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on Economic Geography |
| By: | Pierre M. Picard (CREA, University of Luxembourg and CORE, Université Catholique de Louvain); Pascal Mossay (Department of Economics, University of Reading and CORE) |
| Abstract: | In this paper, we study social interactions between two populations of individuals living in a city. Agents consume land and benefit from intra- and inter-group social interactions. We show that in equilibrium segregation arises: populations get separated in distinct spatial neighborhoods. Two- and three-district urban structures are characterized. For high population ratios or strong inter-group interactions, only a three-district city exists. In other cases, multiplicity of equilibria arises. Moreover, for sufficiently low population ratios or very weak inter-group interactions, all individuals agree on which spatial equilibrium is best. |
| Keywords: | social interaction, segregation, multiple centers, urban districts |
| JEL: | R12 R14 R31 |
| Date: | 2013 |
| URL: | http://d.repec.org/n?u=RePEc:luc:wpaper:13-03&r=geo |
| By: | Aaron Chatterji; Edward L. Glaeser; William R. Kerr |
| Abstract: | This paper reviews recent academic work on the spatial concentration of entrepreneurship and innovation in the United States. We discuss rationales for the agglomeration of these activities and the economic consequences of clusters. We identify and discuss policies that are being pursued in the United States to encourage local entrepreneurship and innovation. While arguments exist for and against policy support of entrepreneurial clusters, our understanding of what works and how it works is quite limited. The best path forward involves extensive experimentation and careful evaluation. |
| JEL: | H70 L26 L52 L53 M13 O25 O38 R00 R10 R12 R50 |
| Date: | 2013–05 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:19013&r=geo |
| By: | Zhu Wang (Federal Reserve Bank of Richmond); Daniel Yi Xu (Duke University); Luis Cabral (New York University) |
| Abstract: | Taking the early U.S. automobile industry as an example, we evaluate two competing hypotheses on geographic concentration of industry: local externalities versus employee spinoffs. Our findings suggest that both forces contribute to industry agglomeration through their specific channels, and the spinoff effect can be viewed as a special form of local externalities. Calibrating our model to the quantitative pattern of industry evolution reveals that traditional local externalities are main driving forces of agglomeration. Particularly, the local economy and related industries play an important role by fostering new entrants. Spinoffs play a secondary role and contribute to an increased concentration at later stages of the industry life cycle. |
| Date: | 2012 |
| URL: | http://d.repec.org/n?u=RePEc:red:sed012:615&r=geo |
| By: | Nguyen Thang Dao (CORE - Université Catholique de Louvain); Julio Dávila (Centre d'Economie de la Sorbonne et CORE - Université Catholique de Louvain) |
| Abstract: | We extend Galor and Weil (2000) by including geographical factors in order to show that under some initial conditions, an economy may be locked in Malthusian stagnation and never take off. Specifically, we characterize the set of geographical factors for which this happens, and this way we show how the interplay of the available “land”, its suitability for living, and its degree of isolation, determines whether an economy can escape stagnation. |
| Keywords: | Geographical factors, loss of technology, human capital. |
| JEL: | O11 O33 |
| Date: | 2013–04 |
| URL: | http://d.repec.org/n?u=RePEc:mse:cesdoc:13037&r=geo |
| By: | Gillanders, Robert |
| Abstract: | This paper examines the relationship between corruption and infrastructure at both the country and regional level using the World Bank’s Enterprise Surveys data. A statistically significant and considerable relationship is established between the measure of corruption in the macro data and the measures of transportation and electricity infrastructure. Countries with more corruption tend to have worse infrastructure in the eyes of their firms. This link is shown to remain when one uses other measures of corruption and after controlling for GDP per capita, institutional quality and land area. At the regional level, the key result is unchanged. The magnitude and significance of this result is shown to vary by global region. Two stage least squares results, using distance from the equator as an instrument at the macro level support the simple OLS results and allow us to have some confidence that the causality runs from corruption to infrastructure. Finally, it is shown that within country variation in corruption has a significant effect on regional infrastructure. |
| Keywords: | Corruption, infrastructure, cross country, regional variation |
| JEL: | D73 H54 O18 |
| Date: | 2013–04–12 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:46679&r=geo |
| By: | Alberto Marzucchi (Catholic University of Milan); Davide Antonioli (University of Ferrara); Sandro Montresor (JRC-IPTS) |
| Abstract: | The paper aims to show how policy makers can stimulate firms' cooperation with research organisations in innovation. We argue that the administration of an R&D subsidy can be effective. Furthermore, this should be more so for extra-regional than intra-regional cooperation. The firms' propensity to extend cooperation across the region is assumed to increase with the amount of support. However, the support must overcome a threshold, for firms to cover the fixed costs of distant interactions. These research hypotheses are tested with respect to a sample of firms in a region of Italy. Propensity score matching is applied to identify the impact of the subsidy receipt. A generalised propensity score technique is employed to investigate the effect of an increasing amount of support. All the hypotheses are not rejected. Firms' cooperation is policy sensitive, but the size of the support is crucial for its effects. |
