Information about the municipality Ferna:

View the information on over 100 topics about the municipality Ferna! With charts, links to more information & an overview of all figures in 1 table.
View the information on over 100 topics about the municipality Ferna! With charts, links to more information & an overview of all figures in 1 table.
Population numbers per year
The number of inhabitants in the municipality Ferna

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Population numbers in the municipality Ferna for the years 2009 thru 2019.

The number of inhabitants is the number of persons as registered in the population register on January 1st.

Population at the map of Ferna
Map of Rural district Eichsfeld with the population per municipality.Municipality Ferna is highlighted with a red edge.. This page shows a lot of information about residents (such as the distribution by age groups, family composition, gender, native or German with an immigration background, ...), homes (numbers, types, price development, use, type of property, ...) and more (car ownership, energy consumption, ...) based on open data from the German Federal Agency for Cartography, the Federal Statistical Office (DESTATIS), the Regional Statistical Offices and various other sources!

Map of Rural district Eichsfeld with the population per municipality.Municipality Ferna is highlighted with a red edge. The numbers at the map represent the following municipalities: 1: municipality Sonnenstein, 2: municipality Ecklingerode, 3: municipality Brehme, 4: municipality Wehnde, 5: municipality Am Ohmberg ...Show more... Map of Rural district Eichsfeld with the population per municipality.Municipality Ferna is highlighted with a red edge. The numbers at the map represent the following municipalities: 1: municipality Sonnenstein, 2: municipality Ecklingerode, 3: municipality Brehme, 4: municipality Wehnde, 5: municipality Am Ohmberg, 6: municipality Tastungen, 7: municipality Teistungen, 8: municipality Ferna, 9: municipality Haynrode, 10: municipality Berlingerode, 11: municipality Glasehausen, 12: municipality Buhla, 13: municipality Reinholterode, 14: municipality Freienhagen, 15: municipality Steinbach, 16: municipality city Leinefelde-Worbis, 17: municipality Hohes Kreuz, 18: municipality Breitenworbis, 19: municipality Rohrberg, 20: municipality Kirchworbis, 21: municipality Schachtebich, 22: municipality Rustenfelde, 23: municipality Bodenrode-Westhausen, 24: municipality Wingerode, 25: municipality Gernrode, 26: municipality Burgwalde, 27: municipality Kirchgandern, 28: municipality Steinheuterode, 29: municipality Gerterode, 30: municipality Marth, 31: municipality Hausen, 32: municipality Hohengandern, 33: municipality city Heilbad Heiligenstadt, 34: municipality Arenshausen, 35: municipality Deuna, 36: municipality Niederorschel, 37: municipality Birkenfelde, 38: municipality Uder, 39: municipality Thalwenden, 40: municipality Geisleden, 41: municipality Kleinbartloff, 42: municipality Kallmerode, 43: municipality Bornhagen, 44: municipality Kreuzebra, 45: municipality Schönhagen, 46: municipality Lenterode, 47: municipality Röhrig, 48: municipality Gerbershausen, 49: municipality Heuthen, 50: municipality Lutter, 51: municipality Fretterode, 52: municipality Wüstheuterode, 53: municipality Silberhausen, 54: municipality Lindewerra, 55: municipality city Dingelstädt, 56: municipality Kefferhausen, 57: municipality Eichstruth, 58: municipality Dietzenrode/Vatterode, 59: municipality Bernterode (bei Heilbad Heiligenstadt), 60: municipality Wahlhausen, 61: municipality Dieterode, 62: municipality Mackenrode, 63: municipality Helmsdorf, 64: municipality Krombach, 65: municipality Asbach-Sickenberg, 66: municipality Schwobfeld, 67: municipality Wachstedt, 68: municipality Küllstedt, 69: municipality Wiesenfeld, 70: municipality Schimberg, 71: municipality Volkerode, 72: municipality Großbartloff, 73: municipality Büttstedt, 74: municipality Sickerode, 75: municipality Pfaffschwende, 76: municipality Effelder, 77: municipality Kella, 78: municipality Geismar ...Show less...

Population per age group
The percentage of inhabitants per age group in the municipality Ferna

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Municipality Ferna, 2019, age groups.

Population, age groups: percentage of inhabitants per age category.

The number of rooms per house (dwelling)
The number of rooms of the houses in the municipality Ferna

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Municipality Ferna, 2019, number of rooms per house.

The percentage shows the relative share of houses per category based on the numer of rooms: 1 to 2 rooms, 3 to 4 rooms or 5 rooms or more. This is based on the total number of rooms as identified for all dwellings in the municipality Ferna.

Data about more than 100 topics!

