Migration in Baldim/MG (2017–2022)

Baldim/MG had a reference population (aged 5 or over in 2022) of 7,170 people. In the 2017–2022 five-year period, the municipality received 555 in-migrants and lost 580 out-migrants to other municipalities in Brazil, resulting in a net migration of −25 people (−3.40 per 1,000 population) and a migration effectiveness index (IEM) of −0.021. This classifies the municipality, for the period, as one of migratory depletion. In addition, 0 arrived with an unreported origin and 5 came from abroad.

Indicators

Migration indicators for Baldim/MG, 2017–2022
Indicator	Estimate	95% CI	Precision
In-migrants	555	431 to 679	good
Out-migrants	580	313 to 847	use with caution
Net migration	−25	−319 to 269	not classified
Net migration rate, TLM (per 1,000 pop.)	−3.40	-	-
Migration effectiveness index (IEM)	−0.021	-	-

Sample of in-migrants: 100-499 observations. Sample of out-migrants: 50-99 observations. 95% confidence interval computed as estimate ± 1.96 × standard error.

Top origins and destinations

Top 10 origins of in-migrants to Baldim/MG
Origin	People	Precision
Belo Horizonte/MG · view pair in the atlas	235	use with caution
Sete Lagoas/MG · view pair in the atlas	45	low precision
Lagoa Santa/MG · view pair in the atlas	40	low precision
São José da Lapa/MG · view pair in the atlas	20	low precision
Jaboticatubas/MG · view pair in the atlas	20	low precision
Pedro Leopoldo/MG · view pair in the atlas	15	low precision

Top 10 destinations of out-migrants from Baldim/MG
Destination	People	Precision
Belo Horizonte/MG · view pair in the atlas	160	low precision
Sete Lagoas/MG · view pair in the atlas	140	low precision
Jequitibá/MG · view pair in the atlas	45	low precision

Profile of migrants and residents

In-migrants (arrivals)

Migrant type
Category	Estimate	Share	Sample
Multi-step migration	240	43.2%	50-99
First move from municipality of birth	235	42.3%	50-99
Return to municipality of birth	80	14.4%	20-49

Educational attainment (people aged 25 and over)
Category	Estimate	Share	Sample
No schooling or incomplete elementary	170	39.5%	50-99
Completed high school, incomplete higher education	115	26.7%	20-49
Completed elementary, incomplete high school	80	18.6%	20-49
Completed higher education	65	15.1%	20-49

Household income per capita (in 2022 minimum wages)
Category	Estimate	Share	Sample
½ to 1 minimum wage	225	40.9%	50-99
¼ to ½ minimum wage	140	25.5%	20-49
1 to 2 minimum wages	125	22.7%	20-49
More than 2 minimum wages	45	8.2%	5-19
Up to ¼ of a minimum wage	15	2.7%	5-19

Age and sex
Category	Estimate	Share	Sample
Ages 40–59, male	105	18.8%	20-49
Ages 40–59, female	90	16.1%	20-49
Ages 25–39, female	65	11.6%	20-49
Ages 60 and over, female	65	11.6%	20-49
Ages 60 and over, male	60	10.7%	5-19
Ages 25–39, male	50	8.9%	5-19
Ages 15–24, male	40	7.1%	5-19
Ages 5–14, male	35	6.2%	5-19
Ages 15–24, female	25	4.5%	5-19
Ages 5–14, female	25	4.5%	5-19

Out-migrants (departures)

Migrant type
Category	Estimate	Share	Sample
Multi-step migration	330	56.4%	20-49
First move from municipality of birth	170	29.1%	20-49
Return to municipality of birth	85	14.5%	5-19

Educational attainment (people aged 25 and over)
Category	Estimate	Share	Sample
Completed high school, incomplete higher education	170	43.6%	20-49
Completed elementary, incomplete high school	95	24.4%	5-19
Completed higher education	65	16.7%	5-19
No schooling or incomplete elementary	60	15.4%	5-19

Household income per capita (in 2022 minimum wages)
Category	Estimate	Share	Sample
½ to 1 minimum wage	235	40.9%	5-19
More than 2 minimum wages	110	19.1%	5-19
¼ to ½ minimum wage	105	18.3%	5-19
1 to 2 minimum wages	100	17.4%	5-19
Up to ¼ of a minimum wage	25	4.3%	5-19

Age and sex
Category	Estimate	Share	Sample
Ages 25–39, male	130	22.2%	5-19
Ages 25–39, female	110	18.8%	5-19
Ages 5–14, male	95	16.2%	5-19
Other / suppressed	80	13.7%	5-19
Ages 40–59, male	70	12.0%	5-19
Ages 40–59, female	70	12.0%	5-19
Ages 5–14, female	30	5.1%	5-19

Non-migrant residents

Educational attainment (people aged 25 and over)
Category	Estimate	Share	Sample
No schooling or incomplete elementary	2,470	49.2%	>=500
Completed high school, incomplete higher education	1,410	28.1%	100-499
Completed elementary, incomplete high school	705	14.0%	100-499
Completed higher education	435	8.7%	100-499

Household income per capita (in 2022 minimum wages)
Category	Estimate	Share	Sample
½ to 1 minimum wage	2,690	38.8%	>=500
¼ to ½ minimum wage	1,680	24.2%	>=500
1 to 2 minimum wages	1,495	21.6%	100-499
Up to ¼ of a minimum wage	680	9.8%	100-499
More than 2 minimum wages	390	5.6%	100-499

Age and sex
Category	Estimate	Share	Sample
Ages 40–59, female	970	14.7%	100-499
Ages 60 and over, female	955	14.5%	100-499
Ages 40–59, male	945	14.3%	100-499
Ages 60 and over, male	805	12.2%	100-499
Ages 25–39, male	680	10.3%	100-499
Ages 25–39, female	665	10.1%	100-499
Ages 15–24, male	435	6.6%	100-499
Ages 5–14, male	400	6.1%	100-499
Ages 15–24, female	380	5.8%	100-499
Ages 5–14, female	370	5.6%	100-499

Commuting (work and study)

Commuting indicators for Baldim/MG
Employed persons (aged 10 and over)	3,210
Commute out to work in another municipality	235
Commute in from another municipality to work here	80
Net commuting	−155
Out-commuting rate (%)	7.27
Commuting attraction index	0.936
Median commuting time	60 min

This municipality is part of Região Metropolitana de Belo Horizonte → see the metropolitan region page

Open Baldim/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]: Baldim/MG. Data from the 2022 Demographic Census (IBGE). Data version: 2026-10-01. Available at: https://atlas-da-migracao.github.io/en/municipio/baldim-mg-3105004/. Dataset DOI: https://doi.org/10.5281/zenodo.22469791.