Country Differences in Material Deprivation in Europe

This paper assesses to what extent differences in the characteristics of individuals (micro‐level perspective) and country‐specific factors (macro‐level perspective) can explain country differences with respect to material deprivation levels. Thus, our work aims to simultaneously consider the macro dimension and the predominantly individually‐oriented study field of material deprivation using multilevel techniques. We make use of the European Union Statistics on Income and Living Conditions. Our results show that country‐specific factors seem to be much more relevant than individual effects in explaining country differences in material deprivation. We estimate that the introduction of country‐specific factors reduces the proportion of total variance due to between‐country differences in deprivation by 72.7 percent, while individual‐level variables reduce this proportion by only 9.4 percent. We also show, through interaction variables, that the effect of sociodemographic characteristics can be shaped by institutional and structural factors, especially by the level of GDP.     

Strategic Capabilities and Performance in Women‐Owned Businesses in Mexico

The dire economic situation in Mexico, with its high rate of unemployment, makes it necessary for many women to find some form of economic activity to provide income for their families. Although such conditions could encourage the creation of new firms, the results of the Global Entrepreneurship Monitor 2006 Report show a gap between the number of women involved in nascent and young entrepreneurship initiatives and the number who owns established firms. This gap may indicate that the firms created need to improve their competitiveness and their ability to survive. The model proposed adopts the resource‐based view of the firm as a theoretical framework from which to study how entrepreneurial orientation, market orientation, and learning orientation, as well as the interactions between them, influence the achievement of competitive advantage and superior performance in businesses owned by women. Our investigation analyzes businesses established and managed by women in Mexico and registered with the Asociación Mexicana de Mujeres Empresarias A.C. (Mexican Association of Business Women) and the Red de Empresarias del Instituto Nacional de Mujeres (Women Entrepreneurs Network of the National Women's Institute). To gather the information needed, the study used a questionnaire as a measuring instrument. The results are based on the 90 complete answers received from the questionnaires distributed. The results show that all of relationships in our model are positive except the hypothesis that learning orientation mediates in the relationship between market orientation and performance. The results suggest that entrepreneurial orientation reinforces the effect of two capabilities, market orientation and learning orientation, on firm performance. They also reaffirm that the three capabilities assessed may lead an organization to differentiate itself from its competitors by improving its performance. In addition to contributing to the literature on female entrepreneurship, the results have important implications for management. Understanding the relationships between capabilities and the performance of women‐owned businesses in Mexico can permit the identification of areas for improvement to promote the growth and survival of this type of firm.     

Can Marketing Help in Tackling Food Waste?: Proposals in Developed Countries

One third of food destined for human consumption is wasted globally, and much of the food waste that comes from high-income or developed countries is caused by poor marketing practices, consumer behavior, and consumption patterns. The present study focuses on developed countries to propose some marketing actions that could help in reducing food waste. A comprehensive analysis was carried out for each marketing variable, to provide a snapshot of actions and proposals that are being developed. Our study highlights the relevance of marketing in contributing to reduce food waste, through the removal of “Buy one, get one free” sales promotions, clarifying date labeling, or raising food waste awareness campaigns. The main contribution of this study is the proposal of marketing actions that help in tacking food waste.     

The α-stable processes and their relationship with the exponent of self-similarity: Exchange rates of USA Dollar,Canadian Dollar,Euro and Yen

This research work analyzes the yields of the exchange rate parities of the American dollar, Canadian dollar, Euro, and Yen; estimates the basic statistics and the α-stables; carries out the Kolmogorov–Smirnov, Anderson–Darling, and Lilliefors goodness of fit tests; estimates the self-similar exponents and carries out the t and F tests, ruling out that the series of parities are multifractal. It also estimates the confidence intervals of the exchange rate parities and concludes that the estimated α-stable distributions are more efficient than the Gaussian distribution to quantify the risks of the market, and that the series are self-similar. Through the ? index, we can infer the risk of the events, indicating that the parities are anti-persistent and thus have short-term memory, mean reversion, and a negative correlation with the high risk in the short and medium term. The estimation and validation of the α-stable distributions and the self-similar exponent are important in the evaluation and creation of innovative investment instruments through financial engineering, risk administration, and the evaluation of derived products.     

