Hyungsik Roger Moon

In this paper we investigate panel regression models with interactive fixed effects. We propose two new estimation methods that are based on minimizing convex objective functions.

Estimation of random coefficients logit demand models with interactive fixed effects

We analyze linear panel regression models with interactive fixed effects and predetermined regressors, for example lagged-dependent variables.

In this paper, we study the least squares (LS) estimator in a linear panel regression model withunknown number of factors appearing as interactive fixed effects.

This paper analyzes linear panel regression models with interactive fixed effects and predetermined regressors, e.g. lagged-dependent variables.

In this paper we study the least squares (LS) estimator in a linear panel regression model with unknown number of factors appearing as interactive fixed effects.

We analyze linear panel regression models with interactive fixed effects and predetermined regressors, e.g. lagged-dependent variables.

In this paper we study the least squares (LS) estimator in a linear panel regression model with interactive fixed effects for asymptotics where both the number of time periods and the number of cross-sectional units go to infinity.

This paper studies a simple dynamic linear panel regression model with interactive fixed effects in which the variable of interest is measured with error. To estimate the dynamic coefficient, we consider the least-squares minimum distance (LS-MD) estimation method.