sweden. The effects of the four sociodemographic variables gender, age, education, and income on attitudes toward health policies are tested using Ordinary Least Squares and ordered probit regressions. The research is performed using cross-sectional data which is supplied by a national survey. The results show that tobacco should be regulated the most, followed by alcohol and lastly sugar. According to the respondents, tobacco and alcohol consumption need clear societal restrictions while individuals should be responsible for their sugar consumption. This implies that tobacco and alcohol restrictions introduced by the government should be effective and should, therefore, reduce the consumption and subsequently decrease a country’s economic costs. The opposite is true for sugar policy. Women, younger people, highly educated people, and people with higher incomes are positively related to support toward tobacco restrictions. Women, younger people, and highly educated people show more support for alcohol restrictions. Lastly, respondents with higher levels of education are more supportive of sugar restrictions.
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Murff, Elizabeth J. Tipton. "On the efficiency of ranked set sampling relative to simple random sampling for estimating the ordinary least squares parameters of the simple linear regression model /." Full text (PDF) from UMI/Dissertation Abstracts International, 2001. http://wwwlib.umi.com/cr/utexas/fullcit?p3008403.
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XIA, QI. "Sufficient Dimension Reduction with Missing Data." Diss., Temple University Libraries, 2017. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/469880.
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StatisticsPh.D.
Existing sufficient dimension reduction (SDR) methods typically consider cases with no missing data. The dissertation aims to propose methods to facilitate the SDR methods when the response can be missing. The first part of the dissertation focuses on the seminal sliced inverse regression (SIR) approach proposed by Li (1991). We show that missing responses generally affect the validity of the inverse regressions under the mechanism of missing at random. We then propose a simple and effective adjustment with inverse probability weighting that guarantees the validity of SIR. Furthermore, a marginal coordinate test is introduced for this adjusted estimator. The proposed method share the simplicity of SIR and requires the linear conditional mean assumption. The second part of the dissertation proposes two new estimating equation procedures: the complete case estimating equation approach and the inverse probability weighted estimating equation approach. The two approaches are applied to a family of dimension reduction methods, which includes ordinary least squares, principal Hessian directions, and SIR. By solving the estimating equations, the two approaches are able to avoid the common assumptions in the SDR literature, the linear conditional mean assumption, and the constant conditional variance assumption. For all the aforementioned methods, the asymptotic properties are established, and their superb finite sample performances are demonstrated through extensive numerical studies as well as a real data analysis. In addition, existing estimators of the central mean space have uneven performances across different types of link functions. To address this limitation, a new hybrid SDR estimator is proposed that successfully recovers the central mean space for a wide range of link functions. Based on the new hybrid estimator, we further study the order determination procedure and the marginal coordinate test. The superior performance of the hybrid estimator over existing methods is demonstrated in simulation studies. Note that the proposed procedures dealing with the missing response at random can be simply adapted to this hybrid method.
Temple University--Theses
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Alothman, Ahmad. "Model-Free Variable Selection For Two Groups of Variables." Diss., Temple University Libraries, 2018. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/515925.
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StatisticsPh.D.
In this dissertation we introduce two variable selection procedures for multivariate responses. Our procedures are based on sufficient dimension reduction concepts and are model-free. In the first procedure we consider the dual marginal coordinate hypotheses, where the role of the predictor and the response is not important. Motivated by canonical correlation analysis (CCA), we propose a CCA-based test for the dual marginal coordinate hypotheses, and devise a joint backward selection algorithm for dual model-free variable selection. The second procedure is based on ordinary least squares (OLS). We derive and study the asymptotic properties of the OLS-based test under the normality assumption of the predictors as well as an asymmetry assumption. When these assumptions are violated, the asymptotic test with elliptical trimming and clustering is still valid with desirable numerical performances. A backward selection algorithm for the predictor is also provided for the OLS-based test. The performances of the proposed tests and the variable selection procedures are evaluated through synthetic examples and a real data analysis.
Temple University--Theses
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Choudhury, Gias Uddin Ahmed. "Impact of Microcredit Program on Women's Empowerment in Rural Bangladesh." Thesis, Karlstads universitet, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-80192.
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Background – This study is an attempt to explore the relationship between microcredit and the socio-economic empowerment of women in rural Bangladesh. Microcredit is simply the extension of a small amount of collateral-free institutional loans to jointly liable poor group members to generate employment and income enhancing activities. As it is too difficult for poor members to get loan from the formal credit institutions, Grameen Bank (GB) or other Non-Government Organizations (NGOs) provide small loans to vulnerable groups of the society by which they are expected to empower over his counterparts. Research questions – RQ1: How does micro-credit affect different indicators of women empowerment in the rural areas of Bangladesh? RQ2– Is the impact different from the male counterparts in the sample households? Purpose – This study is an effort to find the impact of microcredit on a number of indicators of women’s empowerment in the rural areas in Bangladesh. Methodology – Quantitative Regression Techniques such as Ordinary Least Square (OLS) and Instrumental Variable (IV) method have been applied to get the relationship between microcredit and women empowerment. Conclusion – Applying nationally representative cross-section survey data, Bangladesh Integrated Household Survey (BIHS) 2015, this thesis is intended to find the causal linkage between microcredit and women empowerment’s with different dimensions of women’s decisions are taken as empowerment indicators: production, resources, income, leadership, savings and time. The analysis has been conducted at the household level. The study assumes that women empowerment is endogenous. After controlling for endogeneity in the estimation by using an instrumental variable (IV) ‘distance to the market’ this study finds a significant relationship between microcredit and different dimensions of women’s empowerment. Participation in the microcredit program is found to be significant in explaining some of the outcome indicators of empowerment for the sampled households.
