The study of the innovative output of firms often relies on a count of patents filed at one single office of reference such as the European Patent Office (EPO). Yet, not all firms file their patents at the EPO, raising the specter of a selection bias. Using a novel dataset of the whole...

Vector autoregressions with Markov-switching parameters (MS-VARs) fit the data better than do their constant-parameter predecessors. However, Bayesian inference for MS-VARs with existing algorithms remains challenging. For our first contribution, we show that Sequential Monte Carlo (SMC)...

This paper delves into the well-known phenomenon of shrinking wage elasticities for married women in the US over recent decades. The results of a novel model experimental approach via sample data ordering unveil considerable heterogeneity across different wage groups. Yet, surprisingly constant...

The study of the innovative output of organizations often relies on a count of patents filed at one single office of reference such as the European Patent Office (EPO). Yet, not all organizations file their patents at the EPO, raising the specter of a selection bias. Using novel datasets of the...

The constant elasticity of substitution (CES) function is an important function that is widely used in both theoretical analysis and applied economics. We propose a systematic framework to estimate the deep nested CES function using the nonlinear least squares (NLS) method. This method fills the...

We study semi-parametric estimation and inference in cointegrated panels with endogenous feedback, allowing for general time-series and cross-section dependence and heterogeneity.Central to this literature are the fully-modified OLS of Phillips and Hansen (1990) that use a spectral...

I document large variation in empirical methodology in corporate finance regressions in top finance journals. Although methodological variation allows for customization of empirical tests to fit specific theories, it can also enable excessive reporting of statistically significant results. For...

We study parameter estimation from the sample X, when the objective is to maximize the expected value of a criterion function, Q, for a distinct sample, Y. This is the situation that arises when a model is estimated for the purpose of describing other data than those used for estimation. The...

Given the extreme dependence of agriculture on weather conditions, this paper analyses the effect of climatic variations on this economic sector, by considering both a huge dataset and a flexible spatio-temporal model specification. In particular, we study the response of N-fertilizer...

Vector autoregressions with Markov-switching parameters (MS-VARs) fit the data better than do their constant-parameter predecessors. However, Bayesian inference for MS-VARs with existing algorithms remains challenging. For our first contribution, we show that Sequential Monte Carlo (SMC)...