The unemployment–crime link changes sharply by country

Q: Does unemployment cause crime?

This analysis cannot answer causation. It compares city-level unemployment and recorded-crime ranks at one point or period, without measuring policing, reporting, deprivation, urban form or other possible influences. It also cannot say anything about an individual unemployed person’s behaviour; doing so would be the ecological fallacy.

Q: Where is the unemployment–crime relationship strongest?

The strongest reportable Spearman coefficients are Sweden at +0.683, the Netherlands at +0.647 and Belgium at +0.646. Germany follows at +0.583. These are within-country rankings under each country’s own unemployment and recorded-crime definitions, not evidence that their national levels are higher or directly comparable.

Q: Where is the coefficient closest to zero?

Spain is +0.010 across 427 places, Lithuania +0.029 across 30, Portugal +0.044 across 280, Canada +0.081 across 40 and Italy -0.099 across 2,371. These are sample coefficients near zero, not proof that the underlying relationship is exactly zero.

Q: Does city population explain the unemployment–crime result?

No single size explanation fits all countries. Lithuania has a +0.638 population–crime coefficient but only +0.029 for unemployment; Belgium and the Netherlands are positive on both; Portugal is slightly positive for unemployment and negative for population. Population is a competing correlate, not a demonstrated mechanism.

Q: How should movers use these figures?

Use the pairing only as a country-specific screening clue. Check each shortlisted city’s observation year, geographic grain, offence definition and unemployment definition, then compare places covered by the same source system. Direct neighbourhood, offence-category and labour-market evidence is more useful than assuming one national coefficient applies everywhere.

By Max Streltcoff · Published 6 August 2026 · Updated 29 September 2026

Key finding: Across Swedish cities, the rank correlation between the unemployment rate and the recorded crime rate is 0.683; across Portuguese cities it is 0.044, so the link differs by country.

City-level data cannot show that unemployment causes crime. Across 16,342 places in the 18 country samples with at least 20 observations, sixteen Spearman coefficients are positive and two negative, and the range runs from -0.249 in Poland to +0.683 in Sweden. Spain, Canada, Lithuania and Portugal are near zero. A mostly shared sign is not a shared relationship.

What we measured

We tested whether places with higher published unemployment rates also tend to rank higher on recorded offences per 100,000 residents inside the same country. The unit is a place, not a person. Spearman’s coefficient describes whether the two city rankings move together; it does not measure the effect of unemployment on crime.

Unemployment is not one harmonised measure. Some sources publish registered unemployment, others labour-force-survey estimates, and the observation windows range from a single date to a multi-year American Community Survey period. The rates can support within-country ordering under one source definition, but they must not be used to rank national labour markets against one another.

Recorded crime is not all crime and is not a direct safety score. It reflects offences recorded and released by public authorities, so reporting, detection, legal definitions, police practice and geographic boundaries can alter the rate. A Swedish value and a Spanish value do not become comparable merely because both are expressed per 100,000.

The ecological fallacy applies directly. A city-level association says nothing about whether any individual unemployed person commits, experiences or reports an offence. This article makes no inference about individual behaviour in either direction.

The packet contains 16,353 rows across 23 countries. Eighteen countries meet the pre-set floor of 20 complete observations and contribute 16,342 rows to the country results; five below-floor countries contribute 11 rows only to the pooled diagnostic. The data combine official police, statistical-office and population sources.

Geographic grain is mixed. Crime is city grain in 8,646 rows, German kreis_nuts3 district grain in 3,040, municipality grain in 707, county grain in 2,360, regional-context grain in 1,599 and US police-agency service-area grain in one. Unemployment is labelled city grain in 7,334 rows, regional_context in three UK rows, and a special Eurostat city label in two rows. Inherited parent-municipality values were excluded before export.

Observation periods also diverge. Belgium pairs 2011 unemployment with 2025 recorded crime; Portugal is mostly 2026 unemployment against 2022 crime; the UK uses 2018 city unemployment or 2023 regional context against 2024 crime. The Netherlands aligns both measures to 2024; Denmark pairs November 2025 unemployment with 2025 crime, while Sweden is approximately one year apart. These are cross-sectional pairings, not synchronized panels.

