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on Economic Geography |
| By: | Andersson, Martin (Department of Industrial Economics Blekinge Institute of Technology (BTH)); Larsson, Johan P (University of Cambridge, Department of Land Economy) |
| Abstract: | Using longitudinal Swedish data, we document robust evidence of highly local spillovers between individuals in similar occupations. The results are consistent with the existence of knowledge spillovers between workers performing similar work tasks in the same city-district. We further demonstrate less distance-sensitive benefits of working in diverse districts and regions, characterized by high density of employees in other occupations. The diversity benefits exist only in metropolitan areas and pertain to workers performing advanced services or non-routine work tasks. |
| Keywords: | Agglomeration economies; Wages; Spillovers; Attenuation; Clusters; Economic proximity; Relatedness |
| JEL: | J24 R10 R12 |
| Date: | 2020–08–31 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:iuiwop:1352&r=all |
| By: | Eduardo Gutiérrez (Banco de España); Enrique Moral-Benito (Banco de España); Roberto Ramos (Banco de España); Daniel Oto-Peralías (Universidad Pablo de Olavide) |
| Abstract: | We exploit the GEOSTAT 2011 population grid with a very high 1-km2 resolution to document that Spain presents the lowest density of settlements among European countries. We uncover that this anomaly cannot be accounted for by adverse geographic and climatic conditions. Using techniques from spatial econometrics, we identify the clusters that exhibit the lowest densities within Spain after controlling for geo-climatic factors: these areas mainly belong to Teruel, Zaragoza, Ciudad Real, Albacete, Sevilla and Asturias. We also explore the attributes that characterize the municipalities located in these low-density areas: larger population losses during the 1950-1991 rural exodus, higher shares of local-born inhabitants, longer distances to the province capital, higher shares of population employed in agriculture, and larger increases in regionalist vote after the Great Recession. |
| Keywords: | economic geography, Spain |
| JEL: | R10 |
| Date: | 2020–08 |
| URL: | http://d.repec.org/n?u=RePEc:bde:wpaper:2028&r=all |
| By: | Daunfeldt, Sven-Olov (Institute of Retail Economics (Handelns Forskningsinstitut)); Mihaescu, Oana (Institute of Retail Economics (Handelns Forskningsinstitut)); Rudholm, Niklas (Institute of Retail Economics (Handelns Forskningsinstitut)) |
| Abstract: | We use the entry of 17 external shopping malls in Sweden to investigate how they have affected the performance of incumbent firms located in the city centres of small cities. We find that entry by external shopping malls decreased labour productivity for incumbent firms in city centres by -5.31%. However, when using time-specific fixed effects to control for common time trends in retailing in small cities, the impact on labour productivity, revenues, and number of employees due to the entry of external shopping malls becomes insignificant. The negative impact on incumbent firms is thus not due to the entry of external shopping malls but rather due to long-term negative economic trends in these cities. |
| Keywords: | external shopping malls; city centre; firm performance; agglomeration economies; competition; difference-in-differences |
| JEL: | D22 L25 P25 R12 |
| Date: | 2020–08–24 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:hfiwps:0010&r=all |
| By: | Stam, Erik; Welter, Friederike |
| Abstract: | This chapter focuses on contexts of entrepreneurship, in particular geographical contexts, and entrepreneurial agency. The twin concepts space and place are key in understanding geographical contexts for entrepreneurship, not least because place does not exist without physical space. Important research in this regard has touched upon the role of gendered places and spaces for entrepreneurship, social places such as families, households and neighbourhoods and explored new spaces for entrepreneurship such as makerspaces. We combine these spaces and places in a model of entrepreneurial ecosystems that allows us to focus simultaneously on the geographical contexts for entrepreneurship and the agency of entrepreneurs within those. The chapter ends with a future research agenda on geographical contexts for entrepreneurship. |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:ifmwps:0420&r=all |
| By: | Dr. Anett Großmann (GWS - Institute of Economic Structures Research); Svenja Schwarz (GWS - Institute of Economic Structures Research); Frank Hohmann (GWS - Institute of Economic Structures Research); Anke Mönnig (GWS - Institute of Economic Structures Research) |
| Abstract: | The research project “Development of sustainable strategies in the Chilean mining sector through a regionalized national model” – funded by the German Federal Ministry of Education and Research – analyses the socio-economic impacts of copper on the Chilean economy. For this, the model COFORCE (COpper FORecasting in ChilE, www.coforce.cl) was developed from scratch. First, a macro-econometric input-output (IO) model for Chile (COFORCE) was built in line with the INFORUM (Interindustry FORcasting at the University of Maryland) modelling approach to forecast and simulate the impact of copper industry on the overall economy. Second, due to the importance of Chilean copper exports, the COFORCE model is linked to the bilateral trade model TINFORGE which captures among other world trade of copper between 153 countries. The national COFORCE model receives export demand and import prices from the world model according to its global market shares. Third, the COFORCE model was regionalized by using an Interregional Input-Output table developed by partners in Brazil (Haddad et al. 2018). The national and 15 regional models for Chile are linked via final demand components and industries by applying a top-down approach. Therefore, regional economic growth is mainly driven by the industry structure and inter- and intraregional trade. This set of three projection and simulation models considers the main aspects regarding copper: 1. It is the main exporting product, 2. It has a huge impact on the economic development and 3. The copper industry is regionally differently concentrated. The modelling tools are applied for the evaluation of alternative economic scenarios, e. g. copper export scenarios at the national and subnational level. The main focus of this paper is to introduce the methodology used to regionalize the national model COFORCE, to explain the main transmission channels and to present regional modelling results. The national model COFORCE and the underlying model philosophy and characteristics are explained in detail in Mönnig/Bieritz 2019. Section 4 shows examples of applications and how to implement scenarios by using the graphical user interface solver(c) (see section 4.1). which includes the underlying data set (historic data and forecasted) and supports the user in scenario design. |
