The city states of Berlin, Hamburg and Bremen were the states with the three highest crime rates in Germany in 2020, while the federal state of Bavaria had the lowest. Urban areas generally have higher crime rates than rural ones, making it difficult to compare Germany's three city states with the much larger federal states, which typically cover quite large areas. The federal state with the highest crime rate was Saxony-Anhalt at 7996 crimes per 100 thousand people, compared with the German average of 6209.

The crime rate in Germany for 2022 was 6,762 crimes per 100,000 people, making it the first time in seven years in which the crime rate rose compared to the year before. Between 2000 and 2004 the crime rate in Germany increased from 7,625 to 8,037, before declining to 7,253 by 2010. The years between 2010 and 2015 saw an increase in the crime rate, but after 2015, the recent trend of declining crime started, leading to the generally low figures seen in the most recent years. While the uptick in the crime rate in 2022 marks a negative turn compared with these years, the overall crime rate is still much lower on average than in previous decades.

Crime rate highest in cities Germany’s sixteen states are made up of thirteen federal states, and three city states; Berlin, Hamburg and Bremen. These three city states had the highest regional crime rates in Germany, due to only covering urban areas which usually have higher crime rates than rural areas. The large federal state of Bavaria, in the southeast of Germany, had the lowest crime rate in the country at 4,698 crimes per 100,000 people in 2020. Baden-Württemberg, home to the black forest and the city of Stuttgart had the second-lowest crime rate per 100 thousand people in this year, at 4,944.

Notes for publication:

The table presented is based on the data from the Police Crime Statistics (PKS) of the State of Schleswig-Holstein. These are the results of the police investigation before handing them over to the public prosecutor's office or the court. The PKS contains the illegal offences that have become known to the police, including the attempts threatened with punishment, the number of suspects identified and a number of other information on cases, victims or suspects. The data refer to a closed reporting year and are published annually for the previous calendar year.

Table-specific information:

Table 62 (crimes and nationality of non-German suspects)

This dataset contains figures on non-German suspects by nationality recorded in Schleswig-Holstein in the corresponding reporting year.

Structure of the table

The following columns are included:

• Key number of the offence - Crime key number (key of the respective offences or sum key)
• Offence - plain text of the offence or the sum key
• Non-German suspects - Sum of non-German suspects
• Nationality - Number of nationalities
• The preceding number in brackets (1) – (107) denotes the column numbering.

Character set: Western European (Windows – 1252/WinLatin 1)

Social and economic figures for 67 large West German cities. The data aggregated at city level have been collected for most topics over several years, but not necessarily over the entire reference time period.

Topics: 1. Situation of the city: surface area of the city; fringe location in the Federal Republic.

1. Residential population: total residential population; German and foreign residential population.

2. Population movement:live births; deaths; influx; departures; birth rate; death rate; population shifts; divorce rate; migration rate; illegitimate births.

3. Education figures: school degrees; occupational degrees; university degrees.

4. Wage and income: number of taxpayers in the various tax classes as well as municipality income tax revenue in the respective classes; calculated income figures, such as e.g. inequality of income distribution, mean income or mean wage of employees as well as standard deviation of these figures; GINI index.

5. Gross domestic product and gross product: gross product altogether; gross product organized according to area of business; gross domestic product; employees in the economic sectors.

6. Taxes and debts: debt per resident; income tax and business tax to which the municipality is entitled; municipality tax potential and indicators for municipality economic strength.

7. Debt repayment and management expenditures: debt repayment, interest expenditures, management expenditures and personnel expenditures.

8. From the ´BUNTE´ City Test of 1979 based on 100 respondents per city averages of satisfaction were calculated. satisfaction with: central location of the city, the number of green areas, historical buildings, the number of high-rises, the variety of the citizens, openness to the world, the dialect spoken, the sociability, the density of the traffic network, the OEPNV prices {local public passenger transport}, the supply of public transportation, provision with culture, the selection for consumers, the climate, clean air, noise pollution, the leisure selection, real estate prices, the supply of residences, one´s own payment, the job market selection, the distance from work, the number of one´s friends, contact opportunities, receptiveness of the neighbors, local recreational areas, sport opportunities and the selection of further education possibilities.

