Food safety events receive substantial media coverage and can create devastating economics losses for agribusiness firms. It is unclear what factors influence consumers’ purchasing decisions before or after a food safety event occurs. The objectives of this study is to identify these factors that influence purchasing decisions, determine how consumers respond to hypothetical food safety events, and compare these findings across different products and geographical regions. The data for this research was obtained from two surveys. One survey concerned fresh produce while the second focused on meat products. The SPARTA model, based on the Theory of Planned Behavior, is used to determine the impact of probable factors that influence consumers’ purchasing decisions. The result of this research suggests that consumers have clearly-defined levels of trust regarding sources of food safety information. In general, a food safety event occurring in the fresh produce market seems to affect purchasing decisions more than the same event occurring in the meat market. Comparison of findings across geographical regions is less clear. Agribusiness firms can use these results to form a base strategic response plan for food safety events.

In the past few decades spatial econometric models have become a standard tool in empirical research. Nevertheless applications in binary-choice models remain scarce. This paper makes use of Bayesian Spatial Probit Models to model and estimate spatial interactions in location decisions. For this purpose, we focus on the Austrian retail gasoline market, which is going through a process of remarkable structural changes. A short analysis shows that, during the last decade 10.9% of the stations had left the market and a percentage of 29.6% had either left the market or had changed the brand. This paper aims at investigating this process. A special characteristic of this market is the local competition structure which is characterized by spatial dependencies along local competitors. To capture these spatial dependencies and since the dependent variable is binary in nature (an exit had taken place or not), we apply a Bayesian spatial probit model using MCMC estimation on station level data for the whole Austrian retail gasoline market. Our results suggest, that the decision to leave the market, does not only depend on own characteristics, but also on competitors. In particular, we find the exit decisions to exhibit a negative spatial correlation. Moreover, our model allows to quantify spatial spillover effects of this market. (authors' abstract) / Series: Department of Economics Working Paper Series

追求長期穩定的經濟成長是每個國家欲追求的目標，在經濟發展過程中，外在衝擊常常導致經濟體系的景氣循環波動，而短期間景氣循環的大幅波動將不利於經濟體系穩定發展，因為民眾的消費、廠商的投資決策以及政府政策的規劃與實施，都深深受到景氣變動的影響。因此準確預測景氣動向，深受經濟學者、政府以及一般民眾的重視。 預估景氣循環擴張和衰退持續期間的長短並不容易，由美國國家經濟研究局 提供的資料得知，第二次世界大戰後，美國景氣擴張最長的時間，曾經延續了一百零六個月，而最短的則只有十二個月；在景氣衰退方面，最短是六個月，最長則為十六個月。而二次大戰前，時間變化的幅度就更大了。由於景氣變化前的徵兆並不是很顯著，因此許多經濟學者從各種方面來探討與分析景氣循環。 本篇論文引用 ordered Probit 模型對 Dueker (2005) 文章作一個擴展與應用，將Dueker文中原本的二分類：景氣衰退、景氣擴張延伸為景氣三分類：景氣衰退、景氣狀態不明與景氣擴張，帶入 Qual VAR 模型並利用Gibbs sampling模擬未知參數與變數，藉由統計分析，希望能對景氣循環提出一個更為詳細的詮釋。而本篇論文的目的希望在相對於二分類模型，在總體現象上能提供一個更為完善與更明確的描述，使得在分析上能更完整。參考 NBER 所公佈的景氣轉折點並輔以其他指標，將景氣區分為三分類，以 Qual VAR 模型模擬出景氣三分類的景氣指標，再對這個指標做預測分析，並比較美國景氣在二分類與三分類之下的異同。結果指出三分類模型成功的預測出 2002 年第一季到 2003 年第三季美國景氣擴張的狀態，而三選擇模型的模型比起二選擇模型，對於預測景氣狀態有更為明確的判斷，且加入一分類指標，提供新的景氣變動解釋，幫助人們做出更為合適的決策。

The three big credit rating agencies released their unsolicited ratings since 1996 and all of these unsolicited ratings are given to banks in Asia, especially in the emerging markets. This study aims to test whether there are differences between solicited and unsolicited bank ratings. We compare the financial profiles of solicited and unsolicited banks and investigate the factors that influence banks’ credit ratings. The empirical results show that unsolicited bank ratings are significantly lower than solicited ratings. It is seen that the financial variables of banks with solicited ratings are also better than those with unsolicited ratings. However, the profitability of banks with solicited ratings is significantly lower than those with unsolicited ratings. We see that listed and commercial banks tend to have lower credit ratings and it could be due to the fact that listed banks may face the volatility of their short-term stock prices, so their operating strategies are influenced by market noise, which leads to inferior performance. The reason why commercial banks tend to have lower credit ratings is that commercial banks face so fierce competition that their profitability is compressed. In the last section, we use an ordered probit model to examine the determinants of Fitch’s rating. We find that sovereign credit risk, solicited status, listed status, bank specialization, profitability and asset quality are the major factors influencing Fitch’s bank credit ratings.

