Financial returns exhibit common behavior described at best by factor models, but also fat tails, which may be captured by α-stable distributions. This paper concentrates on estimating factor models with multivariate α-stable distributed and independent factors and idiosyncratic noises under...

El objetivo de este artículo es diagnosticar el problema de la segregación del alumnado por nivel socioeconómico en la escuela secundaria argentina, factor que profundiza la inequidad de los aprendizajes. Su contribución es evaluar qué tan desigual es la distribución de los estudiantes de...

Model builders face ambiguity about the true data generating process. Consequently, they need to deal with ambiguity attitudes (inside uncertainty) and ambiguous financial reality (outside uncertainty) when developing and estimating financial models. We introduce a novel approach for...

We investigate whether investors receive compensation for holding stocks with strong systematic liquidity risk in the form of extreme downside liquidity (EDL) risk. Following the logic of Acharya and Pedersen (2005), we capture a stock's EDL risk by the lower tail dependence between (i)...

This paper demonstrates that all rank test statistics are functions of implicit null space estimators. The paper proposes a novel theory of null space estimation that allows for standard asymptotics, polynomial regressions, and cointegration asymptotics. The paper proves that the behaviour of...

Existing econometric approaches for studying price discovery presume that the number of markets are small, and their properties become suspect when this restriction is not met. They also require making identifying restrictions and are in many cases not suitable for statistical inference. The...

We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. This design arises in many institutional settings where a policy variable (such as weekly...

I describe algorithms for drawing from distributions using adaptive Markov chain Monte Carlo (MCMC) methods, introduce a Mata function for performing adaptive MCMC, amcmc(), and a suite of functions amcmc *() allowing an alternative implementation of adaptive MCMC. amcmc() and amcmc *() may be...

This paper proposes a new Bayesian approach for estimating, nonparametrically, parameters in econometric models that are characterized as the solution of a linear inverse problem. By using a Gaussian process prior distribution we propose the posterior mean as an estimator and prove consistency,...

Height is the result of a complex process of growth that begins at birth and reaches the end in early adulthood.  This paper studies the determinants of height from birth to maturity.  A height production function is specified whose structure allows height to be the result of the accumulation...