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<br /> <br />The Effects of a $15 Minimum Wage by 2019 in Santa Clara County and San Jose 60 <br /> <br />A1. THE WAGE SIMULATION MODEL <br />In this section, we describe our simulation model for estimating the number of workers that <br />would be affected by the Scenario A and Scenario B minimum wage increases. We provide a <br />general overview of our methodology here. For full documentation of the model and data we use, <br />see Perry, Thomason and Bernhardt (2016). <br />The logic of our method is to simulate the future San Jose and Santa Clara County wage <br />distributions with and without the scenario minimum wage increases. First, we use our model to <br />run a “baseline” simulation of the wage distribution through 2019 assuming existing minimum <br />wage schedules (see Table 2 and Table 3). We then use our model to run a “scenario” simulation <br />of the wage distribution through 2019 assuming the minimum wage increases specified in the <br />two scenarios. <br />We then compare the baseline and scenario simulated wage distributions to identify the impact <br />of the minimum wage increase scenarios above and beyond currently scheduled minimum wage <br />increases. With this comparison, we are able to estimate (a) the number of workers affected by <br />each scenario, and (b) the additional wages earned as a result of the increase. In our estimate of <br />affected workers, we include those workers who earn just above the new minimum wage but who <br />also receive an increase via the ripple effect (see below). Our estimates are adjusted for <br />projected wage and employment growth. <br />Dataset <br />We combine the 2013 and 2014 IPUMS American Community Survey (ACS) <br />(https://usa.ipums.org/usa/) in order to attain sufficient sample size for our analysis (Ruggles et <br />al. 2015). The American Community Survey is the largest annual survey conducted by the U.S. <br />Census Bureau, and interviews more than 2.3 million households throughout the United States. <br />The ACS is better suited than the Current Population Survey (CPS) for conducting labor market <br />analyses at the state or sub-state level for two main reasons: first, the ACS sample size is much <br />larger than the CPS; and second, the ACS contains place of work data, while the CPS data are <br />limited to place of residence. This allows us to disaggregate wage and employment data for sub- <br />state geographical units. <br />Sample definition <br />We make the following adjustments to our ACS sample: <br />1. We restrict the sample to individuals age 16 to 64 who had positive wage and salary <br />income in the previous 12 months, who worked in the previous 12 months, and who were <br />not self-employed or unpaid family workers. <br />8.A. - Page 74