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on Economic Geography |
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Issue of 2022‒01‒17
eleven papers chosen by Andreas Koch Institut für Angewandte Wirtschaftsforschung |
| By: | Cathrin Söllner (CRIE - Centre for Regional and Innovation Economics, University of Bremen) |
| Abstract: | Collaboration is an important factor for regional economic growth. Still, the literature lacks explanations why some regions collaborate more or less than expected. The present paper proposes regional culture as influencing factor, being region-specific and connected to interactive activities. Estimations are based on a sample of 155,019 collaborative patents from 134 European NUTS-2 regions. Data on regional culture was extracted from the European Values Study. Results reveal that regional culture has a significant effect on the collaboration likelihood. This influence differs due to the various dimensions of regional culture. |
| Keywords: | collaboration propensity, regional culture, Hofstede, EU-regions, patents |
| JEL: | F00 O43 R11 |
| Date: | 2022–01–06 |
| URL: | http://d.repec.org/n?u=RePEc:jrp:jrpwrp:2022-001&r= |
| By: | Philipp Gareis; Tom Broekel; |
| Abstract: | The paper contributes to the literature investigating students’ spatial mobility. By focusing on German higher education students with a novel dataset providing data from 1999 to 2015, we evaluate the impact of the change from a one-tiered to the two-tiered study structure of bachelor and master degrees (Bologna reform) on their inter-regional mobility and its underlying drivers. Our analysis confirms the system change to slightly alter inter-regional mobility of students. However, differences distinguish between different fields of study and universities und universities of applied sciences and indicate that the German higher education system is fairly resilient in its allocation of students. A Bologna-Drain of students moving from rural to urban regions to study master programs, can partially be confirmed for students of business studies. Our results reject the idea of (low) tuition fees discouraging students from enrolling in specific locations. |
| Keywords: | student mobility, Germany, Bologna, higher education |
| JEL: | I23 I25 R12 |
| Date: | 2022–01 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:2201&r= |
| By: | Vicente Rios (Universita degli Studi di Milano); Beatriz Manotas-Hidalgo (Universidad Publica de Navarra); Lisa Gianmoena |
| Abstract: | This study examines the link between spatial income inequality and civil conflict in Africa. To that end, we extend traditional empirical models of conflict to account for both endogenous and exogenous spatial interaction effects in the process of conflict by means of modern spatial econometric techniques. Using a geographically disaggregated annual high-resolution cell data for a sample of African countries during the period 1998 to 2013, we quantify the effect of spatial inequality on the probability of conflict incidence. Estimates show the existence of a positive and statistically signicant relationship between spatial income inequality and conflict in African regions. This is partly due to the role played by spatial spillovers induced by spatial inequality in neighboring regions. The observed link is robust to the inclusion in the analysis of different explanatory variables that may affect both conflict and spatial inequality such as the level of economic development, the endowment of natural resources, infrastructures, geographical conditions, population density, fractionalization, polarization, socialexclusion, or the share of urban population. The observed positive effect does not depend on the level of data disaggregation, the type of conflict, the spatial inequality metric used in the analysis and the econometric specification employed to capture the nature of spatial spillovers. |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:nav:ecupna:2110&r= |
| By: | Persyn, Damiaan |
| Abstract: | I consider a RUM model for migration where destination countries or regions are viewed as collections of ‘opportunities’ which are the fundamental units of choice for migrants. The best opportunity for a prospective migrant is more likely to be found in a destination that has many and diverse opportunities. Recent contributions in economics studying migration rather consider entire regions or countries as the fundamental, atomistic, units of choice. The key role of the size of destinations and the diversity within them is therefore often not fully recognised, which may lead to biased inference. I argue that the coefficient on size equals 1 in the ideal RUM model. This is also required for the gravity model for migration to have some intuitive properties: only then migration flows scale proportionally when aggregating destinations, and there is zero net migration between otherwise similar regions of different size. Models omitting size or using a coefficient on size different from 1 violate these properties. Imposing proportional scaling also has implications for how different sets of opportunities should be combined. The approach is showcased in a study of internal migration and urbanisation in Ethiopia. |
