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  1. Revisiting event study designs
    robust and efficient estimation
    Autor*in: Borusyak, Kirill; Jaravel, Xavier; Spiess, Jann
    Erschienen: 24 April 2022
    Verlag:  Centre for Economic Policy Research, London

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    Verlag (lizenzpflichtig)

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    LZ 161
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    keine Fernleihe

    Standort:
    Universitätsbibliothek Mannheim
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    keine Fernleihe
    Export in Literaturverwaltung   RIS-Format
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Schriftenreihe: Array ; DP17247
    Schlagworte: Ereignisstudie; Differenz von Differenzen; Kausalanalyse; Robustes Verfahren; Kleinste-Quadrate-Methode; Schätztheorie; USA; Difference-in-Differences; event study; Imputation estimator; panel data
    Umfang: 1 Online-Ressource (circa 88 Seiten), Illustrationen
  2. Revisiting event study designs
    robust and efficient estimation
    Autor*in: Borusyak, Kirill; Jaravel, Xavier; Spiess, Jann
    Erschienen: [2022]
    Verlag:  Cemmap, Centre for Microdata Methods and Practice, The Institute for Fiscal Studies, Department of Economics, UCL, [London]

    We develop a framework for difference-in-differences designs with staggered treatment adoption and heterogeneous causal effects. We show that conventional regression-based estimators fail to provide unbiased estimates of relevant estimands absent... mehr

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    Resolving-System (kostenfrei)
    Resolving-System (kostenfrei)

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    DS 243
    Fernleihe:
    keine Fernleihe

     

    We develop a framework for difference-in-differences designs with staggered treatment adoption and heterogeneous causal effects. We show that conventional regression-based estimators fail to provide unbiased estimates of relevant estimands absent strong restrictions on treatment-effect homogeneity. We then derive the efficient estimator addressing this challenge, which takes an intuitive "imputation" form when treatment-effect heterogeneity is unrestricted. We characterize the asymptotic behavior of the estimator, propose tools for inference, and develop tests for identifying assumptions. Extensions include time-varying controls, triple-differences, and certain non-binary treatments. We show the practical relevance of these insights in a simulation study and an application. Studying the consumption response to tax rebates in the United States, we find that the notional marginal propensity to consume is between 8 and 11 percent in the first quarter - about half as large as benchmark estimates used to calibrate macroeconomic models- and predominantly occurs in the first month after the rebate.

     
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    hdl: 10419/260392
    Auflage/Ausgabe: This version: April 2022
    Schriftenreihe: Cemmap working paper ; CWP22, 11
    Schlagworte: Ereignisstudie; Differenz von Differenzen; Kausalanalyse; Robustes Verfahren; Kleinste-Quadrate-Methode; Schätztheorie; USA
    Umfang: 1 Online-Ressource (circa 86 Seiten), Illustrationen
  3. Double and Single Descent in Causal Inference with an Application to High-Dimensional Synthetic Control
    Autor*in: Spiess, Jann; Imbens, Guido; Venugopal, Amar
    Erschienen: October 2023
    Verlag:  National Bureau of Economic Research, Cambridge, Mass

    Motivated by a recent literature on the double-descent phenomenon in machine learning, we consider highly over-parameterized models in causal inference, including synthetic control with many control units. In such models, there may be so many free... mehr

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    Standort:
    Sächsische Landesbibliothek - Staats- und Universitätsbibliothek Dresden
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    keine Fernleihe

    Standort:
    Universitätsbibliothek Freiburg
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    Standort:
    Helmut-Schmidt-Universität, Universität der Bundeswehr Hamburg, Universitätsbibliothek
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    keine Fernleihe

    Standort:
    Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky
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    Standort:
    Technische Informationsbibliothek (TIB) / Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
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    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Fernleihe:
    keine Fernleihe

     

    Motivated by a recent literature on the double-descent phenomenon in machine learning, we consider highly over-parameterized models in causal inference, including synthetic control with many control units. In such models, there may be so many free parameters that the model fits the training data perfectly. We first investigate high-dimensional linear regression for imputing wage data and estimating average treatment effects, where we find that models with many more covariates than sample size can outperform simple ones. We then document the performance of high-dimensional synthetic control estimators with many control units. We find that adding control units can help improve imputation performance even beyond the point where the pre-treatment fit is perfect. We provide a unified theoretical perspective on the performance of these high-dimensional models. Specifically, we show that more complex models can be interpreted as model-averaging estimators over simpler ones, which we link to an improvement in average performance. This perspective yields concrete insights into the use of synthetic control when control units are many relative to the number of pre-treatment periods

     
    Export in Literaturverwaltung   RIS-Format
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Schriftenreihe: NBER working paper series ; no. w31802
    Schlagworte: Kausalanalyse; Induktive Statistik; Lineare Regression; Künstliche Intelligenz; Schätztheorie; Econometrics
    Umfang: 1 Online-Ressource, illustrations (black and white)
    Bemerkung(en):

    Hardcopy version available to institutional subscribers
  4. Rationalizing pre-analysis plans
    statistical decisions subject to implementability
    Autor*in: Kasy, Maximilian; Spiess, Jann
    Erschienen: [2022]
    Verlag:  Department of Economics, University of Oxford, Oxford

    Zugang:
    Verlag (kostenfrei)
    Verlag (kostenfrei)

    Standort:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signatur:
    VS 454
    Fernleihe:
    keine Fernleihe
    Export in Literaturverwaltung   RIS-Format
      BibTeX-Format
    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Schriftenreihe: Department of Economics discussion paper series / University of Oxford ; number 975 (June 2022)
    Schlagworte: Pre-analysis plans; Statistical decisions; Implementability
    Umfang: 1 Online-Ressource (circa 43 Seiten), Illustrationen