Adults of 65 years of age are excluded from the analysis because even though at the time of the collection of the survey in 2014 these individuals were eligible for treatment; we do not know exactly when these individuals became eligible. Moreover, even if we could identify when these individuals became eligible, we could argue that these individuals did not have “enough” exposure to the eligibility-for-treatment to be taken into consideration for this analysis.

Adults receiving contributory pensions were not eligible to receive PAM in 2013, for this reason people who received a contributory pension were excluded from the analysis. The share of people receiving contributory pensions or retirement payments in the treatment group is 27.9, 26.9 and 29.1% for 2010, 2012 and 2014, respectively; and in the control group these numbers are 23.2, 23.1 and 22.8 for 2010, 2012 and 2014, respectively.

Using ENIGH – MCS, CONEVAL first estimates income at the household level, and then assigns income to individuals adjusting by household composition using an adult-equivalent scale. Hence, all members of the same household have the same income level. For this reason, we excluded from the sample those households with cohabitants from both treatment arms. This could also suggest that the effects of PAM on the beneficiary’s income and poverty condition could be generalizable to all members of the beneficiary’s household.

The expansion of the program was announced after the collection of the ENIGH-MCS in 2012. Thus, we do not presume anticipation effects. While President Peña Nieto was already elected president of Mexico by the time that the survey was being collected in 2012, it is unlikely that people would have modified their behavior based on his political campaign proposed initiatives without actual knowledge or information on future treatment. The campaign proposal was to establish a universal pension for the population 65 years old or older, however, it did not mention a specific benefit level or additional eligibility criteria such as wealth or income level conditions, disability status, and others. It is therefore hard to assume that people would have modified their behavior based on the limited information available, so we assume the data collected in the 2012 survey does not reflect anticipation effects.

We first estimate the ITT effects using a difference-in-differences estimation and then we estimate the TOT using an Instrumental Variable methodology with Two Stages Least Squares (2SLS).

# **3.5.1 Intention-to-treat Effects (ITT)**

The identification strategy consists of a difference-in-differences estimation (DD) with a discontinuity framework. We used the exogenous variation in the program’s eligibility criteria at the beginning of 2013, that is the change in minimum eligibility age from 70 years of age and older to 65 years of age and older, as the intervention that allowed us to define treatment and control groups.

While the treatment and comparison groups may not have identical levels in their pre-intervention observed characteristics, their pre-intervention trends over time are similar. Thus, we assume that, in the absence of PAM, the average change in the outcomes would have been the same for the treatment and control groups. This is the well-known parallel trends assumption. While this assumption is untestable, Figure 2 shows that the treatment and control groups are moving in fact in parallel before the intervention took place and right after the intervention there is a sharp change in most of the 14