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on Economic Geography |
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Issue of 2018‒06‒18
eight papers chosen by Andreas Koch Institut für Angewandte Wirtschaftsforschung |
| By: | Rodríguez-Pose, Andrés; Hardy, Daniel |
| Abstract: | There are many challenges to building firm competitiveness in posttransition economies, particularly with the intensification of as global trade integration. Intranation variations in firm competitiveness are also stark, highlighting the need for policies to overcome the legacy of pretransition economic structures. Utilizing data from Georgia's annual firm census and household surveys, this paper analyzes the nature of the country's competitive landscape—measured as labor productivity—over the period 2006–2012. The results of our empirical estimations reveal that although a large proportion of a firm's competitiveness is associated with its own characteristics (sorting and compositional effects), location-specific factors are also highly relevant. In particular, the extent of agglomeration, human capital endowments, and local expenditures—such as transport infrastructure investments—play a significant role in conditioning firm-level competitiveness. Given current regional endowments, these findings highlight the significant attention that needs to be paid to building capacities in less-favored areas, not only to ensure that trade integration does not harm Georgia's less-favored regions, but also to make further progress in developing the country's private sector and fully maximize the export potential across its full stock of enterprises. |
| Keywords: | competitiveness; productivity; firms; Georgia transition economies |
| JEL: | N0 R14 J01 |
| Date: | 2017–04–01 |
| URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:67543&r=geo |
| By: | Ebert, Tobias; Eichstaedt, Johannes C.; Lee, Neil; Obschonka, Martin; Rodríguez-Pose, Andrés |
| Abstract: | There is increasing interest in the potential of artificial intelligence and Big Data (e.g., generated via social media) to help understand economic outcomes and processes. But can artificial intelligence models, solely based on publicly available Big Data (e.g., language patterns left on social media), reliably identify geographical differences in entrepreneurial personality/culture that are associated with entrepreneurial activity? Using a machine learning model processing 1.5 billion tweets by 5.25 million users, we estimate the Big Five personality traits and an entrepreneurial personality profile for 1,772 U.S. counties. We find that these Twitter-based personality estimates show substantial relationships to county-level entrepreneurship activity, accounting for 24% (entrepreneurial personality profile) and 32% (all Big Five trait as separate predictors in one model) of the variance in local entrepreneurship and are robust to the introduction in the model of conventional economic factors that affect entrepreneurship. We conclude that artificial intelligence methods, analysing publically available social media data, are indeed able to detect entrepreneurial patterns, by measuring territorial differences in entrepreneurial personality/culture that are valid markers of actual entrepreneurial behaviour. More importantly, such social media datasets and artificial intelligence methods are able to deliver similar (or even better) results than studies based on millions of personality tests (selfreport studies). Our findings have a wide range of implications for research and practice concerned with entrepreneurial regions and eco-systems, and regional economic outcomes interacting with local culture. |
| Keywords: | artificial intelligence; Big Data; Big Five; Counties; entrepreneurship; personality; psychological traits; social media; Twitter; U.S. |
| JEL: | L26 R11 R12 |
| Date: | 2018–05 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:12949&r=geo |
| By: | Alessia Matano (AQR-IREA, University of Barcelona (UB). Tel.: +34-934021825; Fax.: +34-934021821. Department of Econometrics, Statistics and Applied Economics, University of Barcelona, Diagonal 690, 08034 Barcelona, Spain.); Moisés Obaco (AQR-IREA, University of Barcelona, Av. Diagonal 690 (08034), Barcelona, Spain.); Vicente Royuela (AQR-IREA, University of Barcelona, Av. Diagonal 690 (08034), Barcelona, Spain.) |
| Abstract: | This article investigates the incidence of agglomeration externalities in a typical developing country, Ecuador. In particular, we analyze the role of the informal sector within these relations, since informal employment accounts for a significant part of total employment in the developing countries. Using individual level data and instrumental variable techniques, we investigate the impact of spatial externalities, in terms of population size and local specialization, on the wages of workers in Ecuadorian cities. The results show that spatial externalities matter also for a typical developing country, especially as far as urbanization externalities are concerned. Moreover, analysis of the interaction between spatial externalities and the informal economy shows a general penalization for informal workers in terms of benefits arising from agglomeration externalities. Finally, by investigating the possible channels behind the heterogeneity found in spatial agglomeration gains between formal and informal workers, we show that the advantages from agglomeration for formal workers may well be accounted for by positive sorting and better gains from job changes, while for informal workers they arise from positive learning externalities. |
| Keywords: | Agglomeration Externalities, Developing Economies, Informal Employment, Workers’ Wages, FUAs, Ecuador. JEL classification:J31, J46, R23, R12. |
| Date: | 2018–06 |
| URL: | http://d.repec.org/n?u=RePEc:ira:wpaper:201813&r=geo |
| By: | Brachert, Matthias |
