Information about the municipality Falkenstein:

Population numbers per year
The number of inhabitants in the municipality Falkenstein

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Population numbers in the municipality Falkenstein 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 Falkenstein
Map of Rural district Donnersbergkreis with the population per municipality.Municipality Falkenstein 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 Donnersbergkreis with the population per municipality.Municipality Falkenstein is highlighted with a red edge. The numbers at the map represent the following municipalities: 1: municipality Winterborn, 2: municipality Niederhausen an der Appel, 3: municipality Niedermoschel, 4: municipality Mörsfeld, 5: municipality Kalkofen ...Show more... Map of Rural district Donnersbergkreis with the population per municipality.Municipality Falkenstein is highlighted with a red edge. The numbers at the map represent the following municipalities: 1: municipality Winterborn, 2: municipality Niederhausen an der Appel, 3: municipality Niedermoschel, 4: municipality Mörsfeld, 5: municipality Kalkofen, 6: municipality Münsterappel, 7: municipality city Obermoschel, 8: municipality Alsenz, 9: municipality Oberhausen an der Appel, 10: municipality Unkenbach, 11: municipality Sitters, 12: municipality Oberndorf, 13: municipality Gaugrehweiler, 14: municipality Kriegsfeld, 15: municipality Oberwiesen, 16: municipality Morschheim, 17: municipality Schiersfeld, 18: municipality Mannweiler-Cölln, 19: municipality Ilbesheim, 20: municipality Orbis, 21: municipality Sankt Alban, 22: municipality Finkenbach-Gersweiler, 23: municipality Bayerfeld-Steckweiler, 24: municipality Gerbach, 25: municipality Stetten, 26: municipality Bischheim, 27: municipality Rittersheim, 28: municipality Dielkirchen, 29: municipality city Kirchheimbolanden, 30: municipality Stahlberg, 31: municipality Waldgrehweiler, 32: municipality Einselthum, 33: municipality Gauersheim, 34: municipality Ransweiler, 35: municipality Ruppertsecken, 36: municipality Würzweiler, 37: municipality Katzenbach, 38: municipality Albisheim (Pfrimm), 39: municipality Bisterschied, 40: municipality Schönborn, 41: municipality Zellertal, 42: municipality Bolanden, 43: municipality Immesheim, 44: municipality Teschenmoschel, 45: municipality Dannenfels, 46: municipality Bubenheim, 47: municipality city Rockenhausen, 48: municipality Ottersheim, 49: municipality Bennhausen, 50: municipality Marnheim, 51: municipality Dörrmoschel, 52: municipality Rüssingen, 53: municipality Jakobsweiler, 54: municipality Rathskirchen, 55: municipality Weitersweiler, 56: municipality Falkenstein, 57: municipality Biedesheim, 58: municipality Imsweiler, 59: municipality Steinbach am Donnersberg, 60: municipality Seelen, 61: municipality Dreisen, 62: municipality Standenbühl, 63: municipality Reichsthal, 64: municipality Schweisweiler, 65: municipality Imsbach, 66: municipality Göllheim, 67: municipality Gundersweiler, 68: municipality Lautersheim, 69: municipality Börrstadt, 70: municipality Gehrweiler, 71: municipality Breunigweiler, 72: municipality Kerzenheim, 73: municipality Winnweiler, 74: municipality Höringen, 75: municipality Lohnsfeld, 76: municipality city Eisenberg (Pfalz), 77: municipality Sippersfeld, 78: municipality Gonbach, 79: municipality Münchweiler an der Alsenz, 80: municipality Wartenberg-Rohrbach, 81: municipality Ramsen ...Show less...

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

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Municipality Falkenstein, 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 Falkenstein

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Municipality Falkenstein, 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 Falkenstein.

Data about more than 100 topics!

