Regional extension parameters
These fields exist only under simulations/regional/. National statistics describe broad country context; they are not measured Amazon shopper behavior. A precise source number can still have low confidence when mapped to one skincare campaign.
reference_internet_reach_rate
Meaning. Neutral internet-use fraction used as a comparison point.
Example. 0.9469380188 is the source-dated United States 2024 internet-use fraction. A marketplace with the same value receives an internet-reach ratio of one.
Why it makes sense. Online advertising cannot reach people who are not online. Dividing by a reference prevents the measured fraction from shrinking every market twice.
Relationship. Denominator for internet_reach_rate.
Confidence. High for the sourced statistic and arithmetic; low for its direct connection to Amazon campaign traffic.
reference_target_audience_density
Meaning. Neutral assumed share of internet users who match campaign targeting.
Example. 0.02 represents 2 people out of 100 online people. A marketplace also configured at 0.02 gets an audience-density ratio of one.
Why it makes sense. A premium skincare campaign addresses a narrower group than all internet users.
Relationship. Denominator for target_audience_density.
Limitation. The repository has no verified Amazon reach estimate supporting 2 percent.
Confidence. Low.
reference_income_inequality_gini
Meaning. Neutral Gini coefficient used when scaling daily conversion variation.
Example. 0.35 produces no inequality difference. A value of 0.40 is 0.05 above the reference.
Why it makes sense. A reference turns a national statistic into a relative scenario adjustment. It does not say 0.35 is economically ideal.
Relationship. Compared with income_inequality_gini, then weighted by income_inequality_noise_weight.
Confidence. High for the arithmetic; low for the chosen reference.
economic_willingness_log_odds_weight
Meaning. Controls how strongly the economic-willingness proxy changes conversion log odds.
Example. With weight 1.0 and willingness 1.02, conversion odds are multiplied by 1.02.
Why it makes sense. A weight makes the proxy's influence visible and tunable rather than hard-coded.
Limitation. 1.0 is not estimated from a campaign experiment.
Confidence. Low.
income_inequality_noise_weight
Meaning. Controls how strongly the difference from reference Gini changes daily conversion-noise spread.
Example. With weight 1.0, a Gini value 0.05 above the reference makes the spread 5 percent larger.
Why it makes sense. The Gini coefficient measures distribution, not average willingness to buy. The current model therefore changes variation rather than claiming that inequality always raises or lowers average premium-product demand.
Rejected interpretation. Directly increasing mean demand when Gini rises is not supported. Aggregate inequality cannot identify the income of the targeted shoppers.
Confidence. Low.
internet_reach_rate
Meaning. Fraction of a country's population reported as using the internet.
Example. Japan's 2024 value 0.8554153081 means about 85.54 percent. It does not mean 85.54 percent use Amazon or saw the campaign.
Why it makes sense. Internet access is a necessary, but insufficient, condition for online advertising reach.
Relationship. Multiplies baseline traffic_multiplier as a ratio to reference_internet_reach_rate.
Confidence. High for the World Bank value; low for the campaign mapping.
target_audience_density
Meaning. Assumed fraction of online people matching the campaign's age, income, interest, and targeting conditions.
Example. 0.028 means 2.8 out of 100 online people are treated as addressable prospects in the Japan scenario.
Why it makes sense. In AP Microeconomics terms, not every consumer belongs to the relevant market segment or has both willingness and ability to buy.
Relationship. Combined as a ratio to reference_target_audience_density.
Limitation. This is not an Amazon audience estimate. It should eventually be calibrated to campaign planning or reach evidence.
Confidence. Low.
economic_willingness_multiplier
Meaning. A modest proxy derived from household final-consumption expenditure per-capita growth:
Example. United States growth of about 1.964 percent becomes 1.0196445104.
Why it makes sense. AP Macroeconomics treats consumption as a major part of aggregate demand. Positive real per-person consumption growth can represent a slightly stronger buying environment.
Limitation. Economy-wide realized consumption is not premium-skincare intent. The formula is a scenario conjecture.
Confidence. High for the source statistic; low for the advertising mapping.
income_inequality_gini
Meaning. National Gini coefficient on a zero-to-one scale. Values nearer zero indicate a more equal income distribution; values nearer one indicate more inequality.
Example. Canada uses 0.315 from 2022; the United States uses 0.418 from 2024.
Why it makes sense. A single national average can hide different affordability groups. The current simulator uses the coefficient only as a crude signal for unobserved variation.
Limitation. Survey years differ by country, and Gini alone does not reveal who receives advertising.
Confidence. High for the published statistic; low for the noise mapping.
Regional marketplace inputs
North America
The United States uses 2025 population and official exchange-rate context, 2024 internet reach, 2024 household consumption growth, and 2024 Gini. Canada uses 2025 population, exchange rate, and consumption growth, 2024 internet reach, and 2022 Gini.
The target-audience density is assumed to be 2 percent for both. Overall behavior-mapping confidence is low.
Europe
The United Kingdom, Germany, and France use 2025 population and official exchange rates and 2024 internet reach. Consumption growth uses 2025. Gini uses 2021 for the United Kingdom, 2022 for Germany, and 2023 for France.
The target-audience density is assumed to be 3 percent. Overall behavior-mapping confidence is low.
Japan
Japan uses 2025 population and official exchange rate, 2024 internet reach and household consumption growth, and 2020 Gini.
The target-audience density is assumed to be 2.8 percent. Overall behavior-mapping confidence is low.
Regional volume equation
The regional provider combines the baseline scale with two ratios:
This formula is auditable, but it is not calibrated. Population, budget, bids, ad inventory, product demand, and platform reach can all make real campaign traffic differ.
Official economic sources and provenance
The configuration files record retrieval date 2026-07-30 and World Bank update date 2026-07-13.