Please use this identifier to cite or link to this item: http://hdl.handle.net/10609/149358
Title: La tecnología como inductora de la productividad en la transformación industrial: caso aplicado a la industria pesada de la Dorsal Europea
Author: Méndez Rodríguez, Bruno
Tutor: Cervera Itarte, Diego
Abstract: In a constantly changing world, the transition from an industrial economy to a knowledge-based economy finds in Information and Communication Technology (ICT) a key ally that plays a leading role in the process. Authors like Dale Jorgenson, Mun Ho and Kevin Stiroh (2005)8 have provided conclusive empirical evidence positively linking investment in information technology with efficiency gains in the United States, Canada, the United Kingdom, France, Germany, Italy, and Japan, thereby contributing to explaining advances in labor productivity since the second half of the 1990s. However, since 2005, there has been a noticeable deceleration in the increasing trend of productivity in the economies of OECD countries, a phenomenon described as the "productivity puzzle" due to the difficulties in finding justifiable reasons for it. According to Diane Coyle (2020) 9, technological change complicates the interpretation of discouraging productivity figures in many economies. Beyond contributing factors such as post-2008 financial crisis debt and significant demographic changes, the debate revolves around understanding whether the concept of productivity remains relevant in knowledge-based economies, largely composed of intangible services and digital assets. On the other hand, Brynjolfsson at. al (2016)10 warn us of the difficulty of fully identifying the benefits derived from technological investment and their contribution to productivity improvement. Traditional metrics become insufficient, emphasizing the importance of organizational and management changes in accelerating or hindering productivity gains resulting from technology investments. Evolving towards industrial models where advanced technology contributes to generating value is a key factor in terms of competitiveness. For Europe, from a geopolitical perspective, the technological war between the United States and China (initiated at the end of the Obama administration, consolidated by Trump, and reinforced by Biden) based on technological blockade and national subsidies (Feás, 2023)11 may contribute to a potential and dangerous technological stagnation associated with the loss of competitive advantages. This factor would add to the declining trend in productivity gains, providing an additional reason to justify the need to transform industrial economies into knowledge-based economies. Consequently, it is crucial to understand which policies, once applied to deindustrialization processes, are optimal in terms of productivity gains. This study explores the relationships, their direction and strength, among growth variables, particularly those related to information and communication technologies (ICT) and other aspects of the knowledge economy (intangible capital and innovation), and productivity in the processes of deindustrialization, as analyzed through the impact on per capita GDP. Specifically, it examines the case of the transformation of heavy industry, following the policies implemented in the 1990s, in the European Backbone. This heavily industrialized megalopolis, known as the "Blue Banana," where industry is highly integrated with the territory (Gil, 201912), and where the highest levels of per capita income in the European Union are achieved. As a result of this work, an econometric model is proposed that highlights the relevance of technology and its connection to productivity and growth in the field of industrial manufacturing activities.
Keywords: productivity
economic growth
technology
growth model
EUKLEMS
heavy industry
industrial policies
deindustrialization
Document type: info:eu-repo/semantics/bachelorThesis
Issue Date: 9-Jan-2024
Publication license: http://creativecommons.org/licenses/by-nc-nd/3.0/es/  
Appears in Collections:Trabajos finales de carrera, trabajos de investigación, etc.

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