Forecasting US bond default ratings allowing for previous and initial state dependence in an ordered probit model

In this paper we investigate the ability of a number of different ordered probit models to predict ratings based on firm-specific data on business and financial risks. We investigate models based on momentum, drift and ageing and compare them against alternatives that take into account the initial rating of the firm and its previous actual rating. Using data on US bond issuing firms rated by Fitch over the years 2000 to 2007 we compare the performance of these models in predicting the rating in-sample and out-of-sample using root mean squared errors, Diebold-Mariano tests of forecast performance and contingency tables. We conclude that initial and previous states have a substantial influence on rating prediction.

Intellectual property and competition as complementary policies: a test using an ordered probit model

Este Artigo Testa a Proposição da Teoria Econômica de que Propriedade Intelectual e Defesa da Concorrência são Políticas Complementares. um Modelo Probit Ordenado é Utilizado para Estimar os Efeitos Marginais do Uso e Qualidade do Enforcement dos Direitos de Propriedade Intelectual em uma Medida da Gravidade dos Problemas Relacionados À Concorrência. os Resultados Obtidos Reforçam a Noção de que as Políticas de Concorrência e Propriedade Intelectual não são Contraditórias.

Em Algorithm for MLE of a Probit Model for Multiple Ordinal Outcomes

The correlated probit model is frequently used for multiple ordered data since it allows to incorporate seamlessly different correlation structures. The estimation of the probit model parameters based on direct maximization of the limited information maximum likelihood is a numerically intensive procedure. We propose an extension of the EM algorithm for obtaining maximum likelihood estimates for a correlated probit model for multiple ordinal outcomes. The algorithm is implemented in the free software environment for statistical computing and graphics R. We present two simulation studies to examine the performance of the developed algorithm. We apply the model to data on 121 women with cervical or endometrial cancer. Patients developed normal tissue reactions as a result of post-operative external beam pelvic radiotherapy. In this work we focused on modeling the effects of a genetic factor on early skin and early urogenital tissue reactions and on assessing the strength of association between the two types of reactions. We established that there was an association between skin reactions and polymorphism XRCC3 codon 241 (C>T) (rs861539) and that skin and urogenital reactions were positively correlated. ACM Computing Classification System (1998): G.3.

A Comparison of Bayesian and Sampling Theory Inferences in a Probit Model

HE PROBIT MODEL IS A POPULAR DEVICE for explaining binary choice decisions in econometrics. It has been used to describe choices such as labor force participation, travel mode, home ownership, and type of education. These and many more examples can be found in papers by Amemiya (1981) and Maddala (1983). Given the contribution of economics towards explaining such choices, and given the nature of data that are collected, prior information on the relationship between a choice probability and several explanatory variables frequently exists. Bayesian inference is a convenient vehicle for including such prior information. Given the increasing popularity of Bayesian inference it is useful to ask whether inferences from a probit model are sensitive to a choice between Bayesian and sampling theory techniques. Of interest is the sensitivity of inference on coefficients, probabilities, and elasticities. We consider these issues in a model designed to explain choice between fixed and variable interest rate mortgages. Two Bayesian priors are employed: a uniform prior on the coefficients, designed to be noninformative for the coefficients, and an inequality restricted prior on the signs of the coefficients. We often know, a priori, whether increasing the value of a particular explanatory variable will have a positive or negative effect on a choice probability. This knowledge can be captured by using a prior probability density function (pdf) that is truncated to be positive or negative. Thus, three sets of results are compared:those from maximum likelihood (ML) estimation, those from Bayesian estimation with an unrestricted uniform prior on the coefficients, and those from Bayesian estimation with a uniform prior truncated to accommodate inequality restrictions on the coefficients.

A bayesian spatial individual effects probit model of the 2010 UK general election

The Conservative Party emerged from the 2010 United Kingdom General Election as the largest single party, but their support was not geographically uniform. In this paper, we estimate a hierarchical Bayesian spatial probit model that tests for the presence of regional voting effects. This model allows for the estimation of individual region-specic effects on the probability of Conservative Party success, incorporating information on the spatial relationships between the regions of the mainland United Kingdom. After controlling for a range of important covariates, we find that these spatial relationships are significant and that our individual region-specic effects estimates provide additional evidence of North-South variations in Conservative Party support.

Ordered probit regression analysis of the effect of brand name on beer acceptance by consumers

Ordered probit regression was used to analyze data of sensory acceptance tests designed to study the effect of brand name on the acceptability of beer samples. Eight different brands of Pilsen beer were evaluated by 101 consumers in two sessions of acceptance tests: blind evaluation and brand information test. Ordered probit regression, although a relatively sophisticated technique compared to others used to analyze sensory data, was chosen to enable the observation of consumers' behavior using graphical interpretations of estimated probabilities plotted against hedonic scales. It can be concluded that brands B, C, and D had a positive effect on the sensory acceptance of the product, whereas brands A, F, G, and H had a negative influence on consumers' evaluation of the samples. On the other hand, brand E had little influence on consumers' assessment.