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

BusinessValueUnitYear
Businessesno dataNumber2015
Active personsno dataNumber2015
Gross wagesno dataEuro2015
DwellingsValueUnitYear
Houses 1 room2Number2019
Houses 2 rooms20Number2019
Houses 3 rooms48Number2019
Houses 4 rooms61Number2019
Houses 5 rooms37Number2019
Houses 6 rooms27Number2019
Houses 7+ rooms 33Number2019
Houses 1-2 rooms22Number2019
Houses 3-4 rooms109Number2019
Houses 5+ rooms97Number2019
1-2 rooms10%Percentage2019
3-4 rooms48%Percentage2019
5+ rooms43%Percentage2019
ElectionsValueUnitYear
Voters Bundestag156,00Number2017
Voter turnout Bundestag74Number2017
Votes valid Bundestag90Number2017
Votes Bundestag CDU/CSU31Number2017
Votes Bundestag SPD23Number2017
Votes Bundestag GRÜNE9Number2017
Votes Bundestag FDP4Number2017
Votes Bundestag DIE LINKE10Number2017
Votes Bundestag AfD9Number2017
Votes Bundestag other parties4Number2017
Votes Bundestag total90Number2017
% Votes Bundestag CDU/CSU20%Percentage2017
% Votes Bundestag SPD15%Percentage2017
% Votes Bundestag GRÜNE6%Percentage2017
% Votes Bundestag FDP3%Percentage2017
% Votes Bundestag DIE LINKE6%Percentage2017
% Votes Bundestag AfD6%Percentage2017
% Votes Bundestag other parties3%Percentage2017
EmploymentValueUnitYear
Employees68Number2019
Employees male0Number2019
Employees female0Number2019
Employees foreigner0Number2019
Employees male foreigner0Number2019
Employees female foreigner0Number2019
Unemployed5Number2018
Unemployed foreigners2Number2018
Unemployed severely disabled0Number2018
Unemployed 15-200Number2018
Unemployed 15-250Number2018
Unemployed 55-652Number2018
Unemployed long-term1Number2018
% Unemployed3%Percentage2018
% Unemployed foreigners1%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 receivers110Number2015
Income total€2.706Euro2015
Income tax€368Euro2015
PopulationValueUnitYear
Population185Number2019
Men104Number2019
Women81Number2019
% Men56%Percentage2019
% Women44%Percentage2019
0-1822Number2019
18-3020Number2019
30-4525Number2019
45-6058Number2019
18-60103Number2019
60-7534Number2019
60+60Number2019
Average age49Average number2019
Average age male49Average number2019
Average age female49Average number2019
Birthsno dataNumber2017
Births maleno dataNumber2017
Births femaleno dataNumber2017
1K Birthsno dataNumber per 1000 inhabitants2017
Deaths4Number2018
Deaths male3Number2018
Deaths female1Number2018
1K Deaths21Number2018
0-33Number2019
Girls 0-31Number2019
Boys 0-32Number2019
3-62Number2019
Girls 3-61Number2019
Boys 3-61Number2019
6-103Number2019
10-1510Number2019
15-184Number2019
18-204Number2019
20-259Number2019
25-307Number2019
30-3510Number2019
35-405Number2019
40-4510Number2019
45-5013Number2019
50-5518Number2019
55-6027Number2019
60-6517Number2019
65-7517Number2019
Women 65-709Number2019
Men 65-708Number2019
75+26Number2019
Women 75+10Number2019
Men 75+16Number2019
% 0-104%Percentage2019
% 10-188%Percentage2019
% 18-3011%Percentage2019
% 30-4514%Percentage2019
% 45-6031%Percentage2019
% 60+32%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 amount€11.209Euro2018
Property tax A rate€325Euro2018
Property tax B rateno dataEurono data
Trade tax rateno dataEurono data
Real tax raising forceno dataEurono data
Trade tax levy€7.656Euro2018
Trade tax net€33.258Euro2018
Community share in income taxno dataEurono data
Community share in sales taxno dataEurono data
Tax revenueno dataEurono data
RegionalValueUnitYear
Region code073335006020Code2019
Region code 8 digits07333020Code07333020
Sorting code073335006020Code073335006020
Sorting code 8 digits07333020Code07333020
Region nameFalkensteinName2019
Regional level6Categorical type2019
Region typeMunicipalityCategorical type2019
Region type detailmunicipalityCategorical type2019
Region name with typemunicipality FalkensteinName2019
Region name in GermanGemeinde FalkensteinName2019
Direct subregionsno dataNumber2019
NUTS codeDEB3DCode2019
Area7Area in km²2019
ReligionValueUnitYear
Roman Catholic church90Number2011
Protestant church99Number2011
Other or none56Number2011
% Roman Catholic church37%Percentage2011
% Protestant church41%Percentage2011
% Other or none23%Percentage2011
Roman Catholic church German90Number2011
Protestant church German96Number2011
Other or none German50Number2011
% Roman Catholic church German38%Percentage2011
% Protestant church German41%Percentage2011
% Other or none German Foreign21%Percentage2011
Roman Catholic church Foreign0Number2011
Protestant church Foreign3Number2011
Other or none Foreign6Number2011
% Roman Catholic church Foreign0%Percentage2011
% Protestant church Foreign33%Percentage2011
% Other or none Foreign67%Percentage2011
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.