Creative Destruction and the Rise of Inequality

Common wisdom interprets the rise in inequality of the last two decades as the result of a skill-biased labor demand shift. This explanation does not account for two important observations: (i) within-group inequality has also markedly risen, and (ii) the rise of inequality has been accompanied by a rise of the volatility of earnings. This paper argues that a dual labor market structure, where some workers are paid efficiency-wages can account for the empirical regularities, in the absence of skilled biased technological change. The analysis demonstrates that an unbiased innovation, as well as North–South trade, can contribute to the efficiency wage premium, and thus to wage inequality, by increasing labor turnover.     

Making trading decisions for financial‐engineered derivatives: a novel ensemble of neural networks using information content

Over the last decades, there has been a growing interest in applying artificial intelligence techniques to solve a spectrum of financial problems. A number of studies have shown promising results in using artificial neural networks (ANNs) to guide investment trading. Given the expanding role of ANNs in financial trading, this paper proposes the use of a hybrid neural network, which consists of two independent ANN architectures, and comparatively evaluates its performance against independent ANNs and econometric models in the trading of a financial‐engineered (synthetic) derivative composed of options on foreign exchange futures. We examine the financial profitability and the market timing ability of the competing neural network models and statistically compare their attributes with those based on linear and nonlinear statistical projections. A random walk model and the option pricing method are also included as benchmarks for comparison. Our empirical investigation finds that, for each of the currencies analysed, trading strategies guided by the proposed dual network are financially profitable and yield a more stable stream of investment returns than the other models. Statistical results strengthen the notion that diffusion of information contents and cross‐validation between the independent components within the dual network are able to reduce bias and extreme decision making over the long run. Moreover, the results are robust with respect to different levels of transaction costs. Copyright © 2009 John Wiley & Sons, Ltd.     

The university's Janus face: The innovation–inequality nexus

The university is a key source of talent and a key driver of innovation and economic growth in a knowledge-based economy. But, in performing these economic functions, it also contributes to economic and spatial inequality. Our research uses a variety of new data to examine this Janus face of the university in innovation and inequality across U.S. metro areas. We find evidence that the university plays a role in both regional innovation, boosting local patenting and startup companies, and in economic inequality, with higher rates of income and occupational segregation in metros with highly rated universities.     

Management of Knowledge Sources Supported by Domain Ontologies: Building and Construction Case Studys

This paper introduces a novel conceptual framework to support the creation of knowledge representations based on enriched semantic vectors, using the classical vector space model approach extended with ontological support. This work is focused on collaborative engineering projects where knowledge plays a key role in the process. Collaboration is the arena, engineering projects are the target and knowledge is the currency used to provide harmony into the arena since it can potentially support innovation and, hence, a successful collaboration. The test bed for the assessment of the approach comes from the Building and Construction sector, which is challenged with significant problems for exchanging, sharing and integrating information among actors. Semantic gaps or lack of meaning definition at the conceptual and technical levels, for example, are problems fundamentally originated through the employment of representations to map the ‘world’ into models in an endeavour to anticipate other actors’ views, vocabulary and even motivations. One of the primary research challenges addressed in this work relates to the process of formalization and representation of document contents, where most existing approaches are limited and only take into account the explicit, word-based information in the document. The research described in this paper explores how traditional knowledge representations can be enriched through incorporation of implicit information derived from the complex relationships (semantic associations) modelled by domain ontologies with the addition of information presented in documents, by providing a baseline for facilitating knowledge interpretation and sharing between humans and machines. Preliminary results were collected using a clustering algorithm for document classification, which indicates that the proposed approach does improve the precision and recall of classifications. Future work and open issues are also discussed. Copyright © 2015 John Wiley & Sons, Ltd.     

Equity ownership and control of international joint ventures in the retail sector

Abstract

This study examines the relationships that exist between consumers' perceptions of a retail environment and their emotions, satisfaction and behavioural intentions with respect to that shopping setting. A model of these relationships is developed and then tested in two distinct retail settings—shopping centres and traditional retailing areas. The results show that, in general, positive perceptions of a retail environment have a positive influence on positive emotions, on repatronage intentions, and on the desire to remain longer in the shopping area in both retail settings. However, some interesting differences emerge between shopping centres and traditional retailing areas: (i) the internal environment has a stronger effect on emotions in shopping centres than in traditional retailing areas; and (ii) the internal environment has a negative effect in shopping centres on the disposition to pay more.     

The effects of potential land development on agricultural land prices

We conduct a national-scale analysis of the determinants of agricultural land values. The theoretical basis for the study is a spatial city model with stochastic returns to future land development. The empirical model of agricultural land prices is estimated with a cross-section on approximately three thousand counties in the contiguous US. The results provide evidence that option values associated with irreversible and uncertain land development are capitalized into current farmland values. For each county, we decompose the current agricultural land value into components measuring rents from agricultural production and rents from future land development.