Dissertations / Theses: 'Probit/logit model'

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Santos, Joceline Brigitte Fernandes dos. "Crises bancárias e suas causas : o caso da Argentina." Master's thesis, Instituto Superior de Economia e Gestão, 2012. http://hdl.handle.net/10400.5/10739.

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Mestrado em Economia Monetária e Financeira O presente trabalho estuda as causas das crises bancárias, com base na análise dos rácios financeiros do balanço dos bancos. Nesse sentido, recorremos a uma metodologia que consiste em estimar três regressões diferentes para a probabilidade de falência dos bancos, através dos modelos Logit e Probit, para uma amostra de 99 bancos Argentinos. O objetivo foi saber se as falências bancárias ocorridas durante a crise Argentina de 2001 se explicam por factores monetários ou factores reais, uma vez que o debate teórico se situa nesta dicotomia. Os resultados encontrados são semelhantes para a estimação Logit e Probit e sugerem que apenas os factores monetários explicam a probabilidade de ocorrência das falências. This paper studies the causes of banking crisis, based on the analysis of financial ratios of the banks' balance sheets. In this sense, we used a methodology that consists in estimating three different regressions for the probability of bank failure, through Logit and Probit models for a sample of 99 Argentine banks. The objective was to determine whether the bank failures that have occurred during the Argentina´s 2001 economic crisis are explained by monetary or real factors, since the theoretical debate lies in this dichotomy. The results are similar for Logit and Probit estimation and suggest that only the monetary factors explain the likelihood of bankruptcy.

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Gomes, Nelson António Mendonça. "Impacto dos programas de microcrédito em Angola : Aplicação a Benguela e Huambo." Master's thesis, Instituto Superior de Economia e Gestão, 2011. http://hdl.handle.net/10400.5/3122.

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Mestrado em Matemática Financeira No contexto de paz e estabilidade política que Angola vive, o desenvolvimento social “erradicação da pobreza” tornou-se numa meta a alcançar para manter esta mesma estabilidade; neste sentido, os programas de microcrédito têm um papel importante a desempenhar. O presente trabalho tem como objectivo responder às seguintes questões: Será que os programas de micro crédito têm tido um efeito positivo no bem-estar dos seus beneficiários e familiares? Quais os factores que contribuem para a satisfação “sucesso” do negócio, nas províncias de Benguela e Huambo? As conclusões obtidas evidenciam que, de facto, houve melhorias nas condições de vida dos beneficiários, tanto a nível da habitação, saúde, alimentação como da educação dos filhos. In the context of peace and political stability that Angola lives, social development, “eradication of poverty” have become a goal to achieve in order to maintain the same stability; in this sense, microcredit programs have an important role to play. The present thesis has as main objective to answer the following questions: Do micro-credit programs have a positive effect on recipients and families? What are the factors that contribute to satisfaction "success" of the business? Conclusion shows that there was some improvement in the living conditions of benefi-ciaries, both in housing, health, nutrition and education of children.

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Zhu, Liyu. "Discrete Brand Choice Models: Analysis and Applications." Diss., Available online, Georgia Institute of Technology, 2007, 2007. http://etd.gatech.edu/theses/available/etd-07102007-142035/.

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Thesis (Ph. D.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2008. Esogbue, Augustine, Committee Chair ; Griffin, Paul, Committee Member ; Lu, Jye-Chyi (JC), Committee Member ; Li, MinQiang, Committee Member ; McCarthy, Patrick, Committee Member.

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Ndunda, E. N. (Ezekiel Nthee). "Wastewater reuse in urban and peri-urban irrigation : an economic assessment of improved wastewater treatment, low-risk adaptations and risk awareness in Nairobi, Kenya." Thesis, University of Pretoria, 2013. http://hdl.handle.net/2263/40235.

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The overall goal of this study was to analyse the welfare effect of improved wastewater treatment with the view of making policy recommendations for sustainable urban and peri-urban irrigation agriculture in Kenya. This goal was achieved by investigating three specific objectives. The first objective was to assess the farmers’ awareness of health risks in urban and peri-urban wastewater irrigation. Second objective was to analyse the factors that affect the choice of low-risk adaptations in reuse of untreated wastewater for irrigation. The third objective was to estimate the value that urban and peri-urban farmers who practice wastewater irrigation impute to improvements in specific characteristics of the wastewater input in agriculture. In order to achieve the first objective, an ordered probit model was used to identify the factors that influence farmers’ awareness of health risks in untreated wastewater irrigation. The model was fitted to data collected from a cross-sectional survey of 317 urban farm households in the Kibera informal settlement of Kenya. Results of this study show that gender of household head, household size, education level of household head, farm size, ownership of the farm, membership to farmers’ group, and market access for the fresh produce significantly affect awareness of farmers about health risks in wastewater irrigation. Therefore, there is need for awareness programs to promote public education through regular training and local workshops on wastewater reuse in order to improve the human capital of the urban and peri-urban farmers. To achieve the second objective, the study used a multinomial logit model to analyse the farmers’ choice of low-risk adaptations in untreated wastewater irrigation. A survey of 317 urban and peri-urban farmers was conducted and measures for risk-reduction in wastewater reuse were analysed. The urban and peri-urban farmers were found to have adopted low-risk wastewater irrigation techniques such as cessation of irrigation before harvesting, crop restriction and safer application methods. Results of the study show that adoption of risk-reduction measures is significantly influenced by the following factors: household size, age of the household head, education of household head, access to extension, access to media, access to credit, farmers’ group membership, and risk awareness. Also, marginal analysis of the coefficients confirmed the socio-economic characteristics are key determinants in adoption of low-risk measures in wastewater reuse. The study recommends that policies in support of low-risk urban and peri-urban irrigation agriculture should disaggregate farmers according to their socio-economic and institutional characteristics in order to achieve their intended objectives. To achieve the third objective, the study employed the discrete choice experiment approach to estimate the benefits farmers impute to improvements in attributes of the wastewater irrigation input, whose aim is to reduce the health risks associated with untreated wastewater irrigation. Urban and peri-urban farmers who practice wastewater irrigation drawn from Motoine-Ngong River in Nairobi were randomly selected for the study. A total of 241 farmers completed the presented choice cards for the choice model estimation. A random parameter logit model was used to estimate the individual level willingness to pay for wastewater treatment. The results show that urban and peri-urban farmers are willing to pay significant monthly municipality taxes for treatment of wastewater. Conclusion of this study was that, quality of treated wastewater, quantity of treated wastewater and the riverine ecosystem restoration are significant factors of preference over policy alternative designs in wastewater treatment and reuse. Thesis (PhD)--University of Pretoria, 2013. gm2014 Agricultural Economics, Extension and Rural Development unrestricted

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Pettersson, Fredrik. "En jämförelse av regressioner med binära utfall." Thesis, Uppsala universitet, Statistiska institutionen, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-451007.

