nep-geo New Economics Papers
on Economic Geography
Issue of 2023‒02‒27
six papers chosen by
Andreas Koch
Institut für Angewandte Wirtschaftsforschung

  1. The geography of structural transformation: effects on inequality and mobility By Takeda, Kohei
  2. Regional Capital No More. How the Reform of the Territorial Government has Marginalized Polish Middle-sized Cities By Borys Cie?lak; Paula Nagler; Frank van Oort
  3. Exploring European Regional Trade By Santamaría, Marta; Ventura, Jaume; YeÅŸilbayraktar, UÄŸur
  4. Peer interactions, local markets, and wages: Evidence from Italy By Brunetti, Irene; Intraligi, Valerio; Ricci, Andrea; Vittori, Claudia
  5. ‘Seeing’ the Future: Improving Macroeconomic Forecasts with Spatial Data Using Recurrent Convolutional Neural Networks By Jonathan Leslie
  6. Geographic Mobility over the Life-Cycle By Diaz, Antonia; Jáñez, Álvaro; Wellschmied, Felix

  1. By: Takeda, Kohei
    Abstract: The interplay between structural transformation in the aggregate and local economies is key to understanding spatial inequality and worker mobility. This paper develops a dynamic overlapping generations model of economic geography where historical exposure to different industries creates persistence in occupational structure, and non-homothetic preferences and differential productivity growth lead to different rates of structural transformation. Despite the heterogeneity across locations, sectors, and time, the model remains tractable and is calibrated with the U.S. economy from 1980 to 2010. The calibration allows us to back out measures of upward mobility and inequality, thereby providing theoretical underpinnings to the Gatsby Curve. The counterfactual analysis shows that structural transformation has substantial effects on mobility: if there were no productivity growth in the manufacturing sector, income mobility would be about 6 percent higher, and if amenities were equalized across locations, it would rise by around 10 percent. In these effects, we find that different degrees of historical exposure to industries in local economies play an important role.
    Keywords: structural transformation; upward mobility; labor mobility; economic geography
    JEL: O14 J62 R11 R13
    Date: 2022–12–12
    URL: http://d.repec.org/n?u=RePEc:ehl:lserod:118050&r=geo
  2. By: Borys Cie?lak (Gran Sasso Science Institute); Paula Nagler (Erasmus University Rotterdam); Frank van Oort (Erasmus University Rotterdam)
    Abstract: Among Polish cities facing socio-economic difficulties are the former regional capitals which lost their administrative status due to the 1998 reform, reducing the number of regions from 49 to 16. Making use of this quasiexperimental setting, we assess the impact of the loss of administrative status on the affected cities with difference-in-differences models. Our findings show a significant negative impact on economic and, partly, on other dimensions of development. Restructuring and scaling of devolved regions resulted in ‘leaving places behind’. The problematic socioeconomic trajectories of Poland’s former regional capitals caused or accentuated by the reform suggest a sustained marginalization.
    Keywords: Socioeconomic development, marginalization, decentralization, regional capital status
    JEL: R11 R15 R58
    Date: 2023–01–20
    URL: http://d.repec.org/n?u=RePEc:tin:wpaper:20230001&r=geo
  3. By: Santamaría, Marta (University of Warwick); Ventura, Jaume (CREI, Universitat Pompeu Fabra and Barcelona School of Economics); YeÅŸilbayraktar, UÄŸur (Universitat Pompeu Fabra and Barcelona School of Economics)
    Abstract: We use the new dataset of trade flows across 269 European regions in 24 countries constructed in Santamaría et al. (2020) to systematically explore for the first time trade patterns within and across country borders. We focus on the differences between home trade, country trade and foreign trade. We document the following facts: (i) European regional trade has a strong home and country bias, (ii) geographic distance and national borders are important determinants of regional trade, but cannot explain the strong regional home bias and (iii) the home bias is heterogeneous across regions and seems to be driven by political regional borders.
    Keywords: JEL Codes:
    Date: 2022
    URL: http://d.repec.org/n?u=RePEc:cge:wacage:650&r=geo
  4. By: Brunetti, Irene; Intraligi, Valerio; Ricci, Andrea; Vittori, Claudia
    Abstract: This paper investigates the relationship between the spatial distribution of occupations with a high content of peer interactions and wages among Italian provinces. At this aim, we use a unique employer-employee dataset obtained by merging administrative data on wages and labor market histories of individuals, with survey data on job tasks and contents. The spatial distribution of jobs intensive in peer-interactions is further measured according to the occupational structure of Italian provinces. The econometric analysis shows that the concentration of peer interactions leads to higher wages at the province level. These results are robust to firms and workers' heterogeneity and endogeneity issues.
    Keywords: Peer interactions, Wages, Agglomeration externalities
    JEL: J31 R12 R23
    Date: 2023
    URL: http://d.repec.org/n?u=RePEc:zbw:glodps:1235&r=geo
  5. By: Jonathan Leslie (Indiana University, Department of Economics)
    Abstract: I evaluate whether incorporating sub-national trends improves macroeconomic forecasting accuracy in a deep machine learning framework. Specifically, I adopt a computer vision setting by transforming U.S. economic data into a ‘video’ series of geographic ‘images’ and utilizing a recurrent convolutional neural network to extract spatio-temporal features. This spatial forecasting model outperforms equivalent methods based on country-level data and achieves a 0.14 percentage point average error when forecasting out-of-sample monthly percentage changes in real GDP over a twelve-month horizon. The estimated model focuses on Middle America in particular when making its predictions: providing insight into the benefit of employing spatial data.
    Keywords: Macroeconomic Forecasting, Machine Learning, Deep Learning, Computer Vision, Economic Geography
    Date: 2023–02
    URL: http://d.repec.org/n?u=RePEc:inu:caeprp:2023003&r=geo
  6. By: Diaz, Antonia; Jáñez, Álvaro (Universidad Carlos III de Madrid); Wellschmied, Felix (Universidad Carlos III de Madrid)
    Abstract: When mobility between locations is frictional, a person's economic well-being is partially determined by her place of birth. Using a life cycle model of mobility, we find that search frictions are the main impairment to the mobility of young people in Spain, and these frictions are particularly strong in economically distressed locations. As a result, being born in a high-unemployment urban area carries with it a large welfare penalty. Less stable jobs, slower skill accumulation, lower average wages, and fewer possibilities for geographic mobility all contribute to these welfare losses. Paying transfers to people in distressed economic locations decreases these welfare losses without large adverse effects on mobility. In contrast, several policies that encourage people to move to low-unemployment urban areas increase these welfare losses and fail to meaningfully increase mobility towards these more successful locations.
    Keywords: mobility, local labor markets, search frictions, life cycle, dynamic spatial models
    JEL: E20 E24 E60 J21 J61 J63 J64 J68 R23 R31
    Date: 2023–01
    URL: http://d.repec.org/n?u=RePEc:iza:izadps:dp15896&r=geo

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