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on Economic Geography |
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Issue of 2021‒06‒14
thirteen papers chosen by Andreas Koch Institut für Angewandte Wirtschaftsforschung |
| By: | Combes, Pierre-Philippe (GATE, University of Lyon); Gobillon, Laurent (Paris School of Economics); Zylberberg, Yanos (University of Bristol) |
| Abstract: | A recent literature has used a historical perspective to better understand fundamental questions of urban economics. However, a wide range of historical documents of exceptional quality remain underutilised: their use has been hampered by their original format or by the massive amount of information to be recovered. In this paper, we describe how and when the flexibility and predictive power of machine learning can help researchers exploit the potential of these historical documents. We first discuss how important questions of urban economics rely on the analysis of historical data sources and the challenges associated with transcription and harmonisation of such data. We then explain how machine learning approaches may address some of these challenges and we discuss possible applications. |
| Keywords: | machine learning, history, urban economics |
| JEL: | R11 R12 R14 N90 C45 C81 |
| Date: | 2021–05 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp14392&r= |
| By: | Jing Xiao; Ron Boschma; |
| Abstract: | The purpose of this study is to investigate how a regional knowledge base in Information and Communication Technologies (ICTs) influences the emergence of AI technologies in European regions. Replying on patent data and studying the knowledge production of AI technologies in 233 European regions in the period of 1994 to 2017, our study reveals three results. First, ICTs are a major knowledge source of AI technologies and their importance has been increasing over time. Second, a regional knowledge base in ICTs is highly relevant for regions to engage in AI inventing. Third, the effects of regional knowledge base of ICTs are stronger for regions that recently caught up in AI inventing. Our findings suggest that ICTs play a critically enabling role for regions to diversify into AI technologies, especially in catching-up regions. |
| Keywords: | Artificial intelligence (AI), regional diversification, Information and Communications Technologies (ICTs), technological relatedness, General Purpose Technologies (GPTs), Europe |
| JEL: | O33 R11 O31 |
| Date: | 2021–05 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:2117&r= |
| By: | José Pedro Pontes |
| Abstract: | We describe formally the relationship between population density and per capita income along the two growth regimes put forward by KUZNETS (1960), BOSERUP (1965) and TAMURA (2002). We consider a spatial economy where an undifferentiated consumer good is produced by a continuum of competitive agents. Each agent requires one unit of a capital good to produce the final good and the two goods are assumed to be perfect substitutes in production. Under the first growth regime (called “classical” or “Malthusian”), each agent self-produces the capital good by shifting resources that would otherwise produce one unit of the final good. This economy shows marginal decreasing returns of labour. Population growth brings about congestion and the elasticity of output per worker (and income per capita) is negative. A structural change takes place following a sufficient increase in population density and decrease in transport costs. Then, the supply of capital goods is outsourced to a specialized industry, operating in spatial monopolistic competition in line with SALOP (1979). Under this “modern” growth regime, the specialization of the capital goods production is a source of increasing returns in the aggregate economy. The elasticity of per capita income with respect to population density becomes positive just after the structural transition, but this effect may not persist in the long run. If the outsourcing of capital goods is matched by a rising importance in final production of activities which are not land-based, then aggregate increasing returns can be sustained in the long run. Otherwise, the positive sign of elasticity will be transitory and a further increase in population density will revert the economy to a situation where the use of increasing amounts of labour with non-reproducible resources determines mainly a congestion effect. |
| Keywords: | Economic Development, Population Density, Industrialization, Spatial Competition, Technological Change, Economies of Agglomeration. |
| JEL: | O12 O33 R11 |
| Date: | 2021–05 |
| URL: | http://d.repec.org/n?u=RePEc:ise:remwps:wp01782021&r= |
| By: | Ron Boschma; Ernest Miguelez; Rosina Moreno; Diego B. Ocampo-Corrales |
