Raising minimum wages because of excessive compassion leads to disaster

 

California’s $20 Minimum Wage Experiment Crushes Carl’s Jr. as Crime and Costs Collide

California’s aggressive push for a $20 fast-food minimum wage was sold as a moral victory for workers, a bold stand against corporate greed that would lift families without consequence. Yet the reality unfolding at Carl’s Jr. locations across the state tells a different story—one of shuttered opportunities, fleeing staff, and franchise operators driven to bankruptcy. What began as political virtue-signaling has delivered economic pain that no amount of union rhetoric can disguise.

Standard price-theory predicts exactly this. When the government sets a binding price floor for low-skill labor above many workers’ productivity in a thin‑margin, high‑competition industry, firms can’t absorb the gap. They adjust on every margin they can—prices, hours, staffing, automation, quality, and ultimately exit. The most marginal locations and franchisees go first. Add rising crime and other fixed burdens, and the result accelerates: fewer open stores, worse working conditions, and bankrupt operators.

Why economics predicts these outcomes

• Price floor above productivity: A minimum wage is a price floor. If it’s set above the value of what a given worker in a given store can produce (their marginal revenue product), employing that worker becomes a loss. Firms don’t print money—they adjust or shut down.

• Demand elasticity in fast food: Fast food faces many close substitutes (other restaurants, cooking at home), and consumers are price sensitive. When labor costs jump, menu prices must rise. Because demand is elastic, quantity sold falls more than revenue rises; profits shrink.

• Thin margins and limited pass‑through: Quick-service restaurants typically run on single‑digit operating margins. Rent, royalties, mandated supply contracts, and utilities don’t move much. That leaves labor, hours, and service quality as primary shock absorbers. If those can’t bridge the gap, exit follows.

• Ripple effects up the ladder: Raising the floor compresses pay differentials. Shift leads, assistant managers, and managers expect higher wages too. Benefits and training are often trimmed to compensate, degrading working conditions just as nominal pay rises.

• Heterogeneity matters: A uniform wage floor ignores big differences in store productivity, foot traffic, and local risk. High-volume suburban sites may survive; low-volume or high-crime sites can’t. Closures, cut hours, and bankruptcies concentrate where margins were already thinnest.

• Crime is a real cost: Security, shrinkage, vandalism, and safety risks raise effective operating costs and lower staff willingness to work certain shifts. Combine elevated crime with a mandated wage jump and some units cross from barely viable to nonviable.

• Franchising constraints: Franchisees pay royalties tied to revenue, not profit, and often must buy inputs through the franchisor’s channels. That reduces flexibility to offset a wage shock. If corporate brand support is weak, survival becomes even harder.

• Long-run substitution and exit: Over time, firms automate ordering, close dining rooms, reduce late-night hours, and invest in drive‑thru and kiosks. Where that still doesn’t pencil out, they exit the market or the state.

Why “studies show small effects” can coexist with closures

• Averages hide heterogeneity: A modest average employment change can mask concentrated losses in lower‑productivity, higher‑crime, or higher‑cost locations—the exact places that disappear.
• Hours vs headcount: Total hours worked often fall more than the number of employees, muting headline job-loss stats.
• Short-run vs long-run: Immediate effects look small; the full adjustment (automation, closures, slower openings) plays out over several years.
• Survivorship bias: Data drawn from surviving firms understates the impact on those that exited.

What laissez‑faire recommends instead

• Let wages be set by competition: When wages track productivity, jobs exist because the value produced covers the pay. That sustains employment and on‑the‑job skill building.
• Lower the cost of living rather than forcing pay up: Deregulate housing and land use so rents fall; reduce sales and excise taxes that hit low-income households; streamline permitting and licensing that inflate prices.
• Remove burdens that raise business costs: Cut red tape specific to quick‑service operations (e.g., rigid scheduling and equipment mandates) that make staffing and investment more expensive.
• Restore public safety: Policing and courts are core state functions. Reducing crime lowers a real, distortionary tax on commerce and labor.
• If policymakers insist on income support, prefer less distortionary tools: Broad, neutral tax relief or earned income tax credits are less damaging than wage floors because they don’t force the price of labor above its market value at the point of hire.

Bottom line

You can’t mandate prosperity. In a competitive industry with elastic demand and thin margins, a high uniform wage floor predictably yields higher prices, fewer hours, staff cuts, automation, worse non-wage conditions, and closures—especially where productivity is low and crime is high. Markets raise pay sustainably by boosting productivity and competition for workers; coercive wage floors trade visible raises for hidden losses in opportunity and safety, with the hardest hit concentrated among the most vulnerable stores, franchisees, and employees.

In addition:

Here’s additional, practical, and testable context from a free‑market perspective.

What this law actually did

• Scope: California’s AB 1228 set a $20/hour floor starting April 1, 2024 for “limited‑service” fast‑food chains with 60+ locations nationwide. Smaller independents, full‑service restaurants, and some in‑store/grocery exceptions are carved out.
• Escalator: A state council can ratchet the wage annually by up to the lesser of 3.5% or inflation through 2029. Many cities already layer higher local minimums on top.
• Franchising still pays royalties and ad fees on revenue, not profit, constraining flexibility just as a large cost shock hits.

