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on Economic Geography |
| By: | Andrea Morrison; Ron Boschma |
| Abstract: | This paper investigates the spatial evolution of the Italian motor cycle industry during the period 1893-1993. We find support for both the heritage theory of Klepper and the agglomeration thesis of Marshall. Indeed, being a spinoff company or an experienced firm enhanced the survival rates, but we also found a positive effect of being located in the Motor Valley cluster in Emilia Romagna. Interestingly, this beneficial effect of a cluster could not be found outside the Emilia Romagna region. This might indicate the importance of a favourable local institutional environment, as propagated by the Emilian district literature. |
| Keywords: | spinoff dynamics, agglomeration economies, clusters, industrial districts, Emilian model, evolutionary economic geography |
| JEL: | B15 B52 O18 R11 |
| Date: | 2017–03 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:1707&r=geo |
| By: | Jian Gao; Bogang Jun; Alex "Sandy" Pentland; Tao Zhou; CŽsar A. Hidalgo |
| Abstract: | Industrial development is the process by which economies learn how to produce new products and services. But how do economies learn? And who do they learn from? The literature on economic geography and economic development has emphasized two learning channels: inter-industry learning, which involves learning from related industries; and inter-regional learning, which involves learning from neighboring regions. Here we use 25 years of data describing the evolution of China's economy between 1990 and 2015--a period when China multiplied its GDP per capita by a factor of ten--to explore how Chinese provinces diversified their economies. First, we show that the probability that a province will develop a new industry increases with the number of related industries that are already present in that province, a fact that is suggestive of inter-industry learning. Also, we show that the probability that a province will develop an industry increases with the number of neighboring provinces that are developed in that industry, a fact suggestive of inter-regional learning. Moreover, we find that the combination of these two channels exhibit diminishing returns, meaning that the contribution of either of these learning channels is redundant when the other one is present. Finally, we address endogeneity concerns by using the introduction of high-speed rail as an instrument to isolate the effects of inter-regional learning. Our differences-in-differences (DID) analysis reveals that the introduction of high speed-rail increased the industrial similarity of pairs of provinces connected by high-speed rail. Also, industries in provinces that were connected by rail increased their productivity when they were connected by rail to other provinces where that industry was already present. These findings suggest that inter-regional and inter-industry learning played a role in China's great economic expansion. Length: |
| Date: | 2017–03 |
| URL: | http://d.repec.org/n?u=RePEc:egu:wpaper:1706&r=geo |
| By: | Riccardo Crescenzi; Marco Di Cataldo; Andrés Rodríguez-Pose |
| Abstract: | Transport infrastructure investment is a cornerstone of growth-promoting strategies. However, the link between infrastructure investment and economic performance remains unclear. This may be a consequence of overlooking the role of government institutions. This paper assesses the connection between regional quality of government and the returns of different types of road infrastructure in the regions of the European Union. The results unveil the influence of regional quality of government on the economic returns of transport infrastructure. In weak institutional contexts, investment in motorways – the preferred option by governments – yields significantly lower returns than the more humble secondary roads. Government institutions also affect the returns of transport maintenance investment. |
| Keywords: | transport infrastructure; public capital investment; economic growth; institutions; government quality; institutions; regions; Europe |
| JEL: | O4 R11 R40 R58 |
| Date: | 2016–09 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:65716&r=geo |
| By: | Giulia Faggio; Olmo Silva; William C. Strange |
| Abstract: | Many prior treatments of agglomeration explicitly or implicitly assume that all industries agglomerate for the same reasons, with the traditional Marshallian (1890) factors of input sharing, labor pooling, and knowledge spillovers affecting all industries similarly. An important instance of this approach is the extrapolation from one key sector to the larger economy, such as the drawing of very general lessons about agglomeration from the specific case of the Silicon Valley. Another is the pooling of data to examine common tendencies in agglomeration even across very different industries. This paper uses UK establishment-level data on coagglomeration to document substantial heterogeneity across industries in the microfoundations of agglomeration economies. The analysis shows that the Marshallian factors interact with the organizational and adaptive aspects of agglomeration discussed by Chinitz (1961), Vernon (1960), and Jacobs (1969). Our findings highlight the importance of treating Marshall’s microfoundations of agglomeration as complements to the analysis of Jacobs and others, rather than as alternatives. |
| JEL: | C1 R14 J01 |
| Date: | 2016–03–23 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:64765&r=geo |
| By: | Laurent Scaringella (ESC Rennes School of Business - ESC Rennes School of Business); Jean-Jacques Chanaron (CNRS (French National Center for Scientific Research) - UCBL - Université Claude Bernard Lyon 1, GEM - Grenoble Ecole de Management - Grenoble École de Management (GEM)) |