What the data shows

The pooled Spearman coefficient is +0.447 across all 16,353 rows, but it is not an average country relationship. It re-ranks places after combining 23 non-equivalent systems. The United States supplies 27.3% of the packet; the United States and Germany together supply 46.2%. The pooled value is therefore dominated by sample composition and is retained only as an aggregation warning.

Three countries form the strong end: Sweden at +0.683 across 200 places, the Netherlands at +0.647 across 337 and Belgium at +0.646 across 491. Germany follows at +0.583 across 3,095, Finland at +0.551 across 63 and France at +0.521 across 2,222; Denmark is +0.421 across 97. In those samples, higher unemployment ranks substantially coincide with higher recorded-crime ranks.

The United States is moderate at +0.327 across 4,457 places. It is numerically important because it dominates the row count, but it cannot stand in for the other countries. Germany carries the packet’s largest grain problem: 3,040 of 3,095 outcomes are district rates attached to city unemployment values.

At the other end, Portugal is +0.044, Lithuania +0.029, Canada +0.081 and Spain +0.010, while Italy is -0.099 and Poland -0.249. The Lithuanian coefficient is based on only 30 places and must not be described as proof of no relationship. It is a near-zero estimate in a small sample.

An unadjusted rank test returns p<0.05 for six positive coefficients: Sweden, the Netherlands, Belgium, Denmark, the United States and Germany. The other five do not pass that descriptive check. Spatial clustering, repeated German district outcomes and multiple country tests violate the assumptions needed to treat those p-values as formal national inference.

The strong cases are not an artefact of rank correlation alone. Pearson is +0.665 in Sweden, +0.732 in the Netherlands and +0.600 in Belgium. Portugal is more method-sensitive: Spearman is +0.044 while Pearson is +0.160, indicating that a small number of raw-value contrasts influence a linear coefficient more than the overall rank ordering.

Quartile contrasts tell the same heterogeneous story in plain units. Using inclusive 25th- and 75th-percentile cutoffs, the median recorded-crime rate in the high-unemployment group is 1.94 times the low group in the United States, 1.80 in the Netherlands, 1.77 in Belgium and 1.45 in Sweden. The ratios are 1.06 in Spain, 1.05 in Portugal and 1.02 in the UK; Lithuania is 0.94. These ratios stay within each reporting system.

Figure 1Unemployment against the recorded-crime rate, by country. Sixteen of 18 coefficients are positive and two are negative (Italy, Poland); the strengths run from near zero to +0.68.

Hover, focus, or tap a mark to inspect its exact values.

Use Arrow keys to move between marks. Home/End jump to the first/last mark. Page Up/Page Down move by 10 marks. Tab exits the chart. On small screens, swipe horizontally across the chart. Exact values are listed below.

View exact figure values

Figure conclusion: Unemployment against the recorded-crime rate, by country. Sixteen of 18 coefficients are positive and two are negative (Italy, Poland); the strengths run from near zero to +0.68.

