nep-geo New Economics Papers
on Economic Geography
Issue of 2017‒03‒19
six papers chosen by
Andreas Koch
Institut für Angewandte Wirtschaftsforschung

  1. The domestic productivity effects of FDI in Greece: loca(lisa)tion matters! By Jacob A. Jordaan; Vassilis Monastiriotis
  2. Location Fundamentals, Agglomeration Economies, and the Geography of Multinational Firms By Laura Alfaro; Maggie X. Chen
  3. How do inventor networks affect urban invention? By Laurent Bergé; Nicolas Carayol, GREThA, UMR CNRS 5113, Université de Bordeaux; Pascale Roux
  4. Collective Learning in China's Regional Economic Development By Jian Gao; Bogang Jun; Alex "Sandy" Pentland; Tao Zhou; Cesar A. Hidalgo
  5. Common Factors, spatial dependence, and regional growth in the Italian manufacturing industry By Carlo Ciccarelli; Stefano Fachin
  6. Sectoral Shifts, Diversification, Regional Unemployment on the Eve of Revolution in Tunisia: a Sequential Spatial Panel Approach By Walid Jebili; Lotfi Belkacem

  1. By: Jacob A. Jordaan; Vassilis Monastiriotis
    Abstract: Despite an extensive empirical literature on the factors conditioning the size and prevalence of FDI productivity spillovers, the geographical dimension of these externalities remains relatively under-explored. In this paper we use firm level data from the Greek manufacturing sector to identify how three features of economic geography – spatial heterogeneity (location), spatial proximity (localisation) and spatial concentration (agglomeration) – influence the size and sign of FDI spillovers within and across industries. We find that FDI spillovers predominantly materialise at the sub-national level, with horizontal spillovers being more prominent at the regional scale (NUTS2) and vertical spillovers being highly localised (at the NUTS3 level). Furthermore, we find important synergies between spillovers from FDI and industry-region specific agglomeration. Also, FDI spillovers are found to be conditional on regional characteristics related to each region’s manufacturing base, FDI concentration, urban agglomeration and aggregate productivity. These results highlight the important role played by geography for the materialisation of productivity spillovers accruing from FDI and suggest that these key geographical features (location, localisation and agglomeration) ought to be taken into account both in the study of FDI spillovers and in the design of FDI-promotion and regional development policies.
    Date: 2016–12
  2. By: Laura Alfaro (Harvard Business School and NBER); Maggie X. Chen (George Washington University)
    Abstract: Multinationals exhibit distinct agglomeration patterns which have transformed the global landscape of industrial production (Alfaro and Chen, 2014). Using a unique worldwide plant-level dataset that reports detailed location, ownership, and operation information for plants in over 100 countries, we construct a spatially continuous index of pairwise-industry agglomeration and investigate the patterns and determinants underlying the global economic geography of multinational firms. In particular, we run a horse-race between two distinct economic forces: location fundamentals and agglomeration economies. We find that location fundamentals including market access and comparative advantage and agglomeration economies including capital-good market externality and technology diffusion play a particularly important role in multinationals’ economic geography. These findings remain robust when we use alternative measures of trade costs, address potential reverse causality, and explore regional patterns.
    Keywords: multinational firm, economic geography, agglomeration, location fun-damentals, agglomeration economies
    JEL: F2 D2 R1
    Date: 2016
  3. By: Laurent Bergé (CREA, Université du Luxembourg); Nicolas Carayol, GREThA, UMR CNRS 5113, Université de Bordeaux (GREThA, UMR CNRS 5113, Université de Bordeaux); Pascale Roux (GREThA, UMR CNRS 5113, Université de Bordeaux)
    Abstract: Social networks are expected to matter for invention in cities, but empirical evidence is still puzzling. In this paper, we provide new results on urban patenting covering more than twenty years of European patents invented by nearly one hundred thousand inventors located in France. Elaborating on the recent economic literatures on peer effects and on games in social networks, we assume that the productivity of an inventor’s efforts is positively affected by the efforts of his or her partners and negatively by the number of these partners’ connections. In this framework, inventors’ equilibrium outcomes are proportional to the square of their network centrality, which encompasses, as special cases, several well-known forms of centrality (Degree, Katz-Bonacich, Page-Rank). Our empirical results show that urban inventors benefit from their collaboration network. Their production increases when they collaborate with more central agents and when they have more collaborations. Our estimations suggest that inventors’ productivity grows sublinearly with the efforts of direct partners, and that they incur no negative externality from them having many partners. Overall, we estimate that a one standard deviation increase in local inventors’ centrality raises future urban patenting by 13%.
    Keywords: invention ; cities; network centrality; co-invention network; patent data
    JEL: O31 R11 D85
    Date: 2017
  4. By: Jian Gao; Bogang Jun; Alex "Sandy" Pentland; Tao Zhou; Cesar 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.
    Date: 2017–03
  5. By: Carlo Ciccarelli (University of Rome "Tor Vergata"); Stefano Fachin ("Sapienza" University of Rome)
    Abstract: We review the methods currently available for the analysis of regional datasets characterised by possible non-stationarity over time and both strong and weak spatial dependence and present, as a representative ase study, a comparative analysis of the regional development of the Italian manufacturing industries in the second halves of the 19th and 20th centuries. For highly heterogenous datasets we suggest a two-stages approach: (1) fit a dynam factor model with endogenous determination of the number of factors; (2) estimate a spatial model for the de-factored data. Applying this strategy we find two similar non-stationary afctors sufficient to explain long-run growth of the whole set of series examined in both centuries. Further, the results suggest that some conditional spatial error correction mechanisms seem to have been in action in both centuries.
    Keywords: Cross-sectional dependence, approximate factor models, dynamic spatial panel models, Italy, manufacturing industries.
    JEL: C38 C31 N13 N63 N93
    Date: 2017–03
  6. By: Walid Jebili (University of Sousse); Lotfi Belkacem
    Abstract: This paper investigates how sectoral shifts and industry specialization patterns have influenced Tunisian labor market performance in the recent past years. Building on a sequential spatial framework, while taking into account spatial dependencies and externalities, our empirical investigation highlights that sectoral shifts and congestion effects induced by labor-supply growth exert a negative impact on unemployment dynamics. Our results suggest that some Marshallian externalities manage to soften, and even reverse, the diversification induced effect on unemployment. Moreover, we report high spatial dependence, which evidences a higher degree of contagion. Additionally, negative spillovers of sectoral shifts contrast with positive spillovers of specialization pattern, initial unemployment rate, labor-supply growth and the excess labor demand growth rate. Finally, the revolution had a detrimental effect on unemployment growth, except in the center-west region where unemployment was an inevitable result of an inner-process.
    Date: 2015–10

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