| Keywords: | migration, regional economics, spatial modelling, gravity equations, discrete choice |
| JEL: | C25 F2 R23 |
| Date: | 2021–12–11 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:111064&r= |
| By: | Piyush Panigrahi (University of California, Berkeley) |
| Abstract: | Larger Indian firms selling inputs to other firms tend to have more customers, tend to be used more intensively by their customers, and tend to have larger customers. Motivated by these regularities, I propose a novel empirical model of trade featuring endogenous formation of input-output linkages between spatially distant firms. The empirical model consists of (a) a theoretical framework that accommodates first order features of firm-to-firm network data, (b) a maximum likelihood framework for structural estimation that is uninhibited by the scale of data, and (c) a procedure for counterfactual analysis that speaks to the effects of micro- and macro- shocks to the spatial network economy. In the model, firms with low production costs end up larger because they find more customers, are used more intensively by their customers and in turn their customers lower production costs and end up larger themselves. In the model, differences in production costs across firms arise not just from differences in productivity but also from ï¬ nding the most cost-effective suppliers of intermediate inputs. Firms with low production costs end up larger because they ï¬ nd more customers, are used more intensively by their customers and in turn their customers lower production costs and end up larger themselves. The model is estimated using novel micro-data on firm-to-firm sales between Indian firms. The estimated model implies that a 10% decline in inter-state border frictions in India leads to welfare gains ranging between 1% and 8% across districts. Moreover, over half of the variation in changes in firms’ sales to other firms can be explained by endogenous changes in the network structure. |
| Keywords: | Network formation, Production networks, Firm-to-firm networks, International trade, Economic geography, Spatial economics |
| JEL: | F11 F12 D24 C67 C68 L11 O11 O12 R12 R15 |
| Date: | 2021–11 |
| URL: | http://d.repec.org/n?u=RePEc:cwl:cwldpp:2314&r= |
| By: | Li, Shiyuan; Hao, Miao |
| Abstract: | Based on the analysis of provincial-level data from 2001 to 2015, we find that regional inequality in China is not optimistic. Whether artificial intelligence, as a major technological change, will improve or worsen regional inequality is worthy of researching. We divide regional inequality into two dimensions: production and consumption, a total of three indicators. The empirical research is carried out to the eastern, central and western regions respectively. It is found that industrial intelligence improves the inequality of residents’ consumer welfare among regions, while at the same time there is the possibility of worsening regional inequality of innovation. We also clarify the heterogeneity of the mechanisms that artificial intelligence promotes innovation in different regions. |
| Keywords: | Artificial Intelligence; Regional Inequality; Innovation; Purchasing Power |
| JEL: | L25 O32 |
| Date: | 2021–10 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:110973&r= |
| By: | Nobuo Kobayashi (School of Economics, Kwansei Gakuin University); Takeshi Mori (Nomura Research Institute) |
| Abstract: | This paper presents an analysis of factors that promote and suppress the regional start-up activities of knowledge-intensive business services (KIBS) in Japan, based on the Digital Capability Index (DCI). The results showed that rapid progress in the digitization of public services and local residents f high ICT skills were factors that promoted KIBS start-ups. In addition, the results revealed that the establishment of a high-speed information and communication environment in the region has promoted T-KIBS startups, which utilize the Internet. Regarding factors not included in the DCI, the results showed a positive effect of the concentration of human resources and business establishments in metropolitan areas, which was in line with the findings of previous studies. In contrast, the start-up rates of T-KIBS were high in areas where the ratios of day and night populations were low. This finding suggests that although the main customers of T-KIBS are companies in metropolitan areas, such as Tokyo and Osaka, they locate their offices in the suburbs, where commercial rents are lower than in urban areas. |
| Keywords: | Knowledge Intensive Business Services (KIBS), Digital Capability Index (DCI), start-up activity |
| JEL: | L26 L84 L86 R30 |
| Date: | 2022–01 |
| URL: | http://d.repec.org/n?u=RePEc:kgu:wpaper:234&r= |
| By: | Aron, Janine; Muellbauer, John |
