- Scott de Marchi. 2026. Linking Theory and Empirics: The Importance of Research Communities. The Oxford Handbook of Engaged Methodological Pluralism in Political Science.
- Scott de Marchi (with Max Gallop, Libby Jenke, and Scott Page). 2026. Prediction and Cumulative Knowledge in the Social Sciences. Cambridge University Press (Strategies for Social Inquiry series). Forthcoming..
- Scott de Marchi (with Alan van Beek and Max Gallop). 2026. Rashomon Histories: What the Data Support Is Bigger Than What We Report. Under review.
- Scott de Marchi (with Ha Eun Choi, Max Gallop, and Shahryar Minhas). 2025. Decisive or Distracted: The Effects of United States Constraint on Security Networks. British Journal of Political Science.
- Scott de Marchi (with Michael Laver and Georg Vanberg). 2025. Government Formation in the Shadow of an Uncertain Future Election. Edward Elgar Handbook of Coalition Politics.
- Scott de Marchi (with Ha Eun Choi, Max Gallop, and Shahryar Minhas). 2025. Replication Data for Decisive or Distracted: The Effects of United States Constraint on Security Networks. British Journal of Political Science — Harvard Dataverse.
- Scott de Marchi (with Kenneth Benoit, Conor Laver, Michael Laver, and Jinshuai Ma). 2025. Using Large Language Models to Analyze Political Texts Through Natural Language Understanding. American Journal of Political Science.
- Scott de Marchi (with Kathryn Cochran, Max Gallop, and John Nagl). 2024. Nuclear and Conventional Deterrence in Theory and Practice. OSF Preprints (SocArXiv).
- Scott de Marchi (with Michael Laver). 2023. Replication Data for The Governance Cycle in Parliamentary Democracies. Cambridge University Press.
- Scott de Marchi (with Michael Laver). 2023. The Governance Cycle in Parliamentary Democracies: A Computational Social Science Approach. Cambridge University Press (Studies in Comparative Politics).
- Scott de Marchi. 2022. The Complexity of Polarization. Proceedings of the National Academy of Sciences.
- Scott de Marchi (with Spencer Dorsey and Michael Ensley). 2021. Policy and the Structure of Roll Call Voting in the US House. Journal of Public Policy.
- Scott de Marchi (with Spencer Dorsey and Michael Ensley). 2021. Replication Data for Policy and the Structure of Roll Call Voting in the US House. Journal of Public Policy — Harvard Dataverse.
- Scott de Marchi (with Brandon Stewart). 2020. Computational and Machine Learning Models: The Necessity of Connecting Theory and Empirics. Sage Handbook of Research Methods in Political Science.
- Scott de Marchi (with Michael Laver). 2020. Government Formation as Logrolling in High-Dimensional Issue Spaces. Journal of Politics.
- Scott de Marchi (with Michael Laver). 2020. Replication Data for Government Formation as Logrolling in High-Dimensional Issue Spaces. Journal of Politics.
- Scott de Marchi (with Josh Cutler, Max Gallop, Florian Hollenbach, Michael Laver, and Matthias Orlowski). 2016. Cabinet Formation and Portfolio Distribution in European Multi-party Systems. British Journal of Political Science.
- Scott de Marchi (with Scott Page). 2013. Agent Based Models. Annual Review of Political Science.
- Scott de Marchi (with Terry Sullivan). 2011. Congressional Bargaining in Presidential Time: Give and Take, Anticipation, and the Constitutional Rationalization of Dead Ducks. Journal of Politics.
- Scott de Marchi (with Michael Laver and Hande Mutlu). 2010. Negotiation in Legislatures over Government Formation. Public Choice.
- Scott de Marchi (with Michael Ensley and Michael Tofias). 2009. District Complexity as an Advantage in Congressional Elections. American Journal of Political Science. Reprinted in the AJPS Congressional Elections special issue..
- Scott de Marchi (with Scott Page). 2008. Computational and Agent Based Models. Oxford Handbook of Political Science Methodology.
- Scott de Marchi (with Michael Ensley and Michael Munger). 2008. Costly Search and the Advantages of Incumbency: Some Experimental Results. Public Choice.
- Scott de Marchi (with James Hamilton). 2006. Trust, but Verify: Assessing the Accuracy of Self-reported Pollution Data. Journal of Risk and Uncertainty.
- Scott de Marchi. 2005. Computational and Mathematical Modeling in the Social Sciences. Cambridge University Press.
- Scott de Marchi (with Chris Gelpi and Jeff Grynaviski). 2004. Untangling Neural Networks. American Political Science Review, 98(2).
- Scott de Marchi (with Brandice Canes-Wrone). 2002. The President's Ability to Capitalize on Approval for Legislative Success. Journal of Politics, 64(2).
- Scott de Marchi. 1999. Adaptive Models and Electoral Instability. Journal of Theoretical Politics, 11(3): 393-419.