This thesis is composed of three independent chapters.
The first project studies how wealth can determine employment risk over the business cycle through labor market sorting. I find that workers with low liquid wealth face higher employment risk and propose a theory of wealth-sorting into risky jobs to rationalize it. I then integrate wealth-sorting in a quantitative model with aggregate risk to study its implications for wages and job transitions over the business cycle, as well as its cons...
This thesis contains three chapters. The first one, which is the main one, investigates the role of lenders' expectations in propagating the Greek sovereign debt crisis within the Eurozone periphery. It documents which type of lenders contribute most to the spreading, provides a rationalization, and quantifies the effect on countries' default probabilities. Using data from Consensus Economics survey, I classify lenders according to their GDP forecast precision before the Greek sovereign debt ...
The first chapter presents a work I undertook with my supervisor Giacomo Zanella. We propose a novel estimator for the log pointwise predictive density(lppd) of a Bayesian model. The naive method to calculate this quantity would require running n markov chain Monte Carlo (MCMC) chains, resulting in an unfeasible computational cost. A classical approach to overcome such a problem is to leverage importance sampling, which although solves the computational hurdle results in a estimator that can...
Random measures represent the fundamental building blocks for defining flexible priors in Bayesian nonparametric models. Over the last three decades, there has been a widespread diffusion of proposals aimed at introducing dependence among different random measures, in order to properly account for various forms of heterogeneity in the observations while preserving the possibility to borrow information across them.
The first part of the thesis focuses on vectors of dependent random measures de...
Deterministic approximations of analytically intractable posterior distributions are a common tool in Bayesian analysis. However, accurate extensions of these methods to situations in which data stream in rapidly and sequentially are still under-explored. In this thesis, we cover this gap by deriving a general and provably-accurate skew-symmetric approximation of a target posterior whose parameters can be evaluated via novel window-type estimators that make computations effectively online. Th...
This dissertation comprises three essays centered around the role of subjective expectations in labor markets. In equilibrium search models of the labor market, processes such as wage formation, job creation, offer acceptance, among others, largely depend on agents’ expectations. Throughout these essays, I research how workers form expectations about aggregate and idiosyncratic factors that determine their behavior, with an emphasis on job search.
In the first chapter, I quantify the pass-thr...
The prominent role firms play in the global market makes it crucial to understand how firms respond to changes in trade policies and global market structures. The era of hyper-globalization and recent trends of decoupling emphasize this necessity, particularly in terms of their impact on overall welfare. With this general background in mind, this thesis studies the impact of international trade and trade policies on firm behavior and market outcomes, mostly within the context of China. The av...
In this thesis, I study topics in development economics and finance, focusing on the effects of policies in the digital payments' market and regulation of immigration. The thesis comprises three distinct papers that explore financial behavior, technological adoption, and economic policy impacts in developing contexts.
The first paper examines the impact of substituting bank deposits with digital currency on banks' lending behavior in developing countries. Using an unexpected tax on Mobile Mo...
As the complexity and dimensionality of data continue to increase, it is becoming fundamental to develop advanced strategies for statistical inference and to explore their computational properties (Bishop, 2006).
This thesis considers Bayesian models, known for their ability to frame prediction and uncertainty within a coherent probabilistic framework. However, achieving accurate estimates of posterior quantities within these models generally requires innovative techniques to accommodate the ...
This thesis embodies three chapters on the economics and applications of artificial intelligence (AI). The first chapter explores the economic underpinnings of open-source contributions in AI by for-profit companies, focusing on large language models (LLMs). Three main findings emerge: (1) LLMs align well with the R&D portfolios of diverse technologically advanced firms, (2) models developed by large technology companies are more likely to be open-sourced, and (3) open-sourcing advanced LLMs ...