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When are large female-led firms more resilient against shocks? Learnings from Indian enterprises during COVID-19 with diff-in-diff and causal forests

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  • Merlin Stein

Abstract

In which kind of companies did the prevalence of women on corporate boards matter during the first wave of Covid-19? 2500 large Indian firms, of which only 78% initially complied with an exogenous gender quota enable a quantitative evaluation. By comparing their quarterly revenues with a Difference-in-Differences analysis, this research initially finds a significantly positive relationship between the compliance with the one-female-board-member policy and the change in revenues during the first economic shock of the Covid-19 crisis in 2020. A Triple-Difference and Causal Forest analysis indicates that this is likely endogenously driven by (self-)selection based on sectors, capital dynamics, size, independence of directors and further firm characteristics. There is no simple association of female directors and crisis revenues: The spectrum encompasses a mix of firms with a positive, a neutral and a negative association. With rare causal context for evaluating board gender diversity or other corporate governance and ESG dynamics, this piece of research illustrates the value and limitations of applying adjusted Random Forests to overcome linearity and dimensionality limitations for deeply understanding heterogeneities-within-heterogeneities as indicators of relevant distinctions.

Suggested Citation

  • Merlin Stein, 2022. "When are large female-led firms more resilient against shocks? Learnings from Indian enterprises during COVID-19 with diff-in-diff and causal forests," CSAE Working Paper Series 2022-01, Centre for the Study of African Economies, University of Oxford.
  • Handle: RePEc:csa:wpaper:2022-01
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    References listed on IDEAS

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    More about this item

    Keywords

    Generalized Random Forest; Causal Machine Learning in Double and Triple Difference; Covid-19; large rms; women on corporate boards; female leadership; quota;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D22 - Microeconomics - - Production and Organizations - - - Firm Behavior: Empirical Analysis
    • G30 - Financial Economics - - Corporate Finance and Governance - - - General
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • K22 - Law and Economics - - Regulation and Business Law - - - Business and Securities Law

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