demographic modeling and climate adaptation

Neueste Paper

• The average-farmer illusion in language-model simulations of agricultural decisions

  Zhanliang Zhu, Ziwei Li, Yuchen Liu, Liujun Zhu, Ruiqi Wu, Tongqing Shen, Junliang Jin, Jianyun Zhang · 15. September 2026

  Language-model agents are increasingly used as synthetic people in surveys and social simulations, yet their apparent realism is often judged from population averages or distributional similarity. We tested what such evidence actually establishes by comparing Claude, Codex and Kimi under four prespe…

• Births are difficult to predict even with rich survey and full-population register data

  Elizaveta Sivak, Emily M. Cantrell, Thomas Emery, Javier Garcia-Bernardo, Flavio Hafner, Kasia Karpinska, Malte L\"uken, Adrienne Mendrik, Joris Mulder, Hanzhang Ren, Varun Satish, Mark Verhagen, Angelica M. Maineri, Paulina Pankowska, Jasmin Abdel Ghany, Bruno Arpino, Giovanni Cassani, Julia Hellstrand, Katya Ivanova, Sanni Kuikka, Ana Macanovic, Charles Rahal, Felix C. Tropf, Roland J. Veen, Nicole Walasek, Dani\"el van Wijk, Kelsey Q. Wright, Emilio Zagheni, Henry Abbink, Emanuele Aliverti, Matteo Amestoy, Tilbe Atav, Nicola Barban, Sunnee Billingsley, Goan J. Booij, Louis Boucherie, Yael Broos, Li Ya Chang, Jamie C. Chiu, Chiara Ludovica Comolli, Boris Cule, Qixiang Fang, Dennis M. Feehan, Rachel Ganly, Erwin Gielens, Rolando M. Gonzales Martinez, Andrea Gradassi, Rosember Guerra-Urzola, Mario Guerra-Urzola, St\'ephane Guerrier, Enamul Hassan, Vincent A. Haverhoek, Andrew T. Hendrickson, Amber Howard, Yuxuan Jin, Sayash Kapoor, Erik-Jan van Kesteren, Iris ten Klooster, Marie Labussiere, Lydia T. Liu, Tiffany Liu, Adam Maghout, Simone Meneghello, Lasse Mohr, Clara H. Mulder, Saul J. Newman, Jessica Nis\'en, Janis Norden, Mikkel Odgaard, Riccardo Omenti, Ozancan Ozdemir, Christina Pao, Paige Park, Gaia Penta, Juan C. Perdomo, Tanzir Pial, Alessio Piraccini, Federica Querin, Ziwei Rao, Christian Rellama, Adrien Remund, Frederieke Richert, Arnout van de Rijt, Mojtaba Rostami Kandroodi, Stijn J. Rotman, Lucas Sage, Germans Savcisens, Katrin Schwanitz, Steven Skiena, Alessandro Spata, Yannick Stadtfeld, Benedikt Stroebl, Gaetano Tedesco, Mathilde Theelen, Gianluca Tori, Abigail Tun-Mendicuti, Rishabh Tyagi, Keyon Vafa, Luiz Felipe Vecchietti, Linda Vecgaile, Willem R. J. Vermeulen, Maria-Pia Victoria Feser, Lionel A. Voirol, Thom B. Volker, Xinran Wang, Jiani Yan, Xinyi Zhao, Flora Zhou, Zuzana Zilincikova, Malvina Nissim, Matthew J. Salganik, Gert Stulp · 2. September 2026

  Major life events have proven difficult to predict. Does this reflect limits of theory, data, and algorithms, or the large role of chance? We examine one outcome - having a child within three years - through a near-ideal setting for prediction: a data challenge where 147 researchers predicted births…

• Animarium: an open, reproducible pipeline for synthetic populations of Italian cities, from ISTAT sources to open data (Tech Report v1)

  Mirko Degli Esposti · 28. August 2026

  Synthetic populations of eleven Italian municipalities (1,814,317 individuals in 887,937 households) generated from published aggregates alone: ISTAT census and register tables, census-section counts, the national civic-address register, public-use survey microdata, and six municipal open-data porta…

• Eco3S: Complex Socio-Economic System Simulation via Agent-Based Models

  Shaopeng Wei, Yufei Cheng, Wenxi Sun, Yepeng Ding, Yu Zhao, Gang Kou · 30. Juli 2026

  The rapid development of large language models (LLMs) has renewed interest in agent-based modeling (ABM). However, current LLM-based ABM research faces several key challenges: modeling evolving agent-environment interactions, enabling flexible counterfactual reasoning, and automating simulation work…

• Deep and diverse population synthesis for multi-person households using generative models with conditional inputs

  Hai Yang, Hongying Wu, Linfei Yuan, Xiyuan Ren, Joseph Y. J. Chow, Jinqin Gao, Kaan Ozbay · 8. Juli 2026

  Traditional methods of population synthesis produce stable and interpretable populations but cannot capture the interrelationships between household- and individual-level attributes. Recent deep learning methods offer this flexibility, yet can overfit high-dimensional attribute relationships without…

• Crafting Desirable Climate Trajectories with RL Explored Socio-Environmental Simulations