9. Traffic and economy: airport and Intercity connection; number of kilometers of subway available, kilometers of streetcar, and kilometers of bus lines per resident; car rate; index of traffic quality; commuters; property prices; prices for one´s own home; purchasing power.

10. Crime: recorded total crime and classification according to armed robbery, theft from living-rooms, of automobiles as well as from motor vehicles, robberies and purse snatching; classification according to young or adult suspects with these crimes; crime stress figures. 12. Welfare: welfare recipients and social expenditures; proportion of welfare recipients in the total population and classification according to German and foreign recipients; aid with livelihood; expenditures according to the youth welfare law; kindergarten openings; culture expenditures per resident. 13. Foreigners: proportion of foreigners in the residential population.

11. Students: number of German students and total number of students; proportion of students in the residential population.

12. Unemployed: unemployment rate; unemployed according to employment office districts and employment office departments.

13. Places of work: workers employed in companies, organized according to area of business.

14. Government employees: full-time, part-time and total government employees of federal government, states and municipalities as well as differentiated according to workers, employees, civil servants and judges.

15. Employees covered by social security according to education and branch of economy: proportion of various education levels in the individual branches of the economy.

In 2023, German police recorded around 1.97 million cases of theft crime in the country. These included 77,819 cases of burglary with housebreaking. Theft crimes were among the most reported in Germany.

Panel data on the crime rate of burglary and the clearance rate of the police at the regional level in Germany from 2013 to 2017. Data was retrieved from the annual crime report (PKS) of the German Federal Police (BKA).

Crime and socioeconomic data for the German Reich and mortality statistics for Prussia at county level for 1871 to 1912.

Topics: A: variables for the entire German Reich (1047 counties)

1. crime data: a) totals of all convicted for crimes and offences per 100000 b) number convicted due to dangerous bodily injury per 100000 c) number convicted due to simple theft per 100000

2. demographic information: a) totals of population of the age of criminal responsibility in the counties for 1885, 1905 and 1910 b) male German-speaking population in 1900 c) female German-speaking population in 1900 d) male, non-German-speaking population in 1900 e) female, non-German-speaking population in 1900 f) primary ethnic groups in 1900

3. data on urbanization: a) total population of the municipalities with more than 2000 residents per county in 1900 b) population in medium-sized cities per county in 1900 c) population in large cities per county in 1900 d) total population per county in 1900 e) typing the counties in city counties (=1) and districts (=2) in 1900

4. Geographic data a) short designation of all counties (1881 to 1912) b) identification number of all counties listed under 4a) c) surface area of the county in square kilometers in 1900

B: variables for Prussia (583 counties) mortality data for 1885, 1886, 1904, 1905 and 1906:

a) totals of deaths (according to sex) for the respective year b) number of deaths due to Tuberculosis (according to sex) for the respective year c) number of deaths due to suicide (according to sex) for the respective year d) number of deaths due to murder and manslaughter (according to sex) for the respective year

The variables for the Prussian counties can be compared with the corresponding counties of the German Reich.

Context

Berlin is a special city, multicultural city. And the crime image is special there.

Content

For example there are no bloody drug wars, ghetto or neighborhoods where police afraid to get. Crimes like "deprivation of liberty" and "treat" are in one column. But "larceny" - separated to 4 categories: theft of bikes, of auto, from auto (sic!) and rest kind of theft. Particular column for "Damage to property due graffiti" (Sach-beschädigung durch Graffiti (sic!). Numbers of crimes are connected with every single neighborhood of Berlin's part. Statistics covering period of 2012 - 2019 years.

Acknowledgements

Special thanks for assistance in translation to Alexei Klaus and Benjamin Proksch, Germany.

Inspiration

Questions to community: 1) what part of Berlin is most dangerous? 2) what crimes are growing? 3) what crimes are going low? 4) would be great to build Folium based heatmap.

