Laron Williams

1.1k total citations
42 papers, 752 citations indexed

About

Laron Williams is a scholar working on Political Science and International Relations, Economics and Econometrics and Strategy and Management. According to data from OpenAlex, Laron Williams has authored 42 papers receiving a total of 752 indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Political Science and International Relations, 16 papers in Economics and Econometrics and 15 papers in Strategy and Management. Recurrent topics in Laron Williams's work include Electoral Systems and Political Participation (32 papers), Political Influence and Corporate Strategies (15 papers) and Fiscal Policies and Political Economy (10 papers). Laron Williams is often cited by papers focused on Electoral Systems and Political Participation (32 papers), Political Influence and Corporate Strategies (15 papers) and Fiscal Policies and Political Economy (10 papers). Laron Williams collaborates with scholars based in United States, Germany and Australia. Laron Williams's co-authors include Guy D. Whitten, Zeynep Somer‐Topcu, Mary Stegmaier, Michael T. Koch, Marc Debus, Jason M. Smith, Christopher Gandrud, David Fortunato, John D. Gerlach and Harvey D. Palmer and has published in prestigious journals such as American Journal of Political Science, The Journal of Politics and Public Opinion Quarterly.

In The Last Decade

Laron Williams

41 papers receiving 691 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Laron Williams United States 16 556 251 236 161 57 42 752
Cecilia Martínez‐Gallardo United States 12 555 1.0× 179 0.7× 229 1.0× 116 0.7× 17 0.3× 21 708
Svante Ersson Sweden 14 508 0.9× 111 0.4× 235 1.0× 112 0.7× 35 0.6× 43 653
Stefanie Bailer Switzerland 18 784 1.4× 105 0.4× 162 0.7× 339 2.1× 73 1.3× 44 935
Hee Min Kim United States 2 797 1.4× 113 0.5× 193 0.8× 305 1.9× 85 1.5× 3 901
Jaap Woldendorp Netherlands 10 461 0.8× 254 1.0× 145 0.6× 131 0.8× 18 0.3× 22 643
Alexander C. Tan New Zealand 10 336 0.6× 55 0.2× 207 0.9× 94 0.6× 55 1.0× 55 483
Klaus von Beyme Germany 19 912 1.6× 91 0.4× 432 1.8× 176 1.1× 63 1.1× 132 1.2k
Paul Mitchell United Kingdom 10 650 1.2× 101 0.4× 379 1.6× 127 0.8× 75 1.3× 26 844
Mona M. Lyne United States 4 476 0.9× 103 0.4× 390 1.7× 42 0.3× 27 0.5× 10 643
Luis Fernando Medina United States 6 518 0.9× 125 0.5× 486 2.1× 43 0.3× 30 0.5× 15 753

Countries citing papers authored by Laron Williams

Since Specialization
Citations

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

Fields of papers citing papers by Laron Williams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Laron Williams

This figure shows the co-authorship network connecting the top 25 collaborators of Laron Williams. A scholar is included among the top collaborators of Laron Williams based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Laron Williams. Laron Williams is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Fortunato, David, et al.. (2025). Voters' Perceptions of Party Brands. Cambridge University Press eBooks. 1 indexed citations
2.
Lipsmeyer, Christine S., et al.. (2024). Look over there. Where? A compositional approach to the modeling of public opinion on the most important problem. Social Science Quarterly. 105(4). 913–933.
3.
Yıldırım, Tevfik Murat & Laron Williams. (2024). Problem importance across time and space: updating the “Most Important Problem Dataset”. Journal of Elections Public Opinion and Parties. 35(4). 517–532. 1 indexed citations
4.
Fortunato, David, et al.. (2024). The economic roots of cross‐national similarity in voter preferences. American Journal of Political Science. 69(4). 1203–1217. 1 indexed citations
5.
Williams, Laron, et al.. (2021). Learning at Home and Abroad: How Competition Conditions the Diffusion of Party Strategies. British Journal of Political Science. 52(2). 593–612. 5 indexed citations
6.
Whitten, Guy D., et al.. (2020). X Marks the Spot: Unlocking the Treasure of Spatial-X Models. The Journal of Politics. 83(2). 722–739. 9 indexed citations
7.
Whitten, Guy D., et al.. (2019). Interpretation: the final spatial frontier. Political Science Research and Methods. 9(1). 140–156. 19 indexed citations
8.
Gandrud, Christopher, et al.. (2019). Taking Time (and Space) Seriously: How Scholars Falsely Infer Policy Diffusion from Model Misspecification. Policy Studies Journal. 49(2). 484–515. 14 indexed citations
9.
Fortunato, David, et al.. (2016). All Economics is Local: Spatial Aggregations of Economic Information. Political Science Research and Methods. 6(3). 467–487. 13 indexed citations
10.
Williams, Laron. (2016). Long-Term Effects in Models with Temporal Dependence. Political Analysis. 24(2). 243–262. 5 indexed citations
11.
Williams, Laron, et al.. (2015). You’ve Got Some Explaining To Do The Influence of Economic Conditions and Spatial Competition on Party Strategy. Political Science Research and Methods. 4(1). 47–63. 43 indexed citations
12.
Williams, Laron. (2015). Opposition Parties and the Timing of Successful No-Confidence Motions. Political Science Research and Methods. 4(3). 533–553. 11 indexed citations
13.
Williams, Laron. (2014). It's all relative: Spatial positioning of parties and ideological shifts. European Journal of Political Research. 54(1). 141–159. 39 indexed citations
14.
Somer‐Topcu, Zeynep & Laron Williams. (2013). Opposition party policy shifts in response to no‐confidence motions. European Journal of Political Research. 53(3). 600–616. 7 indexed citations
15.
Williams, Laron. (2013). Hawks, doves, and opportunistic opposition parties. Journal of Peace Research. 51(1). 111–125. 8 indexed citations
16.
Williams, Laron, et al.. (2013). Predictably Unpredictable: The Effects of Conflict Involvement on the Error Variance of Vote Models. British Journal of Political Science. 44(2). 287–299. 6 indexed citations
17.
Williams, Laron & Guy D. Whitten. (2011). Don't Stand So Close to Me: Spatial Contagion Effects and Party Competition. SSRN Electronic Journal. 1 indexed citations
18.
Williams, Laron. (2011). Unsuccessful Success? Failed No-Confidence Motions, Competence Signals, and Electoral Support. Comparative Political Studies. 44(11). 1474–1499. 32 indexed citations
19.
Williams, Laron, et al.. (2009). Democracy and Diversion: Government Arrangements, the Economy, and Dispute Initiation. Journal of Peace Research. 46(6). 777–798. 23 indexed citations
20.
Somer‐Topcu, Zeynep & Laron Williams. (2008). Survival of the Fittest? Cabinet Duration in Postcommunist Europe. Comparative Politics. 40(3). 313–329. 44 indexed citations

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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