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Haubeltova, Libuse. "Case study of Airbnb listings in Berlin : Hedonic pricing approach to measuring demand for tourist accommodation characteristics." Thesis, Högskolan Dalarna, Nationalekonomi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:du-29979.
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The main purpose of this degree project is to reveal the Airbnb customer’s preferences and quantify the impact of non-market factors on the market price of tourist accommodation in Berlin, Germany. The data retrieved from Airbnb listings, publicly available on Inside Airbnb (2017), was supplemented on indicator of sharing economy accommodation using machine learning method in order to distinguish between amateur and business-running professional hosts. The main aim is to examine the consumers’ preferences and quantify the marginal effect of "real sharing economy" accommodation and other key variables on market price. This is accomplished by model approach using hedonic pricing method, which is used to estimate the economic value of particular attribute. Surprisingly, our data indicates the negative impact of sharing economy indicator on price. The set of motivations of consumers, which determine their valuation of Airbnb listings, was identified. The trade-off between encompass and parsimony of the set was desired in order to build an effective model. Calculation of proportion of explained variance showed that the price is affected mainly by number of accommodated persons, degree of privacy, number of bedrooms, cancellation policy, distance from the city centre and sharing economy indicator in decreasing order.
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Cankaya, Ergin Cagatay. "Testing methods for calibrating Forest Vegetation Simulator (FVS) diameter growth predictions." Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/97321.
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The Forest Vegetation Simulator (FVS) is a growth and yield modeling system widely-used for predicting stand and tree-level attributes for management and planning applications in North American forests. The accuracy of FVS predictions for a range of tree and stand level attributes depends a great deal on the performance of the diameter increment model and its predictions of change in diameter at breast height (DBH) over time. To address the challenge of predicting growth in highly variable and geographically expansive forest systems, FVS was designed to include an internal calibration algorithm that makes use of growth observations, when available, from permanent inventory plots. The basic idea is that observed growth rates on a collection of remeasured trees are used to adjust or "calibrate" FVS diameter growth predictions. Therefore, DBH modeling was the focus of this investigation.
Five methods were proposed for local calibration of individual tree DBH growth predictions and compared to two sets of results generated without calibration. Data from the US Forest Service's Forest Inventory and Analysis (FIA) program were used to test the methods for eleven widely-distributed forest tree species in Virginia. Two calibration approaches were based on median prediction errors from locally-observed DBH increments spanning a five year average time interval. Two were based on simple linear regression models fitted to the locally-observed prediction errors, and one method employed a mixed effects regression model with a random intercept term estimated from locally-observed DBH increments. Data witholding, specifically a leave-one-out cross-validation was used to compare results of the methods tested.
Results showed that any of the calibration approaches tested in general led to improved accuracy of DBH growth predictions, with either of the median-based methods or regression based methods performing better than the random-effects-based approach. Equivalence testing showed that median or regression-based local calibration methods met error tolerances within ± 12% of observed DBH increments for all species with the random effects approach meeting a larger tolerance of ± 17%. These results showed improvement over uncalibrated models, which failed to meet tolerances as high as ± 30% for some species in a newly-fitted DBH growth model for Virginia, and as high as ± 170% for an existing model fitted to data from a much larger region of the Southeastern United States. Local calibration of regional DBH increment models provides an effective means of substantially reducing prediction errors when a relatively small set of observations are available from local sources such as permanent forest inventory plots, or the FIA database.MS
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Coughlin, Kevin Barry. "An Analysis of Factor Extraction Strategies: A Comparison of the Relative Strengths of Principal Axis, Ordinary Least Squares, and Maximum Likelihood in Research Contexts that Include both Categorical and Continuous Variables." Scholar Commons, 2013. http://scholarcommons.usf.edu/etd/4459.
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This study is intended to provide researchers with empirically derived guidelines for conducting factor analytic studies in research contexts that include dichotomous and continuous levels of measurement. This study is based on the hypotheses that ordinary least squares (OLS) factor analysis will yield more accurate parameter estimates than maximum likelihood (ML) and principal axis factor anlaysis (PAF); the level of improvement in estimates will be related to the proportion of observed variables that are dichotomized and the strength of communalities within the data sets.
To achieve this study's objective, maximum likelihood, ordinary least squares, and principal axis factor extraction models were subjected to various research contexts. A Monte Carlo method was used to simulate data under 540 different conditions; specifically, this study is a four (sample size) by three (number of variables) by three (initial communality levels) by three (number of common factors) by five (ratios of categorical to continuous variables) design. Factor loading matrices derived through the tested factor extraction methods were evaluated through four measures of factor pattern agreement and three measures of congruence.
To varying degrees, all of the design factors, as main effects, yielded significant differences in measures of factor loading sensitivity, agreement between sample and population, and congruence. However, in all cases, the main effects were components of interactions that yielded differences in values of these measures that were at least medium in effect size. The number of factors imbedded in the population was a component in six interactions that resulted in medium effect size differences in measures of agreement between population and sample factor loading matrices. of factor loading sensitivity, general pattern agreement, per element agreement, congruence, factor score correlations, and factor loading bias; in terms of the number of interactions that yielded at least medium effect size differences in measures of sensitivity, agreement, and congruence. The number of factors design factor exerted a larger influence than any of the other design factors. The level of communality interacted with the number of factors, number of observed variables, and sample size main effects to yield at least medium effect size differences in factor loading sensitivity, general pattern agreement, per element agreement, congruence, factor score correlations, factor loading bias, and RMSE; in terms of the number of factors that included communality as a component, this design factor exerted the second largest amount of influence on the measures of sensitivity, agreement, and congruence. The level of dichotomization, sample size, and number of observed variables were included in smaller numbers of interactions; however, these interactions yielded differences in all of the outcome variables that were at least medium in effect size.
