Methodology

The Concept

Burgernomics tracks the cost of making a single cheeseburger at home using retail ingredient prices. It is inspired by The Economist's Big Mac Index, which uses McDonald's prices to compare purchasing power across countries. Our index focuses on home cooking costs within the United States, broken down by U.S. Census region.

Unlike the Big Mac Index — which tracks a single restaurant chain's pricing — Burgernomics reflects what consumers actually pay at grocery stores. That makes it a more direct measure of food cost inflation as experienced by everyday shoppers, and it lines up with how the BLS Consumer Price Index for food at home is constructed.

The Recipe

Our standard cheeseburger consists of five ingredients, sized for a typical homemade burger. The same quantities are used every month so that price changes are the only variable.

Condiments (ketchup, mustard, pickles) are excluded because the per-burger cost is negligible and the BLS does not track individual condiment prices at regional granularity. We also exclude buns purchased pre-made; the white-bread series is the closest BLS proxy and reflects the underlying flour, yeast, oil, and packaging cost that drives bun pricing.

Step-by-Step Calculation

For each month and region, the burger cost is calculated as:

Cheeseburger Cost = Sum of (ingredient_price × amount_per_burger)

Worked example (national, recent month):
  Ground Beef:  $5.67/lb × 0.330 lbs = $1.871
  Am. Cheese:   $4.92/lb × 0.063 lbs = $0.310
  White Bread:  $1.85/lb × 0.125 lbs = $0.231
  Lettuce:      $1.42/lb × 0.063 lbs = $0.089
  Tomatoes:     $2.18/lb × 0.125 lbs = $0.273
                                       ───────
  Total:                               $2.774

Year-over-year change is the percentage difference between the current month's composite cost and the same calendar month one year earlier. Month-over-month change is the percentage difference between the current month and the immediately prior month. The trailing 12-month average is the simple mean of the most recent 12 monthly composite values.

Per-Field Data Attribution

Every individual data field on every page traces to a specific public source:

• Ground beef price: BLS series APU0000703112, “Ground beef, 100% beef, per lb. (453.6 gm)”.
• American cheese price: BLS series APU0000710212, “Cheese, American, processed, per lb. (453.6 gm)”.
• White bread price: BLS series APU0000702111, “Bread, white, pan, per lb. (453.6 gm)”.
• Iceberg lettuce price: BLS series APU0000FL2101, “Lettuce, iceberg, per lb. (453.6 gm)”.
• Tomatoes price: BLS series APU0000712311, “Tomatoes, field grown, per lb. (453.6 gm)”.
• Regional code: BLS region geographies — 0000 (National), 0100 (Northeast), 0200 (Midwest), 0300 (South), 0400 (West).
• Year-over-year: derived locally as (current_month_total − prior_year_same_month_total) / prior_year_same_month_total.
• Month-over-month: derived locally as (current_month_total − prior_month_total) / prior_month_total.
• 12-month average: derived locally as the simple mean of the most recent 12 composite monthly totals.
• Last updated timestamp: the publication date of the latest BLS release we have ingested, recorded in stats.json.

The Primary Data Source

All retail prices come from a single authoritative source: the U.S. Bureau of Labor Statistics CPI Average Price Data program. BLS publishes average retail prices for approximately 70 food items as part of the Consumer Price Index program. Data is collected monthly from thousands of retail establishments across the country and published at both the national level and for the four Census regions.

This data is U.S. government public domain — there are no licensing restrictions, usage fees, or access limitations. We access it via the BLS Public Data API (version 1.0, no registration required). For agricultural context on commodity supply we cross-reference the USDA Economic Research Service, and for inflation framing we use the Federal Reserve's reported CPI series.

Regional Coverage

The BLS provides average price data for four U.S. Census regions:

• Northeast — CT, ME, MA, NH, NJ, NY, PA, RI, VT
• Midwest — IL, IN, IA, KS, MI, MN, MO, NE, ND, OH, SD, WI
• South — AL, AR, DE, DC, FL, GA, KY, LA, MD, MS, NC, OK, SC, TN, TX, VA, WV
• West — AK, AZ, CA, CO, HI, ID, MT, NV, NM, OR, UT, WA, WY

These are the most granular geographic breakdowns available from the BLS average price program. City-level data is not published for individual food items.

Update Schedule

The BLS releases new average price data monthly, typically two to three weeks after the reference month. We update the index within 24 hours of each BLS release. Historical data is never revised unless the BLS issues a correction; if BLS does issue a correction, we update the affected months and note the change.

Known Limitations

• No city-level data. BLS average prices are published at the regional level, not by city or metro area. Prices within a region can vary significantly between, for example, New York City and rural Pennsylvania.
• Simplified recipe. A real cheeseburger might include different cheese varieties, specific bun types, or additional toppings. Our index uses the closest BLS-tracked proxy for each ingredient and a fixed weight basket.
• Retail prices only. The index tracks grocery store prices, not restaurant prices. The cost to eat a cheeseburger at a restaurant is significantly higher due to labor, occupancy, and franchise margin.
• No quality adjustment. BLS prices are averages across brands and quality tiers. Premium ingredients (grass-fed beef, artisan cheese) cost more; budget options cost less. Hedonic adjustments are not applied.
• Seasonal noise. Iceberg lettuce and tomato prices in particular swing seasonally with growing-region weather. The composite index reflects the realized retail price each month and is not seasonally adjusted.

Frequently Asked Questions

Citation

If you cite Burgernomics in published work, please cite the underlying BLS series IDs (listed above) for raw retail prices and cite Burgernomics for our recipe-weighted composite index and regional breakdowns.