This paper describes a method for estimating panels by imposing a factor structure on the residuals. The method allows SUR estimation of panel models by providing a full-rank estimator of the system covariance matrix when the usual estimate is rank-deficient. We charactersie completely the...

Using the restrictions implied by the heteroskedasticity of stock returns, we identify four factors in the U.S. industry returns. The first correlates highly with the market portfolio; the second is a portfolio of stocks that produce investment goods minus stocks that produce consumption goods;...

We contrast two approaches to the prediction of latent variables in the model of factor analysis. The likelihood statistic is a sufficient statistic for the unobservables when sampling arises from the exponential family of distributions. Linear predictors, on the other hand, can be obtained as...

This paper investigates the effect of minimum wages on employment using a panel of US state-based data. We estimate a minimalist dynamic version of the specification implied by neo-classical theory. We find statistically and economically significant effects of minimum wages on youth employment....

Pairwise maximum likelihood (PML) estimation method is developed for factor analysis models with ordinal data and fitted both in an exploratory and confirmatory set-up. The performance of the method is studied via simulations and comparisons with full information maximum likelihood (FIML) and...

This paper proposes a new approach to the "factor zoo" conundrum. Instead of applying dimension-reduction methods to a large set of portfolios obtained from sorts on characteristics, I construct factors that summarize the information in characteristics across assets and then sort assets into...

This paper introduces a simple and tractable sieve estimation of semiparametric conditional factor models with latent factors. We establish large-N-asymptotic properties of the estimators without requiring large T. We also develop a simple bootstrap procedure for conducting inference about the...

This paper proposes latent factor models for multidimensional panels called 3D-PCA. Factor weights are constructed from a small set of dimension-specific building blocks, which give rise to proportionality restrictions of factor weights. While the set of feasible factors is restricted, factors...

We extend the control function approach of Altonji and Mansfield (2018) to allow for multiple group levels and complementarities. Our analysis provides a foundation for causal interpretation of multilevel mixed effects models in the presence of sorting. In our empirical application, we obtain...

This case study compares the importance of prevailing market factors against that of COVID-19 dynamics and policy responses in explaining the evolution of Eurozone (EZ) sovereign spreads during the first half of 2020. Focusing on daily Eurozone CDS spreads, we adopt a multi-stage econometric...