Migration in Erval Grande/RS (2017–2022)

Erval Grande/RS had a reference population (aged 5 or over in 2022) of 4,665 people. In the 2017–2022 five-year period, the municipality received 315 in-migrants and lost 280 out-migrants to other municipalities in Brazil, resulting in a net migration of +35 people (7.98 per 1,000 population) and a migration effectiveness index (IEM) of 0.063. This classifies the municipality, for the period, as one of migratory attraction. In addition, 5 arrived with an unreported origin and 0 came from abroad.

Indicators

Migration indicators for Erval Grande/RS, 2017–2022
Indicator	Estimate	95% CI	Precision
In-migrants	315	222 to 408	good
Out-migrants	280	166 to 394	use with caution
Net migration	+35	−112 to 182	not classified
Net migration rate, TLM (per 1,000 pop.)	7.98	-	-
Migration effectiveness index (IEM)	0.063	-	-

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 Erval Grande/RS
Origin	People	Precision
Itatiba do Sul/RS · view pair in the atlas	40	low precision
Chapecó/SC · view pair in the atlas	35	low precision
Erechim/RS · view pair in the atlas	20	low precision
São Valentim/RS · view pair in the atlas	20	low precision

Top 10 destinations of out-migrants from Erval Grande/RS
Destination	People	Precision
Chapecó/SC · view pair in the atlas	100	low precision
Aratiba/RS · view pair in the atlas	15	low precision
Faxinalzinho/RS · view pair in the atlas	10	low precision

Profile of migrants and residents

In-migrants (arrivals)

Migrant type
Category	Estimate	Share	Sample
First move from municipality of birth	150	48.4%	50-99
Multi-step migration	100	32.3%	20-49
Return to municipality of birth	60	19.4%	20-49

Educational attainment (people aged 25 and over)
Category	Estimate	Share	Sample
No schooling or incomplete elementary	90	45.0%	20-49
Completed higher education	40	20.0%	5-19
Completed high school, incomplete higher education	40	20.0%	5-19
Completed elementary, incomplete high school	30	15.0%	5-19

Household income per capita (in 2022 minimum wages)
Category	Estimate	Share	Sample
½ to 1 minimum wage	105	33.3%	20-49
1 to 2 minimum wages	80	25.4%	20-49
¼ to ½ minimum wage	55	17.5%	20-49
More than 2 minimum wages	50	15.9%	5-19
Up to ¼ of a minimum wage	25	7.9%	5-19

Age and sex
Category	Estimate	Share	Sample
Ages 25–39, female	65	20.3%	20-49
Ages 15–24, female	40	12.5%	5-19
Ages 40–59, male	40	12.5%	5-19
Ages 40–59, female	30	9.4%	5-19
Ages 25–39, male	30	9.4%	5-19
Ages 5–14, female	25	7.8%	5-19
Ages 5–14, male	25	7.8%	5-19
Ages 15–24, male	25	7.8%	5-19
Ages 60 and over, female	20	6.2%	5-19
Ages 60 and over, male	20	6.2%	5-19

Out-migrants (departures)

Migrant type
Category	Estimate	Share	Sample
First move from municipality of birth	170	61.8%	20-49
Multi-step migration	100	36.4%	20-49
Other / suppressed	5	1.8%	<5

Educational attainment (people aged 25 and over)
Category	Estimate	Share	Sample
No schooling or incomplete elementary	85	40.5%	5-19
Completed higher education	65	31.0%	5-19
Completed high school, incomplete higher education	45	21.4%	5-19
Other / suppressed	15	7.1%	<5

Household income per capita (in 2022 minimum wages)
Category	Estimate	Share	Sample
1 to 2 minimum wages	105	38.2%	20-49
More than 2 minimum wages	80	29.1%	5-19
½ to 1 minimum wage	80	29.1%	5-19
Other / suppressed	10	3.6%	<5

Age and sex
Category	Estimate	Share	Sample
Ages 25–39, male	85	30.9%	5-19
Ages 25–39, female	45	16.4%	5-19
Ages 60 and over, male	30	10.9%	5-19
Ages 15–24, female	30	10.9%	5-19
Ages 40–59, female	30	10.9%	5-19
Ages 5–14, female	30	10.9%	5-19
Other / suppressed	25	9.1%	5-19

Non-migrant residents

Educational attainment (people aged 25 and over)
Category	Estimate	Share	Sample
No schooling or incomplete elementary	2,120	63.0%	>=500
Completed high school, incomplete higher education	515	15.3%	100-499
Completed elementary, incomplete high school	370	11.0%	100-499
Completed higher education	360	10.7%	100-499

Household income per capita (in 2022 minimum wages)
Category	Estimate	Share	Sample
½ to 1 minimum wage	1,845	40.0%	>=500
1 to 2 minimum wages	1,425	30.9%	100-499
¼ to ½ minimum wage	595	12.9%	100-499
More than 2 minimum wages	525	11.4%	100-499
Up to ¼ of a minimum wage	225	4.9%	50-99

Age and sex
Category	Estimate	Share	Sample
Ages 40–59, male	640	14.7%	100-499
Ages 60 and over, female	640	14.7%	100-499
Ages 60 and over, male	610	14.0%	100-499
Ages 40–59, female	595	13.7%	100-499
Ages 25–39, male	465	10.7%	100-499
Ages 25–39, female	415	9.6%	100-499
Ages 5–14, male	265	6.1%	50-99
Ages 15–24, male	260	6.0%	50-99
Ages 5–14, female	235	5.4%	50-99
Ages 15–24, female	220	5.1%	50-99

Commuting (work and study)

Commuting indicators for Erval Grande/RS
Employed persons (aged 10 and over)	2,075
Commute out to work in another municipality	260
Commute in from another municipality to work here	55
Net commuting	−210
Out-commuting rate (%)	12.63
Commuting attraction index	0.895
Median commuting time	80 min

Open Erval Grande/RS 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]: Erval Grande/RS. Data from the 2022 Demographic Census (IBGE). Data version: 2026-10-01. Available at: https://atlas-da-migracao.github.io/en/municipio/erval-grande-rs-4307203/. Dataset DOI: https://doi.org/10.5281/zenodo.22469791.