1,721,052 research outputs found
Modelling the evolution of economic structure and climate change: a review
No full textWe discuss how different models assessing climate change integrate aspects of structural change that are crucial to improve understanding of the relation between changes in the environment and in the economy. We identify six related aspects of structural change, which have significant impact on climate change: sectoral composition, industrial organisation, technology, employment, final demand, and institutions. Economic models vary substantially with respect to the aspects of structural change that they include, and how they model them. We review different modelling families and compare these differences: integrated assessment models (IAM), computable general equilibrium (CGE) models, structural change models (SCM), ecological macroeconomics models in the Keynesian tradition (EMK) and evolutionary agent based models (EABM). We find that IAM and CGE address few of the aspects of structural change identified; SCM focus on the sectoral composition; and EKM study final demand and employment structure. But all these models are aggregate and omit the complexity of the interactions between structural and climate change. EABM have explored a larger number of aspects of structural change, modelling their emergence from the interaction of microeconomic actors, but have not yet exploited their potential to study the interactions among interrelated aspects of structural and climate change. © 2018 Elsevier B.V. All rights reserved
Employment imbalances in EU regions: technological dependence or high-tech trade centrality?
Full text linkWe analyse the role of technological dependence and interregional trade centrality in explaining a region’s employment performance. We first identify the core–periphery technological structure of European Union (EU) regions, clustering them based on their high-tech trade relations (trade blocks) and technological and economic indicators (place-based regional groups). We show that EU regions have a fractal structure: blocks at the core and periphery of the high-tech trade network are divided into core and peripheral subgroups, which differ significantly in terms of innovation and employment performance. Next, the econometric analysis shows that buyer centrality is the main component of employment growth (especially in services), but within trade blocks it has to be combined with low technological dependence on more innovative regions (especially in manufacturing). Cohesion policies should pay attention to the fractal structure of regional inequalities, and Smart Specialisation strategies should consider that unrelated diversification towards activities intensive in the use of high-tech inputs may be more conducive to employment growth
Varieties of european national innovation systems
Full text linkThis paper provides a novel, empirically grounded map of National Innovation Systems (NIS) in Europe, based on a unique micro level analysis across several EU countries. By focusing on the Eurostat Community Innovation Survey 2014 (CIS2014) micro-aggregated data, we perform an exploratory factor analysis to provide a micro-level grounding to the multi-faceted components of NIS. We relate the structure, innovation strategies and performance of the firm to relevant institutional characteristics of the NIS in which it is embedded, including the nature of public sector support (e.g. cooperation and procurement) and the characteristics of the public-private links (e.g. with universities, foreign institutions and/or other firms), amongst others. We then redesign the map of the European technology ‘clubs’ by means of a cluster analysis based on our factors/NIS dimensions. Our findings ground the diagnostics of the European NIS, add to the most recent literature on NIS by taking into account the micro–level sources of the European NIS ‘clubs’, and complement the historical picture provided by Cirillo et al. (2016a)
The complex interactions between economic growth and market concentration in a model of structural change
No full textWe study the relation between variety, market concentration, and economic growth, along different phases of economic development which entail a number of changes to the structure of production and consumption in the economy. We focus on three aspects of structural change, which are connected and are correlated to variety, market concentration, and economic growth: (i) product quality; (ii) firms' mark-ups; and (iii) imitation of consumer preferences for price and quality. We model the interactions among several aspects of structural change such as firm size and hierarchical structure, innovation in capital vintages, the emergence of social classes, income distribution, and consumer preferences across and within classes. We find that market concentration has a significant and positive impact on economic growth only in the presence of sufficiently large demand. The strongest effects emerge in the presence of a more skewed firm size distribution and firms producing higher priced and higher quality goods. We find also that this effect is influenced strongly by different aspects of structural change. Changes in the behaviour (or income) of the less wealthy income classes is crucial as is investment in new capital vintages, and the emergence of diverse income classes with heterogeneous consumption preferences. In contrast, we find that supply side product variety, cœteris paribus, has no significant effect on growth
Structural changes and sustainability: a selected review of the empirical evidence
