|
on Economic Geography |
|
Issue of 2022‒05‒16
seven papers chosen by Andreas Koch Institut für Angewandte Wirtschaftsforschung |
| By: | Ludwig von Auer; Mark Trede |
| Abstract: | This study introduces the urbanicity index of employment. This density-based measure is derived from spatial point pattern analysis and, therefore, makes use of the complete spatial information contained in geo-coded sectoral employment data. The index accounts for both the scale and the concentration aspect of urbanization. Changes in concentration can be decomposed into intersectoral mobility of employment and spatial mobility of sectors and further into the contributions of each sector of the economy. The index is applied to a large industrialized country and reveals that strong urbanization trends have occurred that simpler measures would overlook. |
| Keywords: | agglomeration, concentration, index, measurement, migration |
| JEL: | R12 J21 C43 |
| Date: | 2022–04 |
| URL: | http://d.repec.org/n?u=RePEc:cqe:wpaper:9822&r= |
| By: | Jung-In Yeon; Sojung Hwang; Bogang Jun |
| Abstract: | We examine the spillover effect of neighboring ports on regional industrial diversification and their economic resilience using the export data of South Korea from 2006 to 2020. First, we build two distinct product spaces of ports and port regions, and provide direct estimates of the role of neighboring ports as spillover channels spatially linked. This is in contrast to the previous literature that mainly regarded ports as transport infrastructure per se. Second, we confirm that the knowledge spillover effect from neighboring ports had a non-negligible role in sustaining regional economies during the recovery after the economic crisis but its power has weakened recently due to a loosened global value chain. |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2204.00189&r= |
| By: | ADACHI Yusuke; OGAWA Hikaru; TSUBUKU Masafumi |
| Abstract: | Is there a difference in resilience to crises between urban and rural areas? By using microdata of establishments in the manufacturing industry in Japan from 2007 to 2014, this study estimated how the productivity distribution of establishments in a region changed during two crises caused by different factors: the Global Financial Crisis of 2008 and the Great East Japan Earthquake in 2011. The results indicate the followings. (i) Although establishments in urban areas experienced a larger leftward shift in the productivity distribution than those in rural areas in both crises, their capacity to recover from crises was shown to be greater. (ii) There are several rural areas in which the productivity distribution did not change significantly as a result of crises, where productivity improvement had already stagnated. (iii) In a few rural areas, the distribution of productivity moved to the left during the crises and did not recover afterward, shifting to a different growth path compared to before the crises. |
| Date: | 2022–04 |
| URL: | http://d.repec.org/n?u=RePEc:eti:dpaper:22041&r= |
| By: | Marta Cristina Nunes Simões (University of Coimbra, Centre for Business and Economics Research, CeBER and Faculty of Economics); João Alberto Sousa Andrade (University of Coimbra, Centre for Business and Economics Research, CeBER and Faculty of Economics); Maria Adelaide Pedrosa Silva Duarte (University of Coimbra, Centre for Business and Economics Research, CeBER and Faculty of Economics) |
| Abstract: | This paper examines the influence of human capital on labour market resilience in the seven Portuguese NUTS-2 over the period 1995-2018. We define resilience as the ability of regional employment to recover from a shock to output over the business cycle. We use the Local Projection (LP) methodology applied to a SVAR model with three variables - employment, human capital, real GDP - and the output gap as the switching variable for the identification of recession and expansion regimes. We explore SVAR specifications that condition the response of the labour market to two scenarios: (a) the shock to GDP occurs during recessions; and (b) the shock to GDP occurs during expansions. The comparison of the employment responses to GDP shocks between the two regimes is informative about the degree of resilience of the labour market. We find evidence of: (i) distinct effects in terms of the sign and amplitude of GDP shocks on regional employment according to the level of educational attainment of the employees; (ii) labour market resilience and jobless recoveries in several regions; and (iii) different regional reactions of human capital to GDP shocks depending on the regime. |
| Keywords: | Employment resilience, GDP shocks, local projections, structural VARs, NUTS2, Portugal |
| JEL: | I25 J21 J24 R10 R15 |
| Date: | 2022–01 |
| URL: | http://d.repec.org/n?u=RePEc:gmf:papers:2022-01&r= |
| By: | Rudiger Ahrend; Manuel Bétin; Maria Paula Caldas; Boris Cournède; Marcos Diaz Ramirez; Pierre-Alain Pionnier; Daniel Sanchez-Serra; Paolo Veneri; Volker Ziemann |
