|
on Economic Geography |
Issue of 2024‒04‒01
nine papers chosen by Andreas Koch, Institut für Angewandte Wirtschaftsforschung |
By: | Klaus Desmet; Esteban Rossi-Hansberg |
Abstract: | With average temperature ranging from -20°C at the North Pole to 30°C at the Equator and with global warming expected to reach 1.4°C to 4.5°C by the year 2100, it is clear that climate change will have vastly different effects across the globe. Given the abundance of land in northern latitudes, if population and economic activity could freely move across space, the economic cost of global warming would be greatly reduced. But spatial frictions are real: migrants face barriers, trade and transportation are costly, physical infrastructure is not footloose, and knowledge embedded in clusters of economic activity diffuses only imperfectly. Thus, the economic cost of climate change is intimately connected to these spatial frictions. Building on earlier integrated assessment models that largely ignored space, in the past decade there has been significant progress in developing dynamic spatial integrated assessment models (S-IAMs) aimed at providing a more realistic evaluation of the economic cost of climate change, both locally and globally. This review article discusses this progress and provides a guide for future work in this area. |
JEL: | F1 Q5 R0 |
Date: | 2024–03 |
URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:32197&r=geo |
By: | Luca, Davide |
Abstract: | Despite a large body of work on the impacts of institutions on subnational growth and development, economic geographers have, in the last decades, frequently overlooked the role of politics and, in particular, that of national political economies. Drawing on the political science literature, the paper argues that studying national political dynamics is still key to understand the cumulative process of uneven regional development. Using data from Turkey over the period 2004-2016, the paper shows how national electoral politics and government actions have significantly affected provincial growth patterns. The impact is substantive and increases in election years. Results also suggest that the central government may have influenced sub-national growth trajectories in different ways, including boosting the construction sector and expanding public employment. |
Keywords: | politics of development; electoral politics; distributive politics; regional economic growth; Turkey |
JEL: | C20 D72 H73 O18 O40 R11 |
Date: | 2022–07–01 |
URL: | http://d.repec.org/n?u=RePEc:ehl:lserod:112682&r=geo |
By: | Calignano, Giuseppe (Inland Norway University of Applied Sciences); Nilsen, Trond (Inland Norway University of Applied Sciences) |
Abstract: | The study of agency has received increasing attention in recent years. The focus on change processes at the micro-level has brought new insights into the field of regional development. However, in debates about change and regional development, agents and leaders themselves have received far less attention than agency as a process. We provide an analytical model to show how political leaders and their leadership act as drivers of change through what we call actor properties (i.e., knowledge, networks and resources). We discuss how actor properties interact with the institutional context in which leaders operate and the various transitions from a political leader's legitimacy to the legacy of their political action. Empirical investigations of two peripheral regions in Italy and Norway illustrate how political leaders act as agents of change in geographical areas characterized by different socioeconomic and institutional contexts. |
Keywords: | Human agency; political leaders; place-based leadership; regional development; development paths; analytical framework |
JEL: | R00 R10 R50 |
Date: | 2024–03–05 |
URL: | http://d.repec.org/n?u=RePEc:hhs:lucirc:2024_004&r=geo |
By: | Füner, Lena; Berger, Marius; Bersch, Johannes; Hottenrott, Hanna |
Abstract: | New business formation is a key driver of regional transformation and development. While we know that a region's attractiveness for new businesses depends on its resources, infrastructure, and human capital, we know little about the role of local business networks in promoting or impeding the birth of new firms. We construct local business networks connecting more than 350 million nodes consisting of managers, owners and firms using administrative data on all German businesses from 2002 to 2020. Differentiating between serial and de-novo entrepreneurs, we show a positive but decreasing relation between a region's connectedness and firm entry of serial entrepreneurs. Networks are, moreover, positively linked to firm survival. Relating our findings to a measure of ownership concentration, we show that networks provide additional explanations for regional variation in new business formations. These patterns are robust to synthetic instrumental variable estimations |
Keywords: | New Firm Formation, Business Networks, Serial Entrepreneurship, RegionalDynamics, Ownership Concentration |
JEL: | L14 L26 M13 O31 |
Date: | 2023 |
URL: | http://d.repec.org/n?u=RePEc:zbw:zewdip:283589&r=geo |
By: | Mehmet Selman Colak; Sumeyra Korkmaz; Huseyin Ozturk; Muhammed Hasan Yilmaz |