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The purpose of this bachelor thesis was to compare three different methods for regression with binary outcomes. The three methods used for comparison are: Linear Probability Model, Logit and Probit. To compare the methods, data gathered from the World Value Survey when it last was done in Sweden in 2011 was used. The outcome variable in the creation of the models was whether the respondent preferred protecting the environment or economic growth. A Monte Carlo-simulation was also performed to strengthen the arguments in the comparison. The results from the different models created was very small, but there are still differences. Two examples of the differences are the simplicity of interpretation between the models and errors that argues for not using Linear Probability Model under certain circumstances.

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Monsia, Atoke Frédia. "Macroeconomic imbalances, crises and management of crises in euro area countries." Thesis, Aix-Marseille, 2016. http://www.theses.fr/2016AIXM2024/document.

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L'objet de cette thèse est d'étudier les liens qui existent entre les déséquilibres macroéconomiques et les crises, et de voir dans quelles mesures leur prise en compte peut aider une meilleure gestion des crises dans les pays de la zone euro. Les différents chapitres de cette thèse tentent d'apporter des réponses à trois questions importantes : Quels sont les indicateurs macro-financiers qui pourraient aider à mieux anticiper les épisodes de stress budgétaire dans les pays de la zone euro ? Quelles seraient les conséquences de la mise en place d'un système de garantie des dépôts bancaires sur les variables macroéconomiques et sur le comportement des investisseurs, investisseurs qui tiendraient compte du risque de défaut souverain ? Dans quelle mesure une meilleure qualité des institutions, de la gouvernance pourrait-elle aider à améliorer la croissance de long terme d'une économie contrainte sur le marché international des capitaux ? En retenant une approche de court terme, les deux premiers chapitres montrent l'importance de la confiance des marchés dans l'analyse du lien entre déséquilibres macroéconomiques et crises. Dans le troisième chapitre, nous adoptons une perspective de plus long terme pour analyser les effets de cette confiance des marchés sur la dynamique de la croissance. Notre approche est à la fois théorique et empirique. L'approche théorique se base sur les modèles DSGE (modèles d'équilibre général stochastiques dynamiques et la modélisation d'une crise dans une petite économie ouverte. L'approche empirique se focalise sur les modèles Probit/Logit sur données de panel et sur un modèle d'alerte fondé sur des signaux avancés (early warning indicators) This dissertation consists of three essays on how macro-financial imbalances precede crises and to what extent their consideration can help better management of crises in the Eurozone countries. The different chapters of this thesis, try to answer three important questions : What are the macro-financial imbalances that exposed the Euro area countries to fiscal stress before the outbreak of the debt crises in Europe? What are the impacts of sovereign default and deposit guarantee on macroeconomic variables and on the behavior of investors ? To what extent could better institutions/governance help to improve the long-term growth in a constrained economy on the international capital market ? Using a short-term approach, the first two chapters show the importance of market confidence in analysis of the link between macroeconomic imbalances and crises. In the third chapter, we adopt a long-term perspective to analyze the effects of this market confidence on the dynamics of growth. Our approach is both theoretical and empirical. The theoretical approach is based on the DSGE models (dynamic stochastic general equilibrium models) and the modeling of a crisis in a small open economy (SOE). The empirical approach focuses on Probit/Logit models for panel data and on Signal model based on early warning indicators

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Silva, Eveliny Barroso da. "Modelos dinâmicos de resposta binária para dados em painel." Universidade Federal de São Carlos, 2008. https://repositorio.ufscar.br/handle/ufscar/4522.

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Made available in DSpace on 2016-06-02T20:06:01Z (GMT). No. of bitstreams: 1 2049.pdf: 560086 bytes, checksum: 32b955d6a93e81457f49b0418b1e9514 (MD5) Previous issue date: 2008-06-06 Financiadora de Estudos e Projetos A summary of the state of the art relative to regression models for binary response variable and panel data is presented in this work. Those models may include efects from several sources: specific variables of interest, heterogeneity between individuals and lagged values of the response variable. The original contributions of the author are simulation studies to compare two diferent approaches to maximum likelihood estimation of parameters of dynamic models with all three kinds of efects, and also a study of properties of such estimators in group sequential analysis, using the bootstrap methodology. Original codes were developed in R for implementation of simulation studies. The relevance of the subject and the non availability of appropriate codes in commercial software for fitting dynamic models for binary response justify the choice of the theme. Neste trabalho é apresentado inicialmente um levantamento da literatura referente a modelos de regressão não lineares quando a variável resposta é binária e as observações são um painel de dados. Tais modelos podem incluir efeitos de várias fontes: variáveis específicas de interesse, heterogeneidade não observável dos indivíduos e valores defasados da variável resposta. A parte original do trabalho consiste nos estudos por simulação usando programação criada para esse fim no software R, visando comparar duas propostas recentes da literatura para ajustar, por máxima verossimilhança condicional, modelos dinâmicos que incluem os três tipos de efeitos mencionados. Também é original o estudo empírico, usando a metodologia de reamostragem \bootstrap", de características da distribuição conjunta dos estimadores dos parâmetros em análises intermediárias dos dados. A justificativa do trabalho é a atualidade do tema e a inexistência de programas de ajuste de modelos dinâmicos de resposta binária na maioria dos softwares comerciais.

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Li, Xibao. "Learning From the Implementation of Residential Optional Time of Use Pricing in the U.S. Electricity Industry." The Ohio State University, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=osu1047271855.

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Lejnarová, Šárka. "Modely diskrétní binární volby." Master's thesis, Vysoká škola ekonomická v Praze, 2007. http://www.nusl.cz/ntk/nusl-1615.

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Ve své diplomové práci se zabývám modely diskrétní binární volby. Zkoumám je nejprve z teoretického hlediska, jaká je jejich podstata, jaká jsou jejich specifika a problémy. Postupně rozebírám jednotlivé modely diskrétní binární volby a to lineární pravděpodobnostní model, logitový model a probitový model. Zabývám se jejich odhadem, testováním významnosti jednotlivých koeficientů a shodou modelů s daty. V praktické části se zaměřuji na problematiku životního prostředí a třídění odpadu. Aplikuji jednotlivé modely na získaná data a snažím se vysvětlit, na čem závisí volba jedince mezi ?třídím odpad? a nebo ?netřídím odpad?. Na základě analýzy poté doporučuji, na koho a jakým způsobem zacílit osvětu.

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Kropko, Jonathan Rabinowitz George. "Choosing between multinomial logit and multinomial probit models for analysis of unordered choice data." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2008. http://dc.lib.unc.edu/u?/etd,1680.

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Thesis (M.A.)--University of North Carolina at Chapel Hill, 2008. Title from electronic title page (viewed Sep. 16, 2008). "... in partial full̄lment of the requirements for the degree of Master of Arts in the Department of Political Science." Discipline: Political Science; Department/School: Political Science.

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Park, Seong Yong. "Modeling dynamic choice behavior : empirical analysis using multinomial logit and multiperiod multinomial probit models /." Thesis, Connect to this title online; UW restricted, 1996. http://hdl.handle.net/1773/8727.

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Ivaschenko, Iryna. "Essays on corporate risk, U.S. business cycles, international spillovers of stock returns, and dual listing." Doctoral thesis, Stockholm : Economic Research Institute, Stockholm School of Economics (EFI), 2003. http://www.hhs.se/efi/summary/625.htm.