| Keywords: | Industry-Research Cooperation, Regional Innovation Systems, Behavioural Additionality |
| JEL: | O32 O38 R11 R58 |
| Date: | 2012–11 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc76320&r=geo |
| By: | Kim, Kijin |
| Abstract: | Since the beginning of the Clean Air Act, firms operating in regulated counties have faced with higher costs, which consequently had an impact on local labor markets. This paper investigates the effects of the air quality regulation on local manufacturing wages. Taking into account wage spillover explicitly into the model distinguishes this paper from existing studies in which spillover was ignored or was not a major focus. Using the 1982-2007 Census of Manufactures and the historical pollutant-specific nonattainment status for all counties, I construct the wage model with fixed effects partly based on the model specification in Greenstone (2002). I find the wage reduction in emitters induced by the regulations ranging from 2% to 10% depending on the pollutant, which in the 2005 dollar amount are equivalent to loss of roughly $800~$4,000 a year. I also find that the regulation effects are not uniform across industries: petroleum & coal, chemical & allied products and paper & allied products are influenced most among emitters. I find an evidence of the existence of spillover, but it is not so evident in the preferred fixed effects model. |
| Keywords: | Wage, Spillover, Clean Air Act, Spatial Panel, Spatial 2SLS, Environmental Economics and Policy, |
| Date: | 2013 |
| URL: | http://d.repec.org/n?u=RePEc:ags:crae13:147489&r=geo |
| By: | Hiller, Norbert |
| Abstract: | Beside the specific object attributes, location is the fundamental determinant for real estate. But how important is location within a city? Contrary to popular belief our results suggest that this parameter explains only a small proportion of price variation, whereas object attributes are crucial. Location, location, location does not capture the essence of an apartment value. In a city it is only an explanation part which has relative little impact on price variations. Therefore, we suggest size, age, location as comprehensive determinants for local apartment prices. -- |
| Keywords: | Amenities,Hedonic Method,Real Estate and Urban Economics,Factor Analysis,Relative Importance |
| Date: | 2013 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:cawmdp:64&r=geo |
| By: | Francisco José Goerlich Gisbert (Universitat de València); Isidro Cantarino Martí (Dpto. Ingeniería del Terreno) |
| Abstract: | This paper presents an exercise in the estimation of rural and urban population at municipal level. Our starting point is a population density grid at 1 km2 resolution and national coverage, which has been elaborated previously by the authors. Applying standard criteria in European official statistics (Eurostat) we determine the population that lives in urban clusters (contiguous grid cells with a minimum population density of 300 inhabitants per km2 and a minimum population of 5,000 inhabitants) and outside these clusters, which are called rural areas. Using similar criteria (contiguous grid cells with a minimum population density of 1,500 inhabitants per km2 and a minimum population of 50,000 inhabitants) we determine the population living in urban centers or high density clusters. Transforming this rural/urban grid in rural and urban municipal population is accomplished by means of simple Geographical Information System operations (GIS). In this way, we determine, for each commune, the population that lives in rural areas, in urban clusters and in urban centers, if any of these is present in the commune. Eventually, and also by means of Eurostat criteria, we offer a rural/intermediate/urban typology at municipal and regional level, which we compare with the standard OECD’s typology. Este trabajo presenta un ejercicio de estimación de la población rural y urbana a nivel de municipio. Partimos para ello de una grid de densidad poblacional con resolución 1 km2 y ámbito nacional, elaborada previamente por los autores. La aplicación de criterios estándar en la estadística oficial europea (Eurostat) nos permite determinar la población que vive en aglomeraciones urbanas (celdas contiguas con una densidad mínima de 300 habitantes por km2 y un mínimo de población de 5.000 habitantes) y fuera de ellas, es decir en áreas rurales. Mediante criterios similares (contigüidad, densidad mínima de 1.500 habitantes por km2 y un mínimo de población de 50.000 habitantes) determinamos la población que vive en centros urbanos. La trasformación de esta grid rural/urbana en poblaciones rurales y urbanas a nivel de municipio se realiza mediante simples operaciones en el contexto de los Sistemas de Información Geográfica (SIG), de esta forma para cada municipio somos capaces de determinar la población que vive en áreas rurales, en aglomeraciones urbanas y en centros urbanos, si es que estos últimos están presentes en un municipio concreto. Finalmente, y también mediante la aplicación de criterios Eurostat, ofrecemos una tipología rural/intermedio/urbano tanto a nivel municipal como a nivel regional, y se compara la clasificación estándar de la OECD. |
| Keywords: | Rejillas de población, núcleos urbanos, población rural, demografía. Population grids, urban areas, rural population, demography. |
| Date: | 2013–04 |
| URL: | http://d.repec.org/n?u=RePEc:ivi:wpasec:2013-01&r=geo |