nep-geo New Economics Papers
on Economic Geography
Issue of 2022‒04‒04
eight papers chosen by
Andreas Koch
Institut für Angewandte Wirtschaftsforschung

  1. Place-based policies and agglomeration economies: Firm-level evidence from special economic zones in India By Görg, Holger; Mulyukova, Alina
  2. Place-Based Consequences of Person-Based Transfer: Evidence from Recessions By Brad Hershbein; Bryan Stuart
  3. Structural change and firm dynamics in the south of Italy By Francesco Bripi; Raffaello Bronzini; Elena Gentili; Andrea Linarello; Elisa Scarinzi
  4. The geographic proximity effect on domestic cross-sector vis-a-vis intra-sector research collaborations By Giovanni Abramo; Francesca Apponi; Ciriaco Andrea D'Angelo
  5. A 3D index for measuring economic resilience with application to the modern international and global financial crises By Dimitrios Tsiotas
  6. Using stochastic hierarchical aggregation constraints to nowcast regional economic aggregates By Gary Koop; Stuart McIntyre; James Mitchell; Aubrey Poon
  7. Circular economy in Germany: A methodology to assess the circular economy performance of NUTS3 regions By Kruse, Mirko; Wedemeier, Jan
  8. Nonparametric prediction with spatial data By Abhimanyu Gupta; Javier Hidalgo