Unemployment and recorded-crime correlation by country exact values
Mark	Group	Value	Unit	Sample/note	Exact detail
US	US	0.325	coefficient	4,741 cities	US; Group: US; Value: 0.325 coefficient; 4,741 cities
DE	DE	0.583	coefficient	3,084 cities	DE; Group: DE; Value: 0.583 coefficient; 3,084 cities
IT	IT	-0.11	coefficient	2,393 cities	IT; Group: IT; Value: -0.11 coefficient; 2,393 cities
FR	FR	0.523	coefficient	2,238 cities	FR; Group: FR; Value: 0.523 coefficient; 2,238 cities
JP	JP	0.199	coefficient	1,807 cities	JP; Group: JP; Value: 0.199 coefficient; 1,807 cities
UK	UK	0.458	coefficient	1,691 cities	UK; Group: UK; Value: 0.458 coefficient; 1,691 cities
ES	ES	-0.136	coefficient	1,365 cities	ES; Group: ES; Value: -0.136 coefficient; 1,365 cities
PL	PL	-0.153	coefficient	632 cities	PL; Group: PL; Value: -0.153 coefficient; 632 cities
BE	BE	0.627	coefficient	537 cities	BE; Group: BE; Value: 0.627 coefficient; 537 cities
CA	CA	0.419	coefficient	501 cities	CA; Group: CA; Value: 0.419 coefficient; 501 cities
NL	NL	0.642	coefficient	343 cities	NL; Group: NL; Value: 0.642 coefficient; 343 cities
PT	PT	0.044	coefficient	280 cities	PT; Group: PT; Value: 0.044 coefficient; 280 cities
AT	AT	0.137	coefficient	278 cities	AT; Group: AT; Value: 0.137 coefficient; 278 cities
HU	HU	0.266	coefficient	277 cities	HU; Group: HU; Value: 0.266 coefficient; 277 cities
CZ	CZ	0.387	coefficient	270 cities	CZ; Group: CZ; Value: 0.387 coefficient; 270 cities
GR	GR	-0.43	coefficient	269 cities	GR; Group: GR; Value: -0.43 coefficient; 269 cities
KR	KR	0.211	coefficient	218 cities	KR; Group: KR; Value: 0.211 coefficient; 218 cities
SE	SE	0.657	coefficient	218 cities	SE; Group: SE; Value: 0.657 coefficient; 218 cities
NO	NO	0.356	coefficient	181 cities	NO; Group: NO; Value: 0.356 coefficient; 181 cities
CH	CH	0.572	coefficient	176 cities	CH; Group: CH; Value: 0.572 coefficient; 176 cities
FI	FI	0.474	coefficient	156 cities	FI; Group: FI; Value: 0.474 coefficient; 156 cities
SK	SK	0.191	coefficient	140 cities	SK; Group: SK; Value: 0.191 coefficient; 140 cities
SI	SI	-0.142	coefficient	107 cities	SI; Group: SI; Value: -0.142 coefficient; 107 cities
DK	DK	0.42	coefficient	98 cities	DK; Group: DK; Value: 0.42 coefficient; 98 cities
IE	IE	-0.433	coefficient	84 cities	IE; Group: IE; Value: -0.433 coefficient; 84 cities
NZ	NZ	0.505	coefficient	78 cities	NZ; Group: NZ; Value: 0.505 coefficient; 78 cities
LT	LT	0.098	coefficient	68 cities	LT; Group: LT; Value: 0.098 coefficient; 68 cities
EE	EE	0.42	coefficient	47 cities	EE; Group: EE; Value: 0.42 coefficient; 47 cities
BG	BG	-0.039	coefficient	36 cities	BG; Group: BG; Value: -0.039 coefficient; 36 cities
LV	LV	0.567	coefficient	36 cities	LV; Group: LV; Value: 0.567 coefficient; 36 cities
AU	AU	0.138	coefficient	24 cities	AU; Group: AU; Value: 0.138 coefficient; 24 cities

Table 1Reportable countries. Registered and labour-force-survey unemployment rates both appear here and are not the same measure; only within-country rankings are comparable.

Reportable countries. Registered and labour-force-survey unemployment rates both appear here and are not the same measure; only within-country rankings are comparable.
Country	Cities	Spearman	Pearson	Median unemployment	Median crime
US	4,741	0.33	0.26	4.7%	1,598.8
DE	3,084	0.58	0.53	5.1%	4,501.9
IT	2,393	-0.11	-0.15	6.0%	3,435.6
FR	2,238	0.52	0.44	11.0%	4,740.3
JP	1,807	0.20	0.15	3.8%	507.1
UK	1,691	0.46	0.40	3.5%	6,791.9
ES	1,365	-0.14	-0.04	4.4%	4,750
PL	632	-0.15	-0.13	4.4%	1,665.5
BE	537	0.63	0.59	5.5%	5,408.1
CA	501	0.42	0.16	8.4%	4,296.5
NL	343	0.64	0.72	3.1%	3,110
PT	280	0.04	0.16	2.3%	2,745
AT	278	0.14	0.28	4.8%	3,681.2
HU	277	0.27	0.15	4.6%	1,743.8
CZ	270	0.39	0.39	4.1%	1,330.6
GR	269	-0.43	-0.31	13.5%	2,291.5
KR	218	0.21	0.18	2.7%	2,990
SE	218	0.66	0.65	10.6%	9,954
NO	181	0.36	0.41	1.7%	4,450
CH	176	0.57	0.48	2.3%	6,528.5
FI	156	0.47	0.49	10.6%	8,111.9
SK	140	0.19	0.15	4.2%	700
SI	107	-0.14	-0.18	9.9%	2,089
DK	98	0.42	0.34	2.5%	5,756
IE	84	-0.43	-0.38	9.4%	4,566
NZ	78	0.51	0.46	2.9%	4,102.4
LT	68	0.10	0.04	8.6%	1,404.2
EE	47	0.42	0.46	2.9%	2,030
BG	36	-0.04	0.02	9.2%	1,213
LV	36	0.57	0.53	6.3%	1,526.5
AU	24	0.14	0.14	4.3%	10,155.2

