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on Economic Geography |
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Issue of 2026–08–10
sixteen papers chosen by Andreas Koch, Institut für Angewandte Wirtschaftsforschung |
| By: | Desmet, Klaus; Parro, Fernando |
| Abstract: | We examine the recent literature that studies the spatial distribution of economic activity across both space and time. We discuss the methodological advances enabling the incorporation of dynamic forces of economic activity---such as endogenous innovation, forward-looking location choices, capital and asset accumulation, idea diffusion, and stochastic fundamentals---into frameworks with many heterogeneous locations and a rich economic geography. These frameworks remain tractable for quantitative evaluations. We also discuss the wide range of empirical questions explored in recent work through the lens of these frameworks, including the global and local economic impacts of climate change, the dynamic effects of trade and migration policy, labor market adjustments to import competition, the spatial consequences of structural change, the dynamic effects of place-based policies, and the long-run spatial effects of large-scale infrastructure projects. |
| JEL: | F10 F16 F22 O11 O18 O33 R11 R12 R23 |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19931 |
| By: | Balboni, Clare; Shapiro, Joseph S. |
| Abstract: | How do environmental goods and policies shape spatial patterns of economic activity? How will climate change modify these impacts over the coming decades? How do agglomeration, commuting, and other spatial forces and policies affect environmental quality? We distill theoretical and empirical research linking urban, regional, and spatial economics to the environment. We present stylized facts on spatial environmental economics, describe insights from canonical environmental models and spatial models, and discuss the building blocks for papers and the research frontier in enviro-spatial economics. Most enviro-spatial research remains bifurcated into either primarily environmental or spatial papers. Research is only beginning to realize potential insights from more closely combining spatial and environmental approaches. |
| JEL: | F18 F64 H23 J61 O18 Q50 R11 |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19934 |
| By: | Chen, Yujiang River; Teulings, Coen |
| Abstract: | The high return to human capital on GDP per capita, reaching up to 50% in simple cross country or region regressions, is puzzling. We develop a spatial model with both rural regions and cities. Both human capital and the concentration of employment in city centers drive knowledge spillovers. Regional land prices clear the market for inter-regional labor mobility, leading to joint predictions for the public return to human capital and land prices. We test the model using data on wages and real-estate prices for 47 U.S. rural areas and 34 CMSAs from 1979 to 2015. We find that the public return on wages is 30% of the private return in rural regions, rising to 150% in cities. The total (public + private) return to human capital on GDP per capita is 20%. Increased knowledge spillovers account for the full real wage growth and for most of the increase in house prices in this period. Regional sorting of human capital and the city form each account for 15% of GDP. |
| Keywords: | Agglomeration externalities; Cities; Regional house prices; Spatial sorting; Public return to human capital |
| JEL: | J24 J31 I26 R12 R13 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:20201 |
| By: | Venables, Anthony |
| Abstract: | The idea that people want to go to where the jobs are is intuitive, yet is absent from the standard quantitative spatial modelling approach in which location choices are guided by prices, without reference to quantities (the number of jobs in a place). The purpose of this paper is to fill this gap by making jobs, as well as places, the objects of household choice. This involves minor change to the modelling approach used in the literature and provides a simple description of labour market matching. Similar modification of the modelling of firms’ location choices captures the idea that these are shaped by both wage costs and the availability of workers with appropriate skill. These modifications yield powerful agglomeration forces, as workers’ location choices become positively influenced by the number of jobs in a place, and firms’ decision are shaped by the number of workers with appropriate skills. Results are established analytically and in a regional model in which the equilibrium distributions of workers and sectors are demonstrated. |
| Keywords: | Spatial models |
| JEL: | R1 R12 R23 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:20030 |
| By: | Lindenlaub, Ilse; Oh, Ryungha; Peters, Michael |