  1. By: Görg, Holger; Mulyukova, Alina
    Abstract: This paper exploits time and geographic variation in the adoption of Special Economic Zones in India to assess the direct and spillover effects of the program. We combine geocoded firm-level data and geocoded SEZs using a concentric ring approach, thus creating a novel dataset of firms with their assigned SEZ status. To overcome the selection bias we employ inverse probability weighting with time-varying covariates in a difference-in-differences framework. Our analysis yields that conditional on controlling for initial selection, the establishment of SEZs induced no further productivity gains for within SEZ firms, on average. This effect is predominantly driven by relatively less productive firms, whereas more productive firms experienced significant productivity gains. However, SEZs created negative externalities for firms in the vicinity which attenuate with distance. Neighbouring domestic firms, large firms, manufacturing firms and non-importer firms are the main losers of the program. Evidence points at the diversion of inputs from non-SEZ to SEZ-firms as a potential mechanism.
    Keywords: Special Economic Zones,India,TFP growth,firm performance,spillovers,time-varyingtreatment
    JEL: O18 O25 P25 R10 R58 R23 F21 F60
    Date: 2022
  2. By: Brad Hershbein; Bryan Stuart
    Abstract: This paper studies how government transfers respond to changes in local economic activity that emerge during recessions. Local labor markets that experience greater employment losses during recessions face persistent relative decreases in per capita earnings. However, these areas also experience persistent increases in per capita transfers, which offset 16 percent of the earnings loss on average. The increase in transfers is driven by unemployment insurance in the short run, and medical, retirement, and disability transfers in the long run. Our results show that nominally place-neutral transfer programs redistribute considerable sums of money to places with depressed economic conditions.
    Keywords: recessions; safety net; government transfers
    JEL: E32 H50 R12 R28
    Date: 2022–03–22
  3. By: Francesco Bripi (Bank of Italy); Raffaello Bronzini (Bank of Italy); Elena Gentili (Bank of Italy); Andrea Linarello (Bank of Italy); Elisa Scarinzi (Bank of Italy)
    Abstract: In this paper, we study the structural change in the Centre-North and the South of Italy, focusing on its implications for productivity dynamics and its microeconomic determinants. We document three main results. First, between 2001 and 2018 the deindustrialization process involved both parts of Italy, but in the South it started after the financial crisis and was more pronounced. In the southern regions, the employment shares in low knowledge-intensive services increased more than in the Centre-North, whereas those in the high knowledge-intensive services increased less. Second, structural changes slowed down productivity growth in the Centre-North, but had no role in the fall of productivity registered in the South. Finally, in the Centre-North employment growth has been driven by the net creation of jobs among incumbents and larger firms. In contrast, employment dynamics in the southern regions largely reflected the process of firms entering and exiting the market, in particular in less knowledge-intensive service sectors, and in young and smaller enterprises.
    Keywords: structural change, firm dynamics, North-South gap, productivity growth, shift-share analysis
    JEL: R00 R11 L16 O41 O47
    Date: 2022–03
  4. By: Giovanni Abramo; Francesca Apponi; Ciriaco Andrea D'Angelo
    Abstract: Geographic proximity is acknowledged to be a key factor in research collaborations. Specifically, it can work as a possible substitute for institutional proximity. The present study investigates the relevance of the "proximity" effect for different types of national research collaborations. We apply a bibliometric approach based on the Italian 2010-2017 scientific production indexed in the Web of Science. On such dataset, we apply statistical tools for analyzing if and to what extent geographical distance between co-authors in the byline of a publication varies across collaboration types, scientific disciplines, and along time. Results can inform policies aimed at effectively stimulating cross-sector collaborations, and also bear direct practical implications for research performance assessments.
    Date: 2022–02
  5. By: Dimitrios Tsiotas
    Abstract: The study and measurement of economic resilience is ruled by high level of complexity related to the diverse structure, functionality, spatiality, and dynamics describing economic systems. Towards serving the demand of integration, this paper develops a three-dimensional index, capturing engineering, ecological, and evolutionary aspects of economic resilience that are considered separately in the current literature. The proposed index is computed on GDP data of worldwide countries, for the period 1960-2020, concerning 14 crises considered as shocks, and was found well defined in a conceptual context of its components. Its application on real-world data allows introducing a novel classification of countries in terms of economic resilience, and reveals geographical patterns and structural determinants of this attribute. Impressively enough, economic resilience appears positively related to major productivity coefficients, gravitationally driven, and depended on agricultural specialization, with high structural heterogeneity in the low class. Also, the analysis fills the literature gap by shaping the worldwide map of economic resilience, revealing geographical duality and centrifugal patterns in its geographical distribution, a relationship between diachronically good performance in economic resilience and geographical distance from the shocks origin, and a continent differentiation expressed by the specialization of America in engineering resilience, Africa and Asia in ecological and evolutionary resilience, and a relative lag of Europe and Oceania. Finally, the analysis provides insights into the effect of the 2008 on the globe and supports a further research hypothesis that political instability is a main determinant of low economic resilience, addressing avenues of further research.
    Date: 2022–02
  6. By: Gary Koop; Stuart McIntyre; James Mitchell; Aubrey Poon
    Abstract: Recent decades have seen advances in using econometric methods to produce more timely and higher-frequency estimates of economic activity at the national level, enabling better tracking of the economy in real time. These advances have not generally been replicated at the sub–national level, likely because of the empirical challenges that nowcasting at a regional level presents, notably, the short time series of available data, changes in data frequency over time, and the hierarchical structure of the data. This paper develops a mixed– frequency Bayesian VAR model to address common features of the regional nowcasting context, using an application to regional productivity in the UK. We evaluate the contribution that different features of our model provide to the accuracy of point and density nowcasts, in particular the role of hierarchical aggregation constraints. We show that these aggregation constraints, imposed in stochastic form, play a key role in delivering improved regional nowcasts; they prove to be more important than adding region-specific predictors when the equivalent national data are known, but not when this aggregate is unknown.
    Keywords: Regional data; Mixed frequency; Nowcasting; Bayesian methods; Real-time data; Vector autoregressions
    JEL: C32 C53 E37
    Date: 2022–03–03
  7. By: Kruse, Mirko; Wedemeier, Jan
    Abstract: There is currently a massive methodological gap in the spatial analysis of the Circular Economy (CE) performance in general and in Germany particularly. The authors present a methodology to assess this performance in German regions. The methodology consists of 26 indicators in seven dimensions, namely Policy, Innovation, Circular Employment, Consumption and Production, Waste Management, Socio-economic Development, Municipal Sustainability. Data was obtained from different sources and focuses on the base year 2018. The analysis reveals that Germany does not show a clear core-periphery pattern when it comes to regional CE performance. Instead, the pattern is more differentiated with both urban and rural regions of different sizes being able to rank high in CE performance.
    Keywords: Circular Economy,Germany,Regional Assessment,Sustainability,NUTS3
    JEL: O18 P48 R1 R11
    Date: 2022
  8. By: Abhimanyu Gupta; Javier Hidalgo
    Abstract: We describe a (nonparametric) prediction algorithm for spatial data, based on a canonical factorization of the spectral density function. We provide theoretical results showing that the predictor has desirable asymptotic properties. Finite sample performance is assessed in a Monte Carlo study that also compares our algorithm to a rival nonparametric method based on the infinite AR representation of the dynamics of the data. Finally, we apply our methodology to predict house prices in Los Angeles.
    Keywords: Lattice data, unilateral models, canonical factorization, spectral density, nonparametric prediction
    Date: 2022–01

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