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Cacho, Beatriz Ferreira. "Satisfação do colaborador nos setores da saúde e tecnológico." Master's thesis, Instituto Superior de Economia e Gestão, 2021. http://hdl.handle.net/10400.5/20879.

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Mestrado em Métodos Quantitativos para a Decisão Económica e Empresarial Utilizando os modelos ordenados probit e logit estimou-se a probabilidade de três níveis de satisfação laboral com base em dados relativos a duas empresas (um hospital e uma empresa tecnológica). Deste modo, foram estimados três modelos. Um primeiro que incorpora as duas empresas e os outros dois para o hospital e para a empresa tecnológica. Embora o ponto de partida da análise empírica fosse o modelo global concluiu-se que, estatisticamente, seria pertinente avançar com regressões separadas por empresa. Nos três tipos de modelos os fatores que sumariam as questões de satisfação sobre assuntos em particular, revelaram-se estatisticamente significativos. No modelo global, apenas duas variáveis de escolaridade se revelaram significativas, manifestando impactos positivos no nível de satisfação mais elevado e negativos nos dois níveis de satisfação mais baixos. Da análise do modelo parcial do hospital concluiu-se que as idades mais jovens são estatisticamente significativas e apresentam impactos negativos no nível de satisfação mais elevado. Ao nível das funções, as variáveis Médicos e Técnicos de Saúde são estatisticamente significativas e o impacto de pertencer a uma destas funções em níveis de satisfação mais elevados é positivo. No que se refere às direções apenas a Direção Clínica é estatisticamente significativa e o impacto desta em níveis de satisfação mais elevados é negativo. Da análise do modelo parcial da empresa tecnológica é percetível que apenas as idades entre os 36 e os 45 anos e os 46 e os 55 anos são estatisticamente significativas apresentando impactos positivos no nível de satisfação mais elevado. Using ordered probit and logit models, the probability of three levels of job satisfaction was estimated based on data from two companies (a hospital and a tech company). In this way, three models were estimated. One that incorporates the two companies and the other two for the hospital and the technology company. Although the starting point of the empirical analysis was the global model it was concluded that, statistically, it would be pertinent to proceed with regressions separated by company. In the three models, the factors that summarize the satisfaction issues on specific subjects, proved to be statistically significant. In the global model, only two schooling variables proved to be significant, with positive impacts on the highest level of satisfaction and negative impacts on the two lowest levels of satisfaction. From the analysis of the partial model of the hospital, it was concluded that younger ages are statistically significant and have negative impacts on the highest level of satisfaction. In terms of functions, the variables Doctors and Health Technicians are statistically significant and the impact of belonging to one of these functions in higher levels of satisfaction is positive. As for the directions, only the Clinical Direction is statistically significant and its impact on higher levels of satisfaction is negative. From the analysis of the partial model of the tech company, it is noticeable that only the ages between 36 and 45 years and 46 and 55 years are statistically significant, with positive impacts on the highest level of satisfaction. info:eu-repo/semantics/publishedVersion

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Arabatzis, Alexandros A. "Qualitative response models theory and its application to forestry." Diss., This resource online, 1990. http://scholar.lib.vt.edu/theses/available/etd-09162005-115001/.

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Hirk, Rainer, Kurt Hornik, and Laura Vana. "Multivariate ordinal regression models: an analysis of corporate credit ratings." Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/s10260-018-00437-7.

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Correlated ordinal data typically arises from multiple measurements on a collection of subjects. Motivated by an application in credit risk, where multiple credit rating agencies assess the creditworthiness of a firm on an ordinal scale, we consider multivariate ordinal regression models with a latent variable specification and correlated error terms. Two different link functions are employed, by assuming a multivariate normal and a multivariate logistic distribution for the latent variables underlying the ordinal outcomes. Composite likelihood methods, more specifically the pairwise and tripletwise likelihood approach, are applied for estimating the model parameters. Using simulated data sets with varying number of subjects, we investigate the performance of the pairwise likelihood estimates and find them to be robust for both link functions and reasonable sample size. The empirical application consists of an analysis of corporate credit ratings from the big three credit rating agencies (Standard & Poor's, Moody's and Fitch). Firm-level and stock price data for publicly traded US firms as well as an unbalanced panel of issuer credit ratings are collected and analyzed to illustrate the proposed framework.

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Hirk, Rainer, Kurt Hornik, and Laura Vana. "Multivariate Ordinal Regression Models: An Analysis of Corporate Credit Ratings." WU Vienna University of Economics and Business, 2017. http://epub.wu.ac.at/5389/1/Report132_lvana.pdf.

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Correlated ordinal data typically arise from multiple measurements on a collection of subjects. Motivated by an application in credit risk, where multiple credit rating agencies assess the creditworthiness of a firm on an ordinal scale, we consider multivariate ordinal models with a latent variable specification and correlated error terms. Two different link functions are employed, by assuming a multivariate normal and a multivariate logistic distribution for the latent variables underlying the ordinal outcomes. Composite likelihood methods, more specifically the pairwise and tripletwise likelihood approach, are applied for estimating the model parameters. We investigate how sensitive the pairwise likelihood estimates are to the number of subjects and to the presence of observations missing completely at random, and find that these estimates are robust for both link functions and reasonable sample size. The empirical application consists of an analysis of corporate credit ratings from the big three credit rating agencies (Standard & Poor's, Moody's and Fitch). Firm-level and stock price data for publicly traded US companies as well as an incomplete panel of issuer credit ratings are collected and analyzed to illustrate the proposed framework. Series: Research Report Series / Department of Statistics and Mathematics

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Saúde, Arthur Moreira. "Metodologia de previsão de recessões: um estudo econométrico com aplicações de modelos de resposta binária." reponame:Repositório Institucional do FGV, 2017. http://hdl.handle.net/10438/18221.

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Submitted by Arthur Moreira Saude (arthur-moreira@hotmail.com) on 2017-04-27T16:03:53Z No. of bitstreams: 1 Dissertacao Final.pdf: 947767 bytes, checksum: ca50219ab757930a6d88422c06d48234 (MD5) Approved for entry into archive by GILSON ROCHA MIRANDA (gilson.miranda@fgv.br) on 2017-04-28T19:14:36Z (GMT) No. of bitstreams: 1 Dissertacao Final.pdf: 947767 bytes, checksum: ca50219ab757930a6d88422c06d48234 (MD5) Made available in DSpace on 2017-05-02T19:31:50Z (GMT). No. of bitstreams: 1 Dissertacao Final.pdf: 947767 bytes, checksum: ca50219ab757930a6d88422c06d48234 (MD5) Previous issue date: 2017-03-31 This paper aims to create an econometric model capable of anticipating recessions in the United States economy, one year in advance, using not only monetary market variables that are already used by economists, but also capital market variables. Using a data span from 1959 to 2016, it was observed that the yield spread continues to be an explanatory variable with excellent predictive power over recessions. Evidence has also emerged of new variables that have very high statistical significance, and which offer valuable contributions to the regressions. Out-of-sample tests have been conducted which suggest that past recessions would have been predicted with substantially higher accuracy if the proposed Probit model had been used instead of the most widespread model in the economic literature. This accuracy is evident not only in the predictive quality, but also in the reduction of the number of false positives and false negatives in the regression, and in the robustness of the out-of-sample tests. Este trabalho visa desenvolver um modelo econométrico capaz de antecipar, com um ano de antecedência, recessões na economia dos Estados Unidos, utilizando não só variáveis dos mercados monetários, que já são indicadores antecedentes bastante utilizados por economistas, mas também dos mercados de capitais. Utilizando-se dados de 1959 a 2016, pode-se observar que o spread de juros de longo e curto prazo continua sendo uma variável explicativa com excelente poder preditivo sobre recessões. Também surgiram evidências de novas variáveis que possuem altíssimas significâncias estatísticas, e que oferecem valiosas contribuições para as regressões. Foram conduzidos testes fora da amostra que sugerem que as recessões passadas teriam sido previstas com acurácia substancialmente superior, caso o modelo Probit proposto tivesse sido utilizado no lugar do modelo mais difundido na literatura econômica. Essa acurácia é evidente não só na qualidade preditiva, mas também na redução do número de falsos positivos e falsos negativos da regressão, e na robustez dos testes fora da amostra.

