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Linear regressions with combined data

D'Haultfœuille, Xavier; Gaillac, Christophe; Maurel, Arnaud - 2024

Persistent link: https://www.econbiz.de/10015175860

Inference for regression with variables generated by AI or machine learning

Battaglia, Laura; Christensen, Tim; Hansen, Stephen; … - 2024

Persistent link: https://www.econbiz.de/10015271648

Easy bootstrap-like estimation of asymptotic variances

Honoré, Bo E.; Hu, Luojia - 2018

The bootstrap is a convenient tool for calculating standard errors of the parameter estimates of complicated econometric models. Unfortunately, the bootstrap can be very time-consuming. In a recent paper, Honoré and Hu (2017), we propose a "Poor (Wo)man's Bootstrap" based on one-dimensional...

Persistent link: https://www.econbiz.de/10011879253

Confidence intervals in regressions with estimated factors and idiosyncratic components

Fosten, Jack - In: Economics letters 157 (2017), pp. 71-74

Persistent link: https://www.econbiz.de/10011847312

Sensitivity analysis of an ols multiple regression inference with respect to possible linear endogeneity in the explanatory variables, for both modest and for extremely large sampl...

Ashley, Richard A.; Parmeter, Christopher F. - In: Econometrics : open access journal 8 (2020) 1/11, pp. 1-24

) inference with respect to possible endogeneity in the explanatory variables of the usual k-variate linear multiple regression … whether any selected inference is "robust" versus "fragile." The usefulness of this sensitivity analysis-as a "screen" for …

Persistent link: https://www.econbiz.de/10012265401