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Atlas of internal migration in Brazil 2022 Census · 2017–2022

Migration in Monte Sião/MG (2017–2022)

Monte Sião/MG had a reference population (aged 5 or over in 2022) of 22,775 people. In the 2017–2022 five-year period, the municipality received 2,060 in-migrants and lost 885 out-migrants to other municipalities in Brazil, resulting in a net migration of +1,170 people (51.47 per 1,000 population) and a migration effectiveness index (IEM) of 0.398. This classifies the municipality, for the period, as one of migratory attraction. In addition, 0 arrived with an unreported origin and 10 came from abroad.

Indicators

Migration indicators for Monte Sião/MG, 2017–2022
IndicatorEstimate95% CIPrecision
In-migrants2,0601,570 to 2,550good
Out-migrants885600 to 1,170use with caution
Net migration+1,170603 to 1,737not classified
Net migration rate, TLM (per 1,000 pop.)51.47--
Migration effectiveness index (IEM)0.398--

Sample of in-migrants: 100-499 observations. Sample of out-migrants: 100-499 observations. 95% confidence interval computed as estimate ± 1.96 × standard error.

Top origins and destinations

Top 10 origins of in-migrants to Monte Sião/MG
OriginPeoplePrecision
Águas de Lindóia/SP · view pair in the atlas485use with caution
São Paulo/SP · view pair in the atlas285low precision
Ouro Fino/MG · view pair in the atlas155low precision
Bueno Brandão/MG · view pair in the atlas110low precision
Campinas/SP · view pair in the atlas75low precision
Lindóia/SP · view pair in the atlas45low precision
Top 10 destinations of out-migrants from Monte Sião/MG
DestinationPeoplePrecision
Águas de Lindóia/SP · view pair in the atlas130use with caution
Ouro Fino/MG · view pair in the atlas70low precision
Jacutinga/MG · view pair in the atlas70low precision
Bueno Brandão/MG · view pair in the atlas40low precision

Profile of migrants and residents

In-migrants (arrivals)

Migrant type
CategoryEstimateShareSample
First move from municipality of birth98047.6%50-99
Multi-step migration97047.1%50-99
Return to municipality of birth1105.3%5-19
Educational attainment (people aged 25 and over)
CategoryEstimateShareSample
Completed high school, incomplete higher education52039.5%20-49
No schooling or incomplete elementary31524.0%20-49
Completed elementary, incomplete high school24518.6%20-49
Completed higher education23517.9%20-49
Household income per capita (in 2022 minimum wages)
CategoryEstimateShareSample
1 to 2 minimum wages75536.7%50-99
½ to 1 minimum wage57527.9%50-99
¼ to ½ minimum wage34016.5%20-49
Up to ¼ of a minimum wage2009.7%5-19
More than 2 minimum wages1909.2%5-19
Age and sex
CategoryEstimateShareSample
Ages 25–39, female40019.5%20-49
Ages 25–39, male29014.1%20-49
Ages 15–24, female25012.2%20-49
Ages 40–59, female20510.0%20-49
Ages 5–14, female1959.5%5-19
Ages 40–59, male1808.8%5-19
Ages 15–24, male1708.3%5-19
Ages 60 and over, female1306.3%5-19
Ages 5–14, male1256.1%5-19
Ages 60 and over, male1105.4%5-19

Out-migrants (departures)

Migrant type
CategoryEstimateShareSample
Multi-step migration47553.4%50-99
Return to municipality of birth30033.7%20-49
First move from municipality of birth11512.9%5-19
Educational attainment (people aged 25 and over)
CategoryEstimateShareSample
Completed high school, incomplete higher education20536.3%20-49
No schooling or incomplete elementary15026.5%20-49
Completed elementary, incomplete high school13023.0%5-19
Completed higher education8014.2%5-19
Household income per capita (in 2022 minimum wages)
CategoryEstimateShareSample
½ to 1 minimum wage23526.4%20-49
1 to 2 minimum wages23526.4%20-49
¼ to ½ minimum wage18520.8%5-19
More than 2 minimum wages16518.5%20-49
Up to ¼ of a minimum wage606.7%5-19
Other / suppressed101.1%<5
Age and sex
CategoryEstimateShareSample
Ages 25–39, female17019.2%20-49
Ages 25–39, male11513.0%5-19
Ages 15–24, male11012.4%5-19
Ages 40–59, female10011.3%5-19
Ages 5–14, male9010.2%5-19
Ages 40–59, male809.0%5-19
Ages 5–14, female758.5%5-19
Ages 15–24, female505.6%5-19
Ages 60 and over, male505.6%5-19
Ages 60 and over, female455.1%5-19

Non-migrant residents

Educational attainment (people aged 25 and over)
CategoryEstimateShareSample
No schooling or incomplete elementary7,08045.9%>=500
Completed high school, incomplete higher education3,96025.7%100-499
Completed elementary, incomplete high school2,70517.6%100-499
Completed higher education1,66510.8%100-499
Household income per capita (in 2022 minimum wages)
CategoryEstimateShareSample
1 to 2 minimum wages7,61034.6%>=500
½ to 1 minimum wage7,16032.5%>=500
More than 2 minimum wages2,87013.0%100-499
¼ to ½ minimum wage2,72012.4%100-499
Up to ¼ of a minimum wage1,6307.4%100-499
Other / suppressed300.1%<5
Age and sex
CategoryEstimateShareSample
Ages 40–59, female3,35016.2%100-499
Ages 40–59, male3,13515.1%100-499
Ages 25–39, male2,48012.0%100-499
Ages 25–39, female2,37511.5%100-499
Ages 60 and over, female2,10510.2%100-499
Ages 60 and over, male1,9609.5%100-499
Ages 15–24, male1,4657.1%100-499
Ages 15–24, female1,3406.5%100-499
Ages 5–14, male1,3256.4%100-499
Ages 5–14, female1,1705.7%100-499

Commuting (work and study)

Commuting indicators for Monte Sião/MG
Employed persons (aged 10 and over)13,215
Commute out to work in another municipality595
Commute in from another municipality to work here1,100
Net commuting+505
Out-commuting rate (%)4.50
Commuting attraction index1.034
Median commuting time28 min

Open Monte Sião/MG in the interactive atlas →

Methodological note

Estimates from the sample microdata of the 2022 Demographic Census (IBGE, controlled access), fixed-date migration question (residence on July 31, 2017 compared with residence on July 31, 2022). Every estimate is rounded to multiples of 5 and has passed statistical disclosure control (no cell with fewer than 5 people or 3 sampled households). See the full methodology and the glossary.

How to cite this page

Daniel Pessini Sobreira. Atlas da migração interna no Brasil [Atlas of internal migration in Brazil]: Monte Sião/MG. Data from the 2022 Demographic Census (IBGE). Data version: 2026-10-01. Available at: https://atlas-da-migracao.github.io/en/municipio/monte-siao-mg-3143401/. Dataset DOI: https://doi.org/10.5281/zenodo.22469791.