Table 2The unemployment coefficient beside the city-size coefficient on the same cities. Neither explanation subsumes the other, and in several countries size is the stronger one.

The unemployment coefficient beside the city-size coefficient on the same cities. Neither explanation subsumes the other, and in several countries size is the stronger one.
Country	Cities	Unemployment	City size
US	4,620	0.33	0.28
DE	3,077	0.58	0.20
IT	2,393	-0.11	0.15
FR	2,238	0.52	0.48
JP	1,765	0.20	0.41
UK	1,571	0.46	0.17
ES	1,365	-0.14	0.00
PL	626	-0.15	0.26
BE	536	0.63	0.47
CA	496	0.42	-0.04
NL	337	0.64	0.51
PT	279	0.04	-0.09
AT	278	0.14	0.37
HU	277	0.27	-0.29
CZ	270	0.39	0.14
GR	269	-0.43	0.31
KR	218	0.21	0.10
SE	217	0.66	0.35
NO	181	0.36	0.44
CH	176	0.57	0.26
FI	156	0.47	0.28
SK	140	0.19	0.47
SI	107	-0.14	0.23
DK	98	0.42	0.42
IE	84	-0.43	0.24
NZ	78	0.51	-0.02
LT	68	0.10	0.41
EE	47	0.42	0.11
BG	36	-0.04	-0.05
LV	34	0.57	0.28
AU	21	0.14	-0.42

Figure 2Every paired city: unemployment rate against offences per 100,000 residents. The unit is a city, and a city-level association says nothing about any individual.

Hover, focus, or tap a mark to inspect its exact values.

View exact figure values

Figure conclusion: Every paired city: unemployment rate against offences per 100,000 residents. The unit is a city, and a city-level association says nothing about any individual.

