Industry Groups Slam NY Cannabis Wage Bill Over Transparency And Cost Concerns

Cannabis groups in New York are pushing back against a proposal that seeks to set up a three-member panel to assess and recommend a sector-wide minimum wage.

The legislation was introduced this week at the state Capitol and may come up for a vote in the closing days of the legislative session.

The New York Cannabis Retail Association, Cannabis Farmers Alliance, and the Empire Cannabis Manufacturers’ Alliance submitted statements warning that the proposal could be detrimental for the industry, reported The Times Union.

Why? Because 40% of businesses are already unprofitable, and many have already cut employee hours, according to cannabis groups.

Cannabis stakeholders argued that higher mandated wages could increase retail prices while shrinking legal sales. That would, consequently, push consumers toward the illicit cannabis market. Legal cannabis businesses are already affected by illicit sales statewide.

The legislation from Democratic labor committee chairs Assemblyman Harry B. Bronson and Sen. Jessica Ramos proposes a board consisting of cannabis industry members and the state labor department, and it could force people to provide documents and testimony if needed.

The bill would also increase transparency by requiring public disclosure of ownership structures, management agreements, salaries, and staffing data.

“I think we’ve done a fair job of improving protections to business owners and their interests, and we are now putting in what I believe to be the fairest mechanism in order to hopefully be able to protect workers, worker safety, and workers’ wages as well,” Ramos said.

To that, industry groups say such an approach could reveal confidential business details, potentially giving competitors access to wage structures and operational data.

“Publicly revealing pay ranges by job title allows competitors to undercut a licensee’s workforce by targeting its employees with marginally superior offers,” the memo said. “Scheduling data reveals operational capacity and staffing models that competitors can exploit.”