We examine finite sample properties of estimators for approximate factor models when N is small. Contrary to the “rule-of-thumb”, we find that the principal component analysis estimator and the quasi-maximum likelihood estimator perform well even when N is small.

We develop a sieve bootstrap range test for poolability of cointegrating regressions in dependent panels and evaluate by simulation its performances. The test seems to have good size and power properties even with small cross-sections, moderate time samples, and low heterogeneity.

This work extends Karni’s direct revelation mechanism for eliciting agents’ subjective beliefs over the distribution of a random variable.

We present two Becker–DeGroot–Marschak type incentive compatible elicitation mechanisms. The first can be used to elicit an agent’s belief about the mean of a random variable while the second elicits the quantiles.

We study in this note the class of bilinear processes with periodic time-varying coefficients. We give necessary and sufficient conditions ensuring the existence of strict and second order stationary solutions (in periodic sense) and for the existence of higher order moments. The given...

This paper evaluates the performance of a recently emerging multivariate quadrature-based Sparse Grids Integration (SGI) and the well-known Geweke–Hajivassiliou–Keane (GHK) simulator in estimating multivariate binary probit models. Monte Carlo exercises demonstrate that in lower dimension...

This note shows that two ways of simulation based bias correction–indirect inference and bootstrap bias correction–are equivalent for two-stage-least-squares, as well as k-class estimators for the standard linear model with endogenous regressors.

In this paper we extend the FMLS-based CUSUM cointegration test (Xiao and Phillips, 2002) for testing the smooth time-varying cointegration null hypothesis. For this purpose we use Chebyshev time polynomials to specify time-varying coefficients under the null. We derive the limiting distribution...