| Abstract: | Using administrative data from Germany, we document that high-wage locations have substantially lower labor shares and higher wage dispersion. We show that a parsimonious model, in which firm monopsony power stems from search frictions in local labor markets, can explain these facts as long as “superstar†firms sort into productive locations. This positive sorting, which emerges as the unique equilibrium if firm and location productivity are sufficient complements or labor market frictions are sufficiently large, steepens the local wage ladder in productive locations and leads to not only higher wages, but also greater wage inequality. At the same time, positive firm sorting reduces local labor shares in prosperous places because more productive firms have more monopsony power. Our estimated model indicates that firm sorting can rationalize the lower local labor shares in regions with endogenously higher wages and can account for 40% of their increased wage dispersion. In spatial firm sorting, we thus highlight a new source of disparities in local labor market outcomes. |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:19958 |
| By: | Redding, Stephen |
| Abstract: | The recent development of quantitative urban models provides a new set of tools for evaluating transport improvements. Conventional cost-benefit analyses are typically undertaken in partial equilibrium. In contrast, quantitative urban models characterize the spatial distribution of economic activity within cities in general equilibrium. We compare evaluations of a transport improvement using conventional cost-benefit analysis, sufficient statistics approaches based on changes in market access, and model-based counterfactuals. We show that quantitative urban models predict a reorganization of economic activity within cities in response to a transport improvement, which can lead to substantial differences between the predictions of these three approaches for large changes in transport costs. |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:20021 |
| By: | Luisa Alamá-Sabater (Department of Economics and IIDL, Universitat Jaume I, Castellón, Spain); Miguel Ángel Márquez (Department of Economics, Universidad de Extremadura, Spain); Guillem Rodilla (Department of Applied Mathematics, Universitat Politècnica de València, Spain); Emili Tortosa-Ausina (IVIE, Valencia and IIDL and Department of Economics, Universitat Jaume I, Castellón, Spain) |
| Abstract: | This paper investigates how demographic, socioeconomic, and second-nature geographic factors jointly shape the emergence, spatial distribution, and heterogeneity of left-behind places (LBPs) in Spain. Using municipal-level data, it develops an empirical strategy combining cluster analysis, frontier analysis, and a multinomial logit model to identify distinct types of territorial vulnerability, to measure how close municipalities are to transitioning into more disadvantaged states, and to estimate the probability of belonging to specific LBP categories. The results reveal substantial heterogeneity across left-behind places, uncovering multiple forms of municipal vulnerability. A central contribution is the explicit incorporation of second-nature geography into the clustering procedure itself rather than treating geography as a merely contextual or ex post factor. These variables emerge as critical drivers of territorial disadvantage, and their inclusion leads to the reclassification of nearly 20% of Spanish municipalities, uncovering forms of hidden marginality that would remain invisible in analyses based solely on demographic and socioeconomic characteristics. From a policy perspective, the findings support a shift toward what the authors term systemic place-based policies; forward-looking strategies that seek to reshape the spatial preconditions for economic activity rather than simply adapting to existing territorial structures. |
| Keywords: | cluster analysis, depopulation, left-behind places, rural, urban |
| JEL: | C3 O18 O21 R1 R23 R3 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:jau:wpaper:2026/09 |
| By: | Coelli, Federica; Pelzl, Paul |
| Abstract: | Using oil and gas shocks as an exogenous source of business cycles at the U.S. commuting zone level, we provide novel evidence that local booms increase local patenting, especially in non-metropolitan areas. This reflects agglomeration economies that make incumbent inventors more productive. In contrast to total patenting, innovation in oil and gas — the sector closest to the boom — is countercyclical, consistent with higher opportunity costs of innovation in a booming industry. Our findings shed new light on the spatial dimension of innovation, inform recent debates on place-based industrial policy, and help to reconcile mixed evidence on the cyclicality of innovation. |
| Keywords: | Innovation |
| JEL: | L71 O12 O31 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:20317 |
| By: | W. Addessi; I. Etzo; A. Tidu; S. Usai |
