is binary. The identifying assumption in (1) is that conditional on observable variables X�� and time fixed effects T�, and in the absence of economic shocks, the trend of the dependent variable would have been parallel between Afghan refugees and the host communities. For the LFS sample, we estimate (1) for all individuals in the data and control for age, household size, job experience, having insurance, education, occupation, and dummies for being household head, being married, and gender. We estimate (1) at the household level for the HEIS sample and control for household size and head’s characteristics, including age, gender, literacy, occupation, and being married.

The second approach for estimation is based on a matching method. We match each Afghan household or individual with an Iranian counterpart as explained in section 4.1.1 and then compare the heterogeneous impact of economic shocks between the two groups by estimating (1) but without controlling for variables X�� and time fixed effects T�. The identifying assumption of this approach is that in the absence of shocks, the trend of Afghan refugees’ outcomes would have been similar to the matched sample of Iranians. This approach is similar to matched difference-in-difference strategy, as described in Heckman et al. (1997, 1998).

# **5. Results**

In this section, we present our key findings. We first discuss the results regarding the heterogenous effect of economic shocks on the labor market, income, and consumption. Next, we present our findings on social cohesion measures. We then examine the asymmetric effect of negative and positive economic shocks on the outcomes. Finally, we study how inter-community and intra-community inequalities are affected by economic shocks in Iran.

**5.1. The unequal effect of economic shocks on the labor market** Panel A of Table 3 presents the regression results of estimating (1) using outcome variables computed from LFS surveys. The coefficient of the Afghan dummy is consistent with the summary statistics in Table 2: Afghan individuals work longer hours, have lower unemployment and layoff rates, and their duration of unemployment is shorter than Iranians. The estimated coefficients for the economic shock index suggest that following a negative shock, people work longer hours and have higher layoff rates. We also find that negative shock leads to a shorter duration of unemployment which can be due to the hardships that motivate individuals to accept job offers that they would not take in normal times. Our coefficient of interest, which is the interaction of the Afghan dummy with economic shock, is only significant when the dependent variable is working hours. According to column (3) of Table 3, one unit increase in shock measure – corresponding to a year-on-year increase in log(USD to IRR rate) by one unit – raises the weekly working hours of Afghan individuals 1 hour and 27 mins more than Iranians.

In panel B of Table 3, we estimate the heterogeneous impact of economic shock using our matching approach. Although we find similar results for the Afghan dummy and the measure of shock, their interaction term becomes insignificant. This finding shows that the impact of economic shocks on labor market outcomes is not significantly different between refugees and host communities when comparing every Afghan individual with an Iranian with very similar characteristics. Therefore, in turbulent times, Iranian employers do not discriminate against Afghan refugees by laying them off, suggesting economic shocks do not reduce social cohesion between employers and Afghan refugees. However, as we only observe employment and not its features such as expropriation, withholding salaries, and harassment, this evidence is incomplete and social cohesion may be weakened in those dimensions.

Table 4 shows the estimation results using two approaches when the dependent variable is the dummy of replacing the sample household with another household next year. Columns (1) and (2) show the results of estimating (1) for all individuals in LFS, and column (3) is for the matched individuals. In all estimations, we find that Afghan individuals have a significantly higher replacement rate. The marginal effect in column (3) implies that being an Afghan refugee raises the probability of replacement by 5.6% compared to the matched sample of Iranians. The coefficients of shock variable are significant in estimations with all 9