Using partial identification methods to estimate the effect of violence against women on their children’s health outcomes

A growing literature in economics seeks to estimate the costs of violence against women by examining, for example, its impact on the health outcomes of their children. However, it is difficult to assign a causal interpretation to these nonexperimental studies due to the presence of unobservable characteristics affecting violence and health outcomes simultaneously. The lack of credible instrumental variables applicable in several countries further limits our knowledge. I address this gap by using new partial identification methods to estimate the relative size of the unobservables needed to eliminate the estimated effects in nonexperimental studies. I also expand the external validity of the analysis by using data from five standardized nationally representative household surveys in Latin America. Consistent with previous studies, cross-sectional estimates show large negative associations between violence against women and an array of child health outcomes. However, when accounting for omitted variable bias, at best, two-thirds of the estimates remain robust and they are concentrated on the outcomes with the largest cross-sectional estimated impacts.     

Information and Investor Behavior Surrounding Earnings Announcements

The goal of this paper is to analyze the impact of annual earnings announcements on the market through the order flow data in addition to the usual transaction data. In this respect, examining order flow data can potentially reveal valuable information that is not available from transaction data. In fact, the data allow us to test hypotheses about asymmetric information and investor behavior and to test if the behavior varies with investor sophistication. In addition, the paper tries to identify the determinants of the impact on a firm's value using assumptions about investor behavior.     

The Value of Customer Cocreated Knowledge during the Innovation Process

Customer cocreation during the innovation process has recently been suggested to be a major source for firms' competitive advantage. Hereby, customers actively engage in a firm's innovation process and take over innovation activities traditionally performed by a firm's employees. Despite its suggested importance, previous research has revealed contradictory findings regarding its impact, the nature of involved customers, and the channels of communication that enable cocreation. To provide a more fine‐grained picture, customer cocreated knowledge is first delineated into its key value dimensions of relevance, novelty, and costs, and then their impact on various innovation outcomes is investigated. Next, the study examines the antecedent role of customer determinants; that is, lead user characteristics and customer–firm closeness, on these knowledge value dimensions. Finally, we explore how these effects are moderated by the type of communication channel used. An empirical validation of the conceptual model is performed by means of survey data from 126 customer cocreation projects. The data analysis indicates that customer cocreation is most successful for the creation of highly relevant but moderately novel knowledge. Cocreation with customers who are closely related to the innovating firm results in more highly relevant knowledge at a low cost. Yet, cocreation with lead users produces novel and relevant knowledge. These effects are contingent on the richness and reach of the communication channels enabling cocreation. Overall, the findings shed light on opportunities and limitations of customer cocreation for innovation and reconcile determinants originating in relationship marketing and innovation management. At the same time, managers obtain recommendations for selecting customers and communication channels to enhance the success of their customer cocreation initiatives.     

Sparse Partial Least Squares in Time Series for Macroeconomic Forecasting

Factor models have been applied extensively for forecasting when high‐dimensional datasets are available. In this case, the number of variables can be very large. For instance, usual dynamic factor models in central banks handle over 100 variables. However, there is a growing body of literature indicating that more variables do not necessarily lead to estimated factors with lower uncertainty or better forecasting results. This paper investigates the usefulness of partial least squares techniques that take into account the variable to be forecast when reducing the dimension of the problem from a large number of variables to a smaller number of factors. We propose different approaches of dynamic sparse partial least squares as a means of improving forecast efficiency by simultaneously taking into account the variable forecast while forming an informative subset of predictors, instead of using all the available ones to extract the factors. We use the well‐known Stock and Watson database to check the forecasting performance of our approach. The proposed dynamic sparse models show good performance in improving efficiency compared to widely used factor methods in macroeconomic forecasting. Copyright © 2014 John Wiley & Sons, Ltd.