Across the majority of interactions among the manipulated research contexts, the ordinary least squares factor extraction method yielded factor loading matrices that were in better agreement with the population than either the maximum likelihood or the principal axis methods. In three of the four measures of congruence, the ordinary least squares method yielded factor loading matrices that exhibited less bias and error than the other two tested factor extraction methods. In general, the ordinary least squares method yielded factor loading matrices that correlated more strongly with the population than either of the other two tested methods.
The suggested use of ordinary least squares factor analytic techniques represents the major, empirically derived recommendation derived from the results of this study. In all tested conditions, the ordinary least squares factor extraction method identified common factors with a high degree of efficacy. Suggested studies for future would incorporate the limiting constraints associated with this dissertation into methodological studies to extend the generalizability of conclusions and recommendations into areas that are beyond the scope of this dissertation.
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Aydin, Gunes. "Aerodynamic Parameter Estimation Of A Missile In Closed Loop Control And Validation With Flight Data." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12615044/index.pdf.
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Aerodynamic parameter estimation from closed loop data has been developed as another research area since control and stability augmentation systems have been mandatory for aircrafts. This thesis focuses on aerodynamic parameter estimation of an air to ground missile from closed loop data using separate surface excitations. A design procedure is proposed for designing separate surface excitations. The effect of excitations signals to the system is also analyzed by examining autopilot disturbance rejection performance. Aerodynamic parameters are estimated using two different estimation techniques which are ordinary least squares and complex linear regression. The results are compared with each other and with the aerodynamic database. An application of the studied techniques to a real system is also given to validate that they are directly applicable to real life.
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Deng, Kefu. "The value and validity of software effort estimation models built from a multiple organization data set." Click here to access this resource online, 2008. http://hdl.handle.net/10292/473.
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The objective of this research is to empirically assess the value and validity of a multi-organization data set in the building of prediction models for several ‘local’ software organizations; that is, smaller organizations that might have a few project records but that are interested in improving their ability to accurately predict software project effort. Evidence to date in the research literature is mixed, due not to problems with the underlying research ideas but with limitations in the analytical processes employed: • the majority of previous studies have used only a single organization as the ‘local’ sample, introducing the potential for bias • the degree to which the conclusions of these studies might apply more generally is unable to be determined because of a lack of transparency in the data analysis processes used. It is the aim of this research to provide a more robust and visible test of the utility of the largest multi-organization data set currently available – that from the ISBSG – in terms of enabling smaller-scale organizations to build relevant and accurate models for project-level effort prediction. Stepwise regression is employed to enable the construction of ‘local’, ‘global’ and ‘refined global’ models of effort that are then validated against actual project data from eight organizations. The results indicate that local data, that is, data collected for a single organization, is almost always more effective as a basis for the construction of a predictive model than data sourced from a global repository. That said, the accuracy of the models produced from the global data set, while worse than that achieved with local data, may be sufficiently accurate in the absence of reliable local data – an issue that could be investigated in future research. The study concludes with recommendations for both software engineering practice – in setting out a more dynamic scenario for the management of software development – and research – in terms of implications for the collection and analysis of software engineering data.
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Luo, Hao. "Some Aspects on Confirmatory Factor Analysis of Ordinal Variables and Generating Non-normal Data." Doctoral thesis, Uppsala universitet, Statistiska institutionen, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-149423.
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This thesis, which consists of five papers, is concerned with various aspects of confirmatory factor analysis (CFA) of ordinal variables and the generation of non-normal data. The first paper studies the performances of different estimation methods used in CFA when ordinal data are encountered. To take ordinality into account the four estimation methods, i.e., maximum likelihood (ML), unweighted least squares, diagonally weighted least squares, and weighted least squares (WLS), are used in combination with polychoric correlations. The effect of model sizes and number of categories on the parameter estimates, their standard errors, and the common chi-square measure of fit when the models are both correct and misspecified are examined. The second paper focuses on the appropriate estimator of the polychoric correlation when fitting a CFA model. A non-parametric polychoric correlation coefficient based on the discrete version of Spearman's rank correlation is proposed to contend with the situation of non-normal underlying distributions. The simulation study shows the benefits of using the non-parametric polychoric correlation under conditions of non-normality. The third paper raises the issue of simultaneous factor analysis. We study the effect of pooling multi-group data on the estimation of factor loadings. Given the same factor loadings but different factor means and correlations, we investigate how much information is lost by pooling the groups together and only estimating the combined data set using the WLS method. The parameter estimates and their standard errors are compared with results obtained by multi-group analysis using ML. The fourth paper uses a Monte Carlo simulation to assess the reliability of the Fleishman's power method under various conditions of skewness, kurtosis, and sample size. Based on the generated non-normal samples, the power of D'Agostino's (1986) normality test is studied. The fifth paper extends the evaluation of algorithms to the generation of multivariate non-normal data. Apart from the requirement of generating reliable skewness and kurtosis, the generated data also need to possess the desired correlation matrices. Four algorithms are investigated in terms of simplicity, generality, and reliability of the technique.
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Robacker, Thomas C. "Comparison of Two Parameter Estimation Techniques for Stochastic Models." Digital Commons @ East Tennessee State University, 2015. https://dc.etsu.edu/etd/2567.
