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Demand estimation with machine learning and model combination

Bajari, Patrick L.; Nekipelov, Denis N.; Ryan, Stephen; … - 2015

Persistent link: https://www.econbiz.de/10010496176

Unbalanced data, type II error, and nonlinearity in predicting M&A failure

Lee, Kangbok; Joo, Sunghoon; Baik, Hyeoncheol; Han, Sumin; … - In: Journal of business research : JBR 109 (2020), pp. 271-287

Persistent link: https://www.econbiz.de/10012238067

Does the estimation of the propensity score by machine learning improve matching estimation? : the case of Germany's programmes for long term unemployed

Goller, Daniel; Lechner, Michael; Moczall, Andreas; … - 2019

Matching-type estimators using the propensity score are the major workhorse in active labour market policy evaluation. This work investigates if machine learning algorithms for estimating the propensity score lead to more credible estimation of average treatment effects on the treated using a...

Persistent link: https://www.econbiz.de/10012060603

Does the estimation of the propensity score by machine learning improve matching estimation? : the case of Germany's programmes for long term unemployed

Goller, Daniel; Lechner, Michael; Moczall, Andreas; … - 2019

Persistent link: https://www.econbiz.de/10012098947

Does the estimation of the propensity score by machine learning improve matching estimation? : the case of Germany's programmes for long term unemployed

Goller, Daniel; Lechner, Michael; Moczall, Andreas; … - 2020

Matching-type estimators using the propensity score are the major workhorse in active labour market policy evaluation. This work investigates if machine learning algorithms for estimating the propensity score lead to more credible estimation of average treatment effects on the treated using a...

Persistent link: https://www.econbiz.de/10012165548

BLP-2LASSO for aggregate discrete choice models with rich covariates : editor's choice

Gillen, Benjamin J.; Montero, Sergio; Moon, Hyungsik Roger - In: The econometrics journal 22 (2019) 3, pp. 262-281

Persistent link: https://www.econbiz.de/10012166760

Does the estimation of the propensity score by machine learning improve matching estimation? : the case of Germany's programmes for long term unemployed

Goller, Daniel; Lechner, Michael; Moczall, Andreas; … - In: Labour economics : official journal of the European … 65 (2020)

Persistent link: https://www.econbiz.de/10012522902

Machine learning for treatment effect heterogeneity : recovering partial effects

Guttman, Elad; Leventer, Dor; Saporta-Eksten, Itay; … - 2023

Persistent link: https://www.econbiz.de/10014342246

Machine learning for treatment effect heterogeneity : recovering partial effects

Guttman, Elad; Leventer, Dor; Saporta-Eksten, Itay; … - 2023

Persistent link: https://www.econbiz.de/10014339051

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