Marcelo Gallardo | Searcharxiv

arXiv2026

Information and voting: Evidence from Peru's 2026 presidential election

We study how election-night flash estimates shape voting in Peru's fragmented 2026 presidential election. We exploit a natural experiment: on April 12, 2026, 187 polling tables across 13 voting centers failed to install, and the \emph{Jurado Nacional de Elecciones} (JNE) extended voting for the affected $\approx\!55 000$ electors to Monday, April 13. These voters cast ballots after observing the Ipsos and Datum flash estimates; otherwise comparable Sunday voters did not. A Bayesian-updating model of multi-candidate plurality voting frames the analysis, yielding predictions about vote reallocation toward the three candidates the estimates rendered viable -- L\'opez Aliaga, S\'anchez, and Nieto. We estimate treatment effects on candidate vote shares at both the \emph{acta} level and the acta-weighted polling-station level, comparing treated and control \emph{locales de votaci\'on} matched on pre-treatment covariates. How flash estimates reshape voting is of first-order importance for Peru, given its institutional instability and high political volatility over the past decade.

econ.EM↗

arXiv2024

Congestion and Penalization in Optimal Transport

We introduce a novel model based on the discrete optimal transport problem that incorporates congestion costs and replaces traditional constraints with weighted penalization terms. This approach better captures real-world scenarios characterized by demand-supply imbalances and heterogeneous congestion costs. We develop an analytical method for computing interior solutions, which proves particularly useful under specific conditions. Additionally, we propose an $O((N+L)N^2 L^2)$ algorithm to compute the optimal interior solution. For certain cases, we derive a closed-form solution and conduct a comparative statics analysis. Finally, we present examples demonstrating how our model yields solutions distinct from classical approaches, leading to more accurate outcomes in specific contexts, such as Peru's health and education sectors.

math.OC↗