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Parameter estimation techniques have been successfully and extensively applied to deterministic models based on ordinary differential equations but are in early development for stochastic models. In this thesis, we first investigate using parameter estimation techniques for a deterministic model to approximate parameters in a corresponding stochastic model. The basis behind this approach lies in the Kurtz limit theorem which implies that for large populations, the realizations of the stochastic model converge to the deterministic model. We show for two example models that this approach often fails to estimate parameters well when the population size is small. We then develop a new method, the MCR method, which is unique to stochastic models and provides significantly better estimates and smaller confidence intervals for parameter values. Initial analysis of the new MCR method indicates that this method might be a viable method for parameter estimation for continuous time Markov chain models.
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Shimote, Juliana. "Uma análise do gasto familiar com educação no Brasil e da participação do crédito em seu financiamento." reponame:Repositório Institucional do FGV, 2015. http://hdl.handle.net/10438/13498.
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In the context of the release of the microcredit package and of the payday loan law in 2003, and facing the emergence of credit offers being made to the lower income population, this study aims to evaluate the impact on consumption preferences, specifically those related to educational expenditures. More precisely, it assesses whether the higher credit offer led to a higher investment in education. The data used is drawn from the 2002 and 2008 Consumer Expenditure Survey, or Pesquisa de Orçamentos Familiares (POF), from IBGE, over which were adjusted ordinary least squares regressions. The results show that there was a large expansion in the percentage of families with loans expenditures, as well as a corresponding increase in the amount of these expenditures between the two editions of the survey. Lastly, it was possible to verify that a correlation exists between loan and educational expenditures.
No contexto do lançamento do pacote do microcrédito e da Lei do consignado em 2003, e diante de um novo cenário de oferta de crédito destinada à população de baixa renda, o presente estudo busca avaliar o impacto nas preferências de consumo, especificamente com relação a despesas com educação. A reflexão feita nesse estudo é se esse crédito é utilizado também para garantir investimentos em educação. Os dados utilizados são da Pesquisa de Orçamento Familiar (POF) do IBGE dos anos 2002 e 2008 sobre os quais foram ajustadas regressões de mínimos quadrados ordinários. Os resultados mostram que houve uma grande expansão ao acesso, no que se refere ao percentual de famílias com gastos com empréstimos, e uma correspondente ampliação do valor dessas despesas entre as duas edições da pesquisa analisadas. Por fim, foi possível verificar que existe correlação entre as despesas com empréstimos e com educação.
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Nedrebo, Oystein. "Transnational dimensions of civil conflict severity." Thesis, Stellenbosch : University of Stellenbosch, 2009. http://hdl.handle.net/10019.1/2123.
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Thesis (MA (Political Science. International Studies))--University of Stellenbosch, 2009.ENGLISH ABSTRACT: In an otherwise broad literature on civil conflict little attention has so far been paid to actual conflict violence and variation in severity. Existing work is also hampered by a reliance on a ‘closed polity’ model of the state, leading to disregard of the transnational dimensions of internal conflict, and by a dependence on over‐aggregated data. The present inquiry expands on the existing explanatory framework for variation in civil conflict severity by including transnational factors and characteristics of sub‐national actors. Data on conflict battle deaths are combined with recently available data on transnational ethnic linkages, transnational support and neighbouring conflict as well as other actor and country characteristics. Results from ordinary least squares regression analysis indicate that support for rebel groups from external non‐state actors increase conflict severity, while rebel presence in other states is associated with less severe conflicts. In addition, severity increases with duration but with a diminishing marginal return. Internal armed conflicts are less severe in democratic and ethnically polarised countries but rebel territorial control increases the level of violence.
AFRIKAANSE OPSOMMING: In die andersins omvangryke literatuur oor burgerlike konflik is daar tot op hede min aandag geskenk aan werklike konflikgeweld en variasie in felheid (vernietigende omvang). Bestaande werk word ook belemmer omdat dit staat maak op ’n model van die staat as ‘geslote regering’, wat lei tot verontagsaming van die transnasionale dimensies van interne konflik, en staat maak op oor‐geaggregeerde data. Hierdie ondersoek brei uit op die bestaande verklarende raamwerk vir variasie in felheid van burgerlike konflik deur transnasionale faktore en eienskappe van subnasionale deelnemers in te sluit. Data oor konflikgevegsterftes is gekombineer met onlangse data oor transnasionale etniese koppelings, transnasionale steun en naburige konflik, sowel as ander deelnemer‐ en landeienskappe. Resultate van gewone kleinstekwadrate‐regressie‐analise dui daarop dat steun aan rebellegroepe deur eksterne nie‐staatsdeelnemers konflikfelheid laat toeneem, terwyl rebelleteenwoordigheid in ander lande geassosieer word met minder fel konflikte. Felheid neem ook toe saam met duur maar met ’n afnemende marginale opbrengs. Interne gewapende konflikte is minder fel in demokratiese en etnies gepolariseerde lande, maar rebellebeheer oor grondgebied verhoog die vlak van geweld.
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Covo, Marcelo Braga. "Extraindo as expectativas de mercado para a taxa de juros no Brasil usando opções sobre IDI." reponame:Repositório Institucional do FGV, 2009. http://hdl.handle.net/10438/13620.
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Este trabalho demonstra como podemos usar opções sobre o Índice de Taxa Média de Depósitos Interfinanceiros de Um Dia (IDI) para extrair a função densidade de probabilidade (FDP) para os próximos passos do Comitê de Política Monetária (COPOM). Como a decisão do COPOM tem uma natureza discreta, podemos estimar a FDP usando Mínimo Quadrados Ordinários (MQO). Esta técnica permite incluir restrições sobre as probabilidades estimadas. As probabilidades calculadas usando opções sobre IDI são então comparadas com as probabilidades encontradas usando o Futuro de DI e as probabilidades calculadas através de pesquisas.
