Documentation

Data & Methodology

Understanding the sources, methods, and limitations of this analysis

Data Sources

Data Exclusions

Minnesota Excluded

Minnesota shows artificially high remittance volumes in Banco de Mexico data due to a data collection issue. Some remittance companies reported their server location (Minnesota) rather than the actual sender's location. Minnesota is excluded from all visualizations to ensure accuracy.

“No Identificado” Category

Approximately 5-10% of remittances have unknown US state of origin. These are included in national totals and summary statistics but are not displayed on the geographic map.

Methodology

Remittance Measurement

Remittance data comes from Banco de Mexico, which collects information from licensed money transfer operators. Values represent the USD amount received in Mexico, reported quarterly at the state and municipal level. This is considered the most reliable source for Mexico-bound remittances.

Sender Proxy Methodology

Sub-state US sender data is not directly available from official sources. We use the Mexican-born population from ACS PUMS as a proxy for potential remittance senders. This proxy assumes that Mexican-born individuals are more likely to send remittances to Mexico, though actual sending behavior varies by individual circumstances including income, years in the US, and family ties.

Geographic Codes

# Mexico: Municipality ID 1001 = Aguascalientes, Aguascalientes

# US: “Nueva York” mapped to “New York”

Currency and Units

All monetary values are reported in US Dollars (USD). Values from Banco de Mexico for US state origins are reported in millions of USD. Mexican state and municipal data is reported in raw USD and converted to millions for consistency in visualizations.

Demographic Filters (Mexico)

Demographic filters for Mexico are derived from INEGI's ENIGH 2022 survey, which collects detailed information about household income, expenditures, and demographics. We identify households that reported receiving remittances from abroad and calculate their demographic distribution by state.

When you apply a demographic filter (e.g., “Age 25-34”), the displayed remittance value is scaled by the proportion of remittance-receiving households in that demographic group for each state. This provides an estimate of remittances received by specific demographic segments.

Important: Demographic filters apply proportional scaling based on survey data. The resulting values are estimates, not direct measurements. State-level demographic proportions are applied uniformly, so sub-state variations are not captured.

Income Deciles (Mexico)

Income deciles (D-I through D-X) are calculated from ENIGH 2022 based on household income. D-I represents the lowest 10% of income earners and D-X represents the highest 10%. The distribution shows what percentage of remittance-receiving households fall into each income bracket by state, revealing the economic profile of remittance recipients.

Municipal Demographics (Census 2020)

Municipal-level demographics come from the INEGI Census 2020 (ITER dataset), which is a complete enumeration of Mexico's population. Unlike ENIGH (which is a sample survey representative only at the state level), Census 2020 provides reliable statistics for all 2,469 municipalities.

Municipal demographics include: population, gender distribution, mean age, indigenous language speakers, years of schooling, and infrastructure access (internet, piped water, electricity, cellphone). Note that these are general population demographics, not specific to remittance-receiving households.

Poverty Indicators (CONEVAL 2020)

Municipal poverty indicators come from CONEVAL's official poverty measurement based on Census 2020. CONEVAL uses a multidimensional approach that considers both income and social deprivations.

Key Indicators:

  • Poverty Rate: % of population with insufficient income AND at least one social deprivation
  • Extreme Poverty: % with insufficient income for basic food basket AND 3+ social deprivations
  • Vulnerable: % with social deprivations but adequate income, or adequate social access but low income
  • Social Deprivations: Food insecurity, lack of health access, no social security, housing quality issues

This multidimensional approach captures poverty beyond just income, providing insight into the social conditions of remittance-receiving communities.

Municipal Income (ICMM 2022)

Municipal income data comes from INEGI's ICMM (Ingreso Corriente para los Municipios de México) 2022, which provides estimates of average household income at the municipal level using small area estimation techniques.

Methodology:

  • ICPTH: Average Quarterly Household Current Income (Ingreso Corriente Promedio Trimestral por Hogar)
  • Estimation: Model-based small area estimation combining ENIGH 2022 survey with Census 2020
  • Per Capita: Calculated by dividing household income by average household size
  • USD Conversion: Converted using approximate 2022 exchange rate of 17 MXN/USD

Coverage: Income estimates are available for 1,132 of 2,469 municipalities (46%). Municipalities without estimates are typically smaller or have insufficient auxiliary data for reliable model-based estimation. The coefficient of variation (CV) indicates the precision of each estimate.

US PUMA Demographics

Public Use Microdata Areas (PUMAs) are census geographic units containing approximately 100,000 people. We aggregate ACS PUMS microdata for Mexican-born individuals to calculate demographics at the PUMA level, providing sub-state geographic detail for remittance senders.

PUMA Metrics:

  • Population: Total Mexican-born population in each PUMA
  • Median Wages: Weighted median of WAGP (wages/salary income) for employed individuals
  • Demographics: Age, gender, education, and English proficiency distributions
  • Share of Wages Sent: Estimated percentage of median wages sent as remittances (per capita remittances ÷ median wages)

State Fallback: For PUMAs with insufficient sample size (<20 records), we use state-level median wages as a fallback. This provides 98% coverage across all PUMAs. PUMAs using state-level data are indicated in the interface.

Data Limitations

  • Remittance data captures only formal channels (money transfer operators, banks). Informal transfers are not included.
  • US state of origin is based on sender-reported location, which may not always reflect actual residence.
  • Demographic data from ACS is survey-based and subject to sampling error, particularly for smaller geographies.
  • ENIGH 2022 demographic data is from a point-in-time survey and may not reflect current demographic distributions.
  • Demographic filters assume that the proportion of households in each demographic group remains constant across years, which is an approximation.
  • Municipal demographics (Census 2020) represent the general population, not specifically remittance-receiving households.
  • State-level ENIGH data provides remittance-specific demographics; municipal-level Census data provides general population demographics.
  • Municipal income (ICMM 2022) estimates are only available for 46% of municipalities; smaller municipalities often lack reliable estimates.
  • US PUMA wages reflect Mexican-born individuals only and may differ from overall PUMA wage levels.
  • “Share of wages sent” is an estimate based on per capita remittances and median wages; actual individual sending rates vary significantly.