- We provide novel stylized facts on the share of HtM agents and the share of social transfers reaching them using survey-based dataset from Global Findex. We identify HtM agents in‡uenced by the work of Lusardi et al. (2011) as those who are not able to cope with a ...nancial shock.<sup>5</sup> The recipients of social transfers are identi...ed directly from Global Findex. Two ...ndings stand out from several interesting ones.<sup>6</sup> First, the share of HtM agents is, on average, 23 percent in the sample of developed countries and 60 percent in the Latin American sample.<sup>7</sup> Second, the share of social transfers reaching HtM agents is, on average, 25 percent in the developed sample and 65 percent in the sample of Latin American countries. That is to say, the share of social transfers reaching HtM agents is mostly a re‡ection of the share of HtM agents, rather than the result of a particular social transfers targeting ability. This result suggests that, at least when including all types of social transfers, the usual assumption that social transfers only reach HtM agents (known as perfect targeting) does not seem to hold. We also show that these empirical regularities equally hold for a sample of 99 developed and emerging countries.

- A calibrated standard two-agent New Keynesian (TANK) model is able to match key STM regularities identi...ed empirically. Moreover, we show that about 80-90 percent of the large di¤erence in the size of STMs between Latin American and developed countries is explained by the higher share of ...nancially constrained individuals who live HtM in the Latin American sample relative to the developed countries. This evidence on the quantitative e¤ect of HtM arguments, coupled with the strong evidence supporting a larger share of HtM agents in emerging markets, suggests that a bigger STM may be expected for emerging market economies in general.

The rest of the paper proceeds as follows. Section 2 shows the empirical estimates of STMs for both the developed and the Latin American samples. Section 3 presents the TANK model. Section 4 provides evidence that the share of HtM agents and the share of social transfers actually reaching them in emerging markets are much larger than in developed economies. Section 5 shows that a

> 5 As discussed in Kaplan et al. (2014), while the identi...cation of HtM agents is di¤erent from those studies based on the agents’liquid wealth, the empirical evidence is notably similar in terms of the shares of population living HtM. This robust ...nding is also present in our study when relying on Global Findex. For example, for the United States, Kaplan et al. (2014) ...nd a share of HtM ranging between 25 and 40, with their preferred estimate being one-third. Ours, using Global Findex, is 27 percent. Section 4 provides extensive evidence of these similarities.

> 6 In light of the heated debate in developed countries about the so-called wealthy HtM individuals (i.e., those with signi...cant amounts of illiquid assets like real estate properties, yet high marginal propensity to consume out of transitory changes in income), we ...nd evidence that wealthy HtM individuals also exist in emerging markets. Yet, the HtM phenomenon in emerging markets is largely driven by poor HtM individuals.

> 7 This evidence is also in line with well-established, more macro/aggregate, evidence that emerging market economies have less ...nancial depth, intermediation, and development than their developed counterparts (e.g., King and Levine, 1993; Beck et al., 2000; Beck et al., 2007). More recent micro-based evidence from individual spending data and local-based experiments also support, to di¤erent degrees of explicitness, the relevance of ...nancial fragility on the marginal propensity to consume and on the size of local STMs (e.g., Haushofer and Shapiro, 2016; Egger et al., 2019; Pennings, 2020; Gerard et al., 2020).

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