This paper demonstrates how options on the One-day Brazilian Interfinancial Deposits Index (IDI) can be used to recover the implied probability density function (PDF) for futures Monetary Policy Committee (COPOM) outcomes. The discrete nature of the choices made by the COPOM allows recovering the PDF using ordinary least squares (OLS) estimation. This method also allows the imposition of restrictions on the recovered probabilities. Recovered probabilities using options on IDI are then compared to the probabilities obtained using the futures on DI and the probabilities recovered by surveys.
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Comenda, José Diogo Sampaio. "Government borrowing costs and fiscal developments." Master's thesis, Instituto Superior de Economia e Gestão, 2020. http://hdl.handle.net/10400.5/20692.
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Mestrado em Economia Monetária e FinanceiraNeste artigo, analiso os determinantes do rendimento dos títulos soberanos a 10 anos em relação à Alemanha para um painel de 10 países da área do euro para um período entre 1999 e 2019. Além das variáveis habituais, como o vix, taxa de câmbio efetiva real, saldo orçamental esperado, dívida esperada em relação ao PIB e crescimento do PIB, estudei o impacto das regras fiscais e das medidas de política monetária do BCE, nomeadamente o LTRO, SMP e PSPP. Este trabalho permite concluir que, quando testado individualmente, um aumento dos spreads de compra e venda, taxa de câmbio efetiva real e dívida esperada leva a um aumento nos spreads da dívida soberana, enquanto um aumento no crescimento do PIB e no saldo orçamental leva a uma diminuição nos spreads da dívida soberana. Também concluí que um aumento nas classificações de crédito médias tem um impacto negativo nos spreads da dívida soberana. Finalmente, no que diz respeito ao QE do BCE, não encontrei qualquer evidência de significância estatística.
In this paper, I examine the determinants of 10-year sovereign bond yield relative to Germany for a panel of 10 Euro area countries for a period between 1999 and 2019. Beyond the usual variables such as vix, real effective exchange rate, expected budget balance, expected debt-to-GDP and GDP growth, I studied the impact of fiscal rules and ECB monetary policy measures, namely the LTRO, SMP and PSPP. My work finds that, when tested individually, an increase in bid ask spreads, real effective exchange rate and expected debt leads to an increase in yield spreads while an increase in GDP growth and in budget balance leads to a decrease in bond yields. I also found that an increase on the average credit ratings have a negative impact on bond yields. Finally, in what it concerns with ECB quantitative easing I did not find any evidence of statistically significance.
info:eu-repo/semantics/publishedVersion
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Katsikatsou, Myrsini. "Composite Likelihood Estimation for Latent Variable Models with Ordinal and Continuous, or Ranking Variables." Doctoral thesis, Uppsala universitet, Statistiska institutionen, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-188342.
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The estimation of latent variable models with ordinal and continuous, or ranking variables is the research focus of this thesis. The existing estimation methods are discussed and a composite likelihood approach is developed. The main advantages of the new method are its low computational complexity which remains unchanged regardless of the model size, and that it yields an asymptotically unbiased, consistent, and normally distributed estimator. The thesis consists of four papers. The first one investigates the two main formulations of the unrestricted Thurstonian model for ranking data along with the corresponding identification constraints. It is found that the extra identifications constraints required in one of them lead to unreliable estimates unless the constraints coincide with the true values of the fixed parameters. In the second paper, a pairwise likelihood (PL) estimation is developed for factor analysis models with ordinal variables. The performance of PL is studied in terms of bias and mean squared error (MSE) and compared with that of the conventional estimation methods via a simulation study and through some real data examples. It is found that the PL estimates and standard errors have very small bias and MSE both decreasing with the sample size, and that the method is competitive to the conventional ones. The results of the first two papers lead to the next one where PL estimation is adjusted to the unrestricted Thurstonian ranking model. As before, the performance of the proposed approach is studied through a simulation study with respect to relative bias and relative MSE and in comparison with the conventional estimation methods. The conclusions are similar to those of the second paper. The last paper extends the PL estimation to the whole structural equation modeling framework where data may include both ordinal and continuous variables as well as covariates. The approach is demonstrated through an example run in R software. The code used has been incorporated in the R package lavaan (version 0.5-11).
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Wikström, Gunilla. "Computation of Parameters in some Mathematical Models." Doctoral thesis, Umeå University, Computing Science, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-565.
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In computational science it is common to describe dynamic systems by mathematical models in forms of differential or integral equations. These models may contain parameters that have to be computed for the model to be complete. For the special type of ordinary differential equations studied in this thesis, the resulting parameter estimation problem is a separable nonlinear least squares problem with equality constraints. This problem can be solved by iteration, but due to complicated computations of derivatives and the existence of several local minima, so called short-cut methods may be an alternative. These methods are based on simplified versions of the original problem. An algorithm, called the modified Kaufman algorithm, is proposed and it takes the separability into account. Moreover, different kinds of discretizations and formulations of the optimization problem are discussed as well as the effect of ill-conditioning.
Computation of parameters often includes as a part solution of linear system of equations Ax = b. The corresponding pseudoinverse solution depends on the properties of the matrix A and vector b. The singular value decomposition of A can then be used to construct error propagation matrices and by use of these it is possible to investigate how changes in the input data affect the solution x. Theoretical error bounds based on condition numbers indicate the worst case but the use of experimental error analysis makes it possible to also have information about the effect of a more limited amount of perturbations and in that sense be more realistic. It is shown how the effect of perturbations can be analyzed by a semi-experimental analysis. The analysis combines the theory of the error propagation matrices with an experimental error analysis based on randomly generated perturbations that takes the structure of A into account
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Casselryd, Linnéa, Agnes Lantto, and Alicia Julienne Zanic. "MSCI Climate Paris Aligned Indices : A quantitative study comparing the performance of SR indices and their conventional benchmark indices." Thesis, Umeå universitet, Företagsekonomi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-185021.
