Ambiguity in election games

We construct a model in which the ambiguity of candidates allows them to increase the number of voters to whom they appeal. We focus our analysis on two points that are central to obtain ambiguity in equilibrium: restrictions on the beliefs that candidates can induce in voters, and intensity of voters' preferences. The first is necessary for a pure strategy equilibrium to exist, while the second is necessary for ambiguity in equilibrium when there exists a Condorcet winner in the set of pure alternatives (e.g. the spatial model of electoral competition), and when candidates' only objective is to win the election. In this last case, an ambiguous candidate may offer voters with different preferences the hope that their most preferred alternative will be implemented. We also show that if there are sufficiently many candidates or parties, ambiguity will not be possible in equilibrium, but a larger set of possible policies increases the chance that at least one candidate will choose to be ambiguous in equilibrium. We would like to thank Alberto Alesina, Antonio Cabrales, Steve Coate, Olivier Compte, Tim Feddersen, Itzhak Gilboa, Joe Harrington, Michel Le Breton, Alessandro Lizzeri, George Mailath, Steve Matthews, Steve Morris, Ignacio Ortuno, Tom Palfrey, Larry Samuelson, Murat Sertel, Fernando Vega, Eyal Winter and an anonymous referee for helpful comments. The first author acknowledges financial support from DGICYT-PB 95-0983. This work was done while the first author was visiting the Center in Political Economy at Washington University, and visiting the Center for Basic Research in the Social Sciences at Harvard University. Their hospitality is gratefully acknowledged. The support of the second author's research by the National Science Foundation is also gratefully acknowledged.     

Introducing Environmental Variables in Nonparametric Frontier Models: a Probabilistic Approach

This paper proposes a general formulation of a nonparametric frontier model introducing external environmental factors that might influence the production process but are neither inputs nor outputs under the control of the producer. A representation is proposed in terms of a probabilistic model which defines the data generating process. Our approach extends the basic ideas from Cazals et al. (2002) to the full multivariate case. We introduce the concepts of conditional efficiency measure and of conditional efficiency measure of order-m. Afterwards we suggest a practical way for computing the nonparametric estimators. Finally, a simple methodology to investigate the influence of these external factors on the production process is proposed. Numerical illustrations through some simulated examples and through a real data set on Mutual Funds show the usefulness of the approach.JEL Classification: C13, C14, D20     

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.     

Gaussian process regression for pricing variable annuities with stochastic volatility and interest rate

Decisions in Economics and Finance - In this paper, we investigate value and Greeks computation of a guaranteed minimum withdrawal benefit (GMWB) variable annuity, when both stochastic volatility...     

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.     

Using technology to improve the management of development impacts on biodiversity

The mitigation hierarchy (MH) is a prominent tool to help businesses achieve no net loss or net gain outcomes for biodiversity. Technological innovations offer benefits for business biodiversity management, yet the range and continued evolution of technologies creates a complex landscape that can be difficult to navigate. Using literature review, online surveys, and semi-structured interviews, we assess technologies that can improve application of the MH. We identify six categories (mobile survey, fixed survey, remote sensing, blockchain, data analysis, and enabling technologies) with high feasibility and/or relevance to (i) aid direct implementation of mitigation measures and (ii) enhance biodiversity surveys and monitoring, which feed into the design of interventions including avoidance and minimization measures. At the interface between development and biodiversity impacts, opportunities lie in businesses investing in technologies, capitalizing on synergies between technology groups, collaborating with conservation organizations to enhance institutional capacity, and developing practical solutions suited for widespread use.     

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.     

Does Team-Based Compensation Give Rise to Problems When Agents Vary in Their Ability?

This paper reports the results of an experiment on how team heterogeneity in terms of productivity influences both the revenue sharing proposed by the principal to the team and the employees' performance. Experimental evidence shows that when the team is heterogeneous, the principal does not try to motivate the agents through her sharing offer. Regardless of the level of team-based compensation, a large amount of free riding occurs since each agent is mainly influenced by his teammate's behavior. In contrast, when the team is homogeneous, agents are better able to cooperate, reciprocating the principal's offer.