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Ortega, Sandra. "The impact of outcome measurement on non-profit organizations a case study /." Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1141401440.

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Aloquili, A. "Estimation of credit rating models : case study for MENA countries and their commercial banks." Thesis, Coventry University, 2014. http://curve.coventry.ac.uk/open/items/82213d64-6097-4482-a61a-c67d698f5e95/1.

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Credit Rating Agencies (CRAs) play a key role in financial markets by helping to reduce informative asymmetry between lenders and investors, on one side, and issuers on the other side, with regard to the creditworthiness of banks or countries. This crucial role has expanded alongside financial globalisation and received an additional boost from Basel II which integrates the ratings of CRAs into the rules for setting weights for credit risk. Ratings adjustment tends to be sticky, lagging behind markets, and often overreact when they do change. This overreaction may have aggravated the recent financial crises, contributing to financial instability and cross-country contagion. Criticism has been especially directed towards the high degree of concentration of the ratings industry. Promotion of competition may require policy action at the international level to encourage the establishment of new agencies and to discover alternative rules or regulatory requirements in order to achieve promising results. The recent growth of Middle Eastern and North African countries (MENA) and their commercial banking system has increased the need of paying widespread attention to this region of the world. This thesis crucially identifies, and estimates, the robust determinants of credit ratings for MENA countries and their commercial banks, incorporating a set of bank level accounting and financial risk factors, as well as country-specific characteristics, including indicators for regulatory, supervision, legal and economic environments. The research contributes, firstly, to the theoretical literature on credit ratings industry by reviewing extant methodologies specifically as they apply to banks and sovereign countries. Secondly, it conducts a systematic, cross-country empirical investigation using panel data econometric methodology for the purpose of estimating MENA countries sovereign and bank credit rating models. Thirdly, it provides tangible and statistically significant evidence on the different factors that determines the estimation of credit ratings and influencing bank's risk. The extant literature reviewed serves as a basis to achieve and develop the research aim, objectives and hypotheses of the thesis. The research then constructs an appropriate panel dataset from different sources, containing bank-level and country-level information for a sample of 108 commercial banks covering 13 MENA countries over the period 2000 - 2012. The methodological framework for estimating credit rating models (linear regression, logit and probit) is also reviewed and the procedures for panel data estimation are implemented using the econometric package STATA (version 13). All relevant data are drawn from public sources including Reuters, Bankscope, IMF and the World Bank. Using the random effects ordered probit and logit methodologies to estimate both sovereign (country) and bank level credit ratings models for the MENA countries, the evidence shows that real GDP growth, capital requirements, restrictions on banking activities and control of corruption all contribute negatively to the sovereign ratings. Furthermore, internal management and organisational requirements is considered as an additional regulatory factor not studied in previous research. The statistically significant and inverse relationship of the latter is considered an important and interesting outcome of MENA countries’ sovereign ratings. On the other hand, GDP per capita, investment (as a percentage of GDP), political stability, government effectiveness and the rule of law all reveal significant and positive impact on the sovereign credit ratings. In general, this research finds that improved macroeconomic conditions are correlated with higher ratings, while greater reserve regulations are correlated with lower ratings. The study also does find the significance of governance and regulatory variables plays a key role into the final credit rating. With regard to the impact on banks’ ratings, the results show that higher return on average assets and equity, larger bank size, more restrictions on bank activities, as well as higher official disciplinary power and higher standards of internal management, will yield higher credit ratings. Apart from having direct and positive impact on banks credit ratings, these variables are important for examining the risk-sharing incentives in MENA countries’ banks. In contrast, the estimation results indicate that net interest margin, net loans to deposits, liquid assets to deposits, capital requirements, deposit insurance scheme, liquidity requirements, unemployment rate and government effectiveness have an inverse and negative impact on banks ratings. In general, this study also finds various financial, macroeconomic, and regulatory effects on banks’ credit ratings. To a much lesser extent than government ratings, various macroeconomic variables also helped predict banks’ ratings, including real GDP growth and the unemployment rate. The thesis concludes by arguing that the combined use of financial and non-financial factors for estimating credit ratings models supports the relevant hypotheses examined and adds value to all stakeholders in improving and obtaining a better quality of credit ratings. This study also demonstrates that a diversity of bank-level and country-level factors influence the MENA sovereign and bank ratings differently, implying that policy makers, regulators alongside rating agencies should distinguish the different environmental factors between nations before any judgment and issuance can be model of the ratings. To conclude, there is no study which exclusively investigates credit rating models for the MENA region exploiting the richness of the data and methodology employed, and the current research aims to fill this gap.

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Benitez, Rogério Martin. "Impactos das preferências ambientais sobre os resultados dos métodos de análise conjunta de valoração ambiental : rating e ranking contingent." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2005. http://hdl.handle.net/10183/10351.