Information on non-German suspects (breakdown by offence, total number of suspects, by sex, by age) per federal state

The research project is a subproject of the research association “Strengthening of integration potentials within a modern society” (Scientific head: Prof. Dr. Wilhelm Heitmeyer, Bielefeld) which contains 17 subprojects and is supported by the ministry of education and research. In almost all the economically highly developed countries violent crime increased significantly in the second part of the last century - in contrast to the long term trend of decline of individual (non-governmental) violence since the beginning of modern times. The authors develop an explanatory approach for these facts which is inspired mainly by Norbert Elias´s civilization theory and Emil Durkheim´s theory on society. Detailed time series on the development of different forms of violent crime are presented and set in relation with certain aspects of economic and social structural changes in three countries and also refer to the changes in integration of modern societies. The analysis deals especially with effectivity and legitimacy of the governmental monopoly of violence, the public beneficial security and power system, forms of building social capital, economic and social inequality, precarity of employment, different aspects of increasing economization of society, changes in family structures and usage of mass media and modern communication technologies. Register of tables in HISTAT: A: Crime statistics A.01 Frequency of types of crimes in different countries (1953-2000) A.02 Suspects by crimes of 100.000 inhabitants of Germany, England and Sweden (1955-1998) A.03 Murders, manslaughter and intentional injuries by other persons by sex of 100.000 persons after the statistics of causes of death (1953-2000) A.04 Clearance rate by types of crimes in Germany, England and Sweden (1953-1997) A.05 Prisoners of 100.000 inhabitants of Germany, Great Britain and Sweden (1950-2000) B: Key indicators for economic development in Germany, Great Britain, Sweden and the USA B1: Data on the overall economic framework B1.01 Percent changes in the real GDP per capita in purchasing power parities (1956-1987) B1.02 Percent changes in GDP per capita in prices from 2000 (1955-1998) B1.03 GDP of Germany, Sweden and the United Kingdom in purchasing power parities in percent og the US GDP (1950-1992) B1.04 Labor productivity index for different countries, base: USA 1996 = 100 (1950-1999) B1.05 GDP per hour of labor in different countries in EKS-$ from 1999 (1950-2003) B1.06 Foreign trade - exports and imports in percent of the GDP of different countries (1949-2003) B1.07 GDP, wages and Unit-Labor-Cost in different countries (1960-2003) B2: Unemployment B2.01 Standardized unemployment rate in different countries with regard to the entire working population (1960-2003) B2.02 Share of long-term unemployed of the total number of unemployed in different countries in percent (1992-2004) B2.03 Youth unemployment in different countries in percent (1970-2004) B2.04 Unemployment rate in percent by sex in different countries (1963-2000) B3: Employment B3.01 Employment rate in percent in different countries (1960-2000) B3.02 Share of fixed-term employees and persons in dependent employment in percent in different countries (1983-2004) B3.03 Share of part-time employees by sex compared to the entire working population in different countries (1973-2000) B3.04 Share of un-voluntarily part-time employees by sex in different countries (1983-2003) B3.05 Share of contract workers in different countries in percent of the entire working population (1975-2002) B3.06 Share of self-employed persons in different countries in percent of the entire working population (1970-2004) B3.07 Shift worker rate in different countries in percent (1992-2005) B3.08 Yearly working hours per employee in different countries (1950-2004) B3.09 Employment by sectors in different countries (1950-2003) B3.10 Share of employees in public civil services in percent of the population between 15 and 64 years in different countries (1960-1999) B3.11 Female population, female employees and female workers in percent of the population between 16 and 64 years in different countries (1960-2000) B3.12 Employees, self-employed persons in percent of the entire working population in different countries (1960-2000) B4: Taxes and duties B4.01 Taxes and social security contributions in percent of the GDP (1965-2002) B4.02 Social expenditure in percent of the GDP (1965-2002) B4.03 Social expenditure in percent of the GDP (1960-2000) B4.04 Public expenditure in percent of the GDP in different countries (1960-2003) B4.05 Education expenditure in percent of GDP (1950-2001) B5: Debt B5.01 Insolvencies in Germany and England (1960-2004) B5.02 Insolvencies with regard to total population in different countries (1950-2002) B5.03 Consumer credits in different countries (1960-2002) C: Income distribution in Germany, Great Britain and Sweden C.01 Income inequality in different countries Einkommensungleicheit in verschiedenen Ländern (1949-2000) C.02 Income inequality after different indices and calculations in different countries (1969-2000) C.03 Redistribution: Decline in Gini-Index through transfers and taxes in percent in different countries (1969-2000) C.04 Redistribution: Decline in Gini-Index through transfers and taxes in percent with a population structure as in the United Kingdom in 1969 in different countries (1969-2000) C.05 Redistribution efficiency: Decline in Gini-/ Atkinson-Index through transfers and the share of social expenditure of the GDP in different countries (1969-2000) C.06 Index for concentration of transfers in different countries (1981-2000) C.07 Distribution of wealth in West-Germany (1953-1998) C.08 Distribution of wealth in the United Kingdom (1950-2000) C.09 Distribution of wealth in Sweden (1951-1999) C.10 Relative income poverty in different countries (1969-2000) C.11 Reduction of poverty in different countries (1969-2000) C.12 Neocorporalism index in different countries (1960-1994) D: Perception of safety D.01 Satisfaction with democracy in different countries (1976-2004) D.02 Revenues and employees in the private security sector in different countries (1950-2001) D.03 Decommodification-Score in different countries (1971-2002) E: Demographics E.01 Birth rates: Birth per 1000 women between 15 and 49 years in different countries (1951-2001) E.02 Fertility rate in different countries (1950-2004) E.03 Marriages per 100.000 persons in different countries (1950-2003) E.04 Share of foreigners of the entire population in different countries (1951-2002) E.05 Internal migration in different countries (1952-2001)