Why thin‑margin chains get hit hardest (with a simple, realistic P&L)

• Typical QSR cost structure (ballpark): food 28–33% of sales, labor 25–30%, occupancy 8–12%, royalties 4–6%, ad fund 4–5%, utilities/other 5–8%. Operating margins often sit in the single digits.
• When the floor jumps to $20, the true hourly cost is higher once you add payroll taxes, workers’ comp, and ripple raises for shift leads and managers.
• Illustration:
  • Before: average wage $16; blended labor 28% of $1.6M annual sales = $448k.
  • After: floor to $20 with compression bumps lifts the blended wage bill roughly 20–30% (varies by store). Say 25% for illustration → labor becomes $560k (35% of sales).
  • To hold margin with no drop in traffic, prices must rise enough to recapture an extra $112k. With a 65% contribution margin on an extra dollar of sales after food and variable costs, you need roughly $112{,}000 / 0.65 \approx 172{,}000$ in additional sales—about a 10.8% price hike.
  • But fast‑food demand is price sensitive. If own‑price elasticity is around $-1.5$, a 10.8% price increase implies roughly a 16% drop in transactions. Revenue doesn’t grow enough, the margin shrinks, and marginal stores flip from barely profitable to loss‑making.

Channels of adjustment firms actually use

• Prices: Menu prices and fees rise; discounting and coupons are cut back.
• Hours, staffing, and mix: Fewer total labor hours, thinner night shifts, and more junior staff share.
• Capital substitution: Kiosks, mobile ordering, drive‑thru prioritization, and smaller dining rooms.
• Product and service quality: Tighter menus, slower service at peaks, less cleaning/security—hurting worker safety and customer experience.
• Exit and consolidation: The weakest sites, timeslots, and franchisees disappear first; surviving operators concentrate in higher‑volume, safer trade areas.

Why “average effects look small” can still mask real harm

• Composition: High‑productivity suburban stores survive and pull up the average. Low‑productivity or higher‑crime sites close—a concentrated loss.
• Hours vs. headcount: Total hours fall more than the body count, muting headline employment changes.
• Timing: The largest adjustments (automation, lease non‑renewals, canceled remodels) play out over 12–36 months, not 12 weeks.
• Survivorship bias: Data from surviving units systematically understate the harm to those that exited.

Crime and nonlabor burdens matter a lot

• Security and shrink: Higher incidence of theft, vandalism, and assaults functions like a tax on doing business. Insurance, workers’ comp, and turnover all rise.
• Interaction effect: When a store is already on a razor’s edge, adding both a wage shock and higher security losses pushes it past the viability threshold. The policy multiplies—not just adds to—preexisting pressures.

What to watch in the next 12–24 months

• Transactions vs. sales: Track customer counts, not just revenue. Rising average tickets can mask falling foot traffic.
• Hours per store: Total paid hours and shift coverage, especially late evening and overnight.
• Openings and closures: Net unit counts by ZIP code, with attention to border areas and high‑crime tracts.
• Menu and ops: More kiosks, limited dining rooms, shorter menus, and shorter hours are leading indicators of exit risk.
• Franchise health: Chapter 11 filings, deferred remodels, royalty relief requests—signs that economics aren’t penciling.

How to rigorously test the impact (if you want to analyze it yourself or follow credible work)

• Border‑county difference‑in‑differences: Compare CA counties near AZ/NV/OR with matched neighbors across the border from 2019 onward, focusing on limited‑service NAICS 722513 employment, wages, hours, and establishment counts.
• Store‑level panels: Use foot‑traffic or credit‑card datasets to run event studies around April 1, 2024. Look at transactions, not just spend.
• Hazard models for exit: Predict closures using pre‑policy margins (proxied by traffic, rents, crime, and competition) to test whether marginal, high‑burden stores were the ones that died post‑policy.
• Hours decomposition: Break employment into headcount and hours per worker to capture the intensive‑margin cut that top‑line job counts miss.

Comparisons that inform expectations

• Seattle’s step‑ups to $15+ showed mixed headline results but meaningful cuts to hours and a shift toward higher‑productivity firms—consistent with the mechanism above.
• New York City’s early kiosk wave followed wage hikes, with late‑night hours trimmed first.
• Across countries, large, sudden wage floors in low‑skill sectors reliably trigger substitution to capital and to higher‑productivity firms; the main question is how fast, not whether.

What laissez‑faire would prioritize instead

• Let wages reflect productivity: Competition for labor pushes sustainable raises where output per hour supports it, preserving on‑the‑job training and entry‑level rungs.
• Cut the cost of living directly: Zoning reform to lower housing costs; reduce regressive consumption taxes and fees that squeeze low‑income households.
• Reduce business frictions: Streamline permits, health‑code micromanagement, scheduling mandates, and litigation risk that raise fixed costs.
• Core public safety: Competent policing and courts lower the “crime tax” on both workers and operators.
• If income support is desired, use less distortive tools: Broad tax relief or earned income tax credits top up take‑home pay without forcing the wage above the value produced at the point of hire.

Bottom line
Fast‑food is a competitive, thin‑margin sector serving price‑sensitive customers. A uniform, high wage floor—especially when layered on top of crime, high rents, and rigid franchising costs—predictably yields fewer hours, fewer units, more automation, and worse non‑wage conditions. That’s not a moral failure by businesses; it’s price signals doing their job. Sustainable gains for workers come from higher productivity, robust competition for labor, and lower living costs—not coercive wage setting.