Vienna; Group: AT; Unemployment (%): 9.9; Offences per 100k: 9536.168599
Bad Gleichenberg; Group: AT; Unemployment (%): 4.4; Offences per 100k: 3053.4
Bruck an der Leitha; Group: AT; Unemployment (%): 5.7; Offences per 100k: 4571.9
Elsbethen; Group: AT; Unemployment (%): 2.1; Offences per 100k: 3871.3
Frohnleiten; Group: AT; Unemployment (%): 3.7; Offences per 100k: 3476.1
Graz; Group: AT; Unemployment (%): 8.2; Offences per 100k: 7589.4
Himberg; Group: AT; Unemployment (%): 4.2; Offences per 100k: 4571.9
Kirchberg in Tirol; Group: AT; Unemployment (%): 5.4; Offences per 100k: 4733
Kundl; Group: AT; Unemployment (%): 3; Offences per 100k: 4378.8
Lienz; Group: AT; Unemployment (%): 4.7; Offences per 100k: 3629.2
Nenzing; Group: AT; Unemployment (%): 3.8; Offences per 100k: 5008.3
Perchtoldsdorf; Group: AT; Unemployment (%): 3.4; Offences per 100k: 6605.4
Regau; Group: AT; Unemployment (%): 4.1; Offences per 100k: 3407.3
Seekirchen am Wallersee; Group: AT; Unemployment (%): 2.2; Offences per 100k: 3871.3
St. Valentin; Group: AT; Unemployment (%): 4.7; Offences per 100k: 3459.1
Traiskirchen; Group: AT; Unemployment (%): 5.7; Offences per 100k: 5353.1
Waidhofen an der Thaya; Group: AT; Unemployment (%): 4.2; Offences per 100k: 2666
Wörgl; Group: AT; Unemployment (%): 5.7; Offences per 100k: 4378.8
Sale; Group: AU; Unemployment (%): 5.1; Offences per 100k: 12247.200601443
Zoutleeuw; Group: BE; Unemployment (%): 4.49; Offences per 100k: 4734.200319
Oudenaarde; Group: BE; Unemployment (%): 3.89; Offences per 100k: 6960.218646
Hoeselt; Group: BE; Unemployment (%): 4.62; Offences per 100k: 4719.873641
Aalst; Group: BE; Unemployment (%): 5.71; Offences per 100k: 7509.9586
Niel; Group: BE; Unemployment (%): 4.32; Offences per 100k: 4448.9
Duffel; Group: BE; Unemployment (%): 3.56; Offences per 100k: 5191.5
Herselt; Group: BE; Unemployment (%): 4.99; Offences per 100k: 4628.8
Westerlo; Group: BE; Unemployment (%): 4.65; Offences per 100k: 5154.9
Schaerbeek; Group: BE; Unemployment (%): 19.87; Offences per 100k: 10140.9
Meise; Group: BE; Unemployment (%): 3.36; Offences per 100k: 3453.372087
Lennik; Group: BE; Unemployment (%): 2.49; Offences per 100k: 4519.058178
Keerbergen; Group: BE; Unemployment (%): 3.39; Offences per 100k: 3278.688525
Beauvechain; Group: BE; Unemployment (%): 6.38; Offences per 100k: 4911.7
Villers-la-Ville; Group: BE; Unemployment (%): 6.33; Offences per 100k: 4595.6
Torhout; Group: BE; Unemployment (%): 3.67; Offences per 100k: 4438.9
Harelbeke; Group: BE; Unemployment (%): 3.58; Offences per 100k: 5515.4
Ingelmunster; Group: BE; Unemployment (%): 3.29; Offences per 100k: 4595.7
Nieuport; Group: BE; Unemployment (%): 6.1; Offences per 100k: 8826.9
Laarne; Group: BE; Unemployment (%): 3.07; Offences per 100k: 4119.8
Oosterzele; Group: BE; Unemployment (%): 2.75; Offences per 100k: 3639.6
Stekene; Group: BE; Unemployment (%): 4.13; Offences per 100k: 4946.1
Farciennes; Group: BE; Unemployment (%): 22.11; Offences per 100k: 6050.8
Saint-Ghislain; Group: BE; Unemployment (%): 14.13; Offences per 100k: 7363.7
Thuin; Group: BE; Unemployment (%): 10.27; Offences per 100k: 7119.9
Morlanwelz; Group: BE; Unemployment (%): 16.13; Offences per 100k: 8248.4
Chaudfontaine; Group: BE; Unemployment (%): 9.14; Offences per 100k: 5797.8
Flémalle; Group: BE; Unemployment (%): 14.67; Offences per 100k: 8190.1