| Abstract: | This paper analyzes if the emergence and occurrence of breakthrough technologies in 277 European regions in the period 1981 to 2010 is related to the existing technological portfolio of regions. The study shows that, by far, most combinations breakthrough inventions make are between related technologies: almost no breakthrough patent makes combinations between unrelated combinations only. We also find that breakthrough inventions primarily combine and cite technological classes that are present in the region. Regressions show that the occurrence of breakthrough patents in a technology in a region is positively affected by the local stock of technologies that is related to such technology, but we do not find such an effect for the local stock of unrelated technologies, in contrast to studies that suggest otherwise. However, the region’s ability to enter new breakthrough inventions in a technology relies on the combination of knowledge that is both related and unrelated to such technology. |
| Keywords: | relatedness, unrelatedness, technological breakthroughs, regional diversification, European regions |
| JEL: | O18 O31 O33 R11 |
| Date: | 2021–06 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:2118&r= |
| By: | Chakraborty, Tanika (Indian Institute of Management); Mukherjee, Anirban (University of Calcutta) |
| Abstract: | We propose a regional inequality-based mechanism to explain the heterogeneity in the spread of Covid-19 and test it using data from India. We argue that a core-periphery economic structure is likely to increase the spread of infection because it involves movement of goods and people across the core and peripheral districts. Using nightlights data to measure regional inequality in the degree of economic activity, we find evidence in support of our hypothesis. Further, we find that regions with higher nightlight inequality also experience higher spread of Covid-19 only when lockdown measures have been relaxed and movement of goods and services are near normal. Our findings imply that policy responses to contain Covid-19 contagion needs to be heterogeneous across India, depending on the ex-ante economic structure of a region. |
| Keywords: | COVID-19, contagion, core-periphery, nightlight, industrial-heterogeneity |
| JEL: | I15 I18 R1 |
| Date: | 2021–05 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp14400&r= |
| By: | Manuel Gardt; Tom Brokel; Rosina Moreno |
| Abstract: | This study analyzes the formation and spatial structure of anti-wind-farm citizens’ initiatives (CIs) as a result of the development of wind turbine generators (WT) in Germany over the last three decades. It offers a novel, spatiotemporal view of the intensely discussed tension between WT and citizens’ perceptions of them. Using a new dataset and employing survival models, the study explores for the first time the co-development of WT and anti-wind initiatives, considering a wide range of regional socio-economic factors and multiple periods. The results confirm a rapidly growing dynamic of the establishment of local opposition, which the magnitude of locally existing WT and proximity to established anti-wind farm initiatives strongly drives. |
| Keywords: | Local opposition, wind energy development, Germany, citizens’ initiatives, acceptance, survival analysis |
| JEL: | C54 O18 O33 R11 R15 R59 |
| Date: | 2021–06 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:2119&r= |
| By: | Plechero, Monica (Ca’ Foscari University of Venice); Grillitsch, Markus (CIRCLE, Lund University) |
| Abstract: | Industry 4.0 requires from manufacturing firms to become more innovative in order to remain relevant and competitive. To step-up firm innovation, several studies in Innovation and Economic Geography foreground that firms need to combine knowledge in novel ways either within local industrial structures or over distance. The contribution of this paper is to investigate in-depth how manufacturing firms with traditional roots combine new generative knowledge in and beyond a local production system (LPS), what enables them to access and integrate such knowledge from external sources, and how this relates to the firms’ innovation performance, with a focus on radical and varied forms of innovation. The contribution of this paper lies also in a mixed-methods research approach, which combines a population-based survey of mechatronics firms in an Italian LPS, with in-depth interviews. This allows for a qualitative interpretation of the causes of the identified distributions and correlations. The main finding of the paper is that firms generating radical innovations and varied forms of innovation combine unrelated types of knowledge in-house and through external sources. The pattern is that the traditional manufacturing knowledge of mechatronics firms still prevails but that firms increasingly complement this with new knowledge, in particular science-based analytical knowledge. Firms that have acquired complementary knowledge in-house are able to access new knowledge nationally or internationally. Even though firms source knowledge relatively frequently within the local production system, the firms who access new knowledge nationally and internationally stand out in terms of their innovation performance. |