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Uma das grandes dificuldades na mensuração monetária dos bens e serviços naturais, ou ambientais, reside na valoração do não-uso dos mesmos. Enquanto que o valor de uso de um recurso ambiental pode ser obtido através do mercado, que revela as preferências do consumidor, o valor de não-uso somente pode ser apropriado através do uso de mercados hipotéticos. Dentre as técnicas utilizadas, o método de valoração contingente (CVM) é o mais tradicional mas na última década, diversos economistas têm se voltado para novas abordagens evoluídas das áreas de marketing e transportes. Esses métodos, classificados como de análise conjunta (conjoint analysis) que podem ser, ainda, subdivididos em rating contingent e ranking contingent, são o estudo desse trabalho. O objetivo principal foi comparar os resultados, obtidos por um mesmo conjunto de observações, para as principais estatísticas referentes a precisão dos métodos, quando sujeitas a várias formas funcionais de utilidade, distintos graus de preferência ambiental dos consumidores e diferentes métodos de estimação. Além disso, é apresentada uma síntese crítica dos métodos em análise e os procedimentos metodológicos para o desenvolvimento e aplicação dos mesmos. Para a realização dessa análise, primeiramente foram definidos coeficientes para as utilidades dos bens – ambiental, não ambiental e monetário. Posteriormente, fez-se uso da técnica de Monte Carlo para a simulação da situação/problema e, ao final, foram utilizados os modelos de variável dependente discreta (probit ou logit ordenados) para a estimação final dos parâmetros definidos ex-ante. Constatou-se que o uso do modelo logit ordered para a estimação dos verdadeiros parâmetros mostrou-se mais preciso para a estimação dos coeficientes do que o uso do probit ordenado. Dentre as técnicas em análise, o método de valoração denominado rating contingente apresentou melhores resultados do que o ranking. No que tange às formas funcionais da utilidade e preferências dos consumidores, não foi possível constatar uma relação entre a qualidade das estimativas e a forma funcional. Foi possível, ainda, verificar que os métodos rating e ranking contingente estão bem fundamentados na teoria microeconômica, contudo, verifica-se a dificuldade de se encontrar um valor econômico total a todas as situações que envolvem bens ambientais, pois existem dificuldades a serem vencidas, não especificas aos métodos de valoração mas comum à economia ambiental. The difficulties in giving monetary values on natural services and goods comes from valuing the non-use of them. Although the use value of environmental resources can be appropriated from the market that indicates the consumer preferences, the non-use value can only be appropriated through the hypothetic market. The contingent valuation method (CVM) is the most traditional of the techniques in use, but in the last decade, some economists have directed themselves toward new approaches in the marketing and transport areas. The goal of this work are the methods classified as conjoint analysis, which may be separated into rating contingent and ranking contingent. The main objective is the analysis of the statistics to compare the precision of the methods when submitted to different utility function forms, distinct levels of environmental preferences and diverse estimation methods. It presents, also, a synthesis of the analyzed methods and the methodological procedure to the development and application of the methods. The execution of that work was defined ex-ante the coefficients for the utilities of the goods – being monetary, environmental and non-environmental. Later it was necessary the use of Monte Carlo Method to simulate the situation that was posteriorly solved – being the coefficients estimated - with the use of discrete dependent variable models – ordered probit and ordered logit. Ordered logit model showed to be the most precise in estimating real parameters than ordered probit. The rating contingent get the best results when compared to the ranking contingent. It was not possible to get a good relation between the goods estimates and the functional form of consumer preference. In closing, it was possible to verify that the rating and ranking contingent methods have basis in the microeconomic theory although the difficulties into getting the total economic value of ambiental sources was cleared, as the problems aren´t specified to the methods studied but are general to the environmental economy.

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Mateo, Erroz Sara. "Análisis microeconometrico de las decisiones de participación y gasto turístico de los hogares." Doctoral thesis, Universitat de les Illes Balears, 2012. http://hdl.handle.net/10803/84092.

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La tesis se enmarca en el análisis microeconométrico de la demanda turística de los hogares españoles. Su objetivo general es estudiar los determinantes que influyen en la decisión de consumo turístico, frecuencia de consumo y gasto de los hogares en servicios turísticos. En el análisis de todas las decisiones intervienen variables no estrictamente económicas específicas de cada hogar (número de miembros, existencia de niños y otras variable ligadas al ciclo de vida del hogar) y de sus miembros (edad, nivel educativo, y otras variable ligadas al momento vital por el que atraviesan). Además, se incorporan variables económicas o ligadas a la situación económica del hogar. De esta manera se puede realizar un análisis sobre las diferentes decisiones de consumo turístico de los hogares y vincularlas a sus preferencias, restricciones temporales, restricciones monetarias o diferentes circunstancias condicionadas a su momento vital. Se hace especial referencia a los efectos de la crisis económica mundial y el desempleo de los miembros del hogar sobre su gasto turístico efectivo. Este trabajo está estructurado en cuatro capítulos. En el primer capítulo se aborda el estudio de las restricciones a las que hacen frente los hogares españoles a la hora de viajar. Para ello, se estudia la importancia que tiene la situación económica del hogar como barrera al consumo turístico. Los hogares analizados provienen de la muestra española del año 2000 de la encuesta del Panel de Hogares de la Comunidad Europea (PHOGUE). En el segundo capítulo se examina la frecuencia de participación turística mediante la explotación de los microdatos de la Encuesta de Presupuestos Familiares (EPF) durante el periodo 1999-2005. Además de la renta disponible y las variables del hogar asociadas a su situación económica, el tiempo libre, marcado por la situación laboral del sustentador familiar, y otros factores del hogar y sus miembros se incluye una variable temporal que permita describir la evolución de la frecuencia en el periodo considerado. En el tercer capítulo se examinan las decisiones de participación y gasto turístico de los hogares españoles en un periodo caracterizado por un cambio en el ciclo económico. Se emplean microdatos de la Encuesta de Presupuestos Familiares (EPF) de los años 2006 a 2010, lo que permite analizar las consecuencias que la crisis económica y el desempleo tienen sobre las decisiones de consumo turístico de los hogares. Finalmente, el cuarto capítulo tiene como principal objetivo la clasificación de los hogares en función de sus preferencias de consumo, distinguiendo entre demandantes de baja intensidad (nulo o muy escaso gasto turístico), intensidad media (gasto turístico intermedio) y alta intensidad (gasto turístico elevado). Así, se pretende ofrecer una alternativa a la modelización del gasto turístico teniendo en cuenta, de manera explícita, las preferencias personales ya que estas juegan un papel fundamental en la demanda turística como respuesta a un conjunto de características sociodemográficas y económicas. Los microdatos empleados pertenecen a la Encuesta de Presupuestos Familiares (EPF) de los años 2006 a 2010. Los ingresos son la variable que mayor poder explicativo tiene sobre la demanda turística. Aún así, las variaciones en el nivel de renta no presentan efectos uniformes en la variación del consumo turístico de los diferentes hogares. Los resultados obtenidos ponen de manifiesto la existencia de otros factores sociodemográficos que pueden compensar o restringir el consumo turístico efectivo. Las variaciones de los ingresos en los hogares, debidos a factores externos como la crisis o el desempleo, o a otros factores específicos del hogar y de sus miembros, no tienen el mismo efecto en las variaciones de la demanda turística final. Para el análisis de la demanda turística es necesario utilizar herramientas de estimación que permitan recoger la heterogeneidad de los consumidores. De esta manera, el efecto de los ingresos o de la situación económica de un hogar puede verse compensado por la presencia de otras variables ya sean preferencias o determinantes sociodemográficos. En cuanto a la novedad de introducir el efecto de la crisis, los resultados obtenidos ponen de manifiesto que ante ésta, los hogares modifican parcialmente sus criterios de decisión. En un entorno social de crisis económica los hogares otorgan a los ingresos un papel más conservador en la decisión de participación; no obstante, una vez tomada esa decisión, el gasto efectivo es más sensible al nivel de ingresos del hogar. Los resultados obtenidos revelan la conveniencia de incluir información sobre la situación laboral del sustentador principal, y si cabe, del resto de miembros en las decisiones de participación, frecuencia de viaje y gasto turístico. En España, dónde su economía se caracteriza por las elevadas tasas de desempleo y donde el ciclo económico afecta a la permanencia de empleo de los individuos, esta consideración ayuda a obtener una imagen más real sobre el comportamiento del hogar. Como se observa en los resultados el desempleo tiene un efecto negativo en las decisiones de consumo turístico que es coherente con la literatura revisada. El seguimiento y análisis de la demanda turística debe realizarse en un entorno de constantes cambios y, en la actualidad, con perspectivas de estancamiento. La tesis contribuye al análisis de la demanda turística señalando la heterogeneidad de comportamiento y preferencias de los consumidores, para los que el nivel de ingresos es sólo un factor en el conjunto de determinantes económicos y sociodemográficos que afectan a sus decisiones de consumo.