The table below shows data for more than 100 topics as most recently available for the municipality Ferna. Select a category to display the related topics:

BusinessValueUnitYear
Businesses1Number2017
Active persons0Number2017
Gross wages€0Euro2017
DwellingsValueUnitYear
Houses 1 room1Number2019
Houses 2 rooms9Number2019
Houses 3 rooms30Number2019
Houses 4 rooms54Number2019
Houses 5 rooms59Number2019
Houses 6 rooms46Number2019
Houses 7+ rooms 53Number2019
Houses 1-2 rooms10Number2019
Houses 3-4 rooms84Number2019
Houses 5+ rooms158Number2019
1-2 rooms4%Percentage2019
3-4 rooms33%Percentage2019
5+ rooms63%Percentage2019
ElectionsValueUnitYear
Voters Bundestag470,00Number2017
Voter turnout Bundestag70Number2017
Votes valid Bundestag326Number2017
Votes Bundestag CDU/CSU172Number2017
Votes Bundestag SPD30Number2017
Votes Bundestag GRÜNE11Number2017
Votes Bundestag FDP33Number2017
Votes Bundestag DIE LINKE20Number2017
Votes Bundestag AfD53Number2017
Votes Bundestag other parties7Number2017
Votes Bundestag total326Number2017
% Votes Bundestag CDU/CSU37%Percentage2017
% Votes Bundestag SPD6%Percentage2017
% Votes Bundestag GRÜNE2%Percentage2017
% Votes Bundestag FDP7%Percentage2017
% Votes Bundestag DIE LINKE4%Percentage2017
% Votes Bundestag AfD11%Percentage2017
% Votes Bundestag other parties1%Percentage2017
EmploymentValueUnitYear
Employees245Number2019
Employees male133Number2019
Employees female112Number2019
Employees foreigner5Number2019
Employees male foreigner5Number2019
Employees female foreigner0Number2019
Unemployed8Number2018
Unemployed foreigners0Number2018
Unemployed severely disabled1Number2018
Unemployed 15-200Number2018
Unemployed 15-250Number2018
Unemployed 55-654Number2018
Unemployed long-term3Number2018
% Unemployed1%Percentage2018
% Unemployed foreigners0%Percentage of the population2018
% Unemployed severely disabled0%Percentage of the population2018
% Unemployed 15-200%Percentage of the population2018
% Unemployed 15-250%Percentage of the population2018
% Unemployed 55-651%Percentage of the population2018
% Unemployed long-term1%Percentage of the population2018
IncomeValueUnitYear
Income receivers237Number2015
Income total€8.051Euro2015
Income tax€1.046Euro2015
PopulationValueUnitYear
Population585Number2019
Men300Number2019
Women285Number2019
% Men51%Percentage2019
% Women49%Percentage2019
0-18109Number2019
18-3039Number2019
30-45123Number2019
45-60132Number2019
18-60294Number2019
60-75109Number2019
60+182Number2019
Average age46Average number2019
Average age male45Average number2019
Average age female46Average number2019
Births2Number2018
Births male1Number2018
Births female1Number2018
1K Births3Number per 1000 inhabitants2018
Deaths6Number2018
Deaths male5Number2018
Deaths female1Number2018
1K Deaths10Number2018
0-314Number2019
Girls 0-39Number2019
Boys 0-35Number2019
3-619Number2019
Girls 3-613Number2019
Boys 3-66Number2019
6-1025Number2019
10-1529Number2019
15-1822Number2019
18-2013Number2019
20-2512Number2019
25-3014Number2019
30-3537Number2019
35-4042Number2019
40-4544Number2019
45-5041Number2019
50-5545Number2019
55-6046Number2019
60-6542Number2019
65-7567Number2019
Women 65-7030Number2019
Men 65-7037Number2019
75+73Number2019
Women 75+43Number2019
Men 75+30Number2019
% 0-1010%Percentage2019
% 10-189%Percentage2019
% 18-307%Percentage2019
% 30-4521%Percentage2019
% 45-6023%Percentage2019
% 60+31%Percentage2019
Real estateValueUnitYear
Property tax A revenueno dataEurono data
Property tax B revenueno dataEurono data
Trade tax actual revenueno dataEurono data
Property tax A basic amountno dataEurono data
Property tax B basic amountno dataEurono data
Trade tax basic amountno dataEurono data
Property tax A rateno dataEurono data
Property tax B rateno dataEurono data
Trade tax rateno dataEurono data
Real tax raising forceno dataEurono data
Trade tax levyno dataEurono data
Trade tax netno dataEurono data
Community share in income taxno dataEurono data
Community share in sales taxno dataEurono data
Tax revenueno dataEurono data
RegionalValueUnitYear
Region code160615001031Code2019
Region code 8 digits16061031Code16061031
Sorting code160615001031Code160615001031
Sorting code 8 digits16061031Code16061031
Region nameFernaName2019
Regional level6Categorical type2019
Region typeMunicipalityCategorical type2019
Region type detailmunicipalityCategorical type2019
Region name with typemunicipality FernaName2019
Region name in GermanGemeinde FernaName2019
Direct subregionsno dataNumber2019
NUTS codeDEG06Code2019
Area4Area in km²2019
ReligionValueUnitYear
Roman Catholic church462Number2011
Protestant church33Number2011
Other or none84Number2011
% Roman Catholic church80%Percentage2011
% Protestant church6%Percentage2011
% Other or none15%Percentage2011
Roman Catholic church German462Number2011
Protestant church German33Number2011
Other or none German84Number2011
% Roman Catholic church German80%Percentage2011
% Protestant church German6%Percentage2011
% Other or none German Foreign15%Percentage2011
Roman Catholic church Foreign0Number2011
Protestant church Foreign0Number2011
Other or none Foreign0Number2011
% Roman Catholic church Foreignno dataPercentageno data
% Protestant church Foreignno dataPercentageno data
% Other or none Foreignno dataPercentageno data
Open data sources used

Data is used from multiple German open data providers. See this description of the sources with the definitions of all regional topics.

Sources & definitions
Under development
Work is in progress to add more information to this page

This page will be further expanded with more topics in clear graphs. This will be done in several iterations in the coming weeks.