M: Let’s say I wanted to create a formula for measuring the average cost of small goods and consumer items – that is, disregarding major purchases, like houses and cars. A primary goal being the ability to calculate locally ones wages as a measurable multiplier of this index. My first thoughts involved in the price of a gallon of grade 87 gasoline and the price of eggs and or milk. What other common factors could be included to smooth out the variations betweenvarious areas, in terms of shipping costs and all that

G: Your approach makes sense, focusing on essential, widely available goods that reflect everyday costs. To smooth out regional variations caused by shipping, supply chains, and local economic conditions, consider including:

Bread (basic white or whole wheat loaf) – A staple food with relatively stable demand.
Rice (per pound or kg) – A widely consumed staple with less volatility than some fresh goods.
Chicken or ground beef (per pound/kg) – A basic protein source that reflects local food pricing.
Coffee (per pound or common brand container size) – A global commodity with local price variations.
Fast food meal (e.g., McDonald’s combo or similar local equivalent) – A proxy for both labor costs and food pricing.
Public transportation fare (single-ride ticket in major local system) – Represents mobility costs independent of fuel prices.
Toilet paper (common brand, per roll or pack) – A necessity with price fluctuations based on supply chains.
Electricity (per kWh) – Captures utility costs, which can vary significantly by region.
Internet (baseline broadband plan) – A modern essential that reflects service costs.

These categories balance basic food, energy, and services, helping normalize cost variations. If you’re tying this to wages, you could compare against local minimum wage or median income. Would you want a weighted index based on spending habits, or just a simple average?

M: Simple average. The point is to be able to say “given that my salary is X and I worked my hours, my standing on this index is Z times the local index“. And so on. With the goal of being able to quantitatively compare, say, what is considered a middle class income in San Francisco to that of suburban Richmond.

G: A simple average works well for direct comparisons. Since the goal is to measure purchasing power across different locations, your formula could be structured as:

[ \text{Local Index} = \frac{\sum \text{(Selected Goods' Prices)}}{\text{Number of Items}} ]

[ \text{Income Index} = \frac{\text{Hourly Wage} \times \text{Hours Worked}}{\text{Local Index}} ]

This would give you a measure of how many "units" of the local index a person’s income can buy, making it easy to compare across regions.

For robustness, you'd want to collect prices from multiple sources (local grocery stores, national chains, online retailers) to get a fair estimate. Do you want to account for sales tax, or just focus on sticker prices?