efficient algorithms for small-sample estimation and inference. To fill these important gaps in the literature, this paper makes …, we develop a number of efficient algorithms for small-sample estimation and inference. …

Estimation using simulation techniques may be very time consuming. Specification tests for structuralstability often …

orhistorical and Monte Carlo simulation methods. Although these approaches to overall VaR estimation have receivedsubstantial … proposed estimation approach pairs intuitiveappeal with computational efficiency. We evaluate various alternative estimation …

This paper considers nonparametric identification and estimation of the regression function when a covariate is …

the structure of the formula for identification. We compare this design-based approach with conventional estimation …

We consider estimation and inference for a regression coefficient in panels with interactive fixed effects (i.e., with … minimax linear estimation to form a debiased estimate using a nuclear norm bound on the error of an initial estimate of the … weak, with little cost to estimation error when factors are strong. …