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Fai, Wong Kin, and 黃健輝. "Are Currency crises predictable: The performance of Probit model, Logit model and Markov-switch model." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/ekka4y.

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碩士 國立暨南國際大學 經濟學系 91 This thesis tries to evaluate the Probit model which is proposed by Frankel and Rose in 1996 for predicting currency crises. The idea is try to answer the question：If we had been using the Probit model in late 1996, how well armed would we have been to predict the Asian currency crisis and the South-America currency crisis? Furthermore, we utilized the Logit model and Markov switching model to predict currency crisis, and compared the performance with the Probit model. This study focuses on the empirical analysis of 8 crisis countries from 1990 to 2003. According to the empirical results, we ended up with the following conclusions： Logit model has the best performance for predicting currency crises.

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Yin, Hsieng-Sui, and 殷祥穗. "Credit Default of Cardholders – EmpiricalEvidence with the Logit and the Probit Model." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/58439300579543890169.

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碩士 臺灣大學 經濟學研究所 95 Abstract This paper investigates the determinants of credit card default in Taiwan. Informational asymmetry between credit cardholders and financial institutions cause the problems of adverse selection, moral hazard and the violation of contract. Our sample includes 60,000 cardholders (both 50,000 from general data and 10,000 randomly selected data) from the Bank A in year 2006 to conduct empirical studies. We select 10 explanatory variables: sex, age, career, education, marriage status, credit card type, yearly expenditure, yearly recursion usage, credit amount, residence area etc. The empirical evidence with the Probit model and the Logit model shows that sex, age, career, credit card type, yearly expenditure, yearly recursion usage, credit amount and residence area are statistically significant to explain the default of credit card. However, there is one exception that the variable of yearly recursion usage cannot explain the default in the Logit model of all sample data. In addition, we use the CAP curve and the ROC curve to analyze the predictable ability and have found that the Logit model perform is the same as the Probit model. While both models have predictable ability with out of the sample, we also can say that two models perform perfect. The empirical evidence could provide a “standard” operational procedure to directly predict the violation probability of an credit card applicant.

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Lee, Sangwon active 2013. "Interaction and marginal effects in nonlinear models : case of ordered logit and probit models." 2013. http://hdl.handle.net/2152/22588.

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Interaction and marginal effects are often an important concern, especially when variables are allowed to interact in a nonlinear model. In a linear model, the interaction term, representing the interaction effect, is the impact of a variable on the marginal effect of another variable. In a nonlinear model, however, the marginal effect of the interaction term is different from the interaction effect. This report provides a general derivation of both effects in a nonlinear model and a linear model to clearly illustrate the difference. These differences are then demonstrated with empirical data. The empirical study shows that the corrected interaction effect in an ordered logit or probit model is substantially different from the incorrect interaction effect produced by the margins command in Stata. Based on the correct formulas, this report verifies that the interaction effect is not the same as the marginal effect of the interaction term. Moreover, we must be careful when interpreting the nonlinear models with interaction terms in Stata or any other statistical software package. text

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WU, ZHAO-RONG, and 吳肇榮. "Prediction of investment performance of Taiwan stock market : application of econometric analysis (discriminant analysis, probit model and logit model)." Thesis, 1992. http://ndltd.ncl.edu.tw/handle/40113559142910856170.

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Tu, Chao-Fu, and 杜肇福. "Rethinking 1997 Asian Financial Crisis and Its Behind by Using Factor Analysis on Logit and Probit Model." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/05004524358735598693.

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碩士 清雲科技大學 經營管理研究所 100 The asian financial crisis in1997 caused a severe blow to the monetary financial and economic development of all East Asian countries. The factors on the past research is nothing more than to be divided into the fundamentals and finance, but some blind spots in both arguments are existent, and the situation is different in other Asian countries. In this study, not only to the recognition of traditional view of the financial crisis, but also to find the foreign capital out of Asia "hot money" changes, whether caused by the factors of the financial turmoil before the 1997 Asian financial crisis. The foreign capital is divided into foreign direct investment, and foreign portfolio investment and other foreign investment in this study, which trying to find the factors of changes in foreign investment funds with more explanation. In this thesis, we first use factor analysis to simplify 13 overall economic indicators, and to identify four factors which affect the early warning indicators of the financial crisis. Secondly, we find the warning indicators used in the Logit model and the Probit model in prediction. In order to look for the relationship of ASEAN-5 between the causes and foreign factors, then finally to investigate the causes of the Asian financial crisis in 1997.

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Huang, Chen Shun, and 黃建順. "Analysis of Intraday''s Discrete Price Changes in Taiwan Stock Market -- The Application of Ordered Probit, Multinomial Logit Model." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/36630135936411377868.

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Haddadian, Rojiar. "Simulation-based estimation in regression models with categorical response variable and mismeasured covariates." 2016. http://hdl.handle.net/1993/31535.

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A common problem in regression analysis is that some covariates are measured with errors. In this dissertation we present simulation-based approach to estimation in two popular regression models with a categorical response variable and classical measurement errors in covariates. The first model is the regression model with a binary response variable. The second one is the proportional odds regression with an ordinal response variable. In both regression models we consider method of moments estimators for therein unknown parameters that are defined via minimizing respective objective functions. The later functions involve multiple integrals and make obtaining of such estimators unfeasible. To overcome this computational difficulty, we propose Simulation-Based Estimators (SBE). This method does not require parametric assumptions for the distributions of the unobserved covariates and error components. We prove consistency and asymptotic normality of the proposed SBE's under some regularity conditions. We also examine the performance of the SBE's in finite-sample situations through simulation studies and two real data sets: the data set from the AIDS Clinical Trial Group (ACTG175) study for our logistic and probit regression models and one from the Adult Literacy and Life Skills (ALL) Survey for our regression model with the ordinal response variable and mismeasured covariates. October 2016

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Vana, Laura. "Statistical Modeling for Credit Ratings." Thesis, 2018. http://epub.wu.ac.at/6439/1/dissertation_lvana.pdf.