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There is no clear consensus about whether green investments perform better, worse orequal to conventional brown investments. With the rising popularity of socialinvestments, it becomes increasingly important to understand these investments. Therecent launch of the MSCI Climate Paris Aligned Indices (CPAI) aim to illustrate thedevelopment of an economy that is in line with the requirements and goals of the ParisAgreement from 2015. In this research we aim to find out whether the MSCI Europe,USA and EM Climate Paris Aligned Indices outperform their parent indices. We do thisby comparing performance measures such as the net return, standard deviation of netreturns and Sharpe ratio. We further conduct an ordinary least squares regression to testwhether the betas and Jensen´s alphas of the CPAI differ significantly from their parentindices.The results show that only the USA CPAI clearly outperforms its parent index. This isdue to it having a higher Sharpe Ratio and Jensen’s alpha as well as higher monthly netreturns and a lower standard deviation compared to its parent index. The regressionshows that it does perform better than the parent index. The results for the EM CPAIshow that it performs in a similar way as its parent index. It has a higher monthly netreturn but also slightly higher standard deviation which leads to an equally large Sharperatio. Neither the estimated Jensen’s alpha nor the beta are significantly different fromthose of its parent index and thus the hypothesis of it performing equally as well as itsparent index cannot not be rejected. Lastly, the Europe CPAI has a higher Sharpe ratio,Jensen’s alpha and monthly net returns than its parent index, but it also exhibits a higherstandard deviation. The regression indicated that it performs in a similar way as itsparent index, no difference could be proven. In conclusion, this means that all CPAIperform at least equally as well as their parent indices, if not better.
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Urdinez, Francisco. "A EPI da ascensão chinesa como um ator global chave." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/101/101131/tde-26022014-174514/.
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O Protocolo de Adesão à Organização Mundial do Comércio da China, assinado em dezembro de 2001, permitiu a outros países membros considerarem a China como uma economia \"não de mercado\" até o final de 2016. O objetivo deste trabalho é responder a seguinte pergunta: Pode o Reconhecimento de Economia de Mercado (REM) ser medido em seu compliance? O proxy utilizado parra o compliance foi o número de investigações antidumping iniciadas por país. A expectativa é que os países que reconhecem o status de economia de mercado da China iniciem menos investigações antidumping do que aqueles que ainda tratam a China como uma economia \"não de mercado\". Isso explicaria por que o governo chinês tem feito campanha desde 2001 para ganhar REM entre seus parceiros econômicos. A utilização de modelos de contagem demonstra que o REM teve um impacto positivo na redução do número de investigações antidumping contra produtos chineses. O atual desenvolvimento econômico da China depende muito de seu acesso a recursos energéticos, o que cada vez mais influencía mudanças nos Investimento Direto Estrangeiro (IDE) chinês com a finalidade de possibilitar o acesso a recursos que estão localizados no exterior. O objetivo deste trabalho é responder às seguintes perguntas: Em que medida a procura por recursos energéticos afetou os IDE entre 2005 e 2012? Essa procura foi sensível à locação geográfica dos recursos? Os dados sobre IDE chineses foram obtidos do China Global Investment Tracker, e utilizaram-se determinantes domésticos de IDE, testados empiricamente na literatura existente, para medir o impacto da produção de energia do país anfitrião na alocação de investimentos. Ao aplicar MCO e um modelo com lag espacial em uma amostra de 92 países demostrou-se que os recursos energéticos do país anfitrião foram o principal motor da IDE chinesa, e que não houve sensibilidade geográfica aos recursos.China´s Protocol of Accession to the World Trade Organization, signed on December 2001, allowed other country members to consider China as a Non Market Economy (NME) until the end of 2016. The aim of this paper is to answer the following question: Can the Market Economy Status (MES) Recognition be measured in its compliance? The proxy used for that compliance was the number of antidumping investigations initiated per country. The expectation is that countries recognizing Chinese MES would initiate fewer antidumping investigations than countries still treating China as a Non Market Economy. This would explain why the Chinese Government has been campaigning vigorously since 2001 to gain MES among its economic partners. Using count-models we demonstrate that MES had a positive impact in reducing the number of antidumping investigations against Chinese products. China´s current economic development depends heavily on its access to energetic resources, and it is increasingly shaping Chinese Outward Foreign Direct Investment (OFDI) in a quest for gaining access to resources that are located abroad. The aim of this paper is to answer the two following questions: How much did the Chinese global quest for energy drive its OFDI between 2005 and 2012? Has the quest for energy been sensitive to the geographical location of the resources? Data on Chinese OFDI was retrieved from the China Global Investment Tracker, and we used diverse Host-Countries determinants of OFDI tested before in the literature and measured the impact of Host-Country energy production in the allocation of investments. Using OLS and a Spatial Lagged Model we demonstrate that energetic resources were the main driver of Chinese OFDI in 92 host countries during the studied period, and that there was no sensitivity to the geographical location of the resources.
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Gonçalves, Sofia Maria Lima Fernandes. "The impact of liquidity and solvency constraints in European banks’ efficiency." Master's thesis, Instituto Superior de Economia e Gestão, 2017. http://hdl.handle.net/10400.5/14794.
