A multivariate distance nonlinear causality test based on partial distance correlation: a machine learning application to energy futures

This paper proposes a multivariate distance nonlinear causality test (MDNC) using the partial distance correlation in a time series framework. Partial distance correlation as an extension of the Brownian distance correlation calculates the distance correlation between random vectors X and Y controlling for a random vector Z. Our test can detect nonlinear lagged relationships between time series, and when integrated with machine learning methods it can improve the forecasting power. We apply our method as a feature selection procedure and combine it with the support vector machine and random forests algorithms to study the forecast of the main energy financial time series (oil, coal, and natural gas futures). It shows substantial improvement in forecasting the fuel energy time series in comparison to the classical Granger causality method in time series.     

Easing the assessment of emerging technologies in technology observatories. Findings about patterns of dissemination of emerging technologies on the internet

This paper considers the Web as a big data container that can be used by Technology Observatories and administrations to track emerging issues and more specifically emerging technologies. It considers information that is available on the Internet for free from different sources, and proposes a framework that can be useful to characterise them and to detect patterns of dissemination. This framework is made up of 30 metrics obtained from different kinds of sources (general web, patents, scholars?…). Some of them are obtained directly as the number of hits retrieved by queries on a search engine, and other ones calculated by means of ratios. This paper contains the development of a complete case that utilises this framework to characterise emerging technologies included in the well-known Hype Cycle for Emerging Technologies, in this case the 2015 release¹ and to analyze patterns of dissemination of these technologies on the Internet.     

Towards an operations strategy model of servitization: the role of sustainability pressure

Servitization requires an important strategic shift to drive changes in the operations of manufacturing firms. Using a large-scale survey, the purpose of this paper is (1) to build and validate an operations strategy model of servitization confirming previous case study findings on servitization as a strategic action and (2) to explore the role of sustainability pressures in, and the sustainability performance effects of, pursuing service-based operations strategies. To reach these objectives, a dataset including the responses of 735 manufacturing plants from 21 different countries is analyzed using the PLS-SEM method. The results indicate that the sustainability pressures of stakeholders can push manufacturers to adopt a service-based operations strategy, materializing in the provision of both basic (product-oriented) and advanced (customer-oriented) services (BAS and ADS). Our analysis further indicates that while offering BAS is a precondition for ADS provision, only ADS can offer a competitive edge for manufacturers, both in terms of service and sustainability-related operational performance.     

Job growth in early transition: Comparing two paths*

Small start‐up firms are the engine of job creation in early transition. We ask about differences in their growth across two different transition economies: Estonia, which experienced rapid destruction of pre‐existing firms, and the Czech Republic, which reduced the old sector gradually. We find that the majority of job growth corresponds to within‐industry reallocation. The within‐industry growth of small start‐up firms is similar in the two countries, in line with the convergence to Western industry firm‐size distributions. We also find similar patterns in the evolution of wage differentials between start‐ups and old firms and small differences in the extent of low‐wage employment in start‐ups across the two transition paths. JEL Classifications: J2, J3, J4, L1, O1, P2.     

Determining factors in entry choice for international expansion. The case of the Spanish hotel industry

The hotel sector, as a service industry where it is possible to separate capital investment from management skills, is a clear example of how internationalisation can be modelled without shareholding involvement through foreign direct investment. This paper is an empirical examination of the key factors influencing the decision process carried out by Spanish hotel companies in choosing an entry mode for international expansion. The main objective is to verify whether the concepts derived from the transaction-cost, agency and the strategic theories of organisational capability and knowledge in companies can really explain the mode of foreign expansion employed by the Spanish hotel sector. This study will allow comparison of findings on holiday resort hotel chains with other analyses on the international hotel industry.     

Bivariate and multivariate scaled association models. An application to homogamy of social origin and education in Hungary between 1930 and 1979

In this article we compare bivariate and multivariate models for homogamy of social origin and education to test whether bivariate models of homogamy lead to biased results. We use data on Hungarian couples married between 1930 and 1979 and loglinear models of scaled association. The results indicate some differences between bivariate and multivariate analyses. At each point of time bivariate models overestimate homogamy, both with respect to education and social origin. However, results on trends in time do not differ much between the two analyses. The exception is the period 1940–1959, in which bivariate analysis showed decreasing educational homogamy, and multivariate analysis showed an increasing trend. The latter finding can be explained by declining homogamy of social origin, as well as the weaker reproduction and cross-effects in this period.     

Single or double bounded contingent valuation? A Bayesian test

This paper evaluates the performance of asymptotic approximations of the Bayes factor to appraise the relative likelihoods of the bivariate and the restricted double bounded models for contingent valuation. The performance of the Bayes factor test is studied by Monte Carlo simulation showing that it correctly chooses the bivariate model when appropriate, but tends to over predict the double bounded model when the correlation coefficient is not estimated accurately. However, the quadratic error in estimating willingness to pay is reduced if the model preferred by the test is chosen. In addition, we consider the effect of averaging the estimates of WTP from both models, weighting each model with its posterior probability. The results show that ‘model averaging’ across the competing hypothesis further reduces the squared error. The applications with two data sets on National Parks show that the test rejects the restricted double bounded hypotheses against the bivariate model.     

Network neutrality and the nature of competition between network operators

The neutral architecture of the Internet is being challenged by various parties, such as network operators providing the connections to end-users, who are interested in gaining control of the information exchanged over the Internet. What are the effects on competition and welfare of such practices? Currently, there exists very little economic theory on network neutrality. This paper provides a preliminary analysis of the type of economic modeling that can address network neutrality, as well as of the type of results that can be expected.