Suchergebnisse

This paper addresses consequences of increased labour migration in Europe due to productivity effects in a core-periphery model. Traditional trade and growth models predict an overall beneficial impact of the accession of the current candidate states to the European Union. However, models incorporating imperfect competition warn that peripheral countries may realise only a small portion of this beneficial impact of the accession. In this chapter we go a step further: On the domestic level the countries accession may have negative effects while on the nationals level the effect will be positive. An empirical indication that benefits of accession may be low is the marginal benefits during the early phases of EU membership for Greece and Ireland and the Neue Länder of Germany. The following main questions are addressed in this chapter. What is the consequence of increased migration within the European Union due to deregulation in the context of the creation of a common market, and what will be the consequence of the extension of the European union with central and eastern European countries?

This is the first study that attempts to assess the regional economic impacts of the European Institute of Innovation and Technology (EIT) investments in a spatially explicit macroeconomic model, which allows us to take into account all key direct, indirect and spatial spillover effects of EIT investments via inter-regional trade and investment linkages and a spatial diffusion of technology via an endogenously determined global knowledge frontier with endogenous growth engines driven by investments in knowledge and human capital. Our simulation results of highly detailed EIT expenditure data suggest that, besides sizable direct effects in those regions that receive the EIT investment support, there are also significant spatial spillover effects to other (non-supported) EU regions. Taking into account all key indirect and spatial spillover effects is a particular strength of the adopted spatial general equilibrium methodology; our results suggest that they are important indeed and need to be taken into account when assessing the impacts of EIT investment policies on regional economies.

The Regional Trade Flows and Input output Data for Europe are constructed at the regional NUTS2 level with sectoral NACE2 detail and developed for spatial macroeconomic modelling and social-economic analysis for answering a wide-range of policy questions, including policies related to investments in innovation, human capital, green infrastructure and Sustainable Development Goals. The Regional Trade Flows and Input output Data for Europe are particularly well suited for structural modelling such as spatial computable general equilibrium models, as all data are fully internally consistent. In the Regional Trade Flows and Input output Data all European regions are connected with each other via inter-regional trade flows, input use and output supply in form of regional trade matrices, input output tables and supply-use tables. This data base is result of a joint collaborative effort over a decade of several research institutes across Europe, including the Netherlands Environmental Assessment Agency (PBL), the European Commission (DG JRC) and the University of Groningen (Ivanova, Kancs and Stelder 2009, Thissen et al. 2014, Thissen et al. 2018, Ivanova, Kancs and Thissen 2019). Among others, the new EU Economic Modelling System (EU-EMS) developed within the EU Framework Programme for Research and Innovation makes use of the Regional Trade Flows and Input output Data for Europe.

This paper introduces the EUREGIO database: the first time-series (annual, 2000-2010) of global IO tables with regional detail for the entire large trading bloc of the European Union. The construction of this database, which allows for regional analysis at the level of so-called NUTS2 regions, is presented in detail for its methodology and applications. The tables merge data from WIOD (the 2013 release) with, regional economic accounts, and interregional trade estimates developed by PBL Netherlands Environmental Assessment Agency, complemented with survey-based regional input-output data for a limited number of countries. All used data are survey data and only non-behavioral assumptions have been made to estimate the EUREGIO dataset. These two general rules of data construction allow empirical analyses focused on impacts of changes in behavior (of economies, firms, policies) without endogenously having this behavior embedded already by construction. The tables are publicly available to the research community, from the Dutch government open data website. In this project, both a regional trade database, and production and consumption data of different actors in different regions, were used. The focus is thus intentionally on the regionalization of both trade and the regional use and supply of products by different economic actors. The paper is organized around the successive steps of the data construction: (1) adjustment of WIOD, (2) regional information, (3) Construction of tables, (4) conclusions on the usefulness of this type of regional IO tables with an overview of current applications of the EUREGIO database.

'In a world which increasingly requires place-based approaches to economic development, Regional Competitiveness and Smart Specialization in Europe offers a new methodology and a framework in order to promote the smart specialization of territories. Rich in examples and evidence, the book is an essential tool for the design of sound development strategies and a must read for policy-makers and development practitioners.' (Andrés Rodríguez-Pose, London School of Economics, UK). -- Regions economically differ from each other - they compete in different products and geographical spaces, exhibit different strengths and weaknesses, and provide different possibilities for growth and development. What fosters growth in one region may hamper it in another. This highly original book presents an accessible methodology for identifying competitors and their particular circumstances in Europe, discusses regional competitiveness from a conceptual perspective and explores both past and future regional development policies in Europe. The authors illustrate that for the concept of regional competition to be valued correctly it should not solely be identified by the structural asset characteristics of cities and regions. They therefore present a unique applied analytic framework that takes into account economically valued network relations between places of (mobile) production factors and traded goods. Underpinned with thorough analysis and theory, the framework uses actual networks of competing and economically valued relations between regions to help develop smart specialization strategies that are central in the place-based policy initiatives of the new European cohesion policy.

Abstract. A variety of models have been applied to assess the economic losses of disasters, of which the most common ones are input–output (IO) and computable general equilibrium (CGE) models. In addition, an increasing number of scholars have developed hybrid approaches: one that combines both or either of them in combination with noneconomic methods. While both IO and CGE models are widely used, they are mainly compared on theoretical grounds. Few studies have compared disaster impacts of different model types in a systematic way and for the same geographical area, using similar input data. Such a comparison is valuable from both a scientific and policy perspective as the magnitude and the spatial distribution of the estimated losses are born likely to vary with the chosen modelling approach (IO, CGE, or hybrid). Hence, regional disaster impact loss estimates resulting from a range of models facilitate better decisions and policy making. Therefore, this study analyses the economic consequences for a specific case study, using three regional disaster impact models: two hybrid IO models and a CGE model. The case study concerns two flood scenarios in the Po River basin in Italy. Modelling results indicate that the difference in estimated total (national) economic losses and the regional distribution of those losses may vary by up to a factor of 7 between the three models, depending on the type of recovery path. Total economic impact, comprising all Italian regions, is negative in all models though.