| Abstract: | Over the past decades, the EU heavily invested in Research Infrastructures (RI). What are the expected returns of such investments? In the present article we address the question of returns on public funds/public infrastructures. We consider the role of RI and universities from an economic, social, and entrepreneurial perspective from various Territorial Innovation Models (TIMs): Italian industrial districts, innovative milieus, regional innovation systems, new industrial spaces, and regional clusters. We conducted our empirical study on Grenoble Isère Alpes Nanotechnologies (GIANT), which is composed of large scientific instruments, universities, and engineering and management schools. Our microeconomic methodology measured the socioeconomic and entrepreneurial effects of GIANT with respect to budget, employment, and spin-off generation. We contribute to the existing body of knowledge on TIMs by comparing the long-term investments to the generation of wealth, the creation of employment, and the development of start-ups; adding new insights to the debate opposing positive and negative impacts empirical studies; and offering recommendations for the use of public resources. In our discussion, we compare the GIANT model as a very localized RI-university club to the Grenoble model as localized cluster. |
| Keywords: | Return on investment,Socioeconomic impact,Start-up,University,Research infrastructure,Territorial Innovation Models |
| Date: | 2016–05–26 |
| URL: | http://d.repec.org/n?u=RePEc:hal:gemptp:hal-01472878&r=geo |
| By: | Helen Lawton Smith (Birkbeck, University of London. Oxfordshire Economic Observatory, Oxford University) |
| Date: | 2017–02 |
| URL: | http://d.repec.org/n?u=RePEc:img:wpaper:36&r=geo |
| By: | Riccardo Crescenzi (London School of Economics and Political Science); Andrea Filippetti (National Research Council, Italy. London School of Economics and Political Science. Birkbeck College, University of London, UK); Simona Iammarino (London School of Economics and Political Science) |
| Date: | 2016–02 |
| URL: | http://d.repec.org/n?u=RePEc:img:wpaper:30&r=geo |
| By: | Luca Andriani (Department of Management, Birkbeck College University of London) |
| Abstract: | Institutional conformity might help explain regional credit market failures in Italy in terms of insolvency rate. A credit relation is subject to a certain degree of uncertainty about the credible commitment of the parties to fulfil the contractual obligations. We argue that conformity to informal institutions of reciprocal cooperation and trust can reduce this degree of uncertainty and, hence, contract breaches. We support our argument by conducting an empirical investigation where the regional density of industrial districts is used as indicator of institutional conformity. We find lower insolvency rate in regions with higher institutional conformity. Additionally, we find higher conformity to informal institutions in regions where the punishment system reacts quicker to non-compliant behaviours, suggesting a complementary relationship between conformity to informal institutions and lower cost of punishment. One of the advantages of this indicator consists in the possibility of addressing “Ostrom-type” policy recommendations to reduce regional credit market failures. |
| Date: | 2015–11 |
| URL: | http://d.repec.org/n?u=RePEc:img:manwps:11&r=geo |
| By: | Ingrid Gould Ellen; Keren Mertens Horn; Davin Reed |
| Abstract: | Over the past two decades, crime has fallen dramatically in cities in the United States. We explore whether, in the face of falling central city crime rates, households with more resources and options were more likely to move into central cities overall and more particularly into low income and/or majority minority central city neighborhoods. We use confidential, geocoded versions of the 1990 and 2000 Decennial Census and the 2010, 2011, and 2012 American Community Survey to track moves to different neighborhoods in 244 Core Based Statistical Areas (CBSAs) and their largest central cities. Our dataset includes over four million household moves across the three time periods. We focus on three household types typically considered gentrifiers: high-income, college-educated, and white households. We find that declines in city crime are associated with increases in the probability that highincome and college-educated households choose to move into central city neighborhoods, including low-income and majority minority central city neighborhoods. Moreover, we find little evidence that households with lower incomes and without college degrees are more likely to move to cities when violent crime falls. These results hold during the 1990s as well as the 2000s and for the 100 largest metropolitan areas, where crime declines were greatest. There is weaker evidence that white households are disproportionately drawn to cities as crime falls in the 100 largest metropolitan areas from 2000 to 2010. |
| Keywords: | crime, gentrification, neighborhood choice |
| JEL: | R23 R21 R11 |
| Date: | 2017–01 |
| URL: | http://d.repec.org/n?u=RePEc:cen:wpaper:17-27&r=geo |
| By: | Belen Barroeta; Javier Gomez Prieto (European Commission - JRC); Jonatan Paton; Manuel Palazuelos Martinez (European Commission - JRC); Marcelino Cabrera Giraldez (European Commission - JRC) |
| Abstract: | The Smart Specialisation concept, currently implemented in the European Union, is being widely considered by several countries and regions of Latin-America. The interest towards this approach, highly based on the enhancement of regional innovation capacities, is motivating territorial dialogues, participatory processes and collective vision related to the innovation perspectives of Latin-American regions. This article highlights how policy makers of Mexico, Brazil, Colombia, Peru, Chile and Argentina are considering the smart specialisation concept as an inspirational driver of regional innovation and specialisation. Understanding the socio-economic and contextual differences between EU and Latin-America, this working paper does not seek to elaborate value judgements on the way in which smart specialisation is being (or should be) adapted beyond the EU. Instead, the analysis seeks to emphasise the common tendencies of the concept implementation as a way to frame cooperation between regions of the EU and Latin-America. |
| Keywords: | Smart Specialisation, Regional Innovation, Cooperation, European Union, Latin America |
| Date: | 2017–03 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc106043&r=geo |