| Keywords: | Industry 4.0; knowledge bases; local productive system; innovation; manufacturing firms |
| JEL: | O33 R11 |
| Date: | 2021–06–02 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:lucirc:2021_005&r= |
| By: | Cruzatti C., John |
| Abstract: | This paper analyzes the effects of Free Trade Agreements (FTAs) on various measures of local development in 207 countries over the 1990-2015 period. Using a Difference-in-Differences approach, I exploit spatial and time variation by comparing regions with (exogenously determinded) exploitable and non-exploitable land before and after FTAs are "activated". I show that FTAs have a limited yet positive impact on a region's human development (as measured by the Human Development Index). The results also indicate that this limited impact can be explained by the positive effects of Free Trade Agreements on economic activity (night lights and GDP), together with the lack of significant influence on patterns of inequality (distribution of night lights among population). Finally, I also show that FTAs' impacts on human development are stronger for urbanized regions. Conversely, there is neither clear evidence of a weaker positive effect if trade partners belong to the Global North nor if the agreements include arrangements beyond the elimination of tariffs and quotas. |
| Keywords: | FTAs; Human Development; Economic Activity; Inequality |
| Date: | 2021–06–09 |
| URL: | http://d.repec.org/n?u=RePEc:awi:wpaper:0702&r= |
| By: | Template-Type: ReDIF-Paper 1.0; Hayato Kato (Graduate School of Economics, Osaka University); Toshihiro Okubo (Faculty of Economics, Keio University,) |
| Abstract: | When do multinationals show resilience during natural disasters? To answer this, we develop a simple model in which multinationals and local firms in the host country are interacted through input-output linkages. When natural disasters seriously hit local firms and thus increase the cost of sourcing local intermediates, most multinationals may leave the host country. However, they are likely to stay if they are tightly linked with local suppliers and face low trade costs of importing foreign intermediates. We further provide two extensions of the basic model to allow for multinationals with heterogeneous productivity and disaster reconstruction. |
| Keywords: | Foreign direct investment (FDI); Multinational enterprises (MNEs); Input-output linkages; Supply chain disruptions; Multiple equilibria. |
| JEL: | F12 F23 Q54 R11 |
| Date: | 2021–06 |
| URL: | http://d.repec.org/n?u=RePEc:osk:wpaper:2106&r= |
| By: | Frederik Wild; David Stadelmann |
| Abstract: | We investigate geo-referenced household-level data consisting of up to 206,896 individuals living in 21,826 localities across 28 sub-Saharan African countries over 20 years. We analyse the relevance of coastal proximity as a predictor of individual economic living standards. Our setting allows us to account for country-time fixed effects as well as individual-specific controls such as age, gender, and most importantly, urbanity. Results reveal that individuals living further away from the coast are more disadvantaged than individuals living in coastal regions along an array of welfare indicators. The findings are robust to the inclusion of other geographic covariates of development such as climate (e.g. temperature, precipitation), elevation or terrain ruggedness. We also explore mechanisms through which coastal proximity may influence individual welfare and decompose the estimated effect of coastal proximity via formal mediation analysis. Our results highlight the role of human capital as well as infrastructural endowments in reconciling the large intra-national disparities in individual economic welfare. |
| Keywords: | Geography; Coastal Proximity; Sub-Saharan Africa; Mediation Analysis |
| JEL: | O15 O18 R12 O55 |
| Date: | 2021–06 |
| URL: | http://d.repec.org/n?u=RePEc:cra:wpaper:2021-22&r= |
| By: | Darvas, Zsolt; Mazza, Jan; Midões, Catarina |
| Abstract: | We employ a novel methodology for the study of the characteristics of successful European Union cohesion projects. We first estimated ‘unexplained economic growth’ by controlling for the influence of various region-specific factors, and then analysed its relationship with about two dozen cohesion project characteristics. We found that the best-performing regions have on average projects with longer durations, more inter-regional focus, lower national co-financing, more national (as opposed to regional and local) management, higher proportions of private or non-profit participants among the beneficiaries and higher levels of funding from the Cohesion Fund. No clear patterns emerged concerning the sector of intervention. |
