Appendix E: Robustness Checks Using Accumulated Lags and Leads | RDP 2023-10: Adoption of Emerging Digital General-purpose Technologies: Determinants and Effects

RDP 2023-10: Adoption of Emerging Digital General-purpose Technologies: Determinants and Effects Appendix E: Robustness Checks Using Accumulated Lags and Leads

Kim Nguyen and Jonathan Hambur

December 2023

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While the event study set-up with multiple leads and lags allows us to examine the timing of adoption effects on profitability, it is useful to know if, taken together, there are significant changes in profitability post-adoption from the pre-adoption periods. To this end, we conduct two robustness checks. First, we accumulate all the leads and lags into binary variables indicating pre-adoption and post-adoption, as follows:

(E1)

y_{i, t} = α + β_{J} {(L o g)}_{i, t} + \sum_{j} β_{j} {(T r e a t_{j})}_{i, t} + β_{K} {(L e a d)}_{i, t} {X^{'}}_{i, t} Γ + μ_{i} + θ_{s} + ε_{i, t}

where:

\begin{array}{l} {(L a g)}_{i, t} = 1 {t \leq A d o p t_{i} - 2} indicating pre-adoption \\ {(T r e a t_{j})}_{i, t} = 1 {t = A d o p t_{i} - j} for j \in {0, 1} indicating adoption periods \\ {(L e a d)}_{i, t} = 1 {t \geq A d o p t_{i} + 1} indicating post-adoption \end{array}

We estimate Equation (E1) for the same sub-samples as explored previously. Results show significant evidence of an increase in profitability in the joint post-adoption periods for late adopters with GPT experience, though the increase is not significant for those with female representation on the Board.