The Importance of the Wording of the ECB

This paper analyses the ECB communication, focusing in particular on its transparency dimension. We posit that if the ECB is transparent about its future policy decisions, then we should be able to forecast fairly well its future interest rate setting behaviour. We find that the predicting ability of the European monetary authority's words, is similar to the one implied by market-based measures of monetary policy expectations. Moreover, the ECB's wording provides complementary, rather than substitute, information with respect to economic and monetary variables.ECB communication, transparency, monetary policy forecast, empirical reaction function, Euribor rate curve

Design of an artificial intelligence model that refines the results of analysis in economic decision making. The case of final energy consumption in the UE

[ES] El objetivo de este Trabajo de Fin de Grado, titulado ‘Diseño de un modelo de Inteligencia Artificial que afina los resultados del análisis en la toma de decisiones en economía: el caso del consumo final de energía en la UE’, es arrojar luz sobre el potencial de la Inteligencia Artificial (IA) para el proceso de toma de decisiones. El estudio comienza estableciendo las bases del enfoque tradicional para la toma de decisiones y analizando los procesos que existen. Además, se definen las limitaciones de estos enfoques tradicionales. La siguiente sección explora los nuevos enfoques basados en IA. En primer lugar, se establecen los conceptos fundamentales de la IA. Además, se aclaran las diferencias entre IA y ‘Machine Learning’. Luego, se profundiza en el proceso de toma de decisiones utilizando esta tecnología. Habiendo sentado las bases, la investigación se adentra en los efectos económicos que surgen de la integración de la IA en empresas y organizaciones internacionales, diferenciando entre el nivel de la empresa y las repercusiones micro y macroeconómicas. Por último, se presenta un estudio de un caso real en el sector energético europeo, para comparar el rendimiento predictivo de los métodos tradicionales con las técnicas novedosas de la IA.[EN] The objective of this Final Degree Dissertation, entitled ‘Design of an Artificial Intelligence model that refines the results of the analysis in economic decision making: the case of final energy consumption in the UE’ is to shed light on the potential of Artificial Intelligence (AI) from a decision-maker perspective. The study commences by establishing the bases of the traditional way of conducting data-driven decisions and discussing the various processes that exist. Additionally, it defines the limitations of these traditional approaches. The subsequent section explores the novel AI approaches for the decision making process, first, it establishes the fundamental concepts of AI. Additionally, it clarifies the distinctions between AI and Machine Learning. Then, it dives into the process of making decisions using AI, proposing examples of techniques employed in different areas. Having laid the groundwork, the research delves into the economic effects that arise from the integration of AI in businesses and international organizations, distinguishing between firm level, and microeconomic and macroeconomic level repercussions. Lastly, a real-world case study in the European energy sector is presented, to compare the predictive performance of traditional methods with AI techniques

Airport service quality and passenger satisfaction : the impact of service failure on the likelihood of promoting an airport online

Based on the analysis of 2278 online passenger ratings of airports worldwide, this study uses a standard multinomial logit model to determine the likelihood of a passenger being a promoter of an airport when a service attribute has failed, controlling for several passenger and airport characteristics. Results show that failures associated with airport staff and queueing times are most likely to reduce the probability of a passenger being a promoter of an airport. Failures associated with airport shopping and wifi service are least likely to do so. More importantly, the failure of any service attribute in this study significantly reduces the probability of a passenger being a promoter of an airport. This suggests that all parts of the airport value chain are likely to suffer when a service attribute fails. Passenger and airport characteristics included in this study do not add significant explanation to whether a passenger becomes a promoter. Keywords: airport service quality, service failure, online ratings, airport value chain, passenger satisfactionpublishedVersio