2. Using wage elasticity values and the expected wage increases estimated in (1), estimate the probability of losing the job by age, education, occupation, gender and skill level.<sup>27</sup> 3. To select “job losers”, for each individual generate a random variable that takes the value of “1” with the probability computed in (1); in other words, assign unemployment status randomly.

4. Compute simulated earnings and unemployment.

5. Repeat this procedure 1,000 times and compute average earnings and unemployment across simulations and 95 percent confidence intervals.

**Table 2. Values of wage elasticity used for baseline simulation**

||Base|line|Low|Hi|gh|
|---|---|---|---|---|---|
||Short-term|Long-term|Short-term<br>Long-term|Short-term|Long-term|
|Skilled|-0.5|-0.8|-0.1<br>-0.4|-0.7|-1.0|
|Unskilled|-0.7|-1.0|-0.3<br>-0.6|-0.9|-1.2|

_Source: Lichter, Peichl and Siegloch (2013). Note: Because this is a meta-analysis, the definition of skilled workers is not provided._

# Results

**Our results show that disemployment effects are relatively modest. The overall unemployment rate is simulated to increase less than 1 percentage point, and the overall effect of the proposed minimum wage policy on earnings is small and positive.** Table 3 reports the simulated labor market indicators under the minimum wage policy.<sup>28</sup> The overall unemployment rate is simulated to increase by 0.4 percentage point in the short run and by 0.6 percentage point in the long run and this effect is statistically significant at the 5 percent level. Youth unemployment (aged 15-24) is expected to increase by 0.7 percentage point in the short run and by 1.1 percentage points in the long run.<sup>29</sup> The overall effect of the proposed minimum wage policy on earnings (including job losers with zero earnings) is small and positive in the short run (0.24 percent) but not significantly different from zero in the long run, suggesting that the overall increase in earnings does not compensate the loss of earnings due to job losses in the long run.

**The simulated reduction in wage inequality is small; the change in earnings due to the minimum wage increase is likely to affect only the bottom decile of the income distribution.** Figure 13 shows the simulated reduction in earnings inequality **.** We measure earnings inequality comparing average labor earnings at the 1st, 5th and 9th earnings deciles. The increase in the minimum wage reduces the 50/10 ratio from 1.75 to 1.53 (wages at the median divided by wage at the bottom decile), mostly due to the increase among wages at the bottom decile. However, if we include job losers with zero earnings, it reduces to just 1.72, which suggests that the policy has little effect on earnings inequality. A similar pattern is observed when using the 90/10 ratio.

> 27 Skilled workers are defined as workers who have professional occupations or post-secondary education.

> 28 Notice we did not model the potential impact on labor force participation, but rather focus on movements between employment and unemployment, not on movements in and out of the labor force.

> 29 As shown in Table 3, changes are statistically significant at the 5 percent level.

22