Abstract: | [EN] This paper studies the peer effects on emerging markets credit default swap (CDS) premia. Unlike various other spillover models, spatial econometrics is used to distinguish between direct (countryspecific) and indirect (non-country specific) effects on the CDS premia. This strategy enables us to investigate non-country specific channels driving the shifts in sovereign credit risk. On top of documenting statistically significant spatial interactions, the paper finds that indirect effects are nearly as important as the direct ones in explaining the CDS movements. The findings are robust to a set of additional analyses. This study emphasizes that caution is warranted in using CDS premium as a sovereign risk indicator. [TR] Bu calismada, gelismekte olan ulkelerin kredi temerrut takasi (CDS) primlerindeki akran etkileri incelenmektedir. Diger cesitli yayilim modellerinin aksine, CDS primleri uzerindeki dogrudan (ulkeye ozgu olan) ve dolayli (ulkeye ozgu olmayan) etkilerin ayristirilmasinda mekânsal ekonometrik yontemlerden faydalanilmaktadir. Bu strateji, ulke kredi riskinde degisimlere yol acan ulke-disi belirli kanallarin incelenmesine olanak saglamaktadir. Ýstatistiki olarak anlamli mekânsal etkilesimleri belgelemesinin yani sira, calisma CDS hareketlerini aciklamada dolayli etkilerin neredeyse dogrudan etkiler kadar onemli oldugunu ortaya koymaktadir. Bulgular bir dizi ek analize karsi saglamdir. Bu calisma CDS priminin ulke kredi riskini temsilen gosterge olarak kullaniminda dikkatli olunmasi gerektigine vurgu yapmaktadir. |
Date: | 2024 |
URL: | http://d.repec.org/n?u=RePEc:tcb:econot:2406&r=geo |
By: | Peiffer-Smadja, Océane; Mitra, Alessio; Ravet, Julien; Di Girolamo, Valentina |
Abstract: | This paper uses multiple linear and fractional probit regressions to assess the importance of regional research capacities and assets, as well as intrinsic characteristics of the regions in defining success in the European R&I Framework Programme. We find that quality of research outputs matters more than quantity, particularly in projects targeting societal challenges, while quality of patenting activity matters more than quantity, particularly in projects targeting industrial objectives. Less-developed regions benefit from improved institutions, while advanced regions gain from increased R&D and human resources investments. We provide recommendations on how regions can improve their capacity to participate in the EU FP for R&I. |
Keywords: | European R&I Framework Programme, Regional innovation |
JEL: | O38 R58 |
Date: | 2023 |
URL: | http://d.repec.org/n?u=RePEc:zbw:esprep:283908&r=geo |
By: | García-Suaza, Andres (Facultad de Economía Universidad del Rosario); Varela, Daniela (Universidad del Rosario) |
Abstract: | Monitoring patterns of segregation and inequality at small area geographic levels is extremely costly. However, the increased availability of data through nontraditional sources such as satellite imagery facilitates this task. This paper assess the relevance of data from nightlight and day-time satellite imagery as well as building footprints and localization of points of interest for mapping variability in socioeconomic outcomes, i.e., household income, labor formality, life quality perception and household informality. The outcomes are computed at a granular level by combining census data, survey data, and small area estimation. The results reveal that non traditional sources are important to predict spatial differences socio-economic outcomes. Furthermore, the combination of all sources creates complementarities that enable a more accurate spatial distribution of the studied variables. |
Keywords: | Remote sensing; Satellite imagery; nightlights; points of interest; spatial segregation; urban footprints; informal housing. |
JEL: | C21 E26 R12 |
Date: | 2024–02–13 |
URL: | http://d.repec.org/n?u=RePEc:col:000092:021025&r=geo |
By: | Andreas Ferrara; Patrick A. Testa; Liyang Zhou |
Abstract: | In applied historical research, geographic units often differ in level of aggregation across datasets. One solution is to use crosswalks that associate factors located within one geographic unit to another, based on their relative areas. We develop an alternative approach based on relative populations, which accounts for heterogeneities in urbanization within counties. We construct population-based crosswalks for 1790 through 2020, which map county-level data across U.S. censuses, as well as from counties to congressional districts. Using official census data for congressional districts, we show that population-based weights outperform area-based ones in terms of similarity to official data. |
JEL: | N01 N9 R12 |
Date: | 2024–03 |
URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:32206&r=geo |
By: | John D. Huber; Laura Mayoral |
Abstract: | We develop a novel methodology that uses machine learning to produce accurate estimates of consumption per capita and poverty in 10x10km cells in sub-Saharan Africa over time. Using the new data, we revisit two prominent papers that examine the effect of institutions on economic development, both of which use “nightlights” as a proxy for development. The conclusions from these papers are reversed when we substitute the new consumption data for nightlights. We argue that the different conclusions about institutions are due to a previously unrecognized problem that is endemic when nightlights are used as a proxy for spatial economic well-being: nightlights suffer from nonclassical measurement error. This error will typically lead to biased estimates in standard statistical models that use nightlights as a spatially disaggregated measure of economic development. The bias can be either positive or negative, and it can appear when nightlights are used as either a dependent or an independent variable. Our research therefore underscores an important limitation in the use of nightlights, which has become the standard measure of spatial economic well-being for studies focusing on developing parts of the world. It also demonstrates how machine learning models can generate a useful alternative to nightlights, with important implications for the conclusions we draw from the analyses in which such data are employed. |
Keywords: | economic develpment, poverty, institutions, nightlights, nonclassical measurement error, machine learning |
JEL: | C01 P46 P48 |
Date: | 2024–02 |
URL: | http://d.repec.org/n?u=RePEc:bge:wpaper:1433&r=geo |