| Abstract: | Excess mortality is a more robust measure than the counts of COVID19 deaths typically used in epidemiological and spatial studies. Measurement issues around excess mortality, considering data quality and comparability both internationally and within the U.S., are surveyed. This paper is the first statelevel spatial analysis of cumulative excess mortality for the U.S. in the first full year of the pandemic. There is strong evidence that, given appropriate controls, states with higher Democrat vote shares experienced lower excess mortality (consistent with county level studies of COVID19 deaths). Important demographic and socioeconomic controls from a broad set tested were racial composition, age structure, population density, poverty, income, temperature, and timing of arrival of the pandemic. Interaction effects suggest the Democrat vote share effect of reducing mortality was even greater in states where the pandemic arrived early. Omitting political allegiance leads to a significant underestimation of the mortality disparities for minority populations. |
| Keywords: | Excess Mortality, COVID-19, Spatial Analysis, US States, Political Polarization |
| JEL: | I14 I18 J11 |
| Date: | 2021–12 |
| URL: | http://d.repec.org/n?u=RePEc:amz:wpaper:2021-24&r= |
| By: | Francisco Amaral; Martin Dohmen; Sebastian Kohl; Moritz Schularick |
| Abstract: | We study long-term returns on residential real estate in twenty-seven “superstar” cities in fifteen countries over 150 years. We find that total returns in superstar cities are close to 100 basis points lower per year than in the rest of the country. House prices tend to grow faster in the superstars, but rent returns are substantially greater outside the big agglomerations, resulting in higher long-run total returns. The excess returns outside the superstars can be rationalized as a compensation for risk, especially for higher co-variance with income growth and lower liquidity. Superstar real estate is comparatively safe. |
| Keywords: | housing returns; housing risk; superstar cities; regional housing markets |
| JEL: | G10 G12 N90 R21 R31 |
| Date: | 2021–12–01 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fednsr:93542&r= |
| By: | Giuseppe Simone |
| Abstract: | Large cities are a key driver of technological innovation and economic growth. This paper investigates the developments of Italian metropolitan areas, building on insights from economic geography and innovation studies. The key questions to be investigated are the following: a) Which trajectories of population and economic change can be identified for Italian metropolitan areas? Are we facing a process of economic and technological polarisation that may worsen the country’s imbalances? b) What is the role played in such developments by technological and structural change, and in particular by digital technologies and the rise of finance? The empirical analysis investigates the patterns of technological and economic indicators for the period 2000-2018 for 14 Italian metropolitan areas – proxied by their provinces -, providing evidence of growing polarisation between Milan, where most positive developments are concentrated, and the other metropolitan zones. Rome has been losing ground in most fields; Venice and Genoa are characterised by industrial decline. Few mid-sized cities show some economic dynamism – including Bologna and Cagliari - while most southern and insular Italian cities increase their gap relative to the performances of leading metropolitan areas. |
| Keywords: | urban economics, statistical methods, economic polarization, metropolitan areas, divergence. |
| JEL: | C10 O14 R11 |
| Date: | 2021–11 |
| URL: | http://d.repec.org/n?u=RePEc:usi:wpaper:865&r= |
| By: | Kruse, Mirko; Wedemeier, Jan |
| Abstract: | Strukturwandel ist kein temporäres Phänomen. Abhängig von der jeweiligen regionalen Wirtschaftsstruktur können sich Anpassungsprozesse an den Strukturwandel einfach oder schwerer gestalten und sich positiv oder negativ auf die wirtschaftliche Stärke einer Region auswirken. Deutschland weist sehr heterogene Regionen auf, die sich u.a. hinsichtlich ihrer Raumstruktur, Demografie oder wirtschaftlichen Stärke unterscheiden. Eine Disparität besteht insbesondere zwischen nord- und süddeutschen Bundesländern. Allgemein gilt, dass städtische Räume besonders vorteilhafte Wirtschaftsstrukturen aufweisen, um sich an aktuelle Trends erfolgreich anpassen zu können. In vielen ländlichen Regionen stellt sich dies anders dar. Vor allem in Nord- und Ostdeutschland finden sich Regionen, die deutlich gegenüber anderen Regionen aufholen müssen, um Wandlungsprozesse meistern zu können. In Regionen Thüringens oder Sachsens kommt erschwerend ein ausnahmsloser städtischer Konzentrationsprozess hinzu. Der Artikel zeichnet auf, wie sich aktuelle regionale Disparitäten darstellen und welche Regionen von künftigen Trends und Anpassungsprozessen profitieren können bzw. in welchen der Anpassungsdruck zunehmen wird. Es wird aufgezeigt, dass Veränderungen nicht durch strukturkonservierende Politik aufzuhalten sind, sondern vielmehr aktiv aufgenommen werden sollten, um den Wandel wirksam zu gestalten. Die öffentliche Hand sollte neben der Infrastruktur insbesondere in die Bereiche Bildung, Aus- und Fortbildung sowie Forschung und Entwicklung (F&E) investieren. Notwendig ist zudem eine Innovationspolitik, die verstärkt auf Kooperation und Vernetzung abzielt. Auf Norddeutschland übertragen impliziert dies eine stärkere, bundesländerübergreifende Kooperation in Forschungsvorhaben und Industriepolitik. |
| Keywords: | Strukturwandel,Norddeutschland,Wachstum,Nachhaltigkeit,structural change and transformation,Northern Germany,growth,sustainability |
| JEL: | O11 R10 R11 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:hwwipp:n134&r= |