Data about delinquency in the German ‚Kaiserreich’ are made available by this study. The subjects of investigation are municipalities and administrative districts of the German ‘Reich’, taking into account the changes of the boarders. For all municipalities and administrative districts the crime rate according to the categories crime of violence, criminal assault, as well as simple and aggravated theft are collected. Topics: Development of crime during the period of investigation from 1893 to 1897, 1898 to 1902, divided into total offenses, offenses of bodily harm, simple and aggravated theft, and into adult persons and adolescent. Furthermore, the effect of region and urbanity, the average of condemned per crime-group referring to 100.000 persons of the age of criminal responsibility, the police-force, efficiency of enquiry. Structural variables: size of area, population structure, area and population (1885, 1890, 1895, 1900), religion, ethnic mixture (1.12.1900), urbanisation, birth and death, causes of death, occupation-structure, unemployment (1895), size of agricultural farms, average daily wages of men and women in cities and in the countryside (1892, 1901), taxpayers (1899 to 1903), poor relief (1895, 1903), school system (1891). Daten zur Kriminalität im Kaiserreich. Die Untersuchungseinheiten sind die Stadt- und Landkreise des Deutschen Reiches unter Berücksichtigung von Gebietsänderungen. Für alle erfassten Kreise wurden Kriminalitätsraten in den Kategorien Gesamtkriminalität, gefährliche Körperverletzung, sowie einfacher und schwerer Diebstahl erhoben. Themen: Entwicklung der Kriminalität in den Untersuchungsperioden 1893 bis 1897, 1898 bis 1902, unterteilt nach Gesamtdelikten, Körperverletzungsdelikten, einfacher und schwerer Diebstahl und nach Erwachsenen und Jugendlichen; Einfluss von Region und Urbanität; Durchschnitt der Verurteilten je Deliktgruppe auf 100000 strafmündige Zivilpersonen in den Untersuchungsperioden; Polizeistärke, Ermittlungseffizienz; Strukturvariablen: Gebietsgröße, Bevölkerungsstruktur, Fläche und Bevölkerung (1885, 1890, 1895, 1900); Religion, ethnische Zusammensetzung (1.12.1900), Urbanisierung, Geburten und Sterbefälle; Todesursachen: Tuberkulose, Diarrhöe, Selbstmord; Beschäftigungsstruktur, Arbeitslosigkeit (1895), Landwirtschaftliche Betriebsgröße, durchschnittlicher Tagelohn bei Männern und Frauen in Stadt und auf dem Land (1892, 1901), Steuerpflichtige (1899 bis 1903), Summe der Guthaben auf Sparkassenbüchern (1899), Armenwesen, Armenverbände (1895, 1903), Schulwesen (1891). Census in Baden, Bavaria, Hesse, Prussia, Saxony, Württemberg, inclusive regional subdivision and the former grand duchies, duchies, principalities and the free Hanseatic cities.

