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Regional Economics and Spatial Analysis

Regional Economics and Spatial Analysis is a research topic within Economics and Econometrics. Science Explorer counts 16k research works in it since 1950. 48.7% of them reached the world's top 10% most cited for their field and year.

This cluster of papers explores the spatial economics and agglomeration theory, focusing on topics such as agglomeration economies, urbanization, economic geography, regional development, transportation, city size distribution, human capital externalities, polycentric urban regions, and industrial clusters.

  • Agglomeration Economies
  • Urbanization
  • Economic Geography
  • Spatial Structure
  • Regional Development
  • Transportation
  • City Size Distribution
  • Human Capital Externalities
  • Polycentric Urban Regions
  • Industrial Clusters
Research works
16k
fractional, since 1950
In the world top 10%
8k
per year above
Top-10% rate
48.7%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+11%
the tick is no change

Which countries lead Regional Economics and Spatial Analysis research?

By volume, China and the United States publish the most (944 and 364 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 944 works
  2. 2 United States 364 works
  3. 3 Italy 154 works
  4. 4 United Kingdom 113 works
  5. 5 Russia 88 works
  6. 6 Japan 81 works
  7. 7 Germany 79 works
  8. 8 Spain 63 works
  9. 9 France 59 works
  10. 10 Brazil 46 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 47.4%United States: 18.3%Italy: 7.7%United Kingdom: 5.7%6 others listed: 20.9%47%largest
China944 · 47.4%United States364 · 18.3%Italy154 · 7.7%United Kingdom113 · 5.7%6 others listed416 · 20.9%

Shares of the rows listed above, not of the whole node.

Which institutions lead Regional Economics and Spatial Analysis research?

By volume in 2022–2025, Peking University publishes the most Regional Economics and Spatial Analysis research, followed by Politecnico di Milano and East China Normal University.

Who are the leading researchers in Regional Economics and Spatial Analysis?

The most-cited researchers publishing on Regional Economics and Spatial Analysis include M. Hashem Pesaran, Paúl Krugman and David B. Audretsch.

  1. 1 M. Hashem Pesaran United States 9.1k citations
  2. 2 Paúl Krugman United States 4.4k citations
  3. 3 David B. Audretsch United States 3.7k citations
  4. 4 David Autor United States 3k citations
  5. 5 Edward L. Glaeser United States 3k citations
  6. 6 Luc Anselin United States 2.7k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Regional Economics and Spatial Analysis research done?

The largest centres of Regional Economics and Spatial Analysis research in 2022–2025 are Beijing (China), Shanghai (China), Nanjing (China) and Wuhan (China). Among places with at least 20 works in it, it is an unusually large share of all research in Milan.

Largest cities, 2022–2025

  1. 1 Beijing China 191 works
  2. 2 Shanghai China 82 works
  3. 3 Nanjing China 71 works
  4. 4 Wuhan China 51 works
  5. 5 Guangzhou China 48 works
  6. 6 Hangzhou China 46 works
  7. 7 Moscow Russia 35 works
  8. 8 London United Kingdom 35 works
  9. 9 Milan Italy 29 works
  10. 10 Chongqing China 28 works

Where it is the local speciality

  1. MilanIT · 28.9 works3.8×
← less than its size predictsmore →

Location quotient: how much more of its research is in Regional Economics and Spatial Analysis than the world average.

See Regional Economics and Spatial Analysis on the map

Where is the best place to study Regional Economics and Spatial Analysis?

Among universities, judged by research, Politecnico di Milano, East China Normal University and Renmin University of China score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%50%100%mean 64.13%fractional works in this node (log) →share in the world top 10% →Politecnico di Milano: 18, 73.3%East China Normal University: 16, 71.8%Renmin University of China: 13, 69.3%Peking University: 24, 60.3%Capital University of Economics and Business: 10, 58.1%London School of Economics and Political Science: 10, 57.3%Shanghai University of Finance and Economics: 11, 55.0%Wuhan University: 12, 72.7%Southwestern University of Finance and Economics: 8, 53.7%Nanjing University: 9, 69.8%Politecnico di MilanoEast China Normal Un…Renmin University of…Peking University
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 Politecnico di MilanoItaly 77.773.3%10.0×18 -6.4%
2 East China Normal UniversityChina 71.871.8%13.1×16 -18.9%
3 Renmin University of ChinaChina 68.169.3%15.6×13 +18.3%
4 Peking UniversityChina 62.360.3%6.1×24 +25.8%
5 Capital University of Economics and BusinessChina 56.258.1%51.6×10 +69.5%
6 London School of Economics and Political ScienceUnited Kingdom 56.057.3%16.1×10 -11.8%
7 Shanghai University of Finance and EconomicsChina 54.655.0%41.9×11 +13.9%
8 Wuhan UniversityChina 50.572.7%3.7×12 +55.2%
9 Southwestern University of Finance and EconomicsChina 48.653.7%22.0×8 +22.2%
10 Nanjing UniversityChina 46.869.8%4.6×9 +46.3%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Regional Economics and Spatial Analysis research growing?

Output in 2018–2022 was 11% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Regional Economics and Spatial Analysis.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.