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This thesis deals with the development, implementation and application of statistical modeling techniques which can be employed in the analysis of credit ratings. Credit ratings are one of the most widely used measures of credit risk and are relevant for a wide array of financial market participants, from investors, as part of their investment decision process, to regulators and legislators as a means of measuring and limiting risk. The majority of credit ratings is produced by the "Big Three" credit rating agencies Standard & Poors', Moody's and Fitch. Especially in the light of the 2007-2009 financial crisis, these rating agencies have been strongly criticized for failing to assess risk accurately and for the lack of transparency in their rating methodology. However, they continue to maintain a powerful role as financial market participants and have a huge impact on the cost of funding. These points of criticism call for the development of modeling techniques that can 1) facilitate an understanding of the factors that drive the rating agencies' evaluations, 2) generate insights into the rating patterns that these agencies exhibit. This dissertation consists of three research articles. The first one focuses on variable selection and assessment of variable importance in accounting-based models of credit risk. The credit risk measure employed in the study is derived from credit ratings assigned by ratings agencies Standard & Poors' and Moody's. To deal with the lack of theoretical foundation specific to this type of models, state-of-the-art statistical methods are employed. Different models are compared based on a predictive criterion and model uncertainty is accounted for in a Bayesian setting. Parsimonious models are identified after applying the proposed techniques. The second paper proposes the class of multivariate ordinal regression models for the modeling of credit ratings. The model class is motivated by the fact that correlated ordinal data arises naturally in the context of credit ratings. From a methodological point of view, we extend existing model specifications in several directions by allowing, among others, for a flexible covariate dependent correlation structure between the continuous variables underlying the ordinal credit ratings. The estimation of the proposed models is performed using composite likelihood methods. Insights into the heterogeneity among the "Big Three" are gained when applying this model class to the multiple credit ratings dataset. A comprehensive simulation study on the performance of the estimators is provided. The third research paper deals with the implementation and application of the model class introduced in the second article. In order to make the class of multivariate ordinal regression models more accessible, the R package mvord and the complementary paper included in this dissertation have been developed. The mvord package is available on the "Comprehensive R Archive Network" (CRAN) for free download and enhances the available ready-to-use statistical software for the analysis of correlated ordinal data. In the creation of the package a strong emphasis has been put on developing a user-friendly and flexible design. The user-friendly design allows end users to estimate in an easy way sophisticated models from the implemented model class. The end users the package appeals to are practitioners and researchers who deal with correlated ordinal data in various areas of application, ranging from credit risk to medicine or psychology.

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(6992318), Tariq Usman Saeed. "Road Infrastructure Readiness for Autonomous Vehicles." Thesis, 2019.

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Contemporary research indicates that the era of autonomous vehicles (AVs) is not only inevitable but may be reached sooner than expected; however, not enough research has been done to address road infrastructure readiness for supporting AV operations. Highway agencies at all levels of governments seek to identify the needed infrastructure changes to facilitate the successful integration of AVs into the existing roadway system. Given multiple sources of uncertainty particularly the market penetration of AVs, agencies find it difficult to justify the substantial investments needed to make these infrastructure changes using traditional value engineering approaches. It is needed to account for these uncertainties by doing a phased retrofitting of road infrastructure to keep up with the AV market penetration. This way, the agency can expand, defer, or scale back the investments at a future time. This dissertation develops a real options analysis (ROA) framework to address these issues while capturing the monetary value of investment timing flexibility. Using key stakeholder feedback, an extensive literature review, and discussions with experts, the needed AV-motivated changes in road infrastructure were identified across two stages of AV operations; the transition phase and the fully-autonomous phase. For a project-level case study of a 66-mile stretch of Indiana’s four-six lane Interstate corridor, two potential scenarios of infrastructure retrofitting were established and evaluated using the net present value (NPV) and ROA approaches. The results show that the NPV approach can lead to decisions at the start of the evaluation period but does not address the uncertainty associated with AV market penetration. In contrast, ROA was found to address uncertainty by incorporating investment timing flexibility and capturing its monetary value. Using the dissertation’s framework, agencies can identify and analyze a wide range of possible scenarios of AV-oriented infrastructure retrofitting to enhance readiness, at both the project and network levels.

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Smolár, Peter. "Hodnocení výkonnosti českých modelů úvěrového skórování." Master's thesis, 2020. http://www.nusl.cz/ntk/nusl-436270.

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This thesis provides a comprehensive ranking of 11 Czech statistical and 4 foreign credit scoring models. The ranking is based on the predictive performance of individual models, as measured by the area under curve, evaluated on a randomly sampled set of 250 training and validation samples. After establishing a baseline comparison, 3 avenues of estimation setup optimization are explored, namely missing value treatment, estimation method and the use of additional non-financial variables. After being optimized, the models are once again ranked based on their predictive performance. Statistical inference is drawn using ANOVA and the Friedman test, along with the corresponding Tukey and Nemeyi pos-hoc tests. In their baseline form, the Czech credit scoring models are found to be outperformed by the foreign benchmark model. Treating the missing values by OLS imputation and estimating the models by probit, significantly is found to significantly improve their predictive performance. In their optimized form, the difference in predictive performance between Czech and foreign credit scoring model is found to be only marginal. JEL Classification G28, G32, G33, G38 Keywords credit scoring, multiple discriminant analysis, logit analysis, probit analysis Author's e-mail 71247263@fsv.cuni.cz Supervisor's e-mail...

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Huang, Chieh-Liang, and 黃介良. "An Investigation on the Expenditure Behaviorof Patients in Chain Dental Clinics by using Probit 、Logit and Tobit Models." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/85444961047173288987.

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碩士 國立高雄大學 高階法律暨管理碩士在職專班(EMLBA) 98 The serious financial problem of National Health Insurance in Taiwan is getting difficult because of the political reason. Therefore, the way that government can do to improve the uprising medical insurance budget is to restrict the insurance payment limits. Meanwhile, private clinics will need to expand their income by increasing more self-payment services. Most of existing researches focused only on the investigation regarding factor analysis, as well as the expected value of patients’ satisfaction. This study hence tries to explore the spending behavior of dental patients by using Probit, Logit and Tobit econometric models. We hope to find certain expenditure patterns of dental patients from econometric methods to provide key information for clinic managers. This study uses the data from patients of specific chain dental clinics to randomly choose 6 observations in each age ranging from 19- to 69-year-old. Finally, we utilizes 1,695 observations to conclude that dental patients’ self-payment behaviors are significantly affected by regressors such as “Clinic,” “Age,” “Appointment” and “Chief complain.” The noise to signal ratio of Probit and Logit models are 0.23 and 0.26, respectively, which are acceptable in predicting dental patients’ self-payment probabilities. The Tobit regression also provides valuable information in forecasting the self-payment amount for each specific patient of the chain dental clinics.

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Chen, Tai-Ling, and 陳岱伶. "Managing Customer Churn using a Churn Prediction Model and a Profit Maximization Retention Strategy." Thesis, 2019. http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22107NCHU5402019%22.&searchmode=basic.

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碩士 國立中興大學 行銷學系所 107 Retaining an existing customer costs much less than acquiring a new customer, and increasing customer retention by 5% can increase profits from 25-85% (Reichheld & Sasser, 1990). Customer churn management is very important for companies, but many studies focus on improving the accuracy of predictive models. A churn prediction models lacks a matching strategy, making it difficult to select target customers according to corporate goals. Therefore, the study adopts the profit maximization retention strategy for customer churn management, taking the telecommunications company as an example. CART, logistic regression and neural network are compared according to their ability to predict churners, and the outperformer is applied to adopt a profit maximization strategy in order to accurately target profitable customers and determine the optimal target customer size. The important influence variables of the model are discussed and verified. The results show that the neural network has the best prediction performance, and the profit maximization strategy has higher expected profit in various situations than the churn probability strategy, which confirms the advantage of the profit maximization retention strategy. This study provides companies with the ability to accurately target profitable customers in retention decisions and anticipate the expected profit from a retention activity.

