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Nexus-Based Affordable Housing Fee Analysis for Rental Housing Draft Report 02/26/18 that only those buyers or renters of new housing units relocating from outside Pleasanton should be counted in the impact analysis—would require assuming that the homes left by those households relocating within Pleasanton would be demolished or left vacant in perpetuity. This would only be the case were the City experiencing a significant loss of population and housing inventory, as has occurred, for instance, in Detroit. Pleasanton has not experienced such declines. The Consumer Expenditure Survey from the United States Bureau of Labor Statistics provides data for households at a variety of income levels, detailing the amounts that typical households spend on things like "Food at Home,""Apparel and Services," and "Vehicle Maintenance and Repairs." Interestingly, household expenditures by category are not uniformly proportional to household income levels. For example, households earning around $76,560 (adequate to rent a studio apartment) spend roughly 10.9 percent of their income on food and drink (at home and eating out), while households earning $143,520 who can afford to rent a three-bedroom apartment spend only about 9.5 percent of their income on food and drink. Because of these and other differences in proportionate spending, the expenditure profile varies at different income levels. The renter household's typical expenditures were converted to the number of jobs created by their spending. The first step in this process is to determine how much of an industry's gross receipts are used to pay wages and employee compensation. EPS relied on data from the Economic Census,2 which provides employment, gross sales, and payroll data by industry for Alameda County. In certain instances, Alameda County data was not available for every Economic Census industry—in those cases, EPS relied on statewide Economic Census data for that industry. To link the Economic Census data and the Consumer Expenditure Survey data, EPS made determinations as to the industries involved with expenditures in various categories. For example, purchases in the Consumer Expenditure Survey's"Food at Home"category would likely involve the Economic Census's"Food & Beverage Stores" industry, where gross receipts were more than eight times the employees' wages. By contrast, purchases in the Consumer Expenditure Survey's"Entertainment Fees and Admissions"category were attributed to the Economic Census'"Arts, Entertainment, and Recreation" industry, where gross receipts are only about three times the employees' wages. Where more than one Economic Census category was attributable to a Consumer Expenditure Survey category, EPS estimated the proportion of expenditures associated with each Economic Census category. After determining the amount of the household's expenditures that were used for employee wages, EPS estimated the number of employees those aggregate wages represent. EPS calculated the number of workers supported by that spending using the average wage per worker (also from the 2013 Economic Census). These wages ranged from a low of roughly $11,900 per year for workers in the personal laundry services industry to a high of more than $134,700 average salary for data processing, hosting, and related services industry. 2 Note that the Consumer Expenditure Survey data is based on information current as of 2014. The latest data available for the Economic Census was published in 2013. Because the data sources were from different years, EPS converted all numbers to 2015 dollars using the Consumer Price Index (CPI) for the San Francisco Metropolitan Statistical Area (MSA) from the Bureau of Labor Statistics. Economic&Planning Systems, Inc. 14 P:\ISIOOOs\151111Pka a rtonFee\Repo\4flordabk_Xouslog\151111report022,1arental.doa