Ion hydration is a central topic of discussion in the scientific community, given the important role that solvated ions play in fields as biochemistry, electrochemistry, and environmental chemistry. Despite the large amount of experimental and theoretical studies that involve ions in aqueous solutions, a unified molecular description is still missing: existing models fail to accurately capture the intricate ion-water interactions, leading to inconsistencies between experimental and theoretical results. The surface propensity of halide ions at the air/water interface has been debated for over a century, and the recent introduction of new architectures for the description of molecular interactions allows for the development of accurate and efficient models to describe their behavior.Advanced molecular modelling frameworks based on deep neural networks (DNNs) and many-body expansion (MBE) of the energy are explored and their limitations analysed. Data-driven MBE-based models as MB-nrg are able to provide chemical accuracy at great computational efficiency when compared to classical force fields (FFs), DFT-based ab initio molecular dynamics (AIMD), and modern DNN potentials. After developing an efficient active learning (AL) framework for the generation of comprehensive training sets, we proceed with the development of MB-nrg models for the description of the chloride, bromide, and iodide ions; these provide great accuracy in the description of both gas-phase clusters and bulk systems, by closely reproducing coupled cluster (CC) interaction energies and the experimental x-ray absorption spectra. Lastly, we address the errors associated with the use of semi-local exchange-correlation functionals in modeling hydrated ions within density functional theory (DFT): the recent introduction of density-corrected (DC) SCAN functionals provides a solution to the overdelocalization issue typically encountered in semi-local density functional approximations (DFAs), leading to considerable improvements in the energetics and structural features of hydrated ions. This dissertation presents a significant advancement in the understanding of ion hydration, showcasing novel methods for more precise theoretical predictions, and providing a solid foundation for future research in this challenging field.

This dissertation studies the economic effects of the formation of inflation expectations. It uses both theoretical and empirical tools to bridge gaps in our understanding of the process of expectation formation and its macroeconomic implications. Chapter 1 is motivated by increasing evidence that consumers have particularly limited knowledge about inflationary trends and that they rely heavily on their observation of everyday prices to form their inflation expectations. This chapter asks how the fact that consumers learn from prices affects the price-setting process and the implications for the allocative efficiency of the price system. In environments of high inflation uncertainty, prices provide mostly information about aggregate inflationary shocks and little information about relative prices. This feature makes consumers less price-sensitive in equilibrium, allowing firms to set higher markups. Additionally, these incentives are stronger for high-cost relative to low-cost firms, increasing cross-sectional price dispersion. These distortions to price-setting have first-order welfare implications and explain essentially all of the welfare losses in the model. Chapter 2 causally estimates the effect of information about a monetary policy reform on firm inflation expectations in Uruguay. A causal quantification of this effect has been previously infeasible given data considerations, despite its importance for the cost of disinflation in a broad class of New-Keynesian models. We overcome these problems by conducting a randomized control trial (RCT) providing information to a subset of firms shortly after the reform was announced. The results indicate a strong and long-lived effect of treatment on firm inflation expectations and that firms expect temporarily lower growth as a result of treatment. Taken together, these causal estimates imply a relatively low cost of disinflation. Finally, Chapter 3 inquires whether conventional measures of inflation expectations are a reasonable guide to determine the appropriate monetary policy stance in a model of endogenous expectation formation. The model generates forecast errors that are consistent with the empirical evidence, and I use the model to evaluate inflation and expectations dynamics under different monetary policy rules. Inflation-targeting rules can successfully keep expectations anchored by offsetting second-round effects of inflationary shocks. However, expectations-targeting rule cannot generally keep expectations anchored given that monetary policy can only lean against inflationary shocks if expectations become unanchored. In a dynamic extension, this results in gradual inflation in inflation-targeting regimes, while inflation is volatile and front-loaded in expectations-targeting regimes. In all, these papers contribute to a growing and exciting field within macroeconomics.