treatment effect akin to that in difference-in-difference event studies. If, alternatively, the rule indicator was set to one for all years that a fiscal rule was in place, as in Chrysanthakopoulos and Tagkalakis (2024), the local projections would capture the level effects of the _presence of fiscal rules_ over the medium-term. This would then be capturing how having a rule today influences the government budget over the next _h_ years—and not the dynamic effects of _fiscal rule adoption_ on medium-term fiscal policy.

We assume that the effect of fiscal rule adoption stabilizes after ten years, such that the established impact of fiscal rules influences the level but not the dynamics of the primary balance. This rationale is also applied by Dube et al. (2023) in examining the effect of democratization on output. To control for the initial impact of rule adoption on the primary balance, we include four lags of the fiscal rule indicator, aligning with the average duration of electoral cycles in most countries. We follow Teulings and Zubanov (2014) and include nine leads to mitigate the bias from overlapping forecast horizons. These leads account for future fiscal rule adoptions (i.e., between year _t+1_ and _t+h_ ).<sup>12</sup> Due to data availability constraints in the control variables, some instances of fiscal rule adoption that occurred between 1984 and 2012 do not enter the econometric analysis. The sample used in the analysis comprises 52 cases of fiscal rule adoption across 50 countries. Each case represents the implementation of one or more fiscal rules in a context where no such rule existed in the previous year. Our analysis thus focuses on cases of newly (re-) installed fiscal rules, excluding subsequent adoptions or amendments. Later adoptions are instead treated as secondary treatment effects within the control set.<sup>13</sup> 12 Without these leads, part of the impact of fiscal rule adoption on the primary balance would be absorbed by the fixed effects, leading to a downward bias in the coefficient estimates of the fiscal rule indicator. In the leads-and-lags structure of the rule indicator, we consider all instances of rule adoption, not only the initial set of rules. Moreover, we include a separate variable to capture the effects of subsequent rule adoptions. Including a variable that captures the presence of fiscal rules—but setting it to zero in the first year of adoption—yields similar results as to including second time adoptions in the leads-and-lags structure. Moreover, differentiating between rule frameworks that remained unchanged within their first ten years and those that were amended yields similar outcomes (results are available on request).

13 We assume that the primary balance does not respond the same to later changes to the fiscal rule framework, as the response is conditional on the initial adoption of the rule(s). Therefore, investigating the impact of later rule adoptions (or subsequent rule modifications) would require focusing on countries with an existing rule, while also controlling for the time since the rule was first adopted. Accounting for fiscal rule intensity—such as the number or design of the initial rules—adds further complexity to the analysis. As such, we exclude later changes from the shock indicator to achieve a clearer understanding of the implications of rule adoption for countries. For an in-depth discussion of second treatment effects and their empirical implications, see de Chaisemartin and D’Haultfœuille (2023).

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