scored on a Likert scale running from 0 (significantly worse) – 10 (significantly better). The survey questions on optimism were collected at outreach, baseline and endline.

**Employment status** : Due to slight differences in access to labor markets for refugees in Jordan and Lebanon and differences in how we were able to ask about employment status, we tabulate employment status as whether or not an individual is employed. Participants were asked at outreach about their employment status, and, in subsequent rounds, whether or not this had changed. This variable is coded 0 for not currently employed and 1 for employed.

**Economic scarcity** : We collect survey questions on individual perceptions on: ability to meet current needs; ability to meet future needs; expectation that access to jobs is fair; expectation that salaries are fair; and belief that unfair access to labor markets fuels tensions. Ability to meet current and future needs are coded on a Likert scale running from 1 (completely unable) to 5 (fully able). The “fairness” indicators are coded: 0 (unfair) or 1 (fair). Whether or not competition around employment contributes to tensions is captured on a 1 (not at all) to 5 (absolutely) Likert scale.

**Intergroup behaviors** :  We collect data from two one-shot incentivized behavioral games: the dictator game (a division game where players choose how to split a prize) and stag hunt (which gives players the chance to cooperate).<sup>7</sup> In each wave of data collection, players were randomized, at the session-level, to play either with a partner from the host or refugee community in that country. For example, a Lebanese player could be paired with a Lebanese or a Syrian resident in Lebanon but not with a Jordanian or a Syrian resident in Jordan. Partner identities were re-randomized between the waves so that not all players played with a partner of the same identity in both rounds. We made clear that partners were not individuals in the same room and, at endline, that the partner was not the same partner from baseline.

A hint was given about the partner’s identity based on dialectic differences in the words for common foods, along with a small amount of innocuous information (approximate age, favorite hobby and marital status).<sup>8</sup> Sample intakes and partner assignments by data collection wave are shown in Table 1. This prime relies on a minor, and subtle, difference in dialects in settings with an otherwise high degree of cultural similarity. Standard hints, such as names or language, would not sufficiently differentiate nationalities. More direct ones, such as stating an individual’s nationality, risk interviewer demand biases. This “prime” relies on three things. First, that due to cultural similarities between the countries, many dishes are commonly eaten in both origin and host countries. Second, that dialectic differences mean that some of the same dishes are called (slightly) different things across

> 7 The experimental design and the precise wording of the tasks are presented in Appendix 1. For this and all other appendices, see the full version of the paper: https://isdc.org/publications/building_stability_between_hosts_and_refugees_jordan_lebanon

> 8 This, and a range of other potential identity markers were field tested at the beginning of the project. This “prime” was chosen as, when prompted in qualitative interviews, respondents were able to tell us the nationality of their partner but, before they were prompted, had been unable to tell us the purpose of the experiment.

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