Saint-Vith; Group: BE; Unemployment (%): 3.13; Offences per 100k: 4435.3
Diepenbeek; Group: BE; Unemployment (%): 4.5; Offences per 100k: 5416
Lommel; Group: BE; Unemployment (%): 4.85; Offences per 100k: 5511.8
Messancy; Group: BE; Unemployment (%): 6.46; Offences per 100k: 4619.7
Saint-Hubert; Group: BE; Unemployment (%): 9.01; Offences per 100k: 9318.9
Yvoir; Group: BE; Unemployment (%): 7.53; Offences per 100k: 4168.5
Jemeppe-sur-Sambre; Group: BE; Unemployment (%): 12.17; Offences per 100k: 6256.5
Haskovo; Group: BG; Unemployment (%): 9; Offences per 100k: 1055.8
Svishtov; Group: BG; Unemployment (%): 10.1; Offences per 100k: 1221.9
Spallumcheen; Group: CA; Unemployment (%): 6.15; Offences per 100k: 4021.91
Sunbury-York South; Group: CA; Unemployment (%): 6.5; Offences per 100k: 5734
Baie-Comeau; Group: CA; Unemployment (%): 5.53; Offences per 100k: 3673.05
Brooks; Group: CA; Unemployment (%): 8.76; Offences per 100k: 7390.17
Clarenville; Group: CA; Unemployment (%): 12.97; Offences per 100k: 7222.44
Delson; Group: CA; Unemployment (%): 5.22; Offences per 100k: 3641
Erin; Group: CA; Unemployment (%): 8.24; Offences per 100k: 4296.48
Greater Napanee; Group: CA; Unemployment (%): 9.43; Offences per 100k: 4296.48
Kentville; Group: CA; Unemployment (%): 9.29; Offences per 100k: 7563.58
Laurentides; Group: CA; Unemployment (%): 3.6; Offences per 100k: 3673.05
Metchosin; Group: CA; Unemployment (%): 5.31; Offences per 100k: 6943.25
New Hamburg; Group: CA; Unemployment (%): 6.7; Offences per 100k: 4296.48
Peace River; Group: CA; Unemployment (%): 7.86; Offences per 100k: 7390.17
Port Alberni; Group: CA; Unemployment (%): 9.9; Offences per 100k: 19277.11
Revelstoke; Group: CA; Unemployment (%): 10.08; Offences per 100k: 6561.71
Sainte-Anne-des-Plaines; Group: CA; Unemployment (%): 6.19; Offences per 100k: 3641
Saint-Zotique; Group: CA; Unemployment (%): 5.12; Offences per 100k: 3641
Squamish; Group: CA; Unemployment (%): 6.84; Offences per 100k: 5396.3
Terrace; Group: CA; Unemployment (%): 6.41; Offences per 100k: 16918.23
Wetaskiwin; Group: CA; Unemployment (%): 12.04; Offences per 100k: 7390.17
Baie-Saint-Paul; Group: CA; Unemployment (%): 5.38; Offences per 100k: 3673.05
Fergus; Group: CA; Unemployment (%): 7.1; Offences per 100k: 4296.48
Bradford West Gwillimbury; Group: CA; Unemployment (%): 11.4; Offences per 100k: 4296.48
Drummondville; Group: CA; Unemployment (%): 5.6; Offences per 100k: 4076
Kingsville; Group: CA; Unemployment (%): 9.78; Offences per 100k: 4296.48
Okotoks; Group: CA; Unemployment (%): 9.21; Offences per 100k: 7390.17
Saint-Constant; Group: CA; Unemployment (%): 5.4; Offences per 100k: 3641
Springwater; Group: CA; Unemployment (%): 10; Offences per 100k: 4296.48
West Vancouver; Group: CA; Unemployment (%): 9.4; Offences per 100k: 6943.25
Cobourg; Group: CA; Unemployment (%): 12.4; Offences per 100k: 4296.48
St. Thomas; Group: CA; Unemployment (%): 11.2; Offences per 100k: 4296.48
Brampton; Group: CA; Unemployment (%): 13.3; Offences per 100k: 4296.48
Küsnacht (ZH); Group: CH; Unemployment (%): 1.5; Offences per 100k: 3718.35443
Illnau-Effretikon; Group: CH; Unemployment (%): 2.1; Offences per 100k: 5761.43275513
Spiez; Group: CH; Unemployment (%): 0.8; Offences per 100k: 6101.03432769
Lachen; Group: CH; Unemployment (%): 1.27; Offences per 100k: 5239.204064352244
