Eventually, we accumulated or made other studies sources in the municipal ? seasons height

Eventually, we accumulated or made other studies sources in the municipal ? seasons height

Talking about (1) the populace of females out-of reproductive decades (available with the fresh new Federal Yardsathematical Institute)? (2) the newest term, intercourse, and team of each and every civil mayor and his/the girl vote display (on Electoral Service)? and (3) management records on the any contraception disbursements from societal health service, and you can placebo health consequences produced regarding same administrative fitness details (male morbidity, and you can morbidities regarding puerperium several months).

This is certainly accompanied after the de- Chaise), in which we can matchocean goЕ›ci observe both instantaneous changes and you will changes along side pursuing the two years given the adaptation from inside the cures adoption

We combined such investigation sources with the a document group of Chile’s 346 municipalities more than 15 years, or 5,190 observations/information. Some observations have lost actions in some attacks. Particularly, the way of measuring EC tablet availableness possess 103 destroyed observations to have decades in which municipalities did not render details about the pill disbursement condition. Furthermore, the fresh new measure of denied tablets isn’t designed for 2009. I file bottom line analytics regarding following section.

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Here we follow the notation of Freyaldenhoven et al. (2018), where ?–step one = 0, so that our reference period is one year prior to adoption in each municipality. We are interested in the nine yearly leads and eight yearly lags of the policy change, where leads capture any prevailing trends prior to the reform in earlier versus later adopting municipalities, and lags show the change in health outcomes following EC pill availability. Given variation in reform timing, initial leads and lags capture differences in treatment status (treated vs. untreated), while later periods capture pure variation in timing. Year and municipal fixed effects ??? and ??? absorb time and municipal invariant factors, and standard errors are clustered by Chile’s 346 municipalities. As well as capturing any dynamic impacts of the reform (e.g., growing knowledge diffusion), specification (1) provides evidence in favor of parallel (pre)trends if we can reject that each ?j = 0 ? j 11 It is important to note that in all cases, EC Pill refers to free provision by the public health system. In Chile, following the passage of the EC pill laws, the pill was also sold at private pharmacies. Unlike public data, official data on EC pill usage in the private system are not available (Fernandez et al. 2016). Thus, all estimates refer to the impact of the public reform. Although we cannot formally assess the impact of private market provision without data on disbursements, if private provision fills gaps not met by the public health system “spilling over” to areas not yet treated by the public system, our estimates will understate the actual full effect of EC pill availability (Clarke 2019).

where EC Pillct is a binary variable indicating that the EC pill is available in municipality c and time t. Specifically, such models take care of recent critiques that single-coefficient models may be biased if effects are heterogeneous over time (Goodman-Bacon 2018). However, recent advances by de Chaise) propose an estimator to avoid issues relating to heterogeneous impacts over time and time-varying adoption of policies. We thus follow their proposed DIDM estimator in line with Eq. (2) (full details of this method are included in the online Appendix C). 12 This estimator consists of comparing outcomes between all units that change their EC pill status with those that have not yet changed, around the time that the policy change occurs. In addition, we estimate mirrored leads as placebo tests, which implement the same comparisons between changing and unchanging units, but in periods entirely before treatment is adopted. Besides allowing for a single summary estimate, this method offers the benefit that all identification is drawn off the time period in which the staggered adoption of the EC pill occurred. We consistently conduct inference using a block-bootstrap procedure allowing for within-municipality correlations over time. We also explore one specification where EC Pillct is replaced with Pill Rejectedct, indicating whether each municipality refused to disburse requested EC pills in a given year.

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