The number of shoplifting cases registered by the German police has fluctuated in the last decade, though the figures displayed in this graph show a decrease since 2015. In 2023, around 426,096 cases of shoplifting were recorded by police in Germany, a rather large increase compared to the previous year. Mind the shop Shoplifting is damaging to any business. There are measures that can be taken in order to minimize shoplifting, such as video surveillance, tagging items, as well as hiring security personnel that are visibly present to customers in some shops. The reality is, however, that among theft crimes, shoplifting is the most common, so even with security measures implemented, it is difficult for stores to completely avoid being targeted. Falling crime rate Recent statistics show that the crime rate in Germany (estimated per 100,000 people) was falling considerably. However, since the pandemic the rate of crime in Germany has risen. Police have also recorded more crime offences since 2021.

The aim of the project was to identify and compile the best available historical time series for Germany, and to complement or update them at reasonable expense. Time series were only to be included, if data for the entire period from 1834 to 2012 was at least theoretically available. An integral aspect of the concept of our project is the combination of data with critical commentaries of the time series by established expert scientists. The following themes are covered (authors in parentheses): 1. Environment, Climate, and Nature (Paul Erker) 2. Population, Households, Families (Georg Fertig/Franz Rothenbacher) 3. Migration (Jochen Oltmer) 4. Education and Science (Volker Müller-Benedict) 5. Health Service (Reinhard Spree) 6. Social Policy (Marcel Boldorf) 7. Public Finance and Taxation (Mark Spoerer) 8. Political Participation (Marc Debus) 9. Crime and Justice (Dietrich Oberwittler) 10. Work, Income, and Standard of Living (Toni Pierenkemper) 11. Culture, Tourism, and Sports (Heike Wolter/Bernd Wedemeyer-Kolwe) 12. Religion (Thomas Großbölting/Markus Goldbeck) 13. National Accounts (Rainer Metz) 14. Prices (Rainer Metz) 15. Money and Credit (Richard Tilly) 16. Transport and Communication (Christopher Kopper) 17. Agriculture (Michael Kopsidis) 18. Business, Industry, and Craft (Alfred Reckendrees) 19. Building and Housing (Günther Schulz) 20. Trade (Markus Lampe/ Nikolaus Wolf) 21. Balance of Payments (Nikolaus Wolf) 22. International Comparisons (Herman de Jong/Joerg Baten) Basically, the structure of a dataset is guided by the tables in the print publication by the Federal Agency. The print publication allows for four to eight tables for each of the 22 chapters, which means the data record is correspondingly made up of 120 tables in total. The inner structure of the dataset is a consequence of a German idiosyncrasy: the numerous territorial changes. To account for this idiosyncrasy, we decided on a four-fold data structure. Four territorial units with their respective data, are therefore differentiated in each table in separate columns: A German Confederation/Custom Union/German Reich (1834-1945).B German Federal Republic (1949-1989).C German Democratic Republic (1949-1989).D Germany since the reunification (since 1990). Years in parentheses should be considered a guideline only. It is possible that series for the territory of the old Federal Republic or the new federal states are continued after 1990, or that all-German data from before 1990 were available or were reconstructed.All time series are identified by a distinct ID consisting of an “x” and a four-digit number (for numbers under 1000 with leading zeros). The time series that exclusively contain GDR data were identified with a “c” prefix instead of the “x”.For the four territorial units, the time series are arranged in four blocks side by side within the XLSX files. That means: first all time series for the territory and the period of the Custom Union and German Reich, the next columns contain side by side all time series for the territory of the German Federal Republic / the old federal states, then – if available – those for the territory of the German Democratic Republic / the new federal states, and finally for the reunified Germany. There is at most one row for each year. Dates can be missing if no data for the respective year are available in either of the table’s time series, but no date will appear twice. The four territorial units and the resultant time periods cause a “stepwise” appearance of the data tables.

