Marius Comper

Internal migration · 3,181 localities · 1992–2025

Romania is moving, one commune at a time

Every year since 1990, Romania's National Institute of Statistics has counted how many people registered a new home address in each locality and how many left it — including people arriving from or leaving to another country. The difference between arrivals and departures, set against population, is a net migration rate: who is growing, who is emptying out, year by year. The pattern is unambiguous — big cities no longer grow through migration; the communes ringing them do, sometimes with more than half of today's population made up of net newcomers accumulated over 34 years. And a handful of communes in three counties along the Prut river went through explosive, one-year population jumps of over 100 percent, one after another — something the statistics office itself links to more than just housing.

+56.3‰average net migration rate in the communes ringing Timișoara, 2015–2024, while the city itself lost 10.2‰ a year
86.6%of today's population of Dumbrăvița (Timiș county) is the net migration surplus accumulated since 1992
+1,639‰net migration rate of Moșna (Iași county) in 2014 — its population nearly tripled in a single year
6communes across three border counties (Iași, Botoșani, Vaslui) where population exploded and then corrected, in successive waves from 2014 to today

The map

Net migration rate, year by year

Search for a locality or click it on the map. The card shows how many people registered a home there, how many left, the resulting net rate, and how it has changed from year to year, 1992 to 2025. Press "Play the years" to watch the whole period at once: see the rings around big cities light up gradually, and follow the wave that has moved, since 2014, among the communes along the border with the Republic of Moldova.

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below −30−30…−10−10…−2−2…22…1010…30above 30no data

On a small screen the map zooms with two fingers or the corner buttons; search remains the safest route.

The city and its ring

The city stands still. The commune next to it grows

For the country's 13 largest cities, we compared the city's average net migration rate with the average of the communes directly bordering it, across two windows: 1995–2004 and 2015–2024. Two decades ago the gap was barely visible. Today, with the exception of Bucharest and Iași, the big cities lose net population or stagnate, while the communes around them grow by tens per thousand a year — a suburbanisation pattern that has intensified, not eased.

Timișoara56.3Brașov39.4Iași39.4Cluj-Napoca37.5București35.0Craiova31.3Oradea30.0Constanța22.3Sibiu19.9Târgu Mureș16.2Arad12.9Ploiești10.8Galați9.70204060
the city, 2015–2024neighbouring communes, 2015–2024
Average net domicile-migration rate, per thousand residents per year, 2015–2024. "Neighbouring communes" are the administrative units sharing a border with the city, per the official SIRUTA geometry. Source: INS, POP307A/POP308A/POP107D.

The magnets and the localities emptying out

Where migration has piled up the most — and where it has drained the most

We summed each locality's net migration rate across every available year and set it against its 2025 population. The result measures how much of a locality's current population is, on net, made up of migration — positive for places that gained people, negative for places that lost them. Only localities with more than 500 residents in 2025 are included.

The magnets (top 12)

  1. 1commune, Timiș county+866.222,699
  2. 2commune, Timiș county+840.627,328
  3. 3commune, Ilfov county+822.912,159
  4. 4commune, Timiș county+821.120,184
  5. 5town, Ilfov county+815.436,914
  6. 6commune, Cluj county+814.055,766
  7. 7commune, Ilfov county+796.540,647
  8. 8commune, Brașov county+790.413,754
  9. 9commune, Iași county+784.017,565
  10. 10commune, Iași county+770.733,726
  11. 11commune, Dolj county+770.38,943
  12. 12commune, Iași county+754.910,020

Emptying out (top 12)

  1. 1commune, Vâlcea county−956.61,106
  2. 2commune, Caraș-Severin county−821.4543
  3. 3commune, Dâmbovița county−759.71,968
  4. 4commune, Alba county−748.1532
  5. 5town, Harghita county−705.07,208
  6. 6commune, Vâlcea county−681.92,062
  7. 7commune, Hunedoara county−646.2783
  8. 8commune, Alba county−632.9692
  9. 9commune, Bistrița-Năsăud county−609.33,079
  10. 10commune, Buzău county−600.82,262
  11. 11commune, Sibiu county−597.53,506
  12. 12commune, Buzău county−591.9615

The figure to the right of each line is the cumulative net rate (per thousand, set against 2025 population); below it, the 2025 population. The magnets are almost all satellite communes of the big cities — Timișoara, Cluj-Napoca, Bucharest, Iași, Craiova, Sibiu, Brașov. The emptying localities are almost all mountain or isolated communes, with no shared story beyond ordinary rural depopulation.

The overnight jumps

The localities where population exploded in a single year

Among the largest single-year jumps in net migration rate across the whole series, four names recur, all from three counties bordering the Republic of Moldova — Iași, Botoșani, Vaslui. It is not a coincidence of geography, and the pattern repeats: a sharp rise over 2–4 years, then an equally sharp correction in the opposite direction.