No full textThe paper offers a review of selected topics in the empirical literature on structural change and sustainability. We focus on aspects of structural change that directly affect emissions and energy intensity: changes of the sectoral composition of economies, trade and international fragmentation of production, technological change and innovation, and demand. We identify several empirical facts. First, only a few countries have experienced a decoupling between growth and emissions, due to proportionately faster growth rather than greater energy efficiency. Second, the long-term shift from manufacturing to services has not led, in all cases, to the de-materialisation of economies and a lower environmental burden. Exploitation of energy efficiency increases depends on the ability of the service sectors to incorporate technical changes to reduce energy intensity. Third, global trade and energy and emissions intensity trends support the ‘pollution haven’ hypothesis, which predicts displacement of the environmental burden from developed to emerging countries. The pursuit by developing countries of a long-term strategy of ‘trading jobs for emissions' is likely to exacerbate the asymmetry related to emissions intensities between developed and less developed economies. The review should inform debate on environmental policy within the broader context of innovation and development policies. © 2019 Elsevier B.V. All rights reserved
Towards indicators for 'opening up' science and technology policy
No full textTrabajo presentado a la International Council for Science and Technology Information Annual Conference, celebrada del 20 al 21 de Octubre de 2014 en Tokyo (Japón).Recent years have seen much critical debate over the simplistic use of scientometric tools for formal or informal appraisal of science and technology (S&T) organisations (e.g. in university rankings) or individuals (e.g. the h - index) ( Weingart, 2005 ). As a reaction to these critiques, efforts have been made to improve the robustness of measurements by broadening the range of inputs considered in scientometric evaluations. Examples include the inclusion of books and national or regional journals, or more recently 'altmetrics'. While this 'broadening out' of the range of data used as 'inputs' in scientometric appraisal is, in our view, commendable, we propose in this paper that a second dimension also needs to be considered. This relates to the extent t o which the 'outputs' of appraisal 'open up' contrasting conceptualisations of the phenomena under scrutiny and consequently allow for more considered and rigorous attention to alternative policy options, both by decision makers and within wider policy debate. We use a recent comparative study on the performance and interdisciplinarity of six organisational units (Rafols et al., 2012) to illustrate the difference between increasing the range of inputs ('broadening out') and enhancing the diversity of outputs to policy decision making ('opening out'). In this way, policy appraisal can inform decision making in a more rigorous 'plural and conditional' fashion 'acknowledging the way in which divergent normative assumptions and metrics can yield contrasting understandings of both the phenomena under scru tiny, and of appropriate policy responses (Stirling, 2008).Peer Reviewe
Does exporting cause productivity growth? Evidence from Chilean firms
No full textDoes exporting increase firm productivity, or are increased export sales caused by the firm's ability to increase its productivity? This paper provides new empirical evidence on the causal relation between trade and productivity, adopting a structural vector autoregressive analysis combined with identification algorithms from the machine learning literature. We focus on a well-studied country (Chile) and on already-exporting firms (intensive margin). We identify the contemporaneous and lagged causal structure between firm productivity and export growth using two different machine learning algorithms based on independent components analysis (ICA), which exploit the non-Gaussian distribution of the data to recover the independent structural shocks that drive the observed variables. Our findings show that, for Chilean firms, productivity growth causes export growth in the same year, but that the reverse does not apply. Export growth also has no causal effect on TFP growth in subsequent years. To increase sales in the foreign market, firms should first also increase productivity. The increased presence in the foreign market does not contribute to such productivity growth
Structural Transformations and Cumulative Causation: Towards an Evolutionary Micro-foundation of the Kaldorian Growth Model
No full textChanging Directions: Steering science, technology and innovation towards the Sustainable Development Goals
Full text linkThis report presents the results of the Steering Research and Innovation for Global Goals (STRINGS) project – a major global study into the alignment between science, technology and innovation (STI) and the Sustainable Development Goals (SDGs). It highlights a glaring mismatch between STI and the SDGs; warns that, if this mismatch is not addressed, it will undermine progress on the SDGs; and makes recommendations about how to tackle this imbalance. To help understand and better address the challenges of investing in STI for the SDGs, while embracing the complex relationship between STI and the SDGs, we make use of multiple analytical tools to examine STI-SDG relations for different types of actors, across geographical settings and time horizons. By combining methods from a range of disciplines, we provide complementary mappings, characterizations and understandings of the complex relations between STI and the SDGs. We are then able to build on these mappings and characterizations to illustrate and explain misalignments between STI activities and the SDGs. By combining these analyses, we gained deep insights into the way that particular STI priorities emerge both locally and globally, and how STI can be steered to improve alignment with the SDGs. Our results can help policymakers, research funders, academics, international organizations (INGOs) and aid organizations to make informed decisions about investing in research and innovation that will address the SDGs and ultimately create a positive impact on society.</p
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