5 resultados para random-effects ordered logit


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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

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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.

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While the concept of consumer satisfaction is a central topic in modern marketing theory and practice, citizens' satisfaction with public services, and especially water and waste services, is a eld that still remains empirically rather unexplored. The following study aims to contribute to this area by analysing the determinants of user satisfaction in the water, wastewater and waste sector in Portugal, using a unique survey of 1070 consumers undertaken by the Portuguese Water and Waste Regulator ERSAR. I perform an analysis of the relation between overall service satisfaction and attributespeci c service satisfaction with an ordered logit model. I then explore if subjective consumer satisfaction can be re ected by ERSAR's technical performance indicators. The results suggest that overall consumer satisfaction is driven by consumer's satisfaction with speci c service aspects but unrelated to socioeconomic and demographic characteristics. Furthermore, I show that there is no monotonic association between ERSAR's technical performance indicators and consumers' levels of satisfaction.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

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Emigration has been a very present word in Portugal. Due to the effects of the Economic Crisis and the Memorandum of Understanding policies, we have witnessed a significant yearly migration outflow of people searching for better conditions. This study aims to measure the factors affecting this flow as well as how much the probability of emigrating has evolved during the years bridging 2006 to 2012. I shall consider the decision of emigrating as Discrete Choice Random Utility maximization use a conditional Logit framework to model the probability choice for 31 OECD countries of destination. Moreover I will ascertain the compensating variation required such that the probability of choice in 2012 is adjusted back to 2007 values, keeping all other variables constant. I replicate this exercise using the unemployment rate instead of income. The most likely country of destination is Luxembourg throughout the years analyzed and the values obtained for the CV is of circa 1.700€ in terms of Income per capita and -11% in terms of the unemployment rate adjustment.