nep-geo New Economics Papers
on Economic Geography
Issue of 2023‒08‒28
six papers chosen by
Andreas Koch, Institut für Angewandte Wirtschaftsforschung

  1. Spatial wage inequality in North America and Western Europe: Changes between and within local labour markets 1975-2019 By Bauluz, Luis; Bukowski, P.; Fransham, M.; Lee, A.; López Forero, M.; Novokmet, Filip; Breau, S.; Lee, Neil; Malgouyres, Clément; Schularick, Moritz; Verdugo, Gregory
  2. Nighttime Light Pollution and Economic Activities: A Spatio-Temporal Model with Common Factors for US Counties By Bresson, Georges; Etienne, Jean-Michel; Lacroix, Guy
  3. Incorporating Short Data into Large Mixed-Frequency VARs for Regional Nowcasting By Gary Koop; Stuart McIntyre; James Mitchell; Aubrey Poon; Ping Wu
  4. Learning and Expectations in Dynamic Spatial Economies By Jingting Fan; Sungwan Hong; Fernando Parro
  5. Local Economic Growth and Infant Mortality By Andreas Kammerlander; Günther G. Schulze
  6. Socio-spatial Inequalities in a Context of "Great Economic Wealth". Case study of neighbourhoods of Luxembourg City By Natalia Zdanowska

  1. By: Bauluz, Luis; Bukowski, P.; Fransham, M.; Lee, A.; López Forero, M.; Novokmet, Filip; Breau, S.; Lee, Neil; Malgouyres, Clément; Schularick, Moritz; Verdugo, Gregory
    Abstract: The rise of economic inequalities in advanced economies has been often linked with the growth of spatial inequalities within countries, yet there is limited comparative research that studies the relationship between national and subnational economic inequality. This paper presents the first systematic attempt to create internationally comparable evidence showing how different countries perform in terms of geographic wage inequalities. We create cross-country comparable measures of spatial wage disparities between and within similarly-defined local labour market areas (LLMAs) for Canada, France, (West) Germany, the UK and the US since the 1970s, and assess their contribution to national inequality. By the end of the 2010s, spatial inequalities in LLMA mean wages are similar in Canada, France, Germany and the UK; the US exhibits the highest degree of spatial inequality. Over the study period, spatial inequalities have nearly doubled in all countries, except for France where spatial inequalities have fallen back to 1970s levels. Due to a concomitant increase in within-place inequality, the contribution of places in explaining national wage inequality has remained fairly constant over the 40-year study period, except in the UK where we document a significant increase. Whilst common global social, economic and technological shocks are important drivers of spatial inequality, this variation in levels and trends of spatial inequality opens the way to comparative research exploring the role of national institutions in mediating how global shocks translate into economic disparities between places.
    Keywords: regional inequality, wage inequality, local labour markets
    JEL: J3 R1 R23
    Date: 2023
  2. By: Bresson, Georges (University of Paris 2); Etienne, Jean-Michel (Université Paris-Sud); Lacroix, Guy (Université Laval)
    Abstract: Excessive nighttime light is known to have detrimental effects on health and on the environment (fauna and flora). The paper investigates the link between nighttime light pollution and economic growth, air pollution, and urban density. We propose a county model of consumption which accounts for spatial interactions. The model naturally leads to a dynamic general nesting spatial model with unknown common factors. The model is estimated with data for 3071 continental US counties from 2012–2019 using a quasi-maximum likelihood estimator. Short run and long run county marginal effects emphasize the importance of spillover effects on radiance levels. Counties with high levels of radiance are less sensitive to additional growth than low-level counties. This has implications for policies that have been proposed to curtail nighttime light pollution.
    Keywords: nighttime light pollution, air pollution, GDP, satellite data, space-time panel data model
    JEL: C23 Q53
    Date: 2023–07
  3. By: Gary Koop (Department of Economics, University of Strathclyde); Stuart McIntyre (Department of Economics, University of Strathclyde); James Mitchell (Federal Reserve Bank of Cleveland; Economic Statistics Centre of Excellence); Aubrey Poon (Orebro University; Economic Statistics Centre of Excellence); Ping Wu (Department of Economics, University of Strathclyde)
    Abstract: Interest in regional economic issues coupled with advances in administrative data is driving the creation of new regional economic data. Many of these data series could be useful for nowcasting regional economic activity, but they suffer from a short (albeit constantly expanding) time series which makes incorporating them into nowcasting models problematic. Regional nowcasting is already challenging because the release delay on regional data tends to be greater than that at the national level, and “short†data imply a “ragged edge†at both the beginning and the end of regional data sets, which adds a further complication. In this paper, via an application to the UK, we develop methods to include a wide range of short data into a regional mixed-frequency VAR model. These short data include hitherto unexploited regional VAT turnover data. We address the problem of the ragged edge at both the beginning and end of our sample by estimating regional factors using different missing data algorithms that we then incorporate into our mixed-frequency VAR model. We find that nowcasts of regional output growth are generally improved when we condition them on the factors, but only when the regional nowcasts are produced before the national (UK-wide) output growth data are published.
    Keywords: Regional data, Mixed-frequency data, Missing data, Nowcasting, Factors, Bayesian methods, Real-time data, Vector autoregressions
    JEL: C32 C53 E37
    Date: 2023–04
  4. By: Jingting Fan; Sungwan Hong; Fernando Parro
    Abstract: The impact of shocks in dynamic environments depends on how forward-looking agents anticipate the path of future fundamentals that shape their decisions. We incorporate flexible beliefs about future fundamentals in a general class of dynamic spatial models, allowing beliefs to be evolving, uncertain, and heterogeneous across groups of agents. We show how to implement our methodology to study both ex-ante and ex-post shocks to fundamentals. We apply our method to two settings—an ex-ante study of the economic impacts of climate change, and an ex-post evaluation of the China productivity shock on the U.S. economy. In both cases, we study the impact of deviations from perfect foresight on different outcomes.
    JEL: F1 F11 F16 F18 Q54 R11 R13
    Date: 2023–07
  5. By: Andreas Kammerlander; Günther G. Schulze (Department of International Economic Policy, University of Freiburg)
    Abstract: We show, for the rst time, a causal eect of local economic growth on infant mortality. We use geo-referenced data for non-migrating mothers from 46 developing countries and 128 DHS survey rounds and combine it with nighttime luminosity data at a granular level. Using mother xed eects we show that an increase in local economic activity signicantly reduces the probability that the same mother loses a further child before its first birthday.
    Keywords: local economic growth, child mortality, nighttime lights
    JEL: I15 O18
    Date: 2021–09
  6. By: Natalia Zdanowska
    Abstract: In spite of being one of the smallest and wealthiest countries in the European Union in terms of GDP per capita, Luxembourg is facing socio-economic challenges due to recent rapid urban transformations. This article contributes by approaching this phenomenon at the most granular and rarely analysed geographical level - the neighbourhoods of the capital, Luxembourg City. Based on collected empirical data covering various socio-demographic dimensions for 2020-2021, an ascending hierarchical classification on principal components is set out to establish neighbourhoods' socio-spatial patterns. In addition, Chi2 tests are carried out to examine residents' socio-demographic characteristics and determine income inequalities in neighbourhoods. The results reveal a clear socio-spatial divide along a north-west south-east axis. Moreover, classical factors such as gender or citizenship differences are revealed to be poorly determinant of income inequalities compared with the proportion of social benefits recipients and single residents.
    Date: 2023–07

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