Zuchwil; Group: CH; Unemployment (%): 3.3; Offences per 100k: 13633.52745424
Pratteln; Group: CH; Unemployment (%): 2.6; Offences per 100k: 7978.306718891233
Chur; Group: CH; Unemployment (%): 1.1; Offences per 100k: 11748.46781138
Romanshorn; Group: CH; Unemployment (%): 2.8; Offences per 100k: 5703.3344574
Renens (VD); Group: CH; Unemployment (%): 4.2; Offences per 100k: 11260.496489698526
Visp; Group: CH; Unemployment (%): 0.9; Offences per 100k: 5399.449035812672
Veyrier; Group: CH; Unemployment (%): 3.61; Offences per 100k: 6371.5349607
Vrchlabí; Group: CZ; Unemployment (%): 2.6897; Offences per 100k: 1406.799531066823
Ústí nad Labem; Group: CZ; Unemployment (%): 6.6699; Offences per 100k: 1925.8159984306903
Tišnov; Group: CZ; Unemployment (%): 4.6437; Offences per 100k: 953.4435109205265
Šternberk; Group: CZ; Unemployment (%): 4.8613; Offences per 100k: 1683.7016517221186
Rychvald; Group: CZ; Unemployment (%): 4.8935; Offences per 100k: 1884.4920688491393
Prachatice; Group: CZ; Unemployment (%): 3.1795; Offences per 100k: 1273.7478411053542
Opava; Group: CZ; Unemployment (%): 4.1916; Offences per 100k: 1366.5853770763354
Náchod; Group: CZ; Unemployment (%): 4.2967; Offences per 100k: 1483.000421098885
Luhačovice; Group: CZ; Unemployment (%): 2.2215; Offences per 100k: 1089.8670550101
Kunovice; Group: CZ; Unemployment (%): 3.894; Offences per 100k: 927.4053244143357
Karlovy Vary; Group: CZ; Unemployment (%): 5.3758; Offences per 100k: 1870.7631943106378
Hulín; Group: CZ; Unemployment (%): 3.2975; Offences per 100k: 1034.8116816171582
Havířov; Group: CZ; Unemployment (%): 9.6181; Offences per 100k: 1884.4920688491393
Dobřany; Group: CZ; Unemployment (%): 2.127; Offences per 100k: 2061.884473004121
České Budějovice; Group: CZ; Unemployment (%): 3.3734; Offences per 100k: 1458.3323041353997
Boskovice; Group: CZ; Unemployment (%): 4.8583; Offences per 100k: 883.3699528148975
Prague; Group: CZ; Unemployment (%): 3.58; Offences per 100k: 2476.966549
Solingen; Group: DE; Unemployment (%): 8.1; Offences per 100k: 6868.0400390625
Mainz; Group: DE; Unemployment (%): 5.4; Offences per 100k: 7261
Erfurt; Group: DE; Unemployment (%): 6.3; Offences per 100k: 8977.509765625
Zetel; Group: DE; Unemployment (%): 4.7; Offences per 100k: 4524.404696696577
Wittorf; Group: DE; Unemployment (%): 5.9; Offences per 100k: 18117.78
Wettringen; Group: DE; Unemployment (%): 5.1; Offences per 100k: 5721.787333522244
Wendeburg; Group: DE; Unemployment (%): 5.8; Offences per 100k: 5279.287825166916
Wannweil; Group: DE; Unemployment (%): 4.3; Offences per 100k: 4404.00295758187
Wachtendonk; Group: DE; Unemployment (%): 6.2; Offences per 100k: 6500.568291213534
Untergruppenbach; Group: DE; Unemployment (%): 3.8; Offences per 100k: 3237.5655948253207
Trappenkamp; Group: DE; Unemployment (%): 5.1; Offences per 100k: 5258.109337640445
Süsel; Group: DE; Unemployment (%): 5; Offences per 100k: 5711.959974587039
Stelle; Group: DE; Unemployment (%): 4.6; Offences per 100k: 4657.2683778172295
Sohland; Group: DE; Unemployment (%): 6.2; Offences per 100k: 4501.92749343832
Schwieberdingen; Group: DE; Unemployment (%): 3.9; Offences per 100k: 4004.3035336045455
Schönkirchen; Group: DE; Unemployment (%): 4.4; Offences per 100k: 3506.6496183264553
Schipkau; Group: DE; Unemployment (%): 7.2; Offences per 100k: 5225.756774558645