| Abstract: | We use the locational pattern of clubs in four major professional football leagues in Europe to test the causal effect of changes in premier league membership on regional employment and output growth at the NUTS 3 level. We rely on the relegation mode of the classical round-robin tournament in the European model of sport to develop a regression-discontinuity design. The results indicate small and significant negative short-term effects on regional employment and output in the sports-related economic sector when clubs are relegated from the premier division of the respective football league. In addition, we find small negative effects on overall regional employment growth. However, total regional gross value added remains unaffected, indicating that in the main it is the less productive jobs that disappear in the short-term. |
| Keywords: | professional football,relegation,regional growth,regression discontinuity design |
| JEL: | J40 R11 R12 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:iwhdps:102018&r=geo |
| By: | Baskaran, Thushyanthan; Blesse, Sebastian |
| Abstract: | A recent literature suggests that arbitrarily designed administrative borders are an important reason why sub-Saharan Africa remains one of the least developed regions on the globe. Accordingly, administrative border reforms may be a way to promote growth on the African continent. In this paper, we study the effect of subnational administrative border reforms on local economic development (proxied by nighttime luminosity) by tracking state-level border changes in Africa during 1992-2013 with GIS techniques. Difference-in-difference regressions suggest that mergers have strong positive effects on economic development. Splits, too, have positive effects, but they are substantially smaller on average. To understand why the economic impact of splits and mergers differs in magnitude, we investigate transmission channels. We link border changes to geocoded conflict data and survey evidence on political attitudes as well as service delivery. We find that the differences between splits and mergers are possibly due to different underlying motives for these two types of border reforms. Splits seem to affect development through higher political stability, i.e. a lower incidence of conflicts and more benign political attitudes of citizens, while mergers presumably work through an improvement in administrative efficiency. |
| Keywords: | administrative border reforms,economic development,night-light data,Africa |
| JEL: | D73 H77 R11 |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:zewdip:18027&r=geo |
| By: | Sebastian Galiani; Ivan Lopez Cruz; Gustavo Torrens |
| Abstract: | How to make police deployment strategies more efficient is becoming the crucial research agenda for the economics of crime and law enforcement. We contribute to this agenda developing the first general equilibrium model designed to study how the geographic distribution of police protection affects the decision to pursue illegal activities, the intensity and location of crime, residential choices, housing prices, and the welfare of different socioeconomic groups. The target is to explore the positive and normative long-run effects of different ways of spatially allocating police forces in an urban area. We find that, when the police protect some neighborhoods (concentrated protection), the city becomes segregated, while when the police are evenly deployed across the city (dispersed protection), an integrated city emerges. Unequal societies face a difficult dilemma in that concentrated protection maximizes aggregate welfare but exacerbates social disparities. Taxes and subsidies can be employed to offset the disadvantages of police concentration. Private security makes an integrated city less likely to occur in equilibrium. Even under dispersed public protection, rich agents may use private security to endogenously isolate themselves in closed neighborhoods. |
| Keywords: | Policy deployment, Crime, Spatial equilibrium, Inequality |
| JEL: | K42 R12 |
| Date: | 2018–06–07 |
| URL: | http://d.repec.org/n?u=RePEc:col:000518:016343&r=geo |
| By: | Giorgos Galanis (Goldsmiths, University of London); Ashok Kumar |
| Abstract: | This paper presents a novel understanding of the changing governance structures in global supply chains. Motivated by the global garment sector, we develop a geographical political economy dynamic model which reflects the interaction between bargaining power and distribution of value among buyer and producer firms. We find that the interplay between these two forces, in combination with the spatial specificities of global production, are necessary and sufficient to drive governance structures towards an intermediate position regarding their level of explicit coordination and power asymmetry. |
| Keywords: | Global value chains, global production networks, uneven development, disequilibrium dynamics, monopsony power |
| JEL: | D02 D43 E32 R10 |
| Date: | 2018–03 |
| URL: | http://d.repec.org/n?u=RePEc:pke:wpaper:1804&r=geo |
| By: | Patrizio Lecca (European Commission - JRC); Javier Barbero Jimenez (European Commission - JRC); Martin Aaroe Christensen (European Commission - JRC); Andrea Conte (European Commission - JRC); Francesco Di Comite (European Commission - ECFIN); Jorge Diaz-Lanchas (European Commission - JRC); Olga Diukanova (European Commission - JRC); Giovanni Mandras (European Commission - JRC); Damiaan Persyn (European Commission - JRC); Stylianos Sakkas (European Commission - JRC) |
| Abstract: | In this paper we provide the mathematical presentation of the RHOMOLO model. In addition, we perform some stylized and illustrative simulations with the aim to make the reader familiar with the economic adjustment mechanisms incorporated into the model. Essentially, we attempt to offer the reader and the potential users of the model an intuition of the transmission channels existing in the current version RHOMOLO. The analysis is kept simple to facilitate a better understanding of the model's findings. We simulate a permanent demand-side shock implemented separately for each of the 267 regions contained in the model. We repeat the same simulation under three alternative labour market closures and three different imperfectly competitive product market structures. |
| Keywords: | Numerical General Equilibrium Models, Regional Economic Adjustment, Regional spillover |
| Date: | 2018–05 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc111861&r=geo |