Iván Torre

444 citations
37 papers · 199 · h-index 8

Impact in

Papers in

Iván Torre

27 papers receiving 176 citations

Peers

Iván Torre
Comparison fields: 5 of 50
  • Modeling and Simulation 48
  • Economics and Econometrics 104
  • Political Science and International Relations 39
  • Health 11
  • General Economics, Econometrics and Finance 12
Replace Surbhi Kesar with:
Surbhi Kesar India
Siddharth Kothari United States
Silvia De Poli Spain
Alberto Tumino United Kingdom
Rocco Zizzamia South Africa
Stefanie Haeffele-Balch United States
Wouter van der Wielen Belgium
Ömer Açıkgöz Türkiye
Rizwanul Islam Bangladesh
İsrael Nyaburi Nyadera Türkiye
Iván Torre relative to Surbhi Kesar India Surbhi Kesar's profile →
Citations per field
00.5×6.3×
Surbhi Kesar · 1×
Citations per year

Countries citing papers authored by Iván Torre

Since Specialization
Citations

This map shows the geographic impact of Iván Torre's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Iván Torre with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Iván Torre more than expected).

Fields of papers citing papers by Iván Torre

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Iván Torre. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Iván Torre. The network helps show where Iván Torre may publish in the future.

Co-authors

The 15 scholars most cited alongside Iván Torre, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Iván Torre Line = papers co-authored together Iván Torre links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202045
2 202130
3 202126
4 201613
5 202212
6 20209
7 20197
8 20237
9 20187
10 20236
11 20233
12 20223
13 20193
14 20193
15 20143
16 20223
17 20183
18
Does Job Polarization Explain the Rise in Earnings Inequality? Evidence from Europe
20182
19 20232
20 20232

About Iván Torre

Iván Torre is a scholar working on Economics and Econometrics, Political Science and International Relations, General Health Professions, Sociology and Political Science and Demography, having authored 37 papers that have together received 199 indexed citations. Recurring topics across this work include Social Policy and Reform Studies (12 papers), Employment and Welfare Studies (11 papers), Labor market dynamics and wage inequality (6 papers), COVID-19 Pandemic Impacts (5 papers), COVID-19 epidemiological studies (4 papers), Retirement, Disability, and Employment (4 papers), Income, Poverty, and Inequality (4 papers) and Local Government Finance and Decentralization (4 papers). The work is most often cited by research in Modeling and Simulation (48 citations), Economics and Econometrics (104 citations), Political Science and International Relations (39 citations), Health (11 citations) and General Economics, Econometrics and Finance (12 citations). Iván Torre has collaborated with scholars based in United States, France and Spain. Frequent co-authors include Michael Lokshin, Asli Demirgüç‐Kunt, Maurizio Bussolo, Ada Ferrer‐i‐Carbonell, Sebastián Galiani, Gustavo Torrens, Arti Grover Goswami, Zurab Sajaia, Hernán Winkler and Leonardo Iacovone. Their work appears in journals such as Review of Income and Wealth, Economics and Politics, World Development, Journal of International Economics and Journal of Comparative Economics.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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