In the 1970s, the City of San Francisco, California, adopted a business tax system that levied either a payroll tax or a gross receipts tax, whichever was higher. The approach came under fire in the 1990s, however, when a similar business tax system used by the City of Los Angeles was declared unconstitutional, leading San Francisco to abandon the hybrid approach. A more traditional payroll tax was implemented in its place, and while the move addressed the changing statutory environment, it also led to a loss of $25 million in business tax revenue and $70 million in related litigation costs.
The new approach brought other challenges, as well. The tax was the city’s second largest single source of revenue after property taxes, but it was widely believed to be flawed. Research by outside groups and city staff concluded that the tax was inequitable, lacked stability, impeded economic growth, and was difficult to administer. It also became clear that the tax affected businesses with large numbers of employees more heavily than those with fewer employees. It created incentives for firms with high payrolls to reduce their liability through wage cuts, layoffs, and other workforce reductions, creating a chilling effect on employment. This all-important revenue source eventually became synonymous with raising the cost of labor and discouraging hiring in San Francisco. The equitability problem was further exacerbated by a growing number of exclusions for select industries such as bio-tech, clean energy, and business in the Central Market Street region, along with stock-based compensation for pre-IPO companies. Exclusions became so pervasive that in 2010, fewer than 10% of registered businesses were responsible for paying the levy.
Faced with the challenge of replacing the city’s second largest source of revenue, San Francisco began its search for something that was (1) equitable, (2) stable, (3) growth oriented, and (4) simple to administer as well as statutorily amenable. To accomplish this, the city turned to dynamic modeling, a process that creates mathematical algorithms based on census data, historical behavior patterns, economic indicators, and other data to predict the impact of policy decisions. From the outset it was clear that economic impact assessments would be important because efforts to amend the business tax at the ballot box had been unsuccessful in the past. A more progressive gross receipts approach that was being implemented in other large California cities was believed to be a viable alternative; however, it lacked the quantitative gravitas necessary to convince some skeptics. This is where dynamic modeling made the difference.
The city contracted with an outside firm to develop “censes-driven” forecasts under a number of scenarios. The impact assessments concluded that the gross receipts alternative would shift the tax burden away from labor cost and would likely be a more stable source of revenue for the city. It was also concluded that the gross receipts approach was more equitable because it would address sole proprietors and partnerships that had previously gone untaxed.
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- Forecasting and Data Analysis
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