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Counterfactuals in factor models

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  • Jad Beyhum

Abstract

We study a new model where the potential outcomes, corresponding to the values of a (possibly continuous) treatment, are linked through common factors. The factors can be estimated using a panel of regressors. We propose a procedure to estimate time-specific and unit-specific average marginal effects in this context. Our approach can be used either with high-dimensional time series or with large panels. It allows for treatment effects heterogenous across time and units and is straightforward to implement since it only relies on principal components analysis and elementary computations. We derive the asymptotic distribution of our estimator of the average marginal effect and highlight its solid finite sample performance through a simulation exercise. The approach can also be used to estimate average counterfactuals or adapted to an instrumental variables setting and we discuss these extensions. Finally, we illustrate our novel methodology through an empirical application on income inequality.

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  • Jad Beyhum, 2024. "Counterfactuals in factor models," Papers 2401.03293, arXiv.org.
    • Handle: RePEc:arx:papers:2401.03293
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    References listed on IDEAS

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    1. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, July.
    2. Greenaway-McGrevy, Ryan & Han, Chirok & Sul, Donggyu, 2012. "Asymptotic distribution of factor augmented estimators for panel regression," Journal of Econometrics, Elsevier, vol. 169(1), pages 48-53.
    3. Shou-Yung Yin & Chu-An Liu & Chang-Ching Lin, 2021. "Focused Information Criterion and Model Averaging for Large Panels With a Multifactor Error Structure," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(1), pages 54-68, January.
    4. Artūras Juodis, 2022. "A regularization approach to common correlated effects estimation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 788-810, June.
    5. Bai, Jushan & Ng, Serena, 2023. "Approximate factor models with weaker loadings," Journal of Econometrics, Elsevier, vol. 235(2), pages 1893-1916.
    6. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    7. Jushan Bai & Serena Ng, 2006. "Confidence Intervals for Diffusion Index Forecasts and Inference for Factor-Augmented Regressions," Econometrica, Econometric Society, vol. 74(4), pages 1133-1150, July.
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