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on Economic Geography |
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Issue of 2023‒07‒17
eight papers chosen by Andreas Koch Institut für Angewandte Wirtschaftsforschung |
| By: | Bachtrögler-Unger, Julia; Balland, Pierre-Alexandre; Boschma, Ron; Schwab, Thomas |
| Abstract: | Technological capabilities vary substantially across European regions. Combining these diverse sets of capabilities is crucial to develop the technologies necessary to master the green and digital transition. However, collaboration between regions is sparse today. To increase inter-regional cooperation, linkages that spur the development of green and digital technologies must be identified. In this study, we provide an overview of inter-regional collaborations already in place and map new opportunities for these between regions. A special emphasis is placed on potential collaborations between economically leading and lagging regions. Our results provide new impetus for policy designs that strengthen regional innovation capabilities and cohesion across Europe’s regions. |
| Keywords: | Regional diversification; Relatedness; Technological capabilities; European Union; Europe; Cohesion |
| JEL: | B52 H54 O33 R11 |
| Date: | 2023–04–04 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:117485&r=geo |
| By: | Maucorps, Ambre; Römisch, Roman; Schwab, Thomas; Vujanovic, Nina |
| Abstract: | Closing the prosperity gap between regions has always been a key political aspiration of the European Union – and cohesion policy is the primary means to achieve that goal. Europe is currently undergoing a digital and green transition that is drastically changing the way its economy works. How well prepared are regions to capitalise on the twin transition? And what impact will it have on regional cohesion in Europe? Our study finds that greening and digitalising the economy will likely widen the gap between rich and poor regions in Europe. |
| Keywords: | Europe; European Union; Cohesion; Regional Development |
| JEL: | H54 O18 R11 |
| Date: | 2022–10–12 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:117489&r=geo |
| By: | Neumann, Uwe |
| Abstract: | The study explores to what extent adaptation to digital change has affected regional employment growth and regional disparities in Germany over the past decade. Using data from administrative sources the analysis finds no evidence for a net decline in employment in connection with technological progress during this period. On the contrary, labour market regions where many employees perform occupational tasks susceptible to automation have fared comparatively well so far. After all, these regions often comprise strong manufacturing industries, e.g. in rural southern Germany. In regions dominated by less prosperous industries, however, implementation of job creation potentials may turn out to be a much greater challenge. |
| Keywords: | Digital change, productivity growth, occupational tasks, regional convergence |
| JEL: | E24 J21 J23 J24 R11 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:rwirep:1004&r=geo |
| By: | Daniel Borbely (University of Dundee); Ross Mckenzie (Department of Economics, University of Strathclyde) |
| Abstract: | We investigate the persistent effects of forced migration on sending economies using the postWW2 expulsion of German minorities from Hungary as a natural experiment. We combine historical and contemporary data sources to show that, while towns heavily affected by the expulsions were quite similar to other areas in terms of economic activity and labour market composition before the war, the forced migrations led to lasting reductions in economic activity, and an increasing reliance on agricultural labour. We further show long-term negative correlations between forced migration and local trust levels, suggesting that the expulsion of Germans also affected the local social fabric. Our analysis reveals that forced migration can cause lasting regional inequalities in sending economies. |
| Keywords: | forced migration, economic development, minorities, trust, persistence, regional inequality |
| JEL: | N34 N94 R11 O12 O15 |
| Date: | 2021–11 |
| URL: | http://d.repec.org/n?u=RePEc:str:wpaper:2107&r=geo |
| By: | ARVANITOPOULOS Theodoros; LAZAROU Nicholas (European Commission - JRC) |
| Abstract: | In this study, we employ the pairwise stochastic convergence approach to identify the pairs of NUTS2 regions for all 28 EU Member States that exhibit co-movement in their growth dynamics, over the period 1980-2018. We then use the observed convergence trajectories to assess the role of first nature geography and second nature geography, in causing economic growth convergence patterns. We find that western and northern parts of Europe have higher pairwise convergence (and lower intra-country convergence) rates than regions in East and Southeast Europe. We find strong evidence that first and second nature geography drive cluster-like convergence dynamics. Regions with common locational characteristics (metropolitan, coastal, islands, and mountainous) tend to converge to each other, while they diverge from dissimilar regions. Regardless of national borders, contiguity and accessibility are significant drivers of convergence. Congruence in sectoral specialisation results in divergence, that could be driven by competing economic interests within the common market. The opposite holds for dissimilarities in specialisation, which could be explained by complementarity in the production process. Overall, we find strong evidence for club convergence at the top of the EU. Bottom regions with low market dynamism and poor economic development, do not converge to each other. |
