Modeling regional labor market dynamics in space and time

This paper extends the seminal Blanchard and Katz (1992) regional labor market model to include interaction effects using a dynamic spatial panel data approach. Three key contributions of this extended model are: (i) the unrealistic assumption that regions are independent of one another no longer has to be made, (ii) the magnitude and significance of so-called spillover effects can be empirically assessed, and (iii) both the temporal and spatial propagation of labor demand shocks can be investigated. Using annual data from 1986-2010 for 112 regions across 8 EU countries, both the non-spatial and spatial models are estimated. It is found that the majority of the spillover effects are highly significant. Consistent with economic theory, the impact of a region-specific demand shock is largest in the region where the shock instigates. The shock also propagates to other regions, especially impacting the first and second-order neighbors

Regional labour force participation across the European Union:a time-space recursive modelling approach with endogenous regressors

Regional labour force participation across the European Union: a time-space recursive modelling approach with endogenous regressors. Spatial Economic Analysis. Although there is an abundant regional labour market literature taking a spatial perspective, only a few studies have explored extending the analysis of labour force participation with spatial effects. This paper revisits this important issue, proposing a time-space recursive modelling approach that builds on and appraises Fogli and Veldkamp's methodology from 2011 and finding for the United States that participation rates vary with past values in nearby regions. Major shortcomings in their study are corrected for, including stationarity and the control for endogenous regressors other than the time and space-time-lagged dependent variable using system generalized method of moments (GMM). The paper also highlights interaction effects among explanatory variables for the first time in this context. Using a panel of 108 regions across the European Union over 1986-2010, the results for total, male and female participation rates throw a new light on the socio-economic relevance of different determinants. Importantly, characteristics in neighbouring regions play a significant role, and neglecting endogeneity is found to have serious consequences, underlining increased attention on the specification and estimation of spatial econometric models with endogenous regressors

Modeling regional labor market dynamics in space and time

This paper extends the seminal Blanchard and Katz (1992) regional labor market model to include interaction effects using a dynamic spatial panel data approach. Three key contributions of this extended model are: (i) the unrealistic assumption that regions are independent of one another no longer has to be made, (ii) the magnitude and significance of so-called spillover effects can be empirically assessed, and (iii) both the temporal and spatial propagation of labor demand shocks can be investigated. Using annual data from 1986-2010 for 112 regions across 8 EU countries, both the non-spatial and spatial models are estimated. It is found that the majority of the spillover effects are highly significant. Consistent with economic theory, the impact of a region-specific demand shock is largest in the region where the shock instigates. The shock also propagates to other regions, especially impacting the first and second-order neighbors

Technology Diffusion and Climate Policy: A Network Approach and its Application to Wind Energy

The authors would like to thank for their comments and suggestions the editor, two anonymous reviewers, Michael Grubb, Jochen Hinkel, Diana Mangalagiu, Katrin Millock, and participants of Advances in the Modelling of Innovation and Finance Workshop, the 6th FAERE Green Innovation Workshop, the European Conference on Climate Adaptation 2017. The usual disclaimer applies. Both authors also acknowledge the support of H2020 project grant GREEN-WIN 642018.International audienceThe role of technology transfer in the mitigation of climate change has been strongly emphasized in the recent policy debate. This paper offers a network-based perspective on the issue. First, we propose a methodology to infer from technology adoption data the network of diffusion and apply it to a detailed dataset on wind energy technologies installed globally since the 1980s. We then perform a statistical analysis of the network. It highlights a relatively inefficient organization, characterized in particular by the weakness of South-South links, which leads to relatively long lags in the diffusion process. Against this background, we characterize optimal transfer/seeding strategies for an agent that aims to introduce a new technology in a developing country in view of further diffusion. Our results suggest in particular that CDM projects have been too concentrated in large emerging economies and that developed countries should put a stronger weight on the positive externalities in terms of technology transfer of cooperating with less prominent developing countries

A network-based approach to technology transfers in the context of climate policy

URL des Documents de travail : http://ces.univ-paris1.fr/cesdp/cesdp2017.htmlDocuments de travail du Centre d'Economie de la Sorbonne - 2017.09 - ISSN : 1955-611XIn light of the urgency of climate change, there is a growing literature on the role of technology transfers and how policy can foster diffusion of climate-mitigation technologies. An important challenge is that the diffusion network is generally unknown. To address this key issue, we propose a systemic method building on the network inference literature. We then apply this approach using data on global diffusion patterns of wind energy technologies since the 1980s. Results show that the network's evolution has been remarkable, consistent with the colossal growth and technological progress in wind power over the past decades and the leading role of European firms and other advanced economies in its development. In the context of climate policy and given the multipolar nature and structural inefficiencies in the network, we also appraise strategies to maximize diffusion of new technologies within developing regions and the potential to build bridges through new modes of cooperation.Compte tenu de l'urgence du changement climatique, il existe une littérature de plus en plus importante sur le rôle des transferts de technologie et sur la façon dont les politiques peuvent favoriser la diffusion des technologies d'atténuation du climat. Un défi important est que le réseau de diffusion est généralement inconnu. Pour résoudre ce problème clé, nous proposons une méthode systémique s'appuyant sur la littérature d'inférence de réseau. Nous appliquons ensuite cette approche en utilisant des données sur les modèles de diffusion globale des technologies de l'énergie éolienne depuis les années 1980. Les résultats montrent que l'évolution du réseau a été remarquable, en cohérence avec la croissance colossale et les progrès technologiques dans l'énergie éolienne au cours des dernières décennies et le rôle de premier plan des entreprises européennes et d'autres économies avancées dans son développement. Dans le contexte de la politique climatique et compte tenu de la nature multipolaire et des inefficiences structurelles du réseau, nous évaluons également les stratégies visant à maximiser la diffusion des nouvelles technologies dans les régions en développement et la possibilité de construire des ponts grâce à de nouveaux modes de coopération

