This book provides an overview of three generations of spatial econometric models: models based on cross-sectional data, static models based on spatial panels and dynamic spatial panel data models. The book not only presents different model specifications and their corresponding estimators, but also critically discusses the purposes for which these models can be used and how their results should be interpreted.
This paper examines the role of sectoral spillovers in propagating sectoral shocks in the broader economy, both in the past and during the COVID-19 pandemic. In particular, we study how shocks that occur within a sector itself and spillovers from shocks to other sectors affect sectoral activity, for a large sample of countries from 1995 to 2014. We find that both supply and demand shocks—measured as changes in, respectively, productivity and government purchases at the sector level—have large spillover effects on sector-level gross value added and on a sector’s share of the economy. We then use these historical estimates, together with the network structure of global production, to quantify the spillovers from the economic shock associated with the pandemic. We find spillover effects to be sizeable, making up a significant fraction of the overall decline in activity in 2020.Our results have implications for the design of policies with a sectoral dimension.
There has been much discussion about the importance of networks for regional economic development and knowledge dissemination. However, the inflationary use of the notion networks is often based on rather metaphorical, at worst fuzzy meanings. This book explores ways for more rigorous research on knowledge networks, critically discussing quantitative social network analysis. A theoretical framework for meaningful interpretations in quantitative network research is developed. Afterwards, the monograph links social network analysis to research on localised knowledge spillovers. Here the role of communities and networks of knowledge workers is investigated. The book illustrates how social network analysis can provide fruitful perspectives for further research on knowledge flows. (Back cover)
This edited book focuses on recent developments in Dynamic Network Modeling, including aspects of route guidance and traffic control as they relate to transportation systems and other complex infrastructure networks. Dynamic Network Modeling is generally understood to be the mathematical modeling of time-varying vehicular flows on networks in a fashion that is consistent with established traffic flow theory and travel demand theory. Dynamic Network Modeling as a field has grown over the last thirty years, with contributions from various scholars all over the field. The basic problem which many scholars in this area have focused on is related to the analysis and prediction of traffic flows satisfying notions of equilibrium when flows are changing over time. In addition, recent research has also focused on integrating dynamic equilibrium with traffic control and other mechanism designs such as congestion pricing and network design. Recently, advances in sensor deployment, availability of GPS-enabled vehicular data and social media data have rapidly contributed to better understanding and estimating the traffic network states and have contributed to new research problems which advance previous models in dynamic modeling. A recent National Science Foundation workshop on “Dynamic Route Guidance and Traffic Control” was organized in June 2010 at Rutgers University by Prof. Kaan Ozbay, Prof. Satish Ukkusuri , Prof. Hani Nassif, and Professor Pushkin Kachroo. This workshop brought together experts in this area from universities, industry and federal/state agencies to present recent findings in this area. Various topics were presented at the workshop including dynamic traffic assignment, traffic flow modeling, network control, complex systems, mobile sensor deployment, intelligent traffic systems and data collection issues. This book is motivated by the research presented at this workshop and the discussions that followed.
After decades of liberalization of the telecommunications industry around the world and technological convergence that allows for increasing competition, sector-specific regulation of telecommunications has been on the decline. As a result, the telecommunications industry stands in the middle of a debate that calls for either a total deregulation of access to broadband infrastructures or a separation of infrastructure from service delivery. This book proposes new approaches to dealing with the current and future issues of regulation of telecommunication markets on both a regional and a global scale. This volume represents a valuable compendium of ideas regarding global trends in the telecommunications industry that focus on market and regulatory issues and company strategies. With an international cast of contributors, Regulation and the Evolution of the Global Telecommunications Industry also provides insight into topics including: mobile Internet development, structural function and separation, global experiences with next generation networks, technology convergence and the role of regulation, and the regulatory impact on the balance between static and dynamic efficiencies. The empirical evidence and experiences presented here illustrate the diversity of thoughts and research that characterize this important area of academic and business research. Thus, it will be a critical reference for scholars and students of regulatory economics, policy and finance and researchers and administrators of the telecom industry.
Giving stress tests a macroprudential perspective requires (i) incorporating general equilibrium dimensions, so that the outcome of the test depends not only on the size of the shock and the buffers of individual institutions but also on their behavioral responses and their interactions with each other and with other economic agents; and (ii) focusing on the resilience of the system as a whole. Progress has been made toward the first goal: several models are now available that attempt to integrate solvency, liquidity, and other sources of risk and to capture some behavioral responses and feedback effects. But building models that measure correctly systemic risk and the contribution of individual institutions to it while, at the same time, relating the results to the established regulatory framework has proved more difficult. Looking forward, making macroprudential stress tests more effective would entail using a variety of analytical approaches and scenarios, integrating non-bank financial entities, and exploring the use of agent-based models. As well, macroprudential stress tests should not be used in isolation but be treated as complements to other tools and—crucially—be combined with microprudential perspectives.
Determinants of firm and market organization; Analysis of market behavior; Empirical methods and results; International issues and comparision; government intervention in the Marketplace.
The COVID-19 pandemic plunged the EU into its worst-ever recession and risks increasing inequalities, notably between regions. Thanks to a bold and innovative policy response, including a common instrument to finance national recovery plans (Next Generation EU), growth is rebounding, but ambitious reforms will be essential to heal the scars of the pandemic and succeed in the green and digital transitions.
This book tackles the different aspects of the creation and transmission of knowledge in the context of the characteristics of a general purpose technology. Nanotechnology is investigated as showcase example. Particular emphasis is put on the role of the composition of knowledge as well as the corresponding knowledge spillovers on the one hand and on the concrete impact of collaboration and knowledge sharing in innovator networks on the other hand.