If you find anything missing, unclear, incomprehensible, improvable, etc., please contact me (kontakt@deutschland-in-daten.de). Further reading:Rahlf, Thomas, The German Time Series Dataset 1834-2012, in: Journal of Economics and Statistics 236/1 (2016), pp. 129-143. [DOI: 10.1515/jbnst-2015-1005] Open Access: Rahlf, Thomas, Voraussetzungen für eine Historische Statistik von Deutschland (19./20. Jh.), in: Vierteljahrschrift für Sozial- und Wirtschaftsgeschichte 101/3 (2014), S. 322-352. [PDF] Rahlf, Thomas (Hrsg.), Dokumentation zum Zeitreihendatensatz für Deutschland, 1834-2012, Version 01 (= Historical Social Research Transition 26v01), Köln 2015. http://dx.doi.org/10.12759/hsr.trans.26.v01.2015Rahlf, Thomas (Hrsg.), Deutschland in Daten. Zeitreihen zur Historischen Statistik, Bonn: Bundeszentrale für Politische Bildung, 2015. [EconStor]

In 2023, the German police had roughly 207,150 juvenile criminal suspects. This was an increase compared to the previous year, at almost 189,150 suspects.

The German Victimization Survey is a dark field survey conducted on behalf of the Federal Criminal Police Office (BKA) with the aim of collecting comprehensive information on the topics of fear of crime, victim experiences and reporting behaviour in the Federal Republic of Germany. Other focal points of the survey were fraud offences with EC and credit cards or on the Internet as well as crime-related attitudes. The study, designed as a cross-sectional survey, was first conducted in 2012 and repeated in 2017 with a slightly modified survey instrument. A representative sample of the German population aged 16 and over was interviewed in computer-assisted telephone interviews (CATI). In both surveys, the interviews were conducted in German, Turkish and Russian.

The cumulative dataset presented here contains the complete data of both surveys and thus enables the measurement of changes between 2012 and 2017.

Topics: 1. Number of household members aged 16 and over (fixed-network sample/total sample); household size; household type; age; age group; life satisfaction, trust; self-assessment of health status; general personal trust; institutional trust (federal government, courts, police, political parties, Federal Criminal Police Office (BKA), public prosecutor´s office).

1. Crime-related attitudes: Contact with police in the last 12 months; reason for police contact (reporting a crime, stopped on the street, questioned as a witness, accident, as a suspect, professional contact, given information or advice to get help or advice, other reason); satisfaction with treatment by police at last contact; reasons for dissatisfaction with last police contact (e.g. did not come quickly enough, not helpful enough or not at all, prejudice, etc.). ); reputation of the police among people in the personal environment (image); negative experiences with the police in the last 12 months in the personal environment; assessment of the work of the local police in fighting crime; equal treatment of rich and poor people by the local police when reporting a crime; frequency of disproportionate violence by the local police; assessment of one´s own economic situation; concerns about the deterioration of one´s own standard of living; agreement with the statement: enough people in the personal environment who take me as I am.

Additional questions on justice: frequency of fair and impartial decisions by the courts; equal treatment of rich and poor people in court; frequency of wrong decisions by courts (guilty people not convicted, innocent people convicted); contact with a court in the last five years about a criminal case; time of last contact with a court about a criminal case; own role in last participation in a criminal case; satisfaction with the outcome of the case.

1. Attitudes towards punishment: Importance of different purposes in imposing punishment (deterring offenders from committing further crimes, helping offenders to lead a crime-free life, making offenders pay for their crime, making offenders pay for the harm they have done, increasing the public´s awareness of the law, protecting society from offenders);

Vignette experiment: attitudes towards punishment based on different case studies for different offences (bodily harm, theft, damage to property, fraud, robbery) with regard to appropriate response options of the state, custodial sentence with or without probation, duration of custodial sentence in years/months and most appropriate conditions.