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Mestrado em FinançasO objetivo deste estudo é analisar a relação entre a eficiência bancária e algumas das medidas regulatórias do Basileia III. É feita uma apresentação e discussão da eficácia das normas globais de liquidez e capital, recentemente impostas pelo Comité de Supervisão Bancária do Basileia (BCBS - Basel Committee on Banking Supervision). A nossa análise empírica baseia-se em duas metodologias distintas: (i) regressões lineares múltiplas; (ii) um método não paramétrico designado de Análise de Dados em Envelope (DEA - Data Envelopment Analysis). A eficiência no setor bancário é medida a partir de duas perspetivas diferentes - com base em simples rácios contabilísticos e, alternativamente, a partir do conceito de eficiência técnica que consiste na distância relativa a uma fronteira de eficiência padrão. Os nossos resultados apontam para a presença de efeitos da regulação do Basileia na eficiência bancária, embora estes efeitos não sejam consistentes durante os três anos em análise. Os resultados de ambas as metodologias sugerem impactos contraditórios na eficiência dos bancos europeus.
The purpose of this study is to analyse the relationship between bank efficiency and some Basel III regulatory measures. It presents and discusses the effectiveness of recent liquidity and capital global standards imposed by the Basel Committee on Banking Supervision (BCBS). Our empirical analysis relies on two distinct methodologies: (i) multiple linear regressions; (ii) a non parametric method called Data Envelopment Analysis (DEA). The efficiency in the banking sector is measured in two different perspectives - through simple accounting ratios and, alternatively, through the concept of technical efficiency which consists of the relative distance to a best-practice efficient frontier. Our findings point to the presence of effects of Basel regulation on bank efficiency, although these effects are not consistent throughout the three-year analysis. Evidence from both methodologies suggest a conflicting impact on the efficiency of European banks.
info:eu-repo/semantics/publishedVersion
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Penna, João Barbosa Campbell. "Especificação da paridade descoberta de juros no mercado brasileiro." reponame:Repositório Institucional do FGV, 2014. http://hdl.handle.net/10438/13782.
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Submitted by joao barbosa campbell penna (joao.penna@vale.com) on 2015-02-20T19:44:37Z
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Medimos a validade da paridade descoberta de juros – PDJ - para o mercado brasileiro no período de janeiro de 2010 a julho de 2014. Testamos a equação clássica da PDJ usando o Método dos Mínimos Quadrados Ordinários. Após a estimação dos parâmetros, aplicamos o Teste de Wald e verificamos que a paridade descoberta de juros não foi validada. Estendemos a equação tradicional da PDJ para uma especificação alternativa que captura medidas de risco Brasil e de alteração na liquidez internacional. Especificamente, acrescentamos três variáveis de controle: duas variáveis dummy que capturam condições de liquidez externa e o índice de commoditie CRB, que captura o risco Brasil. Com a especificação alternativa, a hipótese de que os retornos das taxas de juros em Real, dolarizadas, são iguais aos retornos da taxas de juros contratadas em dólares, ambas sujeitas ao risco Brasil, não foi rejeitada. Em complemento à análise das taxas representativas do mercado brasileiro, procurou-se avaliar a predominância da PDJ nas operações de swap cambial realizadas pela Vale S.A.. Para tanto, a série de taxa de juros em dólares do mercado brasileiro foi substituída pela taxa em dólar dos swaps contratados pela Vale. Os resultados encontrados demonstram que, quando comparado ao comportamento do mercado, as taxas em dólares da VALE são mais sensíveis às variações das taxas em Reais.
We measure the validity of uncovered interest parity - UIP - for the Brazilian market from January, 2010 to July, 2014. We tested the classical equation of UIP using the ordinary least squares method. After the estimation, we apply the Wald test and we verify that the uncovered interest parity has not been validated. We extend the traditional UIP equation for an alternative specification that captures Brazil risk and changes in liquidity of the international market. Specifically, we add three control variables: two dummy variables that capture external liquidity conditions and the commodity index CRB, which captures Brazil risk. With the alternative specification, the hypothesis that the returns in interest rates in Real, dollarized, are equal to the return of interest rate contracted in dollars, both subject to Brazil risk, was not rejected. To complement the analysis using the interest rates existing in the Brazilian market, we tried to evaluate the prevalence of UIP in cross currency interest rate swaps carried out by Vale SA. The interest rate in dollar of the Brazilian market was replaced by the dollar rate of swaps contracted by Vale. The results show that, when compared to market behavior, the dollar rates of Vale SA. are more sensitive to changes in Reais interest rates.
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Studený, Marek. "Modelování tržní ceny nemovitosti mnohonásobnou lineární regresí." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2013. http://www.nusl.cz/ntk/nusl-232776.
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The main subject of the diploma thesis is a market price modeling by real estates. As a tool for modeling, is used a multiple linear regression. As starting points, are used an econometrical theory and knowledge about real estate valuation. The main goal is to find optimal model for best capture in the time and place.
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Ly, Mouhamadou Moustapha. "Trois essais sur les effets de la politique budgétaire dans les pays en développement." Phd thesis, Université d'Auvergne - Clermont-Ferrand I, 2011. http://tel.archives-ouvertes.fr/tel-00606175.