Cette thèse s'inscrit dans la littérature qui analyse les déterminants des performances budgétaires des pays en développement. Nous nous intéressons particulièrement à la question de mobilisation des recettes publiques en raison de l'enjeu que suscite le financement des politiques de développement dont les pays en développement se sont dotés. Certes, nombre d'études se sont intéressées au sujet, mais rares sont les analyses qui abordent les effets des chocs dans la mobilisation des recettes publiques des pays en développement. Or, nombreux sont les pays en développement qui connaissent à fréquence élevée des chocs de grande ampleur. La compréhension du mécanisme de transmission de l'effet de ces chocs est déterminante dans la conduite des politiques budgétaires et dans la projection des politiques de développement des pays en développement. Le caractère capital du sujet de la mobilisation des ressources publiques pour l'économie des pays en développement et la non-prise en compte par les précédentes études du rôle des chocs dans la conduite de la mobilisation des recettes publiques constituent nos principales motivations pour cette recherche. Ainsi, le chapitre 1 de la thèse analyse les effets des chocs des produits de base sur la mobilisation des recettes publiques des pays d'Afrique subsaharienne. Le deuxième chapitre examine le rôle des chocs des prix des produits de base à l'export comme à l'import dans la conduite des réformes de transition fiscale engagées par les Etats de l'UEMOA. Il revient sur les entraves que posent les chocs exogènes aux possibilités de mobilisation des recettes internes face à la baisse du poids de la fiscalité tarifaire. Le chapitre 3 analyse l'effet des chocs sociopolitiques, notamment celui des guerres civiles ou conflits intra-étatiques. Enfin, le chapitre 4, prolongement du chapitre 3, porte sur la mobilisation des ressources publiques durant les périodes post-conflictuelles. Le message central qui se dégage de cette thèse est la nécessité de rigueur des pays en développement dans la gestion des retombées des chocs positifs des produits de base pour faire face aux épisodes de chocs négatifs. Cette rigueur doit être complétée par un soutien extérieur bien adapté à la nature des épisodes de chocs. Concernant le cas des chocs sociopolitiques, l'appui externe doit être non seulement financier mais aussi technique durant les périodes post-chocs.

Universiẗat, Diss., 2001--Mannheim.

Esta dissertação analisa os impactos de fatores socioeconômicos e psicossociais sobre a prevalência da depressão no Brasil através de modelos probit e da decomposição de Oaxaca-Blinder aplicados às bases de dados dos suplementos de saúde da Pesquisa Nacional por Amostra de Domicílios (PNAD Saúde) e da Pesquisa Nacional de Saúde 2013 (PNS 2013). Neste trabalho, foram usados dois critérios básicos de identificação de indivíduos deprimidos: os que referiram ter recebido o diagnóstico de depressão de algum profissional de saúde e os que obtiveram um escore superior a 4 no teste PHQ-9 (cujas perguntas constam na PNS 2013). Foram obtidos resultados estatisticamente significativos, evidenciando a maior probabilidade da depressão entre mulheres e a relação inversa do transtorno com as variáveis renda domiciliar, desemprego, escolaridade e idade. Fatores como doenças físicas, doenças mentais e deficiências demonstraram uma relação direta com a depressão, embora as quantificações de suas magnitudes tenham sido sensíveis à especificação dos modelos. Também mostraram uma relação direta com o transtorno depressivo variáveis associadas a traumas e estresse emocional (como ter perdido um filho, ter sofrido algum tipo de violência, ter um filho com problemas de saúde, etc.). Outras variáveis como raça e região geográfica apresentaram resultados ambivalentes, também sensíveis às diferentes especificações de modelo. Ainda, variáveis referentes ao mercado de trabalho como o tipo de vínculo empregatício e setor de atividade apresentaram resultados inconclusivos. Por fim, outra conclusão importante foi que o critério de identificação dos indivíduos com depressão é determinante nos resultados. / This dissertation analyses the impacts of socioeconomic and psychosocial factors over the prevalence of depression in Brazil through probit models and the Oaxaca-Blinder decomposition applied to the data in Brazilian National Household Survey Health Supplement (PNAD Saúde) and the National Health Survey (PNS 2013). In this dissertation, two basic criteria were used to identify individuals with depression: those who declared to have received a depression diagnosis from a health professional and those who scored more than 4 in the PHQ-9 depression test (whose questions are included in PNS 2013). Statistically significant results were found, showing a higher probability of depression among women and an inverse relationship between the disorder and household income, unemployment, education and age. Factors such as chronic physical diseases, mental illnesses and deficiencies have showed a direct relationship with depression, although the quantification of such effects had a rather high sensitivity to model specification. Also, variables associated with emotional stress (such as having lost a child, being victim of some sort of violence, having a child with health problems) showed a direct relationship with depressive disorder. Other variables such as race and geographic region showed ambivalent results also very sensitive to different model specifications. Furthermore, labor market variables like type of work contract and activity sector show inconclusive results. Finally, another important finding is that the criteria for identifying individuals with depression were determinant for the results and conclusions.

