Procedures based on the Generalized Method of Moments (GMM) are basic tools in modern econometrics. In most cases, the theory available for making inference with these procedures is based on first order asymptotic theory. It is well-known that the (first order) asymptotic distribution does not...

It is now widely recognized that the most commonly used efficient two-step GMM estimator may have large bias in small samples. This problem has motivated the search for alternative estimators with better finite sample properties. Two classes of alternatives are considered in this paper. The...

This papers studies and compares the asymptotic bias of GMM and generalized empirical likelihood (GEL) estimators in the presence of estimated nuisance parameters. We consider cases in which the nuisance parameter is estimated from independent and identical samples. A simulation experiment is...

Does economic theory help in forecasting key macroeconomic variables? This article aims to provide some insight into the question by drawing lessons from the literature. The definition of "economic theory" includes a broad range of examples, such as accounting identities, disaggregation and...

In this paper we empirically compare a wide range of different term structure models when it comes to the pricing and, in particular, hedging of caps and swaptions. We analyze the influence of the number of factors on the hedging and pricing results, and investigate which type of data "interest...

This paper empirically quantifies the effect on Spain’s public finances of the asset purchase programmes implemented in the euro area between 2015 and 2022. Specifically, it evaluates the impact of the ECB’s Asset Purchase Programme (APP) and Pandemic Emergency Purchase Programme (PEPP) on...

Este documento ofrece una cuantificación empírica del efecto sobre las cuentas públicas en España de los programas de compras de activos implementados en el área del euro entre 2015 y 2022. En particular, se evalúa el impacto sobre los ingresos, los gastos, el déficit y la deuda pública...

Calibration is a highly challenging task, in particular in multiple yield curve markets. This paper is a first attempt to study the chances and challenges of the application of machine learning techniques for this. We employ Gaussian process regression, a machine learning methodology having many...

I analyze time series momentum along the Treasury term structure. Past bond returns predict future returns both due to autocorrelation in bond risk premia and because unexpected bond return shocks increase the premium. Yield curve momentum is primarily due to autocorrelation in yield changes...