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La réflexion sur l‟utilisation de la politique budgétaire comme outil de stabilisation et de relance connaît un net regain d‟intérêt ces dernières années. Après près de trois décennies qui ont vu la dominance des idées néo-classique, la récente crise financière des années 2008 a consacré le retour aux idées keynésiennes sur l‟efficacité de l‟outil budgétaire. Cette thèse s‟intéresse à ce thème et essaie de caractériser la politique budgétaire dans le contexte des pays en développement et son objectif final est de préciser dans quelle mesure cet outil de politique économique serait efficace pour ces pays. Le chapitre 2 traite de la question des effets des politiques budgétaires surprises. Autrement dit, et à partir d‟une modélisation en VAR structurels, cette partie se pose la question de savoir si le budget peut être utilisé de façon surprise pour relancer une économie et quels sont les défis que pose une telle mesure dans le contexte d‟une économie en développement. Le troisième chapitre à partir d‟un modèle de gravité analyse les relations entre la situation budgétaire dans les économies avancées ainsi que celle des pays émergents et les flux d‟investissement vers les économies à revenu intermédiaire. Cette étude montre qu‟un effet d‟éviction entre pays (développés et émergents) existe mais aussi que l‟économie mondiale tend vers un nouveau paradigme. Le dernier chapitre quant à lui étudie la cyclicité des politiques budgétaires pour un échantillon de pays d‟Afrique subsaharienne et d‟Amérique latine. La méthode choisie a permis de suivre l‟évolution de la procyclicité des politiques budgétaires d‟année en année et de montrer que les pays en développement surtout africains progressivement adoptent des politiques de plus en plus disciplinées et prudentes
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Kizzort, Megan. "Federal Funding and the Rise of University Tuition Costs." Honors in the Major Thesis, University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETH/id/1554.
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Access to education is a central part of federal higher education policy, and federal grant and loan programs are in place to make college degrees more attainable for students. However, there is still controversy about whether there are unintended consequences of implementing and maintaining these programs, and whether they are effectively achieving the goal of increased accessibility. In order to answer questions about whether three specific types of federal aid cause higher tuition rates and whether these programs increase graduation rates, four ordinary least squares regression models were estimated. They include changes in both in-state and out-of-state tuition sticker prices, graduation rates, as well as changes in three types of federal aid, and other variables indicative of the value of a degree for four-year public universities in Arizona, California, Georgia, and Florida for years 2001-2011. The regressions indicate a positive effect of Pell Grants on in-state and out-of-state tuition and fees, a positive effect of disbursed subsidized federal loans on the change in number of degrees awarded, and a positive effect of Pell Grants on graduation rates.B.A.
Bachelors
Business Administration
Economics
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Furlan, Camila Pedrozo Rodrigues. "Especificação do tamanho da defasagem de um modelo dinâmico." Universidade Federal de São Carlos, 2009. https://repositorio.ufscar.br/handle/ufscar/4529.
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Previous issue date: 2009-03-06Financiadora de Estudos e Projetos
Several techniques are proposed to determine the lag length of a dynamic regression model. However, none of them is completely satisfactory and a wrong choice could imply serious problems in the estimation of the parameters. This dissertation presents a review of the main criteria for models selection used in the classical methodology and presents a way for determining the lag length from the perspective Bayesian. A Monte Carlo simulation study is conducted to compare the performance of the significance tests, R2 adjusted, final prediction error, Akaike information criterion, Schwarz information criterion, Hannan-Quinn criterion, corrected Akaike information criterion and fractional Bayesian approach. Two estimation methods are also compared, the ordinary least squares and the Almon approach.
Na literatura, muitas técnicas são propostas para determinar o tamanho da defasagem de um modelo de regressão dinâmico. Entretanto, nenhuma delas é completamente satisfatória e escolhas erradas implicam em sérios problemas na estimação dos parâmetros. Este trabalho apresenta uma revisão dos principais critérios de seleção de modelos disponíveis na metodologia clássica, assim como aborda uma maneira de determinar o tamanho da defasagem sob a perspectiva Bayesiana. Um estudo de simulação Monte Carlo é conduzido para comparar a performance dos testes de significância, do R2 ajustado, do erro de predição final, dos critérios de informação de Akaike, Schwarz, Hannan-Quinn e Akaike corrigido e da aproximação Bayesiana fracionada. Também serão comparados os métodos de estimação de Mínimos Quadrados Ordinários e de Almon.
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Jobst, Mark G., and Jeffrey Palmer. "An analysis of the USMC FITREP: contemporary or inflexible?" Thesis, Monterey California. Naval Postgraduate School, 2005. http://hdl.handle.net/10945/2210.
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Approved for public release, distribution is unlimitedThe purpose of this thesis is threefold. Firstly, to attempt to provide validity for the two-sided matching process; secondly, analyze FITREP attributes to determine their suitability for a weighted criteria evaluation system and; thirdly, compare the USMC promotion and assignment process with contemporary human resource management practices. Using data from the USMC Officer Accession Career file (MCCOAC), a logit model is used to estimate the effects of TBS preference and other officer characteristics on retention to the seven year mark. Findings indicate that there was little difference in the probability of retention throughout most preference levels except for the bottom sixth. Using USMC FITREP data, an ordinary least squares model is used to estimate the effects of rank and MOS on FITREP scores across all attributes. Multiple comparison tests demonstrated that there are statistical differences at the 0.05 level between the means of the MOSs. Additionally, reporting creep is continuing across all attributes. Surveys were also conducted. The first survey indicated that USMC officers believe the FITREP attributes were not all equally important within, and across each MOS - although the USMC assesses them as such. The second survey indicated that the USMC promotion and assignment process can be strengthened through a clearly defined HRM plan that extends beyond 'faces' and 'places', and provides very clear links to the organizational strategy. Based on the findings it is recommended that the USMC review its HRM processes and conduct further analyses on the FITREP data for: (1) correlation, (2) longitudinal analysis as a predictor for success and, (3) relevance and relationship to MOS characteristics, position descriptions, and organizational strategy.
Major, Royal Australian Infantry Corps
Major, United States Marine Corps