| Keywords: | Stochastic convergence, economic geography, pairwise approach, EU Member States, NUTS2 regions, EU Cohesion Fund |
| Date: | 2023–06 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:termod:202306&r=geo |
| By: | Mohammad Reza Farzanegan; Sven Fischer |
| Abstract: | This study provides new causal evidence for the impact of a large-scale natural disaster on local economic activity in Iran using nighttime light intensity. We apply the synthetic control method (SCM) and nighttime light (NTL) data from 1992 to 2020 for 31 provinces and 429 counties to study the impact of the 2003 Bam earthquake in the Iranian Kerman Province. According to the results and statistical inference tests for the SCM, Bam County and four neighboring counties experienced a statistically significant boost in economic activity in the years following the earthquake. This increase in local economic activity can be explained by the combination of several factors, such as an unprecedented inflow of national and international disaster relief during the reformist government of President Khatami, the political trust and mobilization of civil society in this period, the cultural importance of Bam, the severity of the earthquake, and the media attention. Additionally, economic activity in Bam County returns to its pre-disaster development path after seven years. |
| Keywords: | natural disaster, natural hazard, synthetic control, earthquake, economic development, nighttime light, Iran, Bam |
| JEL: | E01 H84 O11 O44 O53 Q51 Q54 R11 R12 |
| Date: | 2023 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_10502&r=geo |
| By: | Adrien Bilal; Esteban Rossi-Hansberg |
| Abstract: | We evaluate how anticipation and adaptation shape the aggregate and local costs of climate change. We develop a dynamic spatial model of the U.S. economy and its 3, 143 counties that features costly forward-looking migration and capital investment decisions. Recent methodological advances that leverage the `Master Equation' representation of the economy make the model tractable. We estimate the county-level impact of severe storms and heat waves over the 20th century on local income, population, and investment. The estimated impact of storms matches that of capital depreciation shocks in the model, while heat waves resemble combined amenity and productivity shocks. We then estimate migration and investment elasticities, as well as the structural damage functions, by matching these reduced-form results in our framework. Our findings show, first, that the impact of climate on capital depreciation magnifies the U.S. aggregate welfare costs of climate change twofold to nearly 5in 2023 under a business-as-usual warming scenario. Second, anticipation of future climate damages amplifies climate-induced worker and investment mobility, as workers and capitalists foresee the slow build-up of climate change. Third, migration reduces substantially the spatial variance in the welfare impact of climate change. Although both anticipation and migration are important for local impacts, their effect on aggregate U.S. losses from climate change is small. |
| JEL: | C6 E3 Q54 R11 |
| Date: | 2023–06 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:31323&r=geo |
| By: | Elton Eduardo Freitas (UFS); João Prates Romero (Cedeplar/UFMG); Gustavo Britto (Cedeplar/UFMG); Alexandre de Queiroz Stein (Cedeplar/UFMG); Ramon Torres (Cedeplar/UFMG) |
| Abstract: | The article presents methodological details regarding the calculation of regional indicators of economic complexity, which have been introduced in the new version of the DataViva platform launched in 2023. This updated platform includes three new indicators, derived from the original methodology of economic complexity, which was initially formulated based on export data. However, in this new version, the methodology has been adapted to utilize employment and occupation data from RAIS, addressing the issues associated with regional-level export data. This adaptation also allows for a flexible definition of regions by aggregating municipal data. The newly introduced indicators are as follows: (i) regional economic complexity indicator (ICE-R); (ii) activity complexity indicator (ICA-R); and (iii) activity density indicator (D), which can be used to calculate the productive coherence indicator (CP) of the regions. Additionally, the article describes the methodology employed for constructing the Activity Space. |
| Keywords: | Economic complexity. Regional indicators. Activity space. DataViva |
| Date: | 2023–06 |
| URL: | http://d.repec.org/n?u=RePEc:cdp:texdis:td657&r=geo |