| Keywords: | EU cohesion policy, growth determinants, regional convergence, project characteristics |
| JEL: | C21 O47 R11 |
| Date: | 2021–04–12 |
| URL: | http://d.repec.org/n?u=RePEc:cvh:coecwp:2021/03&r= |
| By: | Wataru Takahashi (Economist, Policy Research Institute, Ministry of Finance) |
| Abstract: | This article proposes a population forecasting using endogenous population model, which incorporates a spatial model considering the spatially heterogeneous feature of agents and the economy by employing quantitative spatial models. In this endogenous population model, agents migrate to maximize their utility. This model is estimated using the twostage estimation approach, which is extensively used in quantitative spatial literature. Estimated parameters are significant and almost consistent with the economic and demographic stylized facts. Using the parameters concerning migration and local utilities, we conduct projection analyses for 2015-2125 across all prefectures in Japan, which is now experiencing regionally asymmetric population decline. In the baseline projections, the population in less populated prefectures is mitigated slightly by introducing the young generation's migration behavior. Counterfactual analyses are then conducted to break down the factors of population decline in Japan. Among several factors, birth abandonments due to some constraints and slow productivity growth after 1995 turned out to have severely impacted demographics. The development of networks resulted in having negative impacts on demographics though they had positive impacts on the welfare of economic agents in many aspects. |
| Keywords: | endogenous population model, spatial economics, quantitative spatial economics, population mobility. |
| JEL: | C21 J61 R10 R12 R23 P25 |
| URL: | http://d.repec.org/n?u=RePEc:mof:wpaper:ron339&r= |
| By: | Stiller, Johannes; Meister, Moritz; Niebuhr, Annekatrin; Peters, Jan Cornelius |
| Abstract: | Ziel dieses Working Papers ist es, die Wissensbasis über die Determinanten von Wanderungsbewegungen von Arbeitskräften zu erweitern. Die Auswertungen wurden im Rahmen des gemeinsamen Forschungsvorhabens "Die räumliche Mobilität von Arbeitskräften im Erwerbsverlauf − Analysen für ländliche Räume in Deutschland" (MobiLä) des Thünen-Instituts für Ländliche Räume und des Instituts für Arbeitsmarkt- und Berufsforschung (IAB) vorgenommen. Das Projekt wird aus Mitteln des Bundesprogramms Ländliche Entwicklung (BULE) gefördert. Anhand von Regressionsanalysen wird überprüft, welche Faktoren in einem robusten und zugleich bedeutenden Zusammenhang mit dem Wanderungsergebnis einer Region stehen. Die Analysen erfolgen auf der Ebene der 360 Kreisregionen Deutschlands und beziehen sich vorwiegend auf den Zeitraum 2004 bis 2017. Die bereits im Projekt erstellten Wanderungsdaten wurden mit einem Regionaldatensatz verknüpft, der umfangreiche Informationen über die Arbeitsmarktbedingungen und weitere Standortfaktoren beinhaltet. Anhand von zwei Schätzverfahren aus dem Bereich des maschinellen Lernens identifizieren wir diejenigen der insgesamt 30 betrachteten Indikatorvariablen, die mit den Wanderungssalden der Kreisregionen am stärksten in Zusammenhang stehen. Die Ergebnisse der Regressionsanalysen zeigen, dass sowohl Arbeitsmarktbedingungen als auch weitere Standortfaktoren mit den regionalen Wanderungsbilanzen korrelieren. Hinsichtlich der Arbeitsmarktcharakteristika ist ein positiver Zusammenhang zwischen dem Wanderungssaldo einer Region und dem Lohnniveau sowie dem Ausbildungsplatzangebot zu beobachten. Regionale Unterschiede in der Arbeitslosigkeit spielen den Ergebnissen zufolge demgegenüber keine bedeutende Rolle, wobei nicht auszuschließen ist, dass die Bedeutung der Arbeitslosenquote für das Wanderungsergebnis anhand der vorgenommenen Analysen aufgrund einer wechselseitigen Beziehung zwischen beiden Merkmalen unterschätzt wird. Einen robusten und zugleich bedeutenden negativen Zusammenhang beobachten wir zwischen der Nettomigrationsrate einer Region und dem regionalen Anteil des primären Sektors an der sozialversicherungspflichtigen Beschäftigung. Unter den weiteren Standortfaktoren weisen vor allem Indikatoren, die mit dem kulturellen und gastronomischen Angebot bzw. der touristischen Attraktivität korrelieren, einen positiven Zusammenhang mit dem regionalen Wanderungsergebnis auf. Außerdem spiegeln sich in den Ergebnissen ausgeprägte Suburbanisierungstendenzen wider: Zwischen dem Wanderungssaldo einer Region und ihrer eigenen Bevölkerungsdichte besteht ein ausgeprägter negativer Zusammenhang. Die Nachbarschaft eines hoch verdichteten Agglomerationsraums korreliert dagegen positiv mit der Nettomigrationsrate. |
| Keywords: | labor mobility,determinants,Germany,regional characteristics,rural areas,Arbeitskräftemobilität,Determinanten,Deutschland,regionale Charakteristika,ländliche Räume |
| JEL: | R23 J21 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:jhtiwp:176&r= |