3 resultados para Age and employment.

em Repositório Científico da Universidade de Évora - Portugal


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Innovation is at the heart of the Europe 2020 Strategy, in order to promote higher levels of employment and productivity. Special attention is given to increasing the effectiveness of innovation policy instruments, mainly as some authors found evidence that productivity could be negatively affected by subsidies. The aim of the study is to assess how the expected impact on firm productivity and employment is taken into account, when firms apply for public funding for innovation. The analysis is based on the case study of the Portuguese Innovation Incentive System in the Alentejo region. In order to understand which factors influence the public decision to financially support private investment, we estimated a logit model based on firms’ and applications’ characteristics, controlling for the macroeconomic environment. The results indicate that government preferences for promoting exports, exploiting firms R&D results and stimulating the level of qualified employment are shown to be more relevant than the impact on firm productivity. Furthermore, the cost to the government of new jobs created, measured at least by exemption of interest and financial charges on the loan, is almost twice as much for non-SMEs as for SMEs.

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Based on four samples of Portuguese family-owned firmsdi) 185 young, low-sized family-owned firms; ii) 167 young, high-sized familyowned firms; iii) 301 old, low-sized family-owned firms; and iv) 353 old, high-sized family-owned firms d we show that age and size are fundamental characteristics in family-owned firms’ financing decisions. The multiple empirical evidence obtained allows us to conclude that the financing decisions of young, low-sized family-owned firms are quite close to the assumptions of Pecking Order Theory, whereas those of old, high-sized family-owned firms are quite close to what is forecast by Trade-Off Theory. The lesser information asymmetry associated with greater age, the lesser likelihood of bankruptcy associated with greater size, as well as the lesser concentration of ownership and management consequence of greater age and size, may be especially important in the financing decisions of family-owned firms. In addition, we find that GDP, interest rate and periods of crisis have a greater effect on the debt of young, low-sized family-owned firms than on that of family-owned firms of the remainder research samples.

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This paper presents our approach of identifying the profile of an unknown user based on the activities of known users. The aim of author profiling task of PAN@CLEF 2016 is cross-genre identification of the gender and age of an unknown user. This means training the system using the behavior of different users from one social media platform and identifying the profile of other user on some different platform. Instead of using single classifier to build the system we used a combination of different classifiers, also known as stacking. This approach allowed us explore the strength of all the classifiers and minimize the bias or error enforced by a single classifier.