We propose new generalized method of moments (GMM) estimators for the number of latent factors in linear factor models. The estimators are appropriate for data with a large (small) number of cross-sectional observations and a small (large) number of time series observations. The estimation...

We examine the asymptotic and finite-sample properties of the two-pass (TP) cross-sectional regressions estimators when factors and asset returns are conditionally heteroskedastic and/or autocorrelated. Using a minimum distance approach, we derive the heteroskedasticity- and/or...

This paper investigates the reliability of the two-pass (TP) estimators of factor risk prices when betas (multifactor loadings) have high levels of cross-sectional correlation (multicollinearity) and/or when some of them have small cross-sectional variations (near-invariance). Our simulation...

Federal Open Market Committee (FOMC) meeting days provide a natural laboratory for exploring the effects of policy uncertainty and learning on exchange rate determination. A reasonable hypothesis is that the meeting outcomes are price-relevant public information associated with a switch to an...

This paper examines the asymptotic properties of the popular within, GLS estimators and the Hausman test for panel data models with both large numbers of cross-section (N) and time-series (T) observations. The model we consider includes the regressors with deterministic trends in mean as well as...

We propose a generalized method of moment (GMM) estimator of the number of latent factors in linear factor models. The method is appropriate for panels a large (small) number of cross-section observations and a small (large) number of time-series observations. It is robust to heteroskedasticity...

This paper provides an explanation for the concurrence of rigid wages and involuntary unemployment. The authors consider cases in which a firm monitors its workers but at some cost. A key assumption in the model is that the firm cannot perfectly distinguish shirkers from nonshirkers. Thus, the...