Largest single-year positive jumps in net migration rate
LocalityYearNet ratePeoplePopulation
commune, Iași county2014+1,639.4+3,4052,077
commune, Iași county2014+925.6+3,6683,963
commune, Vaslui county2024+664.6+9811,476
commune, Iași county2013+591.8+1,5082,548
commune, Vaslui county2023+558.5+1,1742,102
commune, Iași county2024+511.8+1,7753,468
commune, Botoșani county2021+438.6+9042,061
commune, Botoșani county2023+395.4+5651,429
commune, Botoșani county2018+384.0+1,3863,609
commune, Vaslui county2025+375.1+9392,503
commune, Botoșani county2022+369.2+1,1263,050
commune, Iași county2025+333.5+5831,748

The net rate is per thousand residents; "people" is the raw difference between arrivals and departures that year. Localities under 150 residents are excluded, so that statistical noise does not dominate the ranking.

A methodological story

Sometimes the population map is the map of a law, not of housing

Moșna and Grajduri (Iași) nearly triple their registered population in 2014–2016. Scânteia (Iași) doubles, then triples, between 2016 and 2022. Ripiceni (Botoșani) doubles its population in 2016–2018. Bogdana and Ferești (Vaslui) do the same in 2023–2025 — the most recent wave, still under way. In each case the growth does not come from births: it is registered arrivals, mostly representing people changing their home address from abroad directly into that commune.

1001502002503003501995200020052010201520202025Moșna (Iași)GrajduriScânteiaRipiceniBogdanaFerești
Registered (domicile) population, indexed to 100 in the first available year for each locality. Source: INS, POP107D.

INS explicitly warns, in the methodology of its locality-level population matrix (POP107D), that some demographic jumps — including at Ripiceni and Scânteia, named directly — were influenced by the immigration of people born in the Republic of Moldova. The most plausible mechanism: Moldovan citizens who reacquire Romanian citizenship must, at some point in the procedure, declare a home address in Romania; a handful of small communes, often with relatives or acquaintances willing to host the address, became successive hubs of mass registration. The wave in Scânteia and Ripiceni corrected itself in 2023–2025, with strongly negative net rates — the same people, or others, dropping off the register. Bogdana and Ferești show exactly the start of the same cycle.

This is not an isolated hypothesis: the same two counties, Iași and Vaslui, show up independently flagged in another INS dataset — births by locality — with a birth-count bump over the same years, for the same structural reason. The map on this page is, then, partly a map of a legal incentive: whoever needs a Romanian home address finds one more easily in a small commune than in a big city, and a few small communes experienced that as a sudden demographic explosion, followed by an equally sudden reversal.

The overall picture

For most localities, migration barely moves the needle

The distribution of the cumulative net rate (1992–2025, set against 2025 population) for the 3,153 localities with more than 500 residents shows a central mass close to zero and long tails in both directions — suburban magnets to the right, isolated communes to the left.

831<-100345-100/-50231-50/-20124-20/-582-5/51205/2024220/5034750/100831≥100
Number of localities by band of cumulative net rate (per thousand, 1992–2025, set against 2025 population).

Method and limits

How everything was calculated

The source is INS, TEMPO-Online: matrices POP307A (arrivals with a new home address, including international migration) and POP308A (departures with a new home address, including international migration), by county and locality, 1990–2025; and POP107D (population by domicile, as of 1 January, all ages and sexes summed), 1992–2026. For every locality and year, the net rate is 1000 × (Arrivals − Departures) / Population. 1990–1991 are excluded from the rates because the population series starts in 1992; they are included only in the national totals.

  • "Domicile" does not mean actual residence: someone can live and work elsewhere, in another locality or another country, without changing their official address. Arrivals and departures include international migration, per INS's own definition of these matrices.
  • Localities created or reorganised after 1990 have no registered population before their creation; their series start at the first year with data, not at zero, so their creation does not read as an artificial "arrival."
  • The cumulative net rate used in the "Magnets" and "Distribution" sections divides the sum of net migration across all available years by the 2025 population, not by each year's own population; it measures the relative size of the phenomenon, not an annual average rate.
  • The neighbour relationships used for the city–ring comparison and for each locality's card come from the SIRUTA administrative geometry (geo-spatial.org, CC BY-SA 4.0 licence, ANCPI), the same geometry used elsewhere on this site.
  • The explanation offered for the border phenomenon (domicile tied to citizenship) is a reasonable inference from context — geographic proximity, the known legal mechanism of citizenship reacquisition, INS's own explicit warning for Ripiceni and Scânteia — not a direct, locality-by-locality confirmation from INS or another authority.

Every figure, formula and check is in the published methodology of this project.

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