Equilibrium price formation in markets with differentially informed agents

We consider a pure exchange economy with a finite set of types of agents which have incomplete and asymmetric information on the states of nature. Our aim was to describe the equilibrium price formation and analyze how the lack of information may affect the allocation of resources. To do so, we adapt to an asymmetric information scenario a variant of the Shapley–Shubik game introduced by Dubey and Geanakoplos (J Math Econ 39:391–400, 2003 ).     

Industry dynamics: Foundations for models with an infinite number of firms

This paper explores the connection between three important threads of economic research offering different approaches to studying the dynamics of an industry with heterogeneous firms. Finite models of the form pioneered by Ericson and Pakes (1995) capture the dynamics of a finite number of heterogeneous firms as they compete in an industry, and are typically analyzed using the concept of Markov perfect equilibrium (MPE). Infinite models of the form pioneered by Hopenhayn (1992), on the other hand, consider an infinite number of infinitesimal firms, and are typically analyzed using the concept of stationary equilibrium (SE). A third approach uses oblivious equilibrium (OE), which maintains the simplifying benefits of an infinite model but within the more realistic setting of a finite model. The paper relates these three approaches. The main result of the paper provides conditions under which SE of infinite models approximate MPE of finite models arbitrarily well in asymptotically large markets. Our conditions require that the distribution of firm states in SE obeys a certain “light-tail” condition. In a second set of results, we show that the set of OE of a finite model approaches the set of SE of the infinite model in large markets under a similar light-tail condition.     

DOES SIZE MATTER? THE INFLUENCE OF FIRM SIZE ON WORKING CONDITIONS,JOB SATISFACTION AND QUIT INTENTIONS

Using a detailed survey on Spanish workers, this paper investigates the relationship between firm size and working conditions, the extent to which firm size differences in workers' job satisfaction can be accounted for by differences in their work environment and the impact of firm size on workers' quit intentions. The results indicate that: (1) employees in larger firms face a worse work environment; (2) working in large firms significantly reduces job satisfaction when no controls for working conditions are included, but taking them into account makes differentials across size categories statistically insignificant; and (3) no systematic differences exist in intentions to quit across firm size categories, irrespective of conditioning on wages.     

A Note on Clean Technology Adoption and its Influence on Tradeable Emission Permits Prices

In this paper, we give an example in which the price of tradable emission permits increases despite firms’ adoption of less polluting technology, a result that is in contrast with Montero (J Environ Econ 44:23–44, 2002) and Parry (J Regul Econ 14:229–254, 1998), among others. If two Cournot players switch to a cleaner technology, the price for permits may increase due to an increase in the net demand for permits and a decrease in the net supply of permits after the clean technology is adopted. This is only the case when output demand is quite elastic.     

The Impact of Relational Capital on the Success of New Business Start‐Ups

This study seeks to highlight the key role played by relational capital in new business start‐ups. Following a review of previous research examining the success factors of new ventures and the role played by intellectual capital, our study sets out to achieve this objective by analyzing the impact of a set of intangible relational assets on the initial success of new business start‐ups. Based on a study of 130 firms, we analyzed six hypotheses regarding the possible positive relationship between the relational capital of a start‐up company and its success in its first few years of business.     

Research into Quality Management and Social Responsibility

This article presents a systematic literature review on quality management and social responsibility (focusing on ethical and social issues). It uses the literature review to identify the parallels between quality management and social responsibility, the extent to which qualitative, quantitative and mixed methods are used, the countries that have contributed most to this area, and how the most common quality management practices facilitate social responsibility. The literature review covers articles about quality management and social responsibility (focusing on ethical and social categories) based on a computer search in three databases, namely ABI Inform, Emerald and Science Direct, and includes articles dealing with the subject that were found in the lists of references of the articles found in the primary search, as well as a search in six top management journals. The results show (1) the journals most likely to publish this type of article; (2) the range of qualitative, quantitative and mixed methods used; (3) the most productive countries in this field; (4) the parallels between quality management and social responsibility; and (5) how the most common quality management practices facilitate ethical behaviour and social aspects.     

Impact of copula choice on the modeling of crop yield basis risk

A number of problems in agricultural economics involve modeling joint distributions for which the assumption of multivariate normality may not be warranted. Yet, very little work has been conducted evaluating competing methods for modeling joint dependence. We develop a simulation framework to evaluate the bias and efficiency impacts of copula choice in the context of evaluating county‐to‐farm basis risk. The results suggest significant differences in performance across various copulas and approaches. The findings have important implications for risk analysis, insurance, and policy modeling problems in agriculture regarding the selection of method to model dependence among random variables.     

Nonparametric Estimation of Oligopsony Power in First‐Price Auction

This paper proposes a nonparametric procedure to estimate market power for first‐price auction data and applies the procedure to cattle procurement markets. Most previous studies have used parametric methods, which require specific functional forms for retail demand, input supply and processors’ cost equations. However, researchers often find that market power estimates from parametric methods are sensitive to the choice of functional forms and specifications. An application to data from cattle procurement experiments shows that our nonparametric approach greatly outperforms commonly used parametric methods in estimating the degree of market power. While parametric estimates are sensitive to functional form specification and are at least 90% smaller than ‘true’ market power indices, estimates from our nonparametric procedure deviate from the actual value by no more than 25%.