THE SLX MODEL

We provide a comprehensive overview of the strengths and weaknesses of different spatial econometric model specifications in terms of spillover effects. Based on this overview, we advocate taking the SLX model as point of departure in case a well-founded theory indicating which model is most appropriate is lacking. In contrast to other spatial econometric models, the SLX model also allows for the spatial weights matrix W to be parameterized and the application of standard econometric techniques to test for endogenous explanatory variables. This starkly contrasts commonly used spatial econometric specification strategies and is a complement to the critique of spatial econometrics raised in a special theme issue of the Journal of Regional Science (Volume 52, Issue 2). To illustrate the pitfalls of the standard spatial econometrics approach and the benefits of our proposed alternative approach in an empirical setting, the Baltagi and Li (2004) cigarette demand model is estimated

A regional unemployment model simultaneously accounting for serial dynamics, spatial dependence and common factors

Regional unemployment rates tend to be strongly correlated over time, parallel the national unemployment rate, and be correlated across space. We address these key stylized facts by linking different strands of literature into a unified methodology to investigate regional unemployment disparities. This methodology simultaneously accounts for serial dynamics, spatial dependence and common factors, also known as weak and strong cross-sectional dependence. We apply this approach using provincial level data for the Netherlands. The substantial and persistent division between high and low unemployment clusters makes it an interesting case, and data availability since the early 1970s enables a comparison between prior periods of downturn and recovery to the recent economic crisis. It is found that approaches that do not simultaneously account for serial dynamics, spatial dependence and common factors, or that ignore one of these issues, may lead to biased inference

Voting and the rise of populism : Spatial perspectives and applications across Europe

Populism has expanded over the past decade, especially far-right parties and their respective voter bases. Voting patterns are often unevenly distributed over space, which makes it very relevant to explore, along with other relevant factors, the spatial dimension. This will increase our understanding of the rise of populist parties, and accordingly, policy implications. First, an introduction to the rise of populism is given, especially in the context of Europe, followed by introducing a conceptualization of the spatial dimension of populism. Then, the contributions of the special issue are highlighted. A clear conclusion is that economic development is an important factor in explaining populist voting, but that regional factors such as local public spending on culture, broader welfare and local unemployment, play an equally important role. Instead of more policies, more attention to the context-specific regional needs are urgently required, resulting in a call for place-sensitive policies that take into account regional economic and socio-demographic differences. Finally, ideas on further research directions are proposed.</p

Risk or opportunity? The Belt and Road Initiative and the role of debt in the China-Central Asia-West Asia Economic Corridor

This Research Note provides an empirical contribution to the discussion on the debt implications vis-à-vis the unfolding of the Belt and Road Initiative (BRI). For this purpose, we analyze the impact of external debt and other relevant factors on the economies of the China-Central Asia-West Asia Economic Corridor using panel data over the period 1996–2018. The reasons we focus on this geographic area are threefold: first, these countries form a key part of the BRI with historical connections to the Silk Road; second, it provides a unique combination of economies in transition such as the former Soviet Union countries and larger economies such as Iran and Turkey; and last but not least, this corridor has received relatively less attention in the related literature. Among the main findings is that debt service on external debt has a positive effect on GNI per capita, both with and without China in the empirical analysis. As another key component of this major development strategy, infrastructure is also found to have a positive impact. The results thus foreshadow growing opportunities as the BRI unfolds, albeit with foreseen issues related to debt sustainability, ecological and wellbeing considerations

Accelerating diffusion of climate-friendly technologies: A network perspective

International audienceWe introduce a methodology to estimate the determinants of the formation of technology diffusion networks from the patterns of technology adoption. We apply this methodology to wind energy, which is one of the key technologies in climate change mitigation. Our results emphasize that, in particular, long-term relationships as measured by economic integration are key determinants of technological diffusion. Specific support measures are less relevant, at least to explain the extensive margin of diffusion. Our results also highlight that the scope of technological diffusion is much broader than what is suggested by the consideration of CDM projects alone, which are particularly focused on China and India. Finally, the network of technological diffusion inferred from our approach highlights the central role of European countries in the diffusion process and the absence of large hubs among developing countries