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This open access book encompasses a collection of in-depth analyses showcasing the challenges and ways forward for macroeconomic modelling of R&D and innovation policies. Based upon the proceedings of the EC-DG JRC-IEA workshop held in Brussels in 2017, it presents cutting-edge contributions from a number of leading economists in the field. It provides a comprehensive overview of the current academic and policy challenges surrounding R&D as well as of the state-of-the-art modelling techniques. The book brings to the forefront outstanding issues related to the assessment of the macroeconomic impact of R&D policies and its modelling. It speaks to the rising importance of R&D and innovation policy, and the proliferation of macroeconomic models featuring endogenous technological change. The contents of this book will be of interest to both academic and policy audiences working in the fields of R&D and innovation.
The recent financial crisis and the difficulty of using mainstream macroeconomic models to accurately monitor and assess systemic risk have stimulated new analyses of how we measure economic activity and the development of more sophisticated models in which the financial sector plays a greater role. Markus Brunnermeier and Arvind Krishnamurthy have assembled contributions from leading academic researchers, central bankers, and other financial-market experts to explore the possibilities for advancing macroeconomic modeling in order to achieve more accurate economic measurement. Essays in this volume focus on the development of models capable of highlighting the vulnerabilities that leave the economy susceptible to adverse feedback loops and liquidity spirals. While these types of vulnerabilities have often been identified, they have not been consistently measured. In a financial world of increasing complexity and uncertainty, this volume is an invaluable resource for policymakers working to improve current measurement systems and for academics concerned with conceptualizing effective measurement.
The role of the state in modern capitalism has gone beyond fixing market failures. Those regions and countries that have succeeded in achieving “smart” innovation-led growth have benefited from long-term visionary “mission-oriented” policies—from putting a man on the moon to tackling societal challenges such as climate change and the wellbeing of an ageing population. This book collects the experience of different types of mission-oriented public institutions around the world, together with thought-provoking chapters from leading economists. As the global debate on deficits and debt levels continues to roar, the book offers a challenge to the conventional narrative—asking what kinds of visionary fiscal policies we need to help promote "smart” innovation-led, inclusive, and sustainable growth.
This book looks at the distribution of income and wealth and the effects that this has on the macroeconomy, and vice versa. Is a more equal distribution of income beneficial or harmful for macroeconomic growth, and how does the distribution of wealth evolve in a market economy? Taking stock of results and methods developed in the context of the 1990s revival of growth theory, the authors focus on capital accumulation and long-run growth. They show how rigorous, optimization-based technical tools can be applied, beyond the representative-agent framework of analysis, to account for realistic market imperfections and for political-economic interactions. The treatment is thorough, yet accessible to students and nonspecialist economists, and it offers specialist readers a wide-ranging and innovative treatment of an increasingly important research field. The book follows a single analytical thread through a series of different growth models, allowing readers to appreciate their structure and crucial assumptions. This is particularly useful at a time when the literature on income distribution and growth has developed quickly and in several different directions, becoming difficult to overview.
This book is open access under a CC BY 4.0 license. The book examines the methodological challenges in analyzing the effectiveness of development policies. It presents a selection of tools and methodologies that can help tackle the complexities of which policies work best and why, and how they can be implemented effectively given the political and economic framework conditions of a country. The contributions in this book offer a continuation of the ongoing evidence-based debate on the role of agriculture and participatory policy processes in reducing poverty. They develop and apply quantitative political economy approaches by integrating quantitative models of political decision-making into existing economic modeling tools, allowing a more comprehensive growth-poverty analysis. The book addresses not only scholars who use quantitative policy modeling and evaluation techniques in their empirical or theoretical research, but also technical experts, including policy makers and analysts from stakeholder organizations, involved in formulating and implementing policies to reduce poverty and to increase economic and social well-being in African countries.
The Oxford Handbook of Computational Economics and Finance provides a survey of both the foundations of and recent advances in the frontiers of analysis and action. It is both historically and interdisciplinarily rich and also tightly connected to the rise of digital society. It begins with the conventional view of computational economics, including recent algorithmic development in computing rational expectations, volatility, and general equilibrium. It then moves from traditional computing in economics and finance to recent developments in natural computing, including applications of nature-inspired intelligence, genetic programming, swarm intelligence, and fuzzy logic. Also examined are recent developments of network and agent-based computing in economics. How these approaches are applied is examined in chapters on such subjects as trading robots and automated markets. The last part deals with the epistemology of simulation in its trinity form with the integration of simulation, computation, and dynamics. Distinctive is the focus on natural computationalism and the examination of the implications of intelligent machines for the future of computational economics and finance. Not merely individual robots, but whole integrated systems are extending their "immigration" to the world of Homo sapiens, or symbiogenesis.
We build a model of firm-level innovation, productivity growth and reallocation featuring endogenous entry and exit. A new and central economic force is the selection between highand low-type firms, which differ in terms of their innovative capacity. We estimate the parameters of the model using US Census micro data on firm-level output, R&D and patenting. The model provides a good fit to the dynamics of firm entry and exit, output and R&D. Taxing the continued operation of incumbents can lead to sizable gains (of the order of 1.4% improvement in welfare) by encouraging exit of less productive firms and freeing up skilled labor to be used for R&D by high-type incumbents. Subsidies to the R&D of incumbents do not achieve this objective because they encourage the survival and expansion of low-type firms.
Existing literature looks at national innovation systems from the perspective of either "inside the black box" or "outside the black box". This is the first book that analyzes both the inside and outside of the black box using a general equilibrium framework. The book looks at what is outside the black box and provides models of path-dependent endogenous growth; examines the dynamics of the black box from the intersectoral perspective of the economy; and proposes an innovation flow matrix. It also takes into account both business cycles and endogenous innovation in the unified New Keynesian dynamic stochastic general equilibrium (DSGE) model and examines how business cycles and other policy shocks affect endogenous innovation. The unified treatment of the national innovation system from perspectives both inside and outside the black box using rigorous economic models and empirical analyses makes this an enlightening work, shedding new light on innovation economics.
Christine Greenhalgh explains the complex process of innovation & how it sustains the growth of firms, industries & economies, combining microeconomic & macroeconomic analysis.