Pitfalls of Normal-Gamma Stochastic Frontier Models

Although conceptually pleasing, normal-gamma frontier models lead to difficult estimation problems. It is shown here that unless the sample size reaches several thousands of observations the shape parameter of the gamma density is hard to estimate, and that this carries over to estimates of the stochastic frontier, the individual inefficiencies, and the allocation of the overall variance to the stochastic frontier and to the inefficiencies.     

Assessment of Interjudge Reliability in the Open-Ended Questions Coding Process

In the process of coding open-ended questions, the evaluation of interjudge reliability is a critical issue. In this paper, using real data, the behavior of three coefficients of reliability among coders, Cohen’s K, Krippendorff’s α and Perreault and Leigh’s I _r are patterned, in terms of the number of judges involved and the categories of answer defined. The outcome underlines the importance of both variables in the valuations of interjudge reliability, as well as the higher adequacy of Perreault and Leigh’s I _r and Krippendorff’s α for marketing and opinion research.     

Pseudo empirical likelihood method in the presence of missing data

In this paper, we propose an estimator for the population mean when some observations on the study and auxiliary variables are missing from the sample. The proposed estimator is valid for any unequal probability sampling design, and is based upon the pseudo empirical likelihood method. The proposed estimator is compared with other estimators in a simulation study.     

Micro-level product-market dynamics: Shared knowledge and its relationship to market development

This work draws on consumer and psychology research to explain sociocognitive aspects of product-market dynamics at a higher level of specificity than prior research. The authors extend the field’s understanding of market-shaping shared knowledge through a theory-informed discussion of how shared product knowledge comes to exist and how it changes as product markets develop. They define shared knowledge as the aspects of product representations that are common across the minds of market actors, making it possible for them to understand one another. The authors also discuss ways to track shared knowledge content that is expressed in market narratives. As the characteristics of shared knowledge are explained and linked to stages of product-market development, the authors develop a set of researchable propositions to guide future research. The theoretical arguments and propositions in this article complement extant marketing strategy research by integrating individual-level consumer theory with market evolution models. José Antonio Rosa (jose.rosa@case.edu; Ph.D., University of Michigan) is an assistant professor of marketing at Case Western Reserve University. His research interests include product markets as sociocognitive phenomena, embodied knowledge in consumer and managerial sensemaking, consumer illiteracy and coping, commitment and motivation among members of network marketing organizations, and buying group satisfaction. His research has been published in marketing and management publications, including theJournal of Marketing and theAcademy of Management Journal. Before entering academia, he worked in the automotive and information systems industries. Jelena Spanjol (jspanjol@tamu.edu; Ph.D., University of Illinois) is an assistant professor of marketing at Texas A&M University. Her research interests include product market dynamics, product portfolio management, innovation, sensemaking, and organizational and managerial cognition in marketing strategy. Her research has been published in marketing and management publications, including theJournal of Marketing and several book chapters. Before academia, she worked in the scientific software industry.     

Linking thoughts to feelings: Investigating cognitive appraisals and consumption emotions in a mixed-emotions context

While emotions have been shown to have significant influence on various consumer behaviors, the cognitive appraisals linked to consumption emotions have not been fully explored. This research investigates how individuals' cognitive interpretations of situations correspond to the emotions they experience in these contexts. Using analysis of variance and multiple discriminant analysis, our results show a systematic relationship between cognitive appraisals and 10 consumption emotions. The author's findings offer theoretical insights into these consumption emotions, the appraisal/consumption emotion correspondence, basisversus subordinate-level category differences in emotions, and mixed consumption emotions. The findings provide a practical framework for academics and practitioners interested in better understanding and managing consumption emotions. Julie A. Ruth (Ph.D., University of Michigan) is an assistant professor of marketing in the School of Business—Camden at Rutgers University. Her research interests include affect and emotions, consumer relationships, and consumer response to brand strategies such as brand alliances and sponsorships. Frédéric F. Brunel (Ph.D., University of Washington) is an assistant professor of marketing in the School of Management at Boston University. His research interests include consumer perceptions of product design and aesthetics, consumer attitude and affect, and gender and sociocultural issues in consumption. Cele C. Otnes (Ph.D., University of Tennessee) is an associate professor of business administration in the College of Commerce and Business Administration at the University of Illinois, Urbana. Her research interests include consumer rituals, affect and consumer ambivalence, and gift exchange.     