Desenvolvimento de metodologia de rating baseada no modelo ordered probit

Nos últimos anos o mercado de crédito brasileiro apresentou grande crescimento em termos de volume e modalidade de operações de crédito. Além disso, observou-se também o aumento da participação dos bancos nesse setor, principais intermediários financeiros da economia. Com isso, em um mercado em desenvolvimento, torna-se cada vez mais importante a correta avaliação e administração do risco financeiro envolvido nas operações: o risco de crédito. Nesse contexto, a classificação de rating surge como referência para investidores. No entanto, como o mercado bancário brasileiro ainda é pouco desenvolvido, apenas instituições de grande porte são classificados pelas agências de rating em funcionamento no país. Este trabalho tem como objetivo o desenvolvimento de uma metodologia de rating baseada no modelo ordered probit, que seja capaz de replicar o nível de rating de uma determinada agência, e assim conseguir estimar o nível de rating para aqueles bancos que não têm a referida classificação de rating

An analysis of quit and dismissal determinants between 1988 and 1999 using the bivariate probit model

Excessive labor turnover may be considered, to a great extent, an undesirable feature of a given economy. This follows from considerations such as underinvestment in human capital by firms. Understanding the determinants and the evolution of turnover in a particular labor market is therefore of paramount importance, including policy considerations. The present paper proposes an econometric analysis of turnover in the Brazilian labor market, based on a partial observability bivariate probit model. This model considers the interdependence of decisions taken by workers and firms, helping to elucidate the causes that lead each of them to end an employment relationship. The Employment and Unemployment Survey (PED) conducted by the State System of Data Analysis (SEADE) and by the Inter-Union Department of Statistics and Socioeconomic Studies (DIEESE) provides data at the individual worker level, allowing for the estimation of the joint probabilities of decisions to quit or stay on the job on the worker’s side, and to maintain or fire the employee on the firm’s side, during a given time period. The estimated parameters relate these estimated probabilities to the characteristics of workers, job contracts, and to the potential macroeconomic determinants in different time periods. The results confirm the theoretical prediction that the probability of termination of an employment relationship tends to be smaller as the worker acquires specific skills. The results also show that the establishment of a formal employment relationship reduces the probability of a quit decision by the worker, and also the firm’s firing decision in non-industrial sectors. With regard to the evolution of quit probability over time, the results show that an increase in the unemployment rate inhibits quitting, although this tends to wane as the unemployment rate rises.

Consistent estimation of the fixed effects ordered logit model

The paper considers panel data methods for estimating ordered logit models with individual-specific correlated unobserved heterogeneity. We show that a popular approach is inconsistent, whereas some consistent and efficient estimators are available, including minimum distance and generalized method-of-moment estimators. A Monte Carlo study reveals the good properties of an alternative estimator that has not been considered in econometric applications before, is simple to implement and almost as efficient. An illustrative application based on data from the German Socio-Economic Panel confirms the large negative effect of unemployment on life satisfaction that has been found in the previous literature.

Identification and estimation of thresholds in the fixed effects ordered logit model

This paper proposes a new estimator for the fixed effects ordered logit model. In contrast to existing methods, the new procedure allows estimating the thresholds. The empirical relevance and simplicity of implementation is illustrated in an application on the effect of unemployment on life satisfaction.

Application of a Bivariate Probit Model to Investigate the Intended Evacuation from Hurricane

With evidence of increasing hurricane risks in Georgia Coastal Area (GCA) and Virginia in the U.S. Southeast and elsewhere, understanding intended evacuation behavior is becoming more and more important for community planners. My research investigates intended evacuation behavior due to hurricane risks, a behavioral survey of the six counties in GCA under the direction of two social scientists with extensive experience in survey research related to citizen and household response to emergencies and disasters. Respondents gave answers whether they would evacuate under both voluntary and mandatory evacuation orders. Bivariate probit models are used to investigate the subjective belief structure of whether or not the respondents are concerned about the hurricane, and the intended probability of evacuating as a function of risk perception, and a lot of demographic and socioeconomic variables (e.g., gender, military, age, length of residence, owning vehicles).

Prescription patterns of pharmaceuticals

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

Are two-part tariffs efficient when consumers plan ahead?: An empirical study

During the last two decades there has been an increase in using dynamic tariffs for billing household electricity consumption. This has questioned the suitability of traditional pricing schemes, such as two-part tariffs, since they contribute to create marked peak and offpeak demands. The aim of this paper is to assess if two-part tariffs are an efficient pricing scheme using Spanish household electricity microdata. An ordered probit model with instrumental variables on the determinants of power level choice and non-paramentric spline regressions on the electricity price distribution will allow us to distinguish between the tariff structure choice and the simultaneous demand decisions. We conclude that electricity consumption and dwellings’ and individuals’ characteristics are key determinants of the fixed charge paid by Spanish households Finally, the results point to the inefficiency of the two-part tariff as those consumers who consume more electricity pay a lower price than the others.

Economic development and changes in car ownership patterns

The contributions of this paper are twofold: On the one hand, the paper analyses the factors determining the growth in car ownership in Spain over the last two decades, and, on the other, the paper provides empirical evidence for a controversial methodological issue. From a methodological point of view, the paper compares the two alternative decision mechanisms used for modelling car ownership: ordered-response versus unordered-response mechanisms. A discrete choice model is estimated at three points in time: 1980, 1990 and 2000. The study concludes that on the basis of forecasting performance, the multinomial logit model and the ordered probit model are almost undistinguishable. As for the empirical results, it can be emphasised that income elasticity is not constant and declines as car ownership increases. Besides, households living in rural areas are less sensitive than those living in urban areas. Car ownership is also sensitive to the quality of public transport for those living in the largest cities. The results also confirmed the existence of a generation effect, which will vanish around the year 2020, a weak life-cycle effect, and a positive effect of employment on the number of cars per household. Finally, the change in the estimated coefficients over time reflects an increase in mobility needs and, consequently, an increase in car ownership.