| Abstract: | Given the Cultural and Creative Industries' (CCIs) growing contribution to Italy's GDP and their fragmented structure of small-medium enterprises, this paper explores the impact of agglomeration on Italian province productivity. To overcome the Modifiable Areal Unit Problem (MAUP) inherent in administrative boundaries, we employ a distance-based specialization index to assess whether firms benefit from operating in close proximity to peers within the same industry. We replicate this analysis at both the domain level (Cultural vs Creative) and the macro-sector level (e.g., Architecture and Design, Performing Arts). Our findings reveal a positive effect of agglomeration on Total Factor Productivity (TFP) across all levels of aggregation. However, when utilizing value added per employee as a metric for productivity, the positive impact is exclusively significant at the macro-sector level, dissipating at more aggregated domain classifications. These results underscore the necessity of facilitating co-location policies for CCIs, particularly given their SME-dominated nature. |
| Keywords: | Cultural and Creative Industries, spatial concentration, agglomeration economies, total factor productivity, M-index |
| JEL: | D24 L25 R12 Z11 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:cns:cnscwp:202612 |
| By: | Pardy, Martina; Rodríguez-Pose, Andrés |
| Abstract: | This paper analyses how trade influences intra-regional income inequality across Europe’s NUTS-2 regions. Drawing on newly compiled datasets capturing both inter-regional trade and local-level inequality for all EU member states plus the UK, we employ an econometric framework —complete with Instrumental Variable estimations and robust sensitivity analyses— to gauge the impact of trade on regional interpersonal inequality. In addition to examining aggregate trade, we distinguish between various trade channels, including exchanges within the EU versus those with the rest of the world, links to neighbouring regions versus non-neighbours, and domestic versus international flows. Our findings reveal that higher levels of trade are positively associated with changes in regional income inequality, as measured by the Gini coefficient. Crucially, this link depends on trading partners: trade within a single country, within the EU, and with non-neighbouring regions correlates with rising inequality, whereas international trade, trade with non-EU partners, or trade with neighbouring regions shows no statistically significant effect. These conclusions withstand a battery of robustness checks, including new control variables and a population-weighted approach, further underscoring the role that particular types of trade play in shaping regional income disparities. |
| Keywords: | Trade; Europe |
| JEL: | D63 F14 R13 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:20255 |
| By: | D'Alessandro, Francesco; Santarelli, Enrico; Vivarelli, Marco |
| Abstract: | This study examines how regional technological relatedness and local AI knowledge influence regional innovative activity, as measured by patenting activity. Using a novel three-way longitudinal dataset (670 four-digit CPC classes × 302 NUTS-2 regions × nine four-year periods, 1986-2021) and leveraging a deep learning-based identification of AI patents, we show that two broad mechanisms operate in parallel. First, in accordance with the extant literature, technologies that are cognitively close to a region's existing patent portfolio enjoy higher patenting activity, confirming that relatedness remains a strong and persistent predictor of innovative output. Second, local AI endowments are positively associated with patenting across technological fields, even after conditioning on relatedness, indicating that AI plays an enabling and cross-cutting role in a given regional innovation system. Moreover, the interaction between relatedness and AI turns out to be negative and statistically significant, implying that AI attenuates the extent to which local innovative efforts depend on the technology's proximity to the regional portfolio. In sum, AI appears to enhance overall local innovative activity while reducing its reliance on pre-existing regional knowledge structures. |
| Keywords: | Artificial intelligence, AI, technological change, regional innovation, relatedness |
| JEL: | O31 R11 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:glodps:1792 |
| By: | Spowage, Mairi; Milne, Kate |
| Abstract: | Accurate and timely regional economic data is crucial for effective policymaking and informed decision-making at all levels. Understanding the economic performance of different regions and countries within the UK allows policymakers to identify areas of strength and weakness, target support to those most in need, and develop policies that promote balanced and sustainable growth. Businesses can also use this information to make informed decisions about investment, expansion, and resource allocation. In recent years, the UK Office for National Statistics (ONS) has significantly invested in the development of new and novel sub-national statistics to support economic analysis and insight at a regional and country level. One of these innovations was the introduction of experimental Quarterly Country and Regional Gross Domestic Product (QCRGDP) estimates in 2019. These aimed to provide detailed, timely insights into economic performance at a regional level. However, despite initial success, the series faced some challenges that led to a temporary suspension in 2023. ESCoE was then commissioned to complete a review of its methods and processes. This report provides findings from the review, showing how the experimental nature of the series, coupled with its reliance on administrative data, gave rise to some challenges. It then outlines several recommendations to address these issues and rebuild user confidence. |
