CEMAPRE - Artigos em Revistas Internacionais / Articles in International Journals
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- Using tail conditional expectation for capital requirement calculation of a general insurance undertakingPublication . Duque, João; Reis, Alfredo Egidio dos; Garcia, RicardoIn this paper we develop a solvency model to estimate the necessary economic capital of a real insurance undertaking operating solely in the Automobile branch, applying the Tail Conditional Expectation risk measure. The model assumes a one year time horizon static approach with an unchanged asset and liability structure for the company. After discussing the main factors affecting the whole of the insurance activity and their influence on the assets and liabilities on that real insurance undertaking used in the study, we calculate its necessary economic capital, by using the Monte Carlo simulation technique to generate the probability distribution of the possible future profit and losses with impact on the company’s fair value. This paper introduces an application of a set of techniques that are usually applied to manage asset and liability risks to capital requirements. With a simulated exercise applied to a real insurance undertaking we show its feasibility, its advantages and how useful it may be for investors, regulators and remaining stakeholders when the technique is explored in depth.
- A variant of the method of step algorithm for a delay differential equationPublication . Fabião, Maria de Fátima; Brito, Paulo; St. Aubyn, AntónioIn this paper we develop a new method to obtain explicit solutions for a first order linear delay differential equation based upon the generating function concept. The advantage of this new method as regards the traditional Method of Step Algorithm (MSA) is also showed through an exemple.
- On the weighted maximum likelihood estimator for endogenous stratified samples when the population strata probabilities are unknownPublication . Ramalho, Esmeralda A.; Ramalho, Joaquim J.S.The popular weighted maximum likelihood estimator for endogenous stratified samples requires knowledge on the population proportions of each stratum. In this paper we extend their estimator for cases where such information is not available.
- Binary models with misclassification in the variable of interest and nonignorable nonresponsePublication . Ramalho, Esmeralda A.In this paper we propose a general framework to deal with datasets where a binary outcome is subject to misclassification and, for some sampling units, neither the error-prone variable of interest nor the covariates are recorded. A model to describe the observed data is formalized and efficient likelihood-based generalized method of moments estimators are suggested.
- Discrete choice non-responsePublication . Ramalho, Esmeralda A.; Smith, Richard J.Missing values are endemic in the data sets available to econometricians. This paper suggests a semiparametrically efficient likelihood-based approach to deal with general non-ignorable missing data problems for discrete choice models. Our concern is when the dependent variable and/or covariates are unobserved for some sampling units. A supplementary random sample of observations on all covariates may be available. The key insight of this paper is the recognition of non-response as a modification of choice-based (CB) samples. Semiparametrically efficient generalized method of moments (GMM) estimation appropriate for CB samples is then adapted for the non-response framework considered in this paper. Simulation results for various GMM estimators proposed here are very encouraging.
- Fractional regression models for second stage DEA efficiency analysesPublication . Ramalho, Esmeralda A.; Ramalho, Joaquim J.S.; Henriques, Pedro D.Data envelopment analysis (DEA) is commonly used to measure the relative efficiency of decision-making units. Often, in a second stage, a regression model is estimated to relate DEA efficiency scores to exogenous factors. In this paper, we argue that the traditional linear or tobit approaches to second-stage DEA analysis do not constitute a reasonable data-generating process for DEA scores. Under the assumption that DEA scores can be treated as descriptive measures of the relative performance of units in the sample, we show that using fractional regression models is the most natural way of modeling bounded, proportional response variables such as DEA scores. We also propose generalizations of these models and, given that DEA scores take frequently the value of unity, examine the use of two-part models in this framework. Several tests suitable for assessing the specification of each alternative model are also discussed
- Is neglected heterogeneity really an issue in binary and fractional regression models? : A simulation exercise for logit, probit and loglog modelsPublication . Ramalho, Esmeralda A.; Ramalho, Joaquim J.S.Theoretical and simulation analysis is performed to examine whether unobserved heterogeneity independent of the included regressors is really an issue in logit, probit and loglog models with both binary and fractional data. It is found that unobserved heterogeneity has the following effects. First, it produces an attenuation bias in the estimation of regression coefficients. Second, although it is innocuous for logit estimation of average sample partial effects, it may generate biased estimation of those effects in the probit and loglog models. Third, it has much more deleterious effects on the estimation of population partial effects. Fourth, it is only for logit models that it does not substantially affect the prediction of outcomes. Fifth, it is innocuous for the size of Wald tests for the significance of observed regressors but, in small samples, it substantially reduces their power.
- Explaining consumer confidence in PortugalPublication . Ramalho, Esmeralda A.; Caleiro, António; Dionísio, AndreiaConfidence in general and consumer confidence in particular are subject to increasing interest by many agents, including central banks and governments at the national level, and supranational entities, such as the European Commission of the European Union. Although the academic community shares this interest, the extant literature focuses on the use of consumer confidence to predict variables that describe aspects of the business cycle, such as consumption. Unlike this body of work, the objective of our paper is to analyse the evolution of consumer confidence in Portugal and examine the factors that under pin its formation. Using monthly and quarterly data over the period January 1987 to December 2009, we find that consumer confidence in Portugal is essentially explained by the economic performance, the entrance in the Euro zone and electoral circumstances.
- Alternative estimating and testing empirical strategies for fractional regression modelsPublication . Ramalho, Esmeralda A.; Ramalho, Joaquim J.S.; Murteira, José M.R.In many economic settings, the variable of interest is often a fraction or a proportion, being defined only on the unit interval. The bounded nature of such variables and, in some cases, the possibility of nontrivial probability mass accumulating at one or both boundaries raise some interesting estimation and inference issues. In this paper we (i) provide a comprehensive survey of the main alternative models and estimation methods suitable to deal with fractional response variables, (ii) propose a full testing methodology to assess the validity of the assumptions required by each alternative estimator and (iii) examine the finite-sample properties of most of the estimators and tests discussed through an extensive Monte Carlo study. An application concerning corporate capital structure choices is also provided.
- Alternative versions of the reset test for binary response index models : a comparative studyPublication . Ramalho, Esmeralda A.; Ramalho, Joaquim J.S.Binary response index models may be affected by several forms of misspecification, which range from pure functional form problems (e.g. incorrect specification of the link function, neglected heterogeneity, heteroskedasticity) to various types of sampling issues (e.g. covariate measurement error, response misclassification, endogenous stratification, missing data). In this article we examine the ability of several versions of the RESET test to detect such misspecifications in an extensive Monte Carlo simulation study. We find that: (i) the best variants of the RESET test are clearly those based on one or two fitted powers of the response index; and (ii) the loss of power resulting from using the RESET instead of a test directed against a specific type of misspecification is very small in many cases.