1. Attitudes towards immigration: immigration good or bad for the German economy, cultural life in Germany undermined or enriched by immigrants; Germany made a better or worse place to live by immigrants.

2. Media use: average weekly use of (internet) TV, (internet) radio, internet edition of a newspaper, printed newspaper, internet (excluding TV, radio, newspaper use); interest in different types of TV programmes (news, political magazines, other magazines, reports, documentaries, TV shows, quiz programmes, sports programmes, crime films, feature films, entertainment series, comedy programmes); reasons for TV consumption.

3. Social psychological perspectives and attitudes: Attitudes towards life and the future based on various statements (how my life turns out depends on myself, what one achieves in life is primarily a matter of fate or luck, success has to be worked hard for, when I encounter difficulties in life I often doubt my abilities, more important than all the efforts are the skills one brings, I have little control over the things that happen in my life, I only deal with tasks that are solvable, I like life to be even, I like surprises to come unexpectedly, I feel more comfortable when I know what is coming).

4. General and vocational education: highest school-leaving qualification or school-leaving qualification aspired to; highest vocational training qualification; main occupation (employment status); extent of employment.

5. Neighbourhood: size of the place...

The number of rape and sexual assault cases reported to the police in Germany peaked at 12,186 in 2023 during the period shown here. Previously, the highest number of cases, 11,896, had been recorded the year before. Based on the definition in criminal law, sexual assault includes rape, as well as other sexually driven physical attacks. Rape is defined as forcing a person to have sex. Increased crime clearance rate The question remains how high the number of unreported cases is. Reasons for not reporting a sexual assault vary among victims. In recent years, the German police reported increasing clearance rates for sexual crimes. In 2022, 83.7 percent of rape and sexual assault cases were solved, compared to 78.6 percent in 2016. In 2023, however this figure dropped to 83.4 percent, perhaps due to the increase in the number of cases. Among males suspected of committing such crimes,over 75 percent were young adults aged 18 to 21 years. Types of German police forces German police forces are divided into several different types, which all have clearly established tasks regulated by law. The Federal Criminal Police Office (Bundeskriminalamt, BKA) is often compared to the FBI in the U.S. and investigates federal crimes, such as kidnapping. The Federal Police (Bundespolizei), works in railway stations, at airports, and seaports. They also protect borders, government buildings, and deal with organized crime and terrorism. The criminal police (Kriminalpolizei, Kripo), the only policemen not wearing in uniform in Germany, handle assault, murder, and rape cases, as well as theft. The uniformed police (Schutzpolizei, SchuPo), or beat police, are regularly visible in streets, as they are responsible for traffic safety, among other tasks, and may be approached directly by people in need of assistance or help.

The United States had, by far, the highest homicide rate of the G7 countries between 2000 and 2021. In 2021, it reached 6.81 homicides per 100,000 inhabitants, an increase from 6.52 in 2020 and 5.07 in 2019. By comparison, Canada, the G7 nation with the second highest homicide rate, had 2.07 homicides per 100,000 inhabitants in 2021. Out of each G7 nation, Japan had the lowest rate with 0.23 homicides per 100,000 inhabitants.

English:

The data set contains 503 variables and 624 observations on suicides and suicide rates as well as on demographic, socio-structural, infrastructure and crime statistics on the canton and national level for the years 1952 to 1990. The information was recorded and processed by GDR’s Central Bureau of Statistics on a yearly basis. The statistical yearbooks of the GDR and various files of the Federal Archive were used as the sources of this data.

The demographic statistics include the population distribution by gender and age-groups, the incidence of deaths, homicides, births, stillbirths, as well as infant mortality and domestic migration rates by year and administrative district. The socio-structural information includes marriage and divorce rates, population distribution by education, employment and religious denomination, as well as the number of members and candidates of the Socialist Unity Party of Germany by year and district. The infrastructure data contains information on population density, residential housing construction and retail sales by year and administrative canton. The annual numbers of offenders of criminally liable age and convicted persons in the districts that come from the GDR crime statistics were included in the data set from the GDR crime statistics.