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.

Submitted by Vitor Souza (vitor.souza@fgv.br) on 2008-10-17T15:27:55Z No. of bitstreams: 1 055204042-Tatiana_Coimbra.pdf: 292768 bytes, checksum: f1bfd26bd7e333c30122abfb314cef65 (MD5) / Approved for entry into archive by Francisco Terra(francisco.terra@fgv.br) on 2008-10-17T15:59:44Z (GMT) No. of bitstreams: 1 055204042-Tatiana_Coimbra.pdf: 292768 bytes, checksum: f1bfd26bd7e333c30122abfb314cef65 (MD5) / Made available in DSpace on 2008-10-17T15:59:45Z (GMT). No. of bitstreams: 1 055204042-Tatiana_Coimbra.pdf: 292768 bytes, checksum: f1bfd26bd7e333c30122abfb314cef65 (MD5) / A teoria de escolha do portfólio ótimo, desenvolvida a partir da análise da média-variância de Markowitz (1952) deu início ao estudo de vários destes conceitos. A conclusão definitiva deste modelo é que todos os investidores que levam somente em conta a média e o desvio padrão para análise dos investimentos terão o mesmo portfólio de ativos de risco. Investidores conservadores combinarão este portfólio com ativos livres de risco para compor uma carteira menos arriscada. Investidores moderados reduzirão a quantia em ativos livres de risco, aumentando, assim seu risco total. E investidores agressivos podem até contrair empréstimos para obter um portfólio mais arriscado. Os administradores financeiros têm, tradicionalmente, resistido ao simples conselho sobre investimentos embutido nesta teoria. Esta resistência pode, até certo ponto, ser justificada pela necessidade de cada investidor construir seu portfólio refletindo suas preferências e necessidades particulares. Portanto, a gestão da riqueza é um processo direcionado pelas necessidades do indivíduo e não pelos produtos disponíveis. Logo, a análise acadêmica tradicional de escolha do portfólio ótimo precisa ser modificada com o intuito de tratar tais individualidades. O objetivo deste trabalho é usar a base de dados para comparar os resultados empíricos sobre alocação de portfólio à luz da teoria de investimentos com os resultados obtidos através de um questionário respondido pelos funcionários da Souza Cruz, onde utilizaremos um modelo de regressão ordered probit, que prevê a separação em três níveis, dependentes entre si.

This study examines empirically the transition, persistence, and loan demand in the rural credit market using panel data. The data was collected for seven rounds (1994-2009) from 15 villages in Ethiopia. The sample size is about 1500 households for each round. . Chapter one examines the determinants of simultaneous borrowing and lending. We also investigate why some households in rural Ethiopia simultaneously borrow and lend. Who are these households? Panel logit model is estimated for the sub-sample of borrowers and lenders. The result suggests that households that simultaneously borrows and lends are relatively better-off households. The probability of being a simultaneous borrower and lender is higher for households with strong village level networks. Moreover, households that are affected by common shock are more likely to be a simultaneous borrower and lender. Chapter two examines the dynamics and persistence in the rural credit markets in Ethiopia. It also examines the determinants of dynamics and persistence in borrowing and lending. Duration, dynamic probit, and dynamic multinomial logit models are estimated. We control for unobserved heterogeneity and initial condition. The result reveals the existence of positive duration dependence in both only borrowing households and simultaneously lending and borrowing households. The longer the duration as a borrower, the more likely to exit from borrowing. The longer the duration out of borrowing, the more likely to re-enter to borrowing. Off-farm work, fertilizer use, household size, and storing crop are an important determinant of the probability of exit from borrowing. There is also true state dependence in lending, borrowing, and simultaneously borrowing and lending households. This means the probability of being a borrower in the current period is highly correlated with being in the same state in the previous period. Poverty status, flood, labor sharing, membership in mutual help association, total oxen owned, storing crop, off-farm activities, and fertilizer use are an important determinant of the probability of being a borrower. Chapter three examines the determinants of demand for credit in rural Ethiopia. Bias due to data truncation, variation of the interest rate, and using loan data from a single source are the challenges in estimating demand for credit in the context of rural credit market. This study captures data truncation by estimating a panel Tobit model. The variation in the interest rate is also controlled by using village dummies and their interaction with the source of the loan. Total loan obtained from multiple sources is used as a dependent variable. The result reveals that initial endowment proxied by the value of assets, household size, the age of the head of the households, transitory income, and real per capita consumption are the most important determinants of demand for credit.