Sonia Laszlo

931 citations
25 papers · 554 · h-index 14

Impact in

Papers in

Sonia Laszlo

25 papers receiving 509 citations

Peers

Sonia Laszlo
Comparison fields: 5 of 94
  • General Decision Sciences 38
  • Safety Research 146
  • Business and International Management 23
  • Soil Science 90
  • General Agricultural and Biological Sciences 77
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Jessica Goldberg United States
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Simone Schaner United States
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Rachid Laajaj Colombia
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Citations per field
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Citations per year

Countries citing papers authored by Sonia Laszlo

Since Specialization
Citations

This map shows the geographic impact of Sonia Laszlo'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 Sonia Laszlo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sonia Laszlo more than expected).

Fields of papers citing papers by Sonia Laszlo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sonia Laszlo. 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 Sonia Laszlo. The network helps show where Sonia Laszlo may publish in the future.

Co-authors

The 25 scholars most cited alongside Sonia Laszlo, 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 Sonia Laszlo Line = papers co-authored together Sonia Laszlo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201970
2 202065
3 201164
4 201549
5 201341
6 201139
7 200733
8 202028
9 200527
10 201021
11 200821
12 200816
13 200513
14 200913
15 200912
16 201910
17 20179
18 20197
19
Risk preference, ambiguity aversion and technology choice: Experimental and survey evidence from rural peru
20066
20 20233

About Sonia Laszlo

Sonia Laszlo is a scholar working on Economics and Econometrics, Safety Research, Sociology and Political Science, General Agricultural and Biological Sciences and Soil Science, having authored 25 papers that have together received 554 indexed citations. Recurring topics across this work include Poverty, Education, and Child Welfare (6 papers), Experimental Behavioral Economics Studies (5 papers), Agricultural risk and resilience (5 papers), Agricultural Innovations and Practices (5 papers), Decision-Making and Behavioral Economics (4 papers), Taxation and Compliance Studies (4 papers), Economic and Environmental Valuation (4 papers) and Innovation and Socioeconomic Development (3 papers). The work is most often cited by research in General Decision Sciences (38 citations), Safety Research (146 citations), Business and International Management (23 citations), Soil Science (90 citations) and General Agricultural and Biological Sciences (77 citations). Sonia Laszlo has collaborated with scholars based in Canada, United States and Peru. Frequent co-authors include Javier Escobal, Jennifer Hunt, Franque Grimard, Jim Engle‐Warnick, Stella Muthuri, Shelley Clark, Caroline W. Kabiru, Tingting Zhang, Jennifer Hunt and Leroy E. Phillip. Their work appears in journals such as World Development, The B E Journal of Economic Analysis & Policy, Health Economics, Demography and The Journal of Development Studies.

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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