| Keywords: | Model Building, Input-Output, Sustainable Mining, Copper |
| JEL: | C67 R15 R11 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:gws:dpaper:20-3&r=all |
| By: | John Gibson; Susan Olivia; Geua Boe-Gibson |
| Abstract: | Night lights, as detected by satellites, are increasingly used by economists, typically as a proxy for economic activity. The growing popularity of these data reflects either the absence, or the presumed inaccuracy, of more conventional economic statistics, like national or regional GDP. Further growth in use of night lights is likely, as they have been included in the AidData geo-query tool for providing sub-national data, and in geographic data that the Demographic and Health Survey links to anonymised survey enumeration areas. Yet this ease of obtaining night lights data may lead to inappropriate use, if users fail to recognize that most of the satellites providing these data were not designed to assist economists, and have features that may threaten validity of analyses based on these data, especially for temporal comparisons, and for small and rural areas. In this paper we review sources of satellite data on night lights, discuss issues with these data, and survey some of their uses in economics. |
| Keywords: | Density, development, DMSP, luminosity, night lights, VIIRS |
| JEL: | O15 R12 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:lic:licosd:41920&r=all |
| By: | Mendez-Guerra, Carlos; Santos-Marquez, Felipe |
| Abstract: | Satellite nighttime light data are increasingly used for evaluating the performance of economies in which official statics are non-existent, limited, or non-comparable. In this paper,we use a novel luminosity-based measure of GDP per capita to study regional convergence and spatial dependence across 274 subnational regions of the Association of South East Asian Nations(ASEAN) over the 1998-2012 period. Specifically, we first evaluate the usefulness of this new luminosity indicator in the context of ASEAN regions. Results show that almost 60 percent of the differences in (official) GDP per capita can be predicted by this luminosity-based measure of GDP. Next, given its potential usefulness for predicting regional GDP, we evaluate the spatio-temporal dynamics of regional inequality across ASEAN. Results indicate that although there is an overall (average) process of regional convergence, regional inequality within most countries has not significantly decreased. When evaluating the patterns of spatial dependence, we find increasing spatial dependence over time and stable spatial clusters (hotspots and coldspots) that are located across multiple national boundaries. Taken together, these results provide a new and more disaggregated perspective of the integration process of the ASEAN community. |
| Keywords: | convergence spatial dependence satellite nighttime light data luminosity subnational regions ASEAN |
| JEL: | O57 R10 R11 |
| Date: | 2020–08–17 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:102510&r=all |
| By: | Vasavi Bhatt (Indira Gandhi Institute of Development Research); S. Chandrasekhar (Indira Gandhi Institute of Development Research); Ajay Sharma (Indian Institute of Management, Indore) |
| Abstract: | Despite an increase in the number of workers commuting between rural and urban areas, much of theliterature on worker mobility continues to be migration centric. This paper establishes the importance ofrural-urban commuting in India. As per estimates from Periodic Labour Force Survey 2018-19, anestimated 18.8 million individuals living in rural are working in urban India and the share of earnings from urban in total non-farm rural earnings is 19.3 percent. Among all rural workers, 7.3 percent arerural-urban commuters while only 2.1 percent of urban workers are urban-rural commuters. Wedocument large variations at the sub-national level. Our results from a multinomial model to understand the factors associated with commuting highlight the importance of lagged regional unemployment rate. A high rural unemployment rate acts as a push factor and a low urban unemployment rate acts as a pull factor for rural urban commuting. The urbanness of occupations in aregion is also an important correlate of commuting. The paper concludes by highlighting the need toprioritize questions in Indias labour force survey that would help understand the nature of labour mobility and strength of rural urban linkages. |
| Keywords: | Labour Mobility, Commuting, Rural-Urban Linkages, Classification of Jobs, India |
| JEL: | J21 J61 R12 R23 |
| Date: | 2020–08 |
| URL: | http://d.repec.org/n?u=RePEc:ind:igiwpp:2020-025&r=all |
| By: | Christopher Rauh (Université de Montréal, CIREQ) |
| Abstract: | In this paper I present a methodology to provide uncertainty measures at the regional level in real time using the full bandwidth of news. In order to do so I download vast amounts of newspaper articles, summarize these into topics using unsupervised machine learning, and then show that the resulting topics foreshadow fluctuations in economic indicators. Given large regional disparities in economic performance and trends within countries, it is particularly important to have regional measures for a policymaker to tailor policy responses. I use a vector-autoregression model for the case of Canada, a large and diverse country, to show that the generated topics are significantly related to movements in economic performance indicators, inflation, and the unemployment rate at the national and provincial level. Evidence is provided that a composite index of the generated diverse topics can serve as a measure of uncertainty. Moreover, I show that some topics are general enough to have homogenous associations across provinces, while others are specific to fluctuations in certain regions. |
| Keywords: | machine learning, latent dirichlet allocation, newspaper text, economic uncertainty, topic model, Canada |
| Date: | 2019–09 |
| URL: | http://d.repec.org/n?u=RePEc:mtl:montec:09-2019&r=all |