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Showing 1 to 5 of 5 for “"Double machine learning (DML)"”.

  1. Evaluating the Effects of Financial Deregulation on Bank Risk using Double Machine Learning

    … developments in causal inference, particularly Double Machine Learning (DML), to more accurately estimate treatment effects. DML leverages machine learning algorithms to flexibly model both treatment and outcome processes, controlling for bias via orthogonaliza- tion techniques and …

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  2. Leveraging Machine Learning and Causal Inference for Loan Default Prediction

    … research explores a systematic application of machine learning techniques combined with causal inference to predict loan defaults in peer-to-peer lending. Accurately forecasting loan defaults is crucial for mitigating financial risk and optimizing lending strategies. This analysis is based on …

    embry-riddle Repository record for Leveraging Machine Learning and Causal Inference for Loan Default Prediction (opens in a new tab)

  3. Essays on Regulations in Peer-To-Peer Markets

    … the model and automate this process by using Machine Learning (ML) techniques. I apply the Double Machine Learning (DML) approach proposed by Chernozhukov et al. (2018) and Chernozhukov et al. (2017), to a massive data of Airbnb rentals in the New York City (NYC) and estimate the demand facing …

    washington Repository record for Essays on Regulations in Peer-To-Peer Markets (opens in a new tab)

  4. Predictive and Prescriptive Analytics in Operations Management

    … decision making. This thesis proposes novel Machine Learning (ML) and optimization methods in (i) predictive analytics, (ii) prescriptive analytics, and (iii) their high-impact applications in operations management. On the predictive side, this thesis tackles the problems of interpretability …

    mit Repository record for Predictive and Prescriptive Analytics in Operations Management (opens in a new tab)

  5. Essays in industrial organization

    … and employs causal forest, a novel causal machine learning method, to estimate heterogeneous user click rates based on extensive browsing and ad exposure data from more than 1.6 million internet users. Simulations of user and platform behavior reveal that hypothetical mergers could boost …

    texas Repository record for Essays in industrial organization (opens in a new tab)