| Keywords: | sub-national statistics; regional indicators; GDP; regional GDP |
| JEL: | E01 R11 R12 |
| Date: | 2025–03–31 |
| URL: | https://d.repec.org/n?u=RePEc:eoe:escoet:escoe-tr-27 |
| By: | Rossi-Hansberg, Esteban; Zhang, Jialing |
| Abstract: | We use high-resolution spatial data to build a novel global annual gridded GDP dataset at 1°, 0.5°, and 0.25° resolutions from 2012 onward. Our random forest model trained on local and national GDP achieves an R² above 0.92 for GDP levels and above 0.62 for annual changes in regions left out of the training sample. By incorporating diverse indicators beyond population and nighttime lights, our estimates offer more precise subnational GDP measurements for analyzing economic shocks, local policies, and regional disparities. We evaluate the precision of our estimates with a sample case of COVID-19’s impact on local GDP in China. |
| JEL: | E0 F0 R0 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:20023 |
| By: | Ziang Qiu (Faculty of Business Administration, University of Macau); Baibing Huang (School of Liberal Arts, Macau University of Science and Technology, Macao SAR, China); Yang Zhang (Faculty of Business Administration, University of Macau; Asia-Pacific Academy of Economics and Management, University of Macau, Macao SAR, China) |
| Abstract: | The development of the digital economy has the potential to impact resource allocation efficiency within a region. This study examines the direct and spatial effects of digital economy development on the location choice of foreign direct investment (FDI) in Chinese cities. The findings indicate that digital economy development not only enhances the inflow of foreign direct investment within a region but also influences FDI inflows in neighboring regions, with spillover effects diminishing as geographical distance increases. To address endogeneity concerns, staggered Difference-inDifferences (DID) and spatial DID models are introduced in an event study to validate our main findings. Moreover, regional heterogeneity analysis reveals that the impact of digital economy development on FDI location decisions is particularly significant in eastern and coastal cities. The results offer an empirical foundation for emerging market countries, such as China, to advance sustainable digital economy development, enhance resource allocation efficiency, and support foreign investors in making informed investment location decisions. |
| Keywords: | Digital Economy; FDI Location; Spatial Effect; Spillovers; Emerging Markets |
| JEL: | F23 O33 R12 |
| Date: | 2026–07 |
| URL: | https://d.repec.org/n?u=RePEc:boa:wpaper:202642 |
| By: | Conti, Laura; Francesconi, Marco; Papini, Giulio; Serafinelli, Michel |
| Abstract: | This paper shows how the local labor market (LLM) responds to changes in touristic attractiveness, leveraging a unique classification of Italian localities based on their main touristic assets and aggregate trends in foreign tourists' choices in a shift-share research design. Looking at all LLMs, we find a strong positive relationship between changes in attractiveness and changes in the local tourism-related economic activity, tourism expenditure, and tourism employment, but no effect on total employment. In high-unemployment LLMs, however, we find a sizable overall employment effect and large indirect effects generated through industries related to tourism and firms in the nontradable sector. |
| Keywords: | Tourism; Unemployment; Heterogeneity |
| JEL: | R11 J21 R12 R23 Z30 |
| Date: | 2025–05 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:20281 |
| By: | Chen, Ziyang; Combes, Pierre-Philippe; Démurger, Sylvie; Liu, Xiuyan |
| Abstract: | We document variations in real income for high-skilled, low-skilled, and rural migrant households across Chinese cities. Using comprehensive data on land parcel transactions along with individual data for land development and household expenditure, we construct a city-specific housing cost index and assess how it varies across locations. All three components of housing costs –unit land prices, land share in construction, and housing share in expenditure– decrease from city centres to the periphery, increase with city population, and decrease with city land area, as predicted by theory. Overall, housing costs in China are high and vary widely between locations. While income gains outweigh housing costs when moving from smaller to larger cities, in the largest cities, housing costs begin to dominate, particularly for low-skilled and rural migrant households. This suggests a bell-shaped relationship between real income and city population in China, aligning with theoretical predictions. |
| Keywords: | Housing costs; Income disparities; Land use regulation; City size; Quality of life; Agglomeration economies; China |
| JEL: | O18 R21 R23 R31 R52 O53 |
| Date: | 2025–03 |
| URL: | https://d.repec.org/n?u=RePEc:cpr:ceprdp:20011 |