| Abstract: | The paper introduces a novel, granular house-price dataset sourced from a network of public and private data providers. It offers the first results of investigations into changes in the urban geography of housing markets following the COVID-19 pandemic. The rapid rise of working from home practices is likely to incentivise many people to seek more space and accept living further away from city centres as commuting requirements are reduced. The paper's results indicate that housing demand might have indeed shifted away from the centres to the peripheries of many large urban areas. These early results also show that such a shift has been neither universal nor uniform. It is typically stronger in cities where pre-COVID-19 house price disparities were larger and where moving to the periphery provides significantly better access to green space while still allowing easy access to high-speed internet and/or where COVID-19 restrictions were more stringent. The paper concludes by discussing implications for policy, including the benefits of flexible settings that allow supply to adjust smoothly to new demand patterns and outlining avenues for future work planned to improve and capitalise on the new dataset. |
| Keywords: | COVID-19, digitisation, geospatial economics, housing, teleworking, working from home |
| JEL: | R31 O18 |
| Date: | 2022–05–03 |
| URL: | http://d.repec.org/n?u=RePEc:oec:ecoaaa:1713-en&r= |
| By: | Magali Jaoul-Grammare (BETA - Bureau d'Économie Théorique et Appliquée - UNISTRA - Université de Strasbourg - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Karine Pellier (BETA - Bureau d'Économie Théorique et Appliquée - UNISTRA - Université de Strasbourg - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, LAMETA - Laboratoire Montpelliérain d'Économie Théorique et Appliquée - UM1 - Université Montpellier 1 - UPVM - Université Paul-Valéry - Montpellier 3 - INRA - Institut National de la Recherche Agronomique - Montpellier SupAgro - Centre international d'études supérieures en sciences agronomiques - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique - Montpellier SupAgro - Institut national d’études supérieures agronomiques de Montpellier) |
| Abstract: | The aim of this article is to examine the distribution of university training supply in France. Has there been regional university specialisation or, on the contrary, has there been a diversification of regions? After studying the evolution of regional differences for each university discipline between 1980 and 2000, we attempt to identify the specific features of each region in the supply of training. The results obtained show that there is a certain attenuation of regional differences, mainly for economically profitable disciplines. On the other hand, if we do not really identify regional specialisations, we highlight a type of specialisation that could be called "historical specialisation". |
| Abstract: | L'objet de cet article est de s'interroger sur la répartition de l'offre de formation universitaire en France. Y-a-t-il eu une spécialisation régionale universitaire ou au contraire a-t-on observé une diversification des régions ? Après avoir étudié l'évolution des écarts régionaux pour chaque discipline universitaire entre 1980 et 2000 nous tentons d'identifier les spécificités de chaque région dans l'offre de formation. Les résultats obtenus montrent qu'il existe une certaine atténuation des écarts régionaux, essentiellement pour les disciplines rentables économiquement. En revanche si l'on n'identifie pas réellement de spécialisations régionales, nous mettons en évidence un type de spécialisation que l'on pourrait qualifier de « spécialisation historique ». |
| Keywords: | Regional disparities,Higher education,Disparités régionales,Convergence,Enseignement supérieur |
| Date: | 2020–12–31 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:halshs-03345631&r= |
| By: | Claude DIEBOLT |
| Abstract: | L’objet de cet article est d’étudier les débordements géographiques de connaissance sur l’activité innovante et le processus de convergence des régions européennes de 1981 à 2001. Notre recherche révèle la présence d’effets spatiaux que nous intégrons successivement dans notre analyse de la ? convergence. L’estimation d’un modèle avec autocorrélation spatiale des erreurs montre que les effets de débordement géographique contribuent favorablement au processus de rattrapage des régions les moins performantes. Nous modélisons l’hétérogénéité spatiale par une spécification à deux régimes spatiaux, de type « centre-périphérie ». L’ensemble de ces résultats montrent que le processus de convergence globale masque des disparités au sein des régions européennes où, sur la période considérée, seules convergent les régions appartenant au centre de l’Europe. |
| Keywords: | Brevets, cliométrie, convergence, effets spatiaux, persistance, régions européennes. |
| JEL: | C21 N90 N94 O33 R11 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:ulp:sbbeta:2022-13&r= |