In this paper, we investigate the information content of implied probabilities (Back and Brown, 1993) to improve estimation in unconditional moment conditions models. We propose and evaluate two 3-step euclidian empirical likelihood estimators and their bias-correction versions for weakly...

The Lerner index is widely used to assess firms' market power. However, estimation and interpretation present several challenges, especially for banks, which tend to produce multiple outputs and operate with considerable inefficiency. We estimate Lerner indices for U.S. banks for 2001-18 using...

This paper advances the literature on the impacts of new technologies on labour markets, focusing on wage and labour income shares. Using a dataset from 32 countries and 38 industries, we analyse the effects of new technologies - proxied by patents, information and communication technology (ICT)...

The k Nearest Neighb or (kNN) density estimator first for-malized by Loftsgaarden and Quesenb erry (1965) is central to a broad range of the literature on density estimation. It is knownto b e strongly uniformly consistent if k increases appropriatelywith the sample size. The contribution of...

The evaluation of the likelihood function of the stochastic conditional duration model requires to compute an integral that has the dimension of the sample size. We apply the efficient importance sampling method for computing this integral. We compare EIS-based ML estimation with QML estimation...

The paper provides a proof of consistency of the ridge estimator for regressions where the number of regressors tends to infinity. Such result is obtained without assuming a factor structure. A Monte Carlo study suggests that shrinkage autoregressive models can lead to very substantial...

This paper contributes to the induced innovation literature by extending the analysis of supply and demand determinants of innovation in energy-efficient technologies to account for international knowledge flows and spillovers. In the first part of the paper we select a sample of 38 innovating...

We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors and time varying volatilities, even when the cross sectional dimension of the system N is particularly large. The algorithm is based on a simple triangularisation which allows to...

We use a simple New Keynesian model, with firm specific capital, non-zero steady-state inflation, long-run risks and Epstein-Zin preferences to study the volatility implications of a monetary policy shock. An unexpected increases in the policy rate by 150 basis points causes output and inflation...