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on Economic Geography |
| By: | Rodríguez-Pose, Andrés; Dijkstra, Lewis; Poelman, Hugo |
| Abstract: | While in recent times many regions have flourished, many others are stuck—or are at risk of becoming stuck—in a development trap. Such regions experience decline in economic growth, employment, and productivity relative to their neighbors and to their own past trajectories. Prolonged periods in development traps are leading to political dissatisfaction and unrest. Such discontent is often translated into support for antisystem parties at the ballot box. In this article we study the link between the risk, intensity, and duration of regional development traps and the rise of discontent in the European Union (EU)—proxied by the support for Eurosceptic parties in national elections between 2013 and 2022—using an econometric analysis at a regional level. The results highlight the strong connection between being stuck in a development trap, often in middle- or high-income regions, and support for Eurosceptic parties. They also suggest that the longer the period of stagnation, the stronger the support for parties opposed to European integration. This relationship remains robust whether considering only the most extreme Eurosceptic parties or including parties with more moderate levels of Euroscepticism. |
| Keywords: | discontent; euroscepticism; development trap; economic growth; employment; productivity; regions; EU; Taylor & Francis deal |
| JEL: | D72 R58 R11 |
| Date: | 2024–04–17 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:122411&r=geo |
| By: | Andres Gomez-Lievano; Michail Fragkias |
| Abstract: | There are many benefits and costs that come from people and firms clustering together in space. Agglomeration economies, in particular, are the manifestation of centripetal forces that make larger cities disproportionately more wealthy than smaller cities, pulling together individuals and firms in close physical proximity. Measuring agglomeration economies, however, is not easy, and the identification of its causes is still debated. Such association of productivity with size can arise from interactions that are facilitated by cities ("positive externalities"), but also from more productive individuals moving in and sorting into large cities ("self-sorting"). Under certain circumstances, even pure randomness can generate increasing returns to scale. In this chapter, we discuss some of the empirical observations, models, measurement challenges, and open question associated with the phenomenon of agglomeration economies. Furthermore, we discuss the implications of urban complexity theory, and in particular urban scaling, for the literature in agglomeration economies. |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2404.13178&r=geo |
| By: | Andres Rodriguez-Pose; Zhuoying You; ; |
| Abstract: | Artificial intelligence (AI) and robotics are revolutionising production, yet their potential to stimulate innovation and change innovation patterns remains underexplored. This paper examines whether AI and robotics can spearhead technological innovation, with a particular focus on their capacity to deliver where other policies have mostly failed: less developed cities and regions. We resort to OLS and IV-2SLS methods to probe the direct and moderating influences of AI and robotics on technological innovation across 270 Chinese cities. We further employ quantile regression analysis to assess their impacts on innovation in more and less innovative cities. The findings reveal that AI and robotics significantly promote technological innovation, with a pronounced impact in cities at or below the technological frontier. Additionally, the use of AI and robotics improves the returns of investment in science and technology (S&T) on technological innovation. AI and robotics moderating effects are often more pronounced in less innovative cities, meaning that AI and robotics are not just powerful instruments for the promotion of innovation but also effective mechanisms to reduce the yawning gap in regional innovation between Chinese innovation hubs and the rest of the country. |
| Keywords: | AI, robotics, China, technological innovation, territorial inequality |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:2412&r=geo |
| By: | Stephen J. Redding; Daniel M. Sturm |
| Abstract: | We use the German bombing of London during the Second World War as an exogenous source of variation to provide evidence on neighborhood effects. We construct a newly-digitized dataset at the level of individual buildings on wartime destruction, property values, and socioeconomic composition in London before and after the Second World War. We develop a quantitative spatial model, in which heterogeneous groups of individuals endogenously sort across locations in response to differences in natural advantages, wartime destruction and neighborhood effects. We find substantial and highly localized neighborhood effects, which magnify the direct impact of wartime destruction, and make a substantial contribution to observed patterns of spatial sorting across locations. |
| JEL: | F16 N9 R23 |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:32333&r=geo |
| By: | Jan David Bakker; Alvaro Garcia Marin; Andrei V. Potlogea; Nico Voigtländer; Yang Yang |
| Abstract: | Does international trade affect the growth of cities, and vice versa? Assembling disaggregate data for four countries, we document a novel stylized fact: Export activity is disproportionately concentrated in larger cities – even more so than overall economic activity. We rationalize this fact by marrying a standard quantitative spatial economics model with a heterogeneous firm model that features selection into the domestic and the export market. Our model delivers novel predictions for the bi-directional interactions between trade and urban dynamics: On the one hand, trade liberalization shifts employment towards larger cities, and on the other hand, liberalizing land use raises exports. We structurally estimate the model using data for the universe of Chinese manufacturing and French firms. We find that trade policies have quantitatively meaningful impacts on urban outcomes and vice versa, and that the aggregate effects of trade and urban policies differ from more standard models that do not account for the interaction between trade and cities. In addition, a distinguishing prediction of our model – which we confirm in the data – is that local trade elasticities vary systematically with city size, so that a country's aggregate trade elasticity depends on the spatial distribution of production within its borders. |
| JEL: | F1 R1 |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:32377&r=geo |
| By: | Jos\'e M. Gaspar |
| Abstract: | We study the impact of economic integration on spatial development in a model where all consumers are inter-regionally mobile and have heterogeneous preferences regarding their residential location choices. This heterogeneity is the unique dispersion force in the model. We show that, under reasonable values for the elasticity of substitution among varieties of consumption goods, a higher trade integration always promotes more symmetric patterns, irrespective of the functional form of the dispersion force. We also show that an increase in the degree of heterogeneity in preferences for location leads to less spatial inequality. |
| Date: | 2024–04 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2404.09796&r=geo |