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Barros, Gabriel Cupertino Osório de. "Modelos de Previsão da Falência de Empresas Aplicação Empírica ao Caso das Pequenas e Médias Empresas Portuguesas." Master's thesis, 2007. http://hdl.handle.net/10071/1462.

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Partindo de uma revisão bibliográfica, desenvolveu-se um estudo cujo objectivo consistiu em aferir a aplicabilidade de um modelo de classificação da situação financeira de empresas, de forma a permitir identificar estatisticamente aquelas com tendência para falir, no âmbito do enquadramento e características específicas das pequenas e médias empresas portuguesas. Para o efeito, utilizaram-se, numa amostra de empresas falidas e não falidas, as técnicas estatísticas de análise Logit, Probit e Gompit. As primeiras foram seleccionadas com base no facto de terem sido declaradas Falidas ou ter sido requerida a falência. As segundas constituem um conjunto de empresas consideradas saudáveis, encontrando-se entre as maiores (e aparentemente mais bem geridas) Pequenas e Médias Empresas Portuguesas. A amostra foi obtida, seguindo um conjunto de procedimentos que se convencionou denominar "paired sample design" (amostras emparelhadas), tendo sido seleccionada por cada empresa falida uma empresa considerada sã (seleccionadas entre as maiores). A partir dos Balanços e Demonstrações de Resultados do ano anterior à data de falência das empresas declaradas falidas (2005) e com base num conjunto de rácios económico - financeiros previamente seleccionados, no âmbito de uma análise Logit, Probit e Gompit, derivaram-se várias funções específicas a partir da base de dados disponível. A "taxa de erro global aparente" obtida para o ano anterior à data de falência das empresas foi, no modelo seleccionado (Gompit), de 5,4%, isto é, grande parte das empresas da amostra foram correctamente classificadas com base no modelo obtido. Based on a bibliographic revision, a study was developed with the purpose of testing the applicability of a classification model of the companies’ financial situation, in order to allow the statistical identification of those with trend to bankruptcy, in scope of the specific environment and characteristics of the Portuguese “small and medium enterprises”. To achieve that goal, statistical techniques of Logit, Probit and Gompit analysis, were used in a sample of bankrupt and healthy companies. The first ones were selected based on the fact that bankruptcy was declared or required. The second ones constitute a group of companies considered healthy, amongst the biggest (and apparently better managed) Portuguese small and medium enterprises. The sample was obtained following a group of procedures that are usually named “paired sample design”, having been choosed a healthy company for each bankrupt company. Using the Balance and the Income Statement of the year previous to the date of the companies’ bankruptcy (data of the year 2005) and based on a group of economic and financial ratios previously selected, in the context of the Logit, Probit and Gompit analysis, specific functions were derived from the available data sample. The “percentage of apparent global error” obtained for the year previous to the bankruptcy of the companies, in the selected model (Gompit), was of 5.4%, which means that most of the companies of the sample were correctly classified by the obtained model.

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Chang, Yung-Lin, and 張永霖. "Application of Machine Learning in Analysis of Sales Gross Profit Data and Model Construction -An Empirical Study of Photoelectric Touch Control Device Manufacturer." Thesis, 2019. http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22107NCHU5396023%22.&searchmode=basic.

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碩士 國立中興大學 資訊管理學系所 107 The market value is great for intelligent display and touch control device, the hot business currently. The corporate competence is based on the research capability, which is key performance index for touch control device industrial. During the product research phase, cost and gross profit of product should be estimated to preview the revenue in the future. Gross profit estimation after mass production is important, for it decides the corporate resource arrangement priority at the mass production phase. This research is to apply Machine Learning on above issue. The research purpose is to build a predict model, for touch control device industrial, to predict gross profit high or low for pilot run product after its mass production, supporting the decision making for resource arrangement and produce priority at mass production phase. The research method is applying Maching Learning algorithm, association rule(apriori) and classification rule(Decision tree C4.5, Decision tree CART, OneR, SVM, Naive Bayes, Back Propagation Neural Network), using feature selection by information gain and gain ratio with data set cross validation and split 50% train, remainder test method. After the experiment via software tool Weka, it is found that Back Propagation Neural Network is the appropriate algorithm because of its highest accuracy rate and higher perfomance on “True Positive Rate”, “Precision Rate”, “Recall Rate” and “Area Under ROC”.

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Λίβανος, Θεόδωρος. "Υποδείγματα χρονοσειρών περιορισμένης εξαρτημένης μεταβλητής και μέτρηση της ταχείας διάχυσης αρνητικών χρηματοοικονομικών συμβάντων". Thesis, 2011. http://nemertes.lis.upatras.gr/jspui/handle/10889/4359.

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Abstract:

Στόχος της παρούσης διπλωματικής εργασίας είναι να μελετηθεί η Ταχεία Διάχυση Αρνητικών Χρηματοοικονομικών Συμβάντων (financial contagion) όπως αυτή παρουσιάζεται στην βιβλιογραφία καθώς επίσης οι αιτίες, οι τρόποι διάχυσης και οι τρόποι μέτρησης της. Όσον αφορά στο εφαρμοσμένο κομμάτι της υπάρχουσας βιβλιογραφίας εξετάζεται το μέρος αυτής το οποίο αφορά στην εξέταση της Ταχείας Διάχυσης Αρνητικών Χρηματοοικονομικών Συμβάντων με μοντέλα περιορισμένης εξαρτημένης μεταβλητής. Γίνεται εκτενέστερη ανάλυση στο multinomial logit μοντέλο το οποίο φανερώνει την πιθανότητα εμφάνισης ενός ενδεχομένου σε σχέση με τις επεξηγηματικές μεταβλητές που επιλέγονται. Στα πλαίσια της εργασίας αυτής γίνεται και μια εμπειρική εφαρμογή ενός τέτοιου μοντέλου με δεδομένα που αφορούν την Ελληνική Χρηματιστηριακή Αγορά με σκοπό να δειχθεί αν οι χαμηλές αποδόσεις ορισμένων υποδεικτών του Γενικού Δείκτη Τιμών επηρεάζουν την πιθανότητα εμφάνισης ταυτόχρονων κοινών υπερβάσεων στις αποδόσεις (coexceedances) και άλλων υποδεικτών. The aim of this thesis is to study the rapid dissemination Negative Financial Events (financial contagion) as presented in the literature as well as the causes, ways and methods of diffusion measurement. As far as the applied part of the existing literature is concerned, it is examined the part which concerns the examination of the Rapid Diffusion of Negative Financial Events (financial contagion) with limited dependent variable models. There is extensive analysis of the multinomial logit model. As part of this work it is presented an empirical application of such a model with data from the Greek stock market in order to indicate whether the low returns of certain subindices of the General Price Index affect the likelihood of simultaneous joint excesses in returns (coexceedances) of other subindices .

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Dissertations / Theses on the topic 'Probit/logit model'

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