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

Migration in Gaúcha do Norte/MT (2017–2022)

Gaúcha do Norte/MT had a reference population (aged 5 or over in 2022) of 7,790 people. In the 2017–2022 five-year period, the municipality received 1,150 in-migrants and lost 610 out-migrants to other municipalities in Brazil, resulting in a net migration of +540 people (69.49 per 1,000 population) and a migration effectiveness index (IEM) of 0.308. This classifies the municipality, for the period, as one of migratory attraction.

Indicators

Migration indicators for Gaúcha do Norte/MT, 2017–2022
IndicatorEstimate95% CIPrecision
In-migrants1,150958 to 1,342good
Out-migrants610429 to 791use with caution
Net migration+540276 to 804not classified
Net migration rate, TLM (per 1,000 pop.)69.49--
Migration effectiveness index (IEM)0.308--

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 Gaúcha do Norte/MT
OriginPeoplePrecision
Paranatinga/MT · view pair in the atlas85low precision
Primavera do Leste/MT · view pair in the atlas55low precision
Rondonópolis/MT · view pair in the atlas55low precision
Barra do Garças/MT · view pair in the atlas50low precision
Canarana/MT · view pair in the atlas45low precision
Bom Jesus das Selvas/MA · view pair in the atlas35low precision
Sorriso/MT · view pair in the atlas30low precision
Cuiabá/MT · view pair in the atlas20low precision
Água Boa/MT · view pair in the atlas20low precision
Alto Garças/MT · view pair in the atlas20low precision
Top 10 destinations of out-migrants from Gaúcha do Norte/MT
DestinationPeoplePrecision
Paranatinga/MT · view pair in the atlas65low precision

Profile of migrants and residents

In-migrants (arrivals)

Migrant type
CategoryEstimateShareSample
Multi-step migration62053.9%100-499
First move from municipality of birth51044.3%100-499
Return to municipality of birth201.7%5-19
Educational attainment (people aged 25 and over)
CategoryEstimateShareSample
Completed high school, incomplete higher education24034.0%50-99
No schooling or incomplete elementary24034.0%50-99
Completed higher education11516.3%20-49
Completed elementary, incomplete high school11015.6%20-49
Household income per capita (in 2022 minimum wages)
CategoryEstimateShareSample
1 to 2 minimum wages37532.5%100-499
½ to 1 minimum wage37032.0%100-499
More than 2 minimum wages22019.0%50-99
¼ to ½ minimum wage16514.3%50-99
Up to ¼ of a minimum wage252.2%5-19
Age and sex
CategoryEstimateShareSample
Ages 25–39, male22019.0%50-99
Ages 25–39, female20517.7%50-99
Ages 5–14, female13011.3%20-49
Ages 15–24, male11510.0%20-49
Ages 40–59, female1059.1%20-49
Ages 40–59, male1059.1%20-49
Ages 5–14, male1008.7%20-49
Ages 15–24, female1008.7%20-49
Ages 60 and over, male403.5%5-19
Ages 60 and over, female353.0%5-19

Out-migrants (departures)

Migrant type
CategoryEstimateShareSample
Multi-step migration34556.6%50-99
First move from municipality of birth18029.5%20-49
Return to municipality of birth8513.9%5-19
Educational attainment (people aged 25 and over)
CategoryEstimateShareSample
No schooling or incomplete elementary13040.6%20-49
Completed high school, incomplete higher education8025.0%5-19
Completed elementary, incomplete high school6520.3%5-19
Completed higher education4514.1%5-19
Household income per capita (in 2022 minimum wages)
CategoryEstimateShareSample
½ to 1 minimum wage21034.4%20-49
More than 2 minimum wages11518.9%5-19
1 to 2 minimum wages10517.2%5-19
¼ to ½ minimum wage9515.6%5-19
Up to ¼ of a minimum wage8013.1%20-49
Other / suppressed50.8%<5
Age and sex
CategoryEstimateShareSample
Ages 15–24, female11018.3%5-19
Ages 25–39, male8514.2%5-19
Ages 25–39, female7512.5%5-19
Ages 5–14, female7512.5%5-19
Ages 40–59, female6510.8%5-19
Ages 40–59, male508.3%5-19
Ages 5–14, male457.5%5-19
Ages 15–24, male406.7%5-19
Ages 60 and over, female305.0%5-19
Other / suppressed254.2%5-19

Non-migrant residents

Educational attainment (people aged 25 and over)
CategoryEstimateShareSample
No schooling or incomplete elementary1,70042.3%>=500
Completed high school, incomplete higher education1,29532.3%100-499
Completed elementary, incomplete high school63515.8%100-499
Completed higher education3859.6%100-499
Household income per capita (in 2022 minimum wages)
CategoryEstimateShareSample
½ to 1 minimum wage1,88525.2%>=500
1 to 2 minimum wages1,87525.0%>=500
¼ to ½ minimum wage1,42018.9%100-499
Up to ¼ of a minimum wage1,36018.1%100-499
More than 2 minimum wages95512.7%100-499
Age and sex
CategoryEstimateShareSample
Ages 40–59, male89013.4%100-499
Ages 25–39, male86012.9%100-499
Ages 25–39, female84512.7%100-499
Ages 40–59, female75511.4%100-499
Ages 5–14, male75511.4%100-499
Ages 5–14, female68010.2%100-499
Ages 15–24, female5959.0%100-499
Ages 15–24, male5708.6%100-499
Ages 60 and over, male3405.1%100-499
Ages 60 and over, female3054.6%50-99
Other / suppressed500.8%5-19

Commuting (work and study)

Commuting indicators for Gaúcha do Norte/MT
Employed persons (aged 10 and over)3,455
Commute out to work in another municipality10
Commute in from another municipality to work here110
Net commuting+95
Out-commuting rate (%)0.30
Commuting attraction index1.019
Median commuting time15 min

Open Gaúcha do Norte/MT 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]: Gaúcha do Norte/MT. Data from the 2022 Demographic Census (IBGE). Data version: 2026-10-01. Available at: https://atlas-da-migracao.github.io/en/municipio/gaucha-do-norte-mt-5103858/. Dataset DOI: https://doi.org/10.5281/zenodo.22469791.