Transmission of information within transnational social networks: a field experiment

Several studies have shown a relationship between the stocks of migrants and country-level investment in the home country; however the mechanism through which this relationship operates is still unexplored. We use a field experiment in which participants who are recent immigrants send information about risky decisions to others in their social network in their home country. The results demonstrate how this information influences decisions in the home country. We find that the advice given by family members and decisions made by friends significantly affects an individual’s risky decision-making.     

Learning patterns in early stage R&D projects: empirical evidence from the fibre raw material technology project in the Netherlands

Past research has reported that learning processes in early stage R&D are either chaotic, or absent. We challenge this finding by elaborating Van de Ven et al.’s trial‐and‐error learning model and explore an alternative conceptualization. We explored the combinations of positive and negative outcomes and action course continuation and modification. We use data gathered in an R&D setting of a 4‐years pre‐competitive knowledge generation project in the Dutch paper and board industry. Whereas the Van de Ven and Polley (1992) approach applied on our data also would lead us to conclude that ‘no learning’ would happen, our decomposed model identified three distinct learning patterns: (1) a virtuous pattern of positive outcomes resulting in continuations of action courses; (2) a vacuous pattern of negative outcomes resulting in modifications of action courses; and (3) a verification pattern of positive outcomes resulting in modifications of action courses. We observed the virtuous and verification patterns during the first 2 years and virtuous and vacuous learning in the second 2 years. These results might be useful for R&D managers since they provide insight into how an early stage R&D project can develop and where managers might intervene and adjust action courses.     

Financial Instruments and Promotional Banking in the EU are Growing — But is this Justified?

Institutions and the European Investment Bank are at the forefront of EU investment policy. Their role is expanding and it is now a widely-held position that an improvement in the economy will not eliminate the need for their intervention. The proposals for the 2021–2027 MFF launch more financial instruments and present ‘InvestEU’ as a larger more powerful version of the European Fund for Strategic Investments (EFSI). However, promotional banking is often misunderstood and so is the actual size of promotional banking in Europe in which InvestEU will operate.     

Characterization of the Row Geometric Mean Ranking with a Group Consensus Axiom

An axiomatic approach is applied to the problem of extracting a ranking of the alternatives from a pairwise comparison ratio matrix. The ordering induced by row geometric mean method is proved to be uniquely determined by three independent axioms, anonymity (independence of the labelling of alternatives), responsiveness (a kind of monotonicity property) and aggregation invariance, which requires the preservation of group consensus, that is, the pairwise ranking between two alternatives should remain unchanged if unanimous individual preferences are combined by geometric mean.     

Fixed-Term Contracts and Labor Market Duality in France

The French labor market is segmented between permanent and temporary workers. The second category has difficulty in getting an open-ended contract. This paper aims at depicting workers on short-term contracts and shows the consequences on their professional career are negative and significant. A large part of the wage gap between permanent and temporary workers remains unexplained by observable characteristics. They receive less on-the-job training and their likelihood of obtaining a stable job is lower than 30% after 1 year and a half. They have also a higher probability of being the adjustment variable in case of an economic negative shock. These different findings show the importance of using public policies to encourage transitions from fixed-term to permanent employment and reducing labor-market duality.     

A New Regulatory Paradigm for the Digital Sector in Europe

The new regulatory framework in the digital sector in Europe is likely to fall short of expectations. A fragmented digital market with insuffi cient incentives for investment is the probable outcome. European regulators should abandon their approach in favour of a new and more flexible set of ideas discussed in this paper.     

Integrated bio-economic models as tools to support land-use decision making: a review of potential and limitations

Bio-economic modelling has become a useful tool for anticipating the outcomes of policies and technologies before their implementation. Advances in mathematical programming have made it possible to build more comprehensive models. In an overview of recent studies about bio-economic models applied to land-use problems in agriculture and forestry, we evaluated how aspects such as uncertainty, multiple objective functions, system dynamics and time have been incorporated into models. We found that single objective models were more frequently applied at the farm level, while multiple objective modelling has been applied to meet concerns at the landscape level. Among the objectives, social aspects are seldom represented in all models, when being compared to economic and environmental aspects. The integration of uncertainty is occasionally a topic, while stochastic approaches are more frequently applied than non-stochastic robust methods. Most multiple-objective models do not integrate uncertainty or sequential decision making. Static approaches continue to be more recurrent than truly dynamic models. Even though integrating multiple aspects may enhance our understanding of a system; it involves a tradeoff between complexity and robustness of the results obtained. Land-use models have to address this balance between complexity and robustness in order to evolve towards robust multiple-objective spatial optimization as a prerequisite to achieve sustainability goals.     

Application of Standardization Methods for Environmental Improvement as an Element of Quality of Life Through the Development of a Company’s Business Potential

Various aspects of sustainable development and quality of life are considered, including the impact of standardization. Particular attention is paid to the study of the role played by standardization in improving environmental protection. In this connection the significance of standardization is shown as a factor of improving the technological potential of an enterprise and the quality of life. Various approaches to methods for assessing the effective impact of standardization on the quality of life are analyzed.     

Foreign competition and the durability of US firm investments

How does the exposure to product market competition affect the investment horizon of firms? We study if firms have an incentive to shift investments toward more short‐term assets when exposed to tougher competition. Based on a stylized firm investment model, we derive a within‐firm estimator using variation across investments with different durabilities. Exploiting the Chinese World Trade Organization (WTO) accession, we estimate the effects of product market competition on the composition of US firm investments. Firms that experienced tougher competition shifted their expenditures toward investments with a shorter durability. This effect is larger for firms with lower total factor productivity.     

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.