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<br /> <br />The Effects of a $15 Minimum Wage by 2019 in Santa Clara County and San Jose 63 <br /> <br />A2. CALIBRATING THE UC BERKELEY IRLE MINIMUM WAGE MODEL <br />A2.1 Structure of the model, and calculations step by step <br />Table A1 summarizes the structure of our model. The table has four components. The top part <br />describes the number of workers in the state who will receive pay increases by 2021. Part A <br />describes the effects of automation and worker productivity gains. Part B describes how much <br />consumer prices will increase and how much those increases will reduce consumer demand and <br />employment. Part C describes how we calculate the income effect: how pay increases will <br />increase consumer spending and employment. Part D describes how we calculate the net effect <br />on employment. In this section we document in detail the data and methods that we use in each <br />part of Table A1. In section A2.2, we document the source of the key parameters used to <br />calibrate our model. <br />Top part: Workers affected and wage increase <br />Lines [1] to [3] in Table A1 use our estimates (described in detail in the first section of the <br />appendix) on how the labor force will grow and how the proposed minimum wage increase would <br />affect the wage distribution of workers in San Jose (respectively Santa Clara County). The wage <br />estimates include the number of workers directly and indirectly affected by the two scenarios, <br />and their nominal wages with and without the policy. We also use our estimate of the total wage <br />bill by 2019: it will be $31.1 billion in San Jose with minimum wage increase (as described in <br />scenario A) and $30.7 billion without the minimum wage increase. In Santa Clara County, we <br />estimate that the total wage bill will be 90.0 billion with the minimum wage increase (as <br />described in scenario B) and 89.1 billion without the minimum wage increase. <br />Part A: Impact of capital-labor substitution and productivity gains <br />Part A calculates the impact of capital-labor substitution and productivity gains on employment <br />and the total wage bill. Our estimates are calculated as follows: <br />The reduction in number of jobs from substitution effects (line [5] in Table A2) is calculated by <br />multiplying four components: (i) the capital-labor substitution elasticity (see section A2.2) (ii) the <br />average wage increase of workers getting increases, that we estimate to be 18 percent based in <br />San Jose (respectively 19 percent in Santa Clara County), (iii) the profit share of revenues (see <br />section A2.2), and (iv) the total number of affected workers. <br />The reduction in number of jobs from productivity gains ([6]) is calculated by multiplying two <br />components: (i) the productivity gains (see section A2.2 for a description of the values we use to <br />calibrate the model) and (ii) the total number of affected workers (that we estimate to be <br />115,000 in San Jose and 250,000 million in Santa Clara County according to our wage <br />simulation model). <br />8.A. - Page 77