Eventually, i collected or produced some other studies sources at the civil ? seasons height

These are (1) the population of females off reproductive decades (available with the newest Federal Statistical Institute)? (2) the fresh new term, intercourse, and class of every municipal mayor along with his/their choose show (throughout the Electoral Service)? and (3) management information towards some other birth prevention disbursements from societal fitness service, and you can placebo wellness effects produced from the same management health information (men morbidity, and you can morbidities on puerperium months).

It is accompanied adopting the de Chaise), in which we can to see each other immediate changes and changes along the following 24 months given the version into the treatment use

We mutual such analysis source toward a data number of Chile’s 346 municipalities more than 15 years, or 5,190 observations/documents. A few findings possess forgotten procedures in some episodes. Particularly, our measure of EC pill availableness have 103 forgotten findings to have many years in which municipalities don’t promote information on their pill disbursement standing. Similarly, the latest way of measuring declined pills is not readily available for 2009. We document realization statistics throughout the following the point.

Strategies

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 Pill_ct 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 DID_M estimator in line with Eq milfaholic site. (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 Pill_ct is replaced with Pill Rejected_ct, indicating whether each municipality refused to disburse requested EC pills in a given year.