_Prices_ . The database includes 120 results on prices where prices refer to all types of prices from food and non-food items, to rents and services. Results in Table 7 show that 37-46% of results are positive and significant, between 18 and 23% are non-significant and between 36 and 39% are negative and significant. As mentioned, there is no good or bad interpretation of these results as changes in prices benefit some hosts and damage others. An analysis of the positive results shows that these are almost entirely represented by food and rents prices whereas an analysis of the negative values shows that these are represented mostly by overall inflation, luxury goods, services, and labor-intensive products.

Overall, a forced displacement crisis generates significant changes in prices. The probability of these changes to be positive or negative is approximately similar but associated to the type of product or service observed. Prices for food and rents tend to increase whereas prices for labor intensive products and services tend to decline. As compared to the basic theory illustrated at the outset of the paper, these results show that prices do not unequivocally increase. The main surprise and in contrast to popular views, in some cases prices decline. These findings remain working hypotheses based on very preliminary data and future research will need to be much more comprehensive in coverage of different products and countries. It will also be essential to expand research on price elasticities, including cross elasticities, and relate this research with the research on household well-being.

# 4.2.2 Employment and Wages

_Employment_ . The database on employment contains 334 observations where employment can be a rate, a status or a probability. In all these cases a positive value indicates that employment among host communities has improved as a result of forced displacement. Results in Table 7 show that between 12 and 14% of results are positive and significant, between 65 and 67% are non-significant and between 19 and 24% are negative and significant. Therefore, the majority of results is non-significant, and this reaches 7681% of all results if we add positive and significant results. However, negative results outweigh positive results.

To see whether we could trace results to some specific population characteristics, we constructed dummy variables for positive and negative results and run multivariate logit regressions using these dummies as dependent variables. Predictors are dummies representing population groups including males and females, formal and informal, young and old, and low-skilled and high-skilled workers. Table 8 shows the results.<sup>19</sup> Only two results are consistent across weighted and unweighted regressions. One is that males show a negative association with negative results indicating that this group is not well represented among negative results as compared to its representation among positive or non-significant results.<sup>20</sup> However, since females also show negative signs, we cannot conclude that gender helps to explain positive or negative results. The second is that older workers are associated with positive coefficients indicating that this group is highly represented among positive and significant results. The variable young is dropped because there are no observations among positive coefficients. Unlike gender, this indicates that age is a critical factor in explaining positive results with younger workers clearly disadvantaged vis-à-vis older workers.

As a robustness test, we run the same regressions proposed above in a bivariate mode also adding the time lag between shock and evaluation, the average share of refugees, the countries’ classification in HICs, MICs and LICs, and the 14 crises considered. Results are shown in Table 9 where, for simplicity, we only report t-statistics with values significant at 90% level or above highlighted in bold. As before, we only comment results that are robust to the weighted and unweighted specifications. Males, young and informal workers have a positive association with negative values whereas old, formal and low-skilled workers have a higher association with positive values (except for the weighted t-stat for old which has a negative value). As compared to Table 8, results for males in Table 9 are not consistent with the sign changing between the two

> 19 These results should be treated with caution as the number of results for population sub-groups is small.

> 20 Note that zero values in the dependent variable represent positive and non-significant values.

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