Product relatedness role on driving industrial policy success

This thesis aims to study how product relatedness to the current pattern of specialization influences the success of industrial policies in underdeveloped sectors. Drawing from Hausmann and Klinger (2006), this work extends the existing literature on the importance of proximity spillovers to explain economic development by focusing on underdeveloped sectors. We find that investment's success in an underdeveloped sector is more likely if it is highly related to the current pattern of specialization. However, heterogeneity amongst sectors is remarkable. Moreover, industrial policy cases are sometimes successful despite the bad odds provided by this criterion, suggesting further factors should be considered.

Genetics of berry colour and anthocyanin content variation in grapevine (Vitis vinifera L.subsp. vinifera)

Dissertation presented in fulfillment of the requirements for the Degree of Doctor of Philosophy in Biology (Molecular Genetics) at the Instituto de Tecnologia Química e Biológica da Universidade Nova de Lisboa

Post-merger innovative performance in the renewable energy sector

Due to global warming and shrinking fossil fuel resources, politics as well as society urge for a reduction of green house gas (GHG) emissions. This leads to a re-orientation towards a renewable energy sector. In this context, innovation and new technologies are key success factors. Moreover, the renewable energy sector has entered a consolidation stage, where corporate investors and mergers and acquisitions (M&A) gain in importance. Although both M&A and innovation in the renewable energy sector are important corporate strategies, the link between those two aspects has not been examined before. The present thesis examines the research question how M&A influence the acquirer’s post-merger innovative performance in the renewable energy sector. Based on a framework of relevant literature, three hypotheses are defined. First, the relation between non-technology oriented M&A and post-merger innovative performance is discussed. Second, the impact of absolute acquired knowledge on postmerger innovativeness is examined. Third, the target-acquirer relatedness is discussed. A panel data set of 117 firms collected over a period of six years has been analyzed via a random effects negative binomial regression model and a time lag of one year. The results support a non-significant, negative impact of non-technology M&A on postmerger innovative performance. The applied model did not support a positive and significant impact of absolute acquired knowledge on post-merger innovative performance. Lastly, the results suggest a reverse relation than postulated by Hypothesis 3. Targets from the same industry significantly and negatively influence the acquirers’ innovativeness.