Missing values indicate that no information could be found for the given year or region. However, the missing information on the distribution by gender and age-groups, as well as suicide rates by age-group can be estimated using the attached do-files. A detailed description of how the missing values have been determined can be found in the document “Imputation und Standardisierung.pdf”. The do-files and the description are available in a zip file below.

Deutsch:

Dieser Datensatz umfasst 503 Variablen und 624 Beobachtungen. Er beinhaltet Informationen zu Suizidzahlen sowie demographische, sozialstrukturelle, infrastrukturelle Statistiken und Kriminalstatistiken in den Bezirken der DDR sowie des gesamten Landes von 1952 bis 1990. In der DDR war die Staatliche Zentralverwaltung für Statistik (SZS) für die Sammlung und Aufbereitung der verschiedenen Jahresstatistiken zuständig, weshalb die langen Zeitreihen größtenteils aus dem Primärbestand der SZS ermittelt und anschließend vergleichbar über die Bezirke und den Zeitverlauf berechnet wurden. Als Recherchequellen dienen die statistischen Jahrbücher der DDR sowie verschiedene Akten des Bundesarchivs.

Die demographischen Statistiken umfassen die jährlichen bezirksspezifischen Verteilungen der Geschlechter, Altersgruppen, Verstorbenen, Ermordeten, Lebendgeborenen, Totgeborenen, gestorbenen Säuglinge und Binnenmigration. Die sozialstrukturellen Informationen umfassen Angaben zu regionalen Verteilungen der Eheschließung, Ehescheidung, Bildung, Beschäftigung und Konfession sowie Statistiken über die Mitgliedschaft und Kandidatur für eine Mitgliedschaft bei der SED. Die verschiedenen infrastrukturellen Daten umfassen jährliche Statistiken der Bevölkerungsdichte, des Wohnungsbaus und des Einzelhandelsumsatzes in den Bezirken der DDR. Zudem wurden aus der Kriminalstatistik der DDR die jährliche Anzahl der strafmündigen Täter und der Verurteilten in den Bezirken in den Datensatz aufgenommen.

Missings werden in dem Datensatz ausgewiesen, wenn für bestimmte Jahre oder Regionen keine Zahlen recherchiert werden konnten bzw. die Informationen nicht erhoben wurden. Fehlende Suizidzahlen und fehlende Bevölkerungszahlen in bestimmten Altersgruppen können mittels der beigefügten Do-Files geschätzt und importiert werden. Eine ausführliche Beschreibung der Bestimmung der fehlenden Zahlen lassen sich dem Dokument „Imputation und Standardisierung.pdf“ entnehmen. Zudem ist ein unverzerrter Vergleich der Suizidraten über Regionen und Zeit nur anhand von standardisierten Suizidraten möglich. Auch dieses Vorgehen der indirekten Standardisierung ist im genannten Dokument beschrieben und kann anhand der Do-Files repliziert werden. Sie sind unten in einer Zip-Datei verfügbar.

Information on the proportion of non-German suspects, broken down by nationality, in the total crime and in each type of offence

As the number of refugees rises across the world, anti-refugee violence has become a pressing concern. What explains the incidence and support of such hate crime? We argue that fears among native men that refugees pose a threat in the competition for female partners are a critical but understudied factor driving hate crime. Employing a comprehensive dataset on the incidence of hate crime across Germany, we first demonstrate that hate crime rises where men face disadvantages in local mating mar-kets. Next, we complement this ecological evidence with original survey measures and confirm that individual-level support for hate crime increases when men fear that the inflow of refugees makes it more difficult to find female partners. Mate competition concerns remain a robust predictor even when controlling for anti-refugee views, perceived job competition, general frustration, and aggressiveness. We conclude that a more complete understanding of hate crime and immigrant conflict must incorporate marriage markets and mate competition.