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.     

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.     

The Variegated Financialization of Housing

There is a small but growing literature on the financialization of housing that demonstrates how housing is a central aspect of financialization. Despite the varied analyses of the financialization of housing and the importance of housing to financialization, the relations between housing and financialization remain under‐researched and under‐theorized. The financialization of housing is not really a specific form of financialization, transcending as it does a number of different forms of financialization. Housing systems, in particular, vary widely across the globe, which implies that housing financialization will be inherently variegated, path‐dependent and uneven. In this introduction to the symposium, I will discuss how the articles to follow contribute to the literature on the financialization of housing. Housing has entered a post‐Fordist, neoliberal and financialized regime. Increasingly, both mortgaged homeownership and subsidized rental housing are there to keep financial markets going, rather than being facilitated by those markets. There is little evidence that the global financial crisis has resulted in any de‐financialization of housing. There are common trajectories within uneven and variegated financialization, rather than radically different and completely unrelated forms of housing financialization.     

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.     

Measuring price discovery: The variance ratio, the R, and the weighted price contribution

We analyze the statistical properties of three price discovery measures: The variance ratio, the weighted price contribution (WPC), and the R² of unbiasedness regressions. We find that, if the price process is a driftless martingale, only the WPC is an unbiased estimator for the return variance explained during a time interval. For autocorrelated processes with a drift, only the R² of the unbiasedness regression is consistent, but it is biased for small samples.     

Is Supply's Actual Contribution to Sustainable Development Strategic and Operational?

This paper addresses the issue of how sustainable supply practices are actually used as a leverage for sustainable development (SD). In order to assess the level of sustainable supply management within an organization, the authors have reviewed the literature extensively and then developed a five‐step maturity model around five management dimensions. A qualitative exploratory approach based on two detailed case studies of organizations whose reputation for SD is recognized internationally has been used. This methodology allowed us to show (1) how sustainable supply practices could be used as a leverage for an organization's sustainable development approach and (2) that sustainable supply practices still have quite a distance to go with regards to the maturity model for sustainable supply, even in organizations that are often mentioned as leaders in the SD area. In these organizations, managers still emphasize environmental considerations, while neglecting practices that would make it possible to reach the three SD objectives simultaneously. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment     

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.