  James Rudd-Jones, Fiona Thendean, Mar\'ia P\'erez-Ortiz · 29. Mai 2026

  Climate change poses an existential threat, necessitating effective climate policies to enact impactful change. Decisions in this domain are incredibly complex, involving conflicting entities and evidence. In the last decades, policymakers increasingly use simulations and computational methods to gu…

• Using Zero-Shot LLM-Generated Survey Data for Geographically Explicit Population Synthesis

  Taylor Anderson, Sara Von Hoene, Orhan Yagizer Cinar, Emma Von Hoene, Amira Roess, Andrew Crooks, Hamdi Kavak · 28. Mai 2026

  There is a growing interest in utilizing synthetic populations for a diverse range of applications. At the same time, we are witnessing a tremendous growth in artificial intelligence in all walks of life. This paper evaluates whether zero-shot large language model (LLM)-generated health survey data …

• Benchmarking LLMs for Community Governance Simulation with Life-history Narratives

  Xu Chen, Yuanzi Li, Lei Wang, Nan Lu, Yang Wang, Anding Wang, Lei Shi, Xiaoxing Fu, Ji-Rong Wen · 25. Mai 2026

  Effective community governance hinges on understanding what specific residents think and need. Recent work has used large language models (LLMs) to simulate human respondents, offering a scalable, reproducible way to study human attitudes and behaviors at low cost. However, these studies typically p…

• SAGA: A Sequence-Adaptive Generative Architecture for Multi-Horizon Probabilistic Forecasting with Adaptive Temporal Conformal Prediction

  Gustav Olaf Yunus Laitinen-Fredriksson Lundstr\"om-Imanov, Hafize Gonca C\"omert · 20. Mai 2026

  Microsimulation models used by ministries of finance and central banks rely on parametric processes for lifetime earnings that capture only first and second moments of the conditional distribution and miss long-range nonlinear structure. We propose SAGA, a decoder-only transformer for irregular tabu…

• We Need Strong Preconditions For Using Simulations In Policy

  Steven Luo, Saanvi Arora, Carlos Guirado · 10. April 2026

  Simulations, and more recently LLM agent simulations, have been adopted as useful tools for policymakers to explore interventions, rehearse potential scenarios, and forecast outcomes. While LLM simulations have enormous potential, two critical challenges remain understudied: the dual-use potential o…

• Scalable Maximum Entropy Population Synthesis via Persistent Contrastive Divergence

  Mirko Degli Esposti · 31. März 2026

  Maximum entropy (MaxEnt) modelling provides a principled framework for generating synthetic populations from aggregate census data, without access to individual-level microdata. The bottleneck of existing approaches is exact expectation computation, which requires summing over the full tuple space $…

• Maximum Entropy Relaxation of Multi-Way Cardinality Constraints for Synthetic Population Generation

  Fran\c{c}ois Pachet, Jean-Daniel Zucker · 25. März 2026

  Generating synthetic populations from aggregate statistics is a core component of microsimulation, agent-based modeling, policy analysis, and privacy-preserving data release. Beyond classical census marginals, many applications require matching heterogeneous unary, binary, and ternary constraints de…

• No Text Needed: Forecasting MT Quality and Inequity from Fertility and Metadata

  Jessica M. Lundin, Ada Zhang, David Adelani, Cody Carroll · 4. März 2026

  We show that translation quality can be predicted with surprising accuracy \textit{without ever running the translation system itself}. Using only a handful of features, token fertility ratios, token counts, and basic linguistic metadata (language family, script, and region), we can forecast ChrF sc…

• Inferring stochastic dynamics with growth from cross-sectional data

  Stephen Zhang, Suryanarayana Maddu, Xiaojie Qiu, Victor Chard\`es · 4. Februar 2026

  Time-resolved single-cell omics data offers high-throughput, genome-wide measurements of cellular states, which are instrumental to reverse-engineer the processes underpinning cell fate. Such technologies are inherently destructive, allowing only cross-sectional measurements of the underlying stocha…

• Predicting Long-Term Self-Rated Health in Small Areas Using Ordinal Regression and Microsimulation

  Se\'an Caulfield Curley, Karl Mason, Patrick Mannion · 22. Januar 2026

  This paper presents an approach for predicting the self-rated health of individuals in a future population utilising the individuals' socio-economic characteristics. An open-source microsimulation is used to project Ireland's population into the future where each individual is defined by a number of…

• Ireland in 2057: Projections using a Geographically Diverse Dynamic Microsimulation

  Se\'an Caulfield Curley, Karl Mason, Patrick Mannion · 21. Januar 2026

  This paper presents a dynamic microsimulation model developed for Ireland, designed to simulate key demographic processes and individual life-course transitions from 2022 to 2057. The model captures four primary events: births, deaths, internal migration, and international migration, enabling a comp…

• Exact Synthetic Populations for Scalable Societal and Market Modeling

  Thierry Petit, Arnault Pachot · 9. Dezember 2025

  We introduce a constraint-programming framework for generating synthetic populations that reproduce target statistics with high precision while enforcing full individual consistency. Unlike data-driven approaches that infer distributions from samples, our method directly encodes aggregated statistic…