Playing the synthesizer with Canadian data: Adding polls to a structural forecasting model

Election forecasting has become a fixture of election campaigns in a number of democracies. Structural modeling, the major approach to forecasting election results, relies on ‘fundamental’ economic and political variables to predict the incumbent’s vote share usually a few months in advance. Some political scientists contend that adding vote intention polls to these models—i.e., synthesizing ‘fundamental’ variables and polling information—can lead to important accuracy gains. In this paper, we look at the efficiency of different model specifications in predicting the Canadian federal elections from 1953 to 2015. We find that vote intention polls only allow modest accuracy gains late in the campaign. With this backdrop in mind, we then use different model specifications to make ex ante forecasts of the 2019 federal election. Our findings have a number of important implications for the forecasting discipline in Canada as they address the benefits of combining polls and ‘fundamental’ variables to predict election results; the efficiency of varying lag structures; and the issue of translating votes into seats.     

Forecasting recovery rates on non-performing loans with machine learning

We compare the performance of a wide set of regression techniques and machine-learning algorithms for predicting recovery rates on non-performing loans, using a private database from a European debt collection agency. We find that rule-based algorithms such as Cubist, boosted trees, and random forests perform significantly better than other approaches. In addition to loan contract specificities, predictors that refer to the bank recovery process — prior to the portfolio’s sale to a debt collector — are also shown to enhance forecasting performance. These variables, derived from the time series of contacts to defaulted clients and client reimbursements to the bank, help all algorithms better identify debtors with different repayment ability and/or commitment, and in general those with different recovery potential.     

Institutions and economic growth in Portugal: a quantitative exploration

This paper presents a broad diagnostic of the level of institutional development in Portugal in the legal, corporate governance and financial systems. A comparative assessment suggests that Portuguese institutions are less developed than their European Union and East Asian counterparts, more developed than Greek institutions and on a level similar to that of Spanish institutions. We use data for a wide cross-section of countries since 1960 and correlate indicators of institutional development with the long-term average growth rate, identifying issues where reform is likely to significantly affect economic growth. We construct three new indices that measure the potential of institutional reform - the impact of reform on growth, the required reform effort and the efficiency of reform index - by taking into consideration the institutional distance between Portugal and the European Union. These indices measure, respectively, which reforms have the most payoff in terms of growth, which are less costly to undertake and which deliver the most growth per required effort. Our results strongly suggest that in a large number of issues, institutional reform may translate into substantially higher rates of economic growth. Of the ten most promising reforms, six are in the legal area, irrespective of which of the indices is considered. Whereas legal reform is promising at the aggregate and the microeconomic levels, in the financial sector aggregate indicators offer the wider scope for productive reform, while in the corporate governance area it is indices at the micro level that hold the most promise. These results support the view that a comprehensive reform effort is likely to deliver higher rates of growth in Portugal, allowing faster real convergence with the rest of the European Union.Received: January 2003, Accepted: February 2004, JEL Classification: O0, O5, K00, K4, G2, G3This paper is based on Firms, Financial Markets and the Law: Institutions and Economic Growth in Portugal, prepared for the conference Desenvolvimento Económico Português no Espaço Europeu: Determinantes e Políticas, organized by the Banco de Portugal. Financial support by the Banco de Portugal, NOVA FORUM and FUNDAÇÃO Para a Ciência e tecnologia and Polti through feder are gratefully acknowledged. Comments from Marcelo Rebelo de Sousa, two anonymous referees and the editor are sincerely appreciated. The usual disclaimer applies.     

Mixed Duopoly,Merger and Multiproduct Firms

The literature on mergers has extensively analyzed the decision to merge by private firms, but it has not considered the decision to merge by private and public firms. We assume that when a private firm and a public firm merge (or when one of them acquires the other), they set up a multiproduct firm in which the government owns an exogenous percentage stake. In this framework, we show that the decision to merge by firms depends on the degree to which goods are substitutes and on the percentage of the shares owned by the government in the multiproduct firm.