most citedLinear Regression for Panel With Unknown Number of Factors as Interactive Fixed Effects

303 citations · 539 across the 4 of their papers we have counts for

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econ.EM2026

Bounding Treatment Effects by Pooling Limited Information across Observations

Sokbae Lee, Martin Weidner

We provide novel bounds on average treatment effects (on the treated) that are valid under an unconfoundedness assumption. Our bounds are designed to be robust in challenging situa…

econ.EM202620 cited

Analysis of interactive fixed effects dynamic linear panel regression with measurement error

Nayoung Lee, Hyungsik Roger Moon, Martin Weidner

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 c…

econ.EM2026303 cited

Linear Regression for Panel With Unknown Number of Factors as Interactive Fixed Effects

Hyungsik Roger Moon, Martin Weidner

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. Assuming that the…

econ.EM2026192 cited

Dynamic Linear Panel Regression Models with Interactive Fixed Effects

Hyungsik Roger Moon, Martin Weidner

We analyze linear panel regression models with interactive fixed effects and predetermined regressors, for example lagged-dependent variables. The first-order asymptotic theory of…

econ.EM202624 cited

Estimation of random coefficients logit demand models with interactive fixed effects

Hyungsik Roger Moon, Matthew Shum, Martin Weidner

We extend the Berry, Levinsohn and Pakes (BLP, 1995) random coefficients discrete-choice demand model, which underlies much recent empirical work in IO. We add interactive fixed ef…

econ.EM20261 cited

Nuclear Norm Regularized Estimation of Panel Regression Models

Hyungsik Roger Moon, Martin Weidner

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.…