Publications

Working papers

Avalos, C., Wang, Y., & Shryane, N. Generalizing food labelling trials under unmeasured confounding: A doubly robust BART approach with synthetic cognitive proxies. (Under review, Journal of the Royal Statistical Society: Series A)
Perez Ruiz, D., & Avalos, C. How Much Non-Probability Data Is Enough? An Entropy-Based Stopping Rule for Sample Integration with an Application to Political Efficacy in the ANES 2012. (Submitted, Survey Research Methods)
Avalos, C. Estimating the population health and economic burden of food labelling policy in England: A microsimulation approach with causal generalisation. (In preparation)

Avalos, C., Wang, Y., & Shryane, N. (2026). Food label readability and consumption frequency: Isolating content-specific effects via a non-equivalent dependent variable design. Nutrients, 18(2), 197. https://www.mdpi.com/2072-6643/18/2/197
Avalos, C. (2025). Food label granularity and working memory: Effects on food choice in a randomised controlled trial. Journal of Health, Population and Nutrition, 44, 375. https://link.springer.com/article/10.1186/s41043-025-01076-x

FAO (2019). World Programme for the Census of Agriculture 2020, Vols 1 & 2. Chilean case study.
INE Chile (2018). Statistical Yearbook 2018 — National Agricultural Statistics chapter.
INE Chile (2018). Bulletin of Livestock, Crop, and Dairy Food Industry Statistics.