Oct 2026· Econometric Theory· pp. 1-50· 0 citations· 46 references
Abstract
This article studies panel data models with two-dimensional unobserved slope heterogeneity and interactive fixed effects. We propose a two-step approach to estimate the parameters in the model. We apply the proposed model to estimate heterogeneous treatment effects at both individual and aggregate levels. Monte Carlo simulations show that the proposed estimators perform remarkably well in finite samples in comparison with some existing methods such as the synthetic control ones. We apply our method to study the effect of economic liberalization on economic growth and find a positive and significant aggregate average treatment effect on the treated.
We study recursive-design wild bootstrap inference for dynamic panel data models with unobserved common factors estimated by Common Correlated Effects. In the large N,T setting, the bootstrap reproduces the biased limiting distribution in pure autoregressive models, but fails to capture all bias and factor-estimation v...
Artūras Juodis, Ovidijus Stauskas, Sander Tromp· 0 citations
We study dynamic linear panel data models in which the lagged outcomes and strictly exogenous covariates carry individual-specific coefficients and the time-varying errors have a flexible covariance structure. With a fixed number of time periods, we point-identify the joint distribution of the random coefficients and t...
We propose a nonparametric test for unobserved treatment effect heterogeneity in regression discontinuity designs. Under the null of no unobserved heterogeneity, a transformed outcome that imputes treated potential outcomes for untreated units must have a continuous conditional distribution at the cutoff. We convert th...
Problem definition: We study how adding new vendors to the Massachusetts Healthy Incentives Program (HIP), a food subsidy program, affects program utilization. This is an instance of a core problem in causal inference: estimating heterogeneous treatment effects (HTEs) using panel data. Existing methods either do not ut...
R. Levi, Elisabeth Paulson, Georgia Perakis et al.· Manufacturing & Service...· 0 citations
This paper studies the practice of combining multiple outcomes into a summary index to estimate a causal effect. For common estimators and index constructions, the estimate equals a weighted sum of the estimated effects on the components, with weights that are implicit and rarely reported. The paper derives the weights...
D. Fedchenko· 0 citations
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