The number of response categories in ordered response models

The choice of the number m of response categories is a crucial issue in categorization of a continuous response. The paper exploits the Proportional Odds Models’ property which allows to generate ordinal responses with a different number of categories from the same underlying variable. It investigates the asymptotic efficiency of the estimators of the regression coefficients and the accuracy of the derived inferential procedures when m varies. The analysis is based on models with closed-form information matrices so that the asymptotic efficiency can be analytically evaluated without need of simulations. The paper proves that a finer categorization augments the information content of the data and consequently shows that the asymptotic efficiency and the power of the tests on the regression coefficients increase with m. The impact of the loss of information produced by merging categories on the efficiency of the estimators is also considered, highlighting its risks especially when performed in its extreme form of dichotomization. Furthermore, the appropriate value of m for various sample sizes is explored, pointing out that a large number of categories can offset the limited amount of information of a small sample by a better quality of the data. Finally, two case studies on the quality of life of chemotherapy patients and on the perception of pain, based on discretized continuous scales, illustrate the main findings of the paper.

Numeral order and the operationalization of the numerical system

Recent years have witnessed an increase in research on how numeral ordering skills relate to children’s and adults’ mathematics achievement both cross-sectionally and longitudinally. Nonetheless, it remains unknown which core competency numeral ordering tasks measure, which cognitive mechanisms underlie performance on these tasks, and why numeral ordering skills relate to arithmetic and math achievement. In the current study, we focused on the processes underlying decision-making in the numeral order judgement task with triplets to investigate these questions. A drift-diffusion model for two-choice decisions was fit to data from 97 undergraduates. Findings aligned with the hypothesis that numeral ordering skills reflected the operationalization of the numerical system, where small numbers provide more evidence of an ordered response than large numbers. Furthermore, the pattern of findings suggested that arithmetic achievement was associated with the accuracy of the ordinal representations of numbers.

Semiparametric Estimation of a Corporate Bond Rating Model

This paper investigates the incentive of credit rating agencies (CRAs) to bias ratings using a semiparametric, ordered-response model. The proposed model explicitly takes conflicts of interest into account and allows the ratings to depend flexibly on risk attributes through a semiparametric index structure. Asymptotic normality for the estimator is derived after using several bias correction techniques. Using Moody’s rating data from 2001 to 2016, I found that firms related to Moody’s shareholders were more likely to receive better ratings. Such favorable treatments were more pronounced in investment grade bonds compared with high yield bonds, with the 2007–2009 financial crisis being an exception. Parametric models, such as the ordered-probit, failed to identify this heterogeneity of the rating bias across different bond categories.

Indicators of Individual Wine Reputation for Friuli Venezia Giulia

The main objective of this paper is to study indicators of individual wine reputation and how they may affect the price of wines in Friuli Venezia Giulia. The analysis is built on the assumption that consumers base their wine purchase decisions on easily available information such as expert quality ratings and reputation builds on past awards for a wine. We estimate a hedonic pricing model using a data set of 1078 Friulian wines listed in the Gambero Rosso wine guide. The categorical nature of the dependent variable suggests the use of ordered response models. The results not only show that awards for the current quality of a wine carry a positive and substantial premium, but also that having received an award in the past (indicating individual wine reputation) has a positive effect on prices. Moreover, the province of production has a considerable effect on prices and white, older wines tend to be more expensive. The paper confirms the important role of current quality ratings and of individual wine reputation in determining wine prices. An important marketing implication is that wineries and retailers should communicate the current quality of a wine together with any past quality recognitions received as this should foster the reputation of an individual wine in the future.

ICTs usage and skills matching at work: some evidence from Spain

PurposeThis article focuses on the Spanish labour market, and its primary objectives are to analyse the factors determining the ICTs usage at workplace, and examine how the workers' e-skills match with the job tasks requiring ICTs. Furthermore, it will explore whether doing ICTs training activities has a positive effect on the probability of carrying out appropriately the ICTs at work.Design/methodology/approachThe methodology applied is an ordered response model analysing how the workers' e-skills match with the knowledge required to the ICTs usage at the job. This econometric specification will control by the selection bias generated because not all employees use ICTs to perform the job tasks. Data are obtained from the Survey on Equipment and Use of ICTs in Households (ICTS-H Survey).FindingsEducational attainment and the type of ICTs training are the most relevant variables to explain the ICTs usage and the quality of the job match.Research limitations/implicationsData used are cross-sectional, and it excludes the possibility of observing how the workers' careers evolve depending on their ICTs training.Practical implicationsThe methodology applied allows the authors to obtain the marginal effects to the variables explaining the probability of using ICTs at job, and how the workers' knowledge match with the e-skill required by the employers.Social implicationsThe results are a source of information to policymakers about how workers face the introduction of ICTs in the labour market.Originality/valueTo the best of author's knowledge, the article's topic and its methodology are unprecedented in the economic literature and, specially, in the Spanish case.