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What If Legislatures Looked Different? Simulating Counterfactual Representation

πŸ”¬ How counterfactual representation is simulated

This approach uses multilevel modeling and post-stratification to estimate how legislative outcomes would change under alternative representation rules. The method can simulate scenarios that, for example, boost the share of women in a legislature or change how votes translate into seats.

πŸ“Š How outcomes are estimated

  • Multilevel modeling and post-stratification (MRP/post-strat) are combined to produce estimates of legislators’ preferences and roll-call outcomes under different representation rules.
  • Counterfactual schemes considered include altering the demographic composition of delegations and converting votes into seats by party-proportional rules.

πŸ“Œ Applied questions

The technique is applied to two illustrative questions:

  • Would the U.S. Congress be less polarized if state delegations were formed according to the principle of party proportional representation?
  • Would there have been stronger support for legalizing same-sex marriage in the U.K. House of Commons if Parliament more closely reflected the population in gender and age?

πŸ’‘ Why this matters

  • Provides a practical toolkit for estimating the legislative consequences of alternative representation designs without needing real-world reform.
  • Enables direct comparison of institutional changes (seat allocation rules) and descriptive representation changes (gender and age composition) on policy-related outcomes.

πŸ“Ž What readers can expect

  • A clear description of the modeling and post-stratification workflow used to generate counterfactual legislatures.
  • Concrete applications showing how the method addresses questions about polarization and substantive representation in two well-known democracies.
Political Analysis
Simulating Counterfactual Representation was authored by Andrew Eggers and Benjamin Lauderdale. It was published in Pol. An. in 2016. Find on Google Scholar10.1093/pan/mpw005
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