Alt-Sanitz; Group: DE; Unemployment (%): 9.1; Offences per 100k: 7270.3106385248675
Rottendorf; Group: DE; Unemployment (%): 2.7; Offences per 100k: 2095.9708043596193
Rodenbach; Group: DE; Unemployment (%): 5.6; Offences per 100k: 4131.010135086977
Reichenbach an der Fils; Group: DE; Unemployment (%): 4; Offences per 100k: 4300.02925823843
Pullach im Isartal; Group: DE; Unemployment (%): 3.2; Offences per 100k: 3223.5126807300308
Pfalzgrafenweiler; Group: DE; Unemployment (%): 3.9; Offences per 100k: 3185.522884927598
Ostseebad Binz; Group: DE; Unemployment (%): 9.2; Offences per 100k: 6959.940149533231
Obertraubling; Group: DE; Unemployment (%): 2.7; Offences per 100k: 1977.4428809508036
Oberammergau; Group: DE; Unemployment (%): 3.4; Offences per 100k: 4499.641641282924
Niederzier; Group: DE; Unemployment (%): 7.4; Offences per 100k: 5780.117084698426
Neuhofen; Group: DE; Unemployment (%): 4.2; Offences per 100k: 4076.801683324566
Namborn; Group: DE; Unemployment (%): 4.1; Offences per 100k: 3944.746222085568
Morsbach; Group: DE; Unemployment (%): 5.5; Offences per 100k: 3976.545025304955
Michelau; Group: DE; Unemployment (%): 4.3; Offences per 100k: 3321.5096691847607
Markt Indersdorf; Group: DE; Unemployment (%): 3; Offences per 100k: 2696.0513037533774
Losheim; Group: DE; Unemployment (%): 4.5; Offences per 100k: 4866.748177497495
Lensahn; Group: DE; Unemployment (%): 5; Offences per 100k: 5711.959974587039
Langquaid; Group: DE; Unemployment (%): 3.1; Offences per 100k: 2581.7815403413283
Künzell; Group: DE; Unemployment (%): 3.7; Offences per 100k: 4424.98976529919
Köngen; Group: DE; Unemployment (%): 4; Offences per 100k: 4300.02925823843
Kirchlinteln; Group: DE; Unemployment (%): 4.1; Offences per 100k: 5060.378284015986
Kalefeld; Group: DE; Unemployment (%): 6.1; Offences per 100k: 5081.075917626549
Immendingen; Group: DE; Unemployment (%): 4.4; Offences per 100k: 2924.7699851247867
Homberg; Group: DE; Unemployment (%): 4.4; Offences per 100k: 4109.209888991034
Hilzingen; Group: DE; Unemployment (%): 4.1; Offences per 100k: 5267.594340754041
Hemhofen; Group: DE; Unemployment (%): 2.9; Offences per 100k: 2346.6473883968915
Harsefeld; Group: DE; Unemployment (%): 5.8; Offences per 100k: 4879.15262397689
Gschwend; Group: DE; Unemployment (%): 3.6; Offences per 100k: 3552.3128152299582
Großbeeren; Group: DE; Unemployment (%): 5; Offences per 100k: 5377.403088559723
Goldbach; Group: DE; Unemployment (%): 3.8; Offences per 100k: 2615.4611132235514
Georgensgmünd; Group: DE; Unemployment (%): 2.4; Offences per 100k: 2307.357422725294
Fürth; Group: DE; Unemployment (%): 4.11; Offences per 100k: 2765.8123274330796
Feucht; Group: DE; Unemployment (%): 2.7; Offences per 100k: 2750.972970091166
Erdweg; Group: DE; Unemployment (%): 3; Offences per 100k: 2696.0513037533774
Elmpt; Group: DE; Unemployment (%): 5.8; Offences per 100k: 5596.645370093703
Egelsbach; Group: DE; Unemployment (%): 5.1; Offences per 100k: 4193.597041522588
Driedorf; Group: DE; Unemployment (%): 6; Offences per 100k: 3846.517156418996
Dettingen unter Teck; Group: DE; Unemployment (%): 4; Offences per 100k: 4300.02925823843
Cappeln; Group: DE; Unemployment (%): 4.5; Offences per 100k: 3591.583109730264
Büchenbach; Group: DE; Unemployment (%): 2.4; Offences per 100k: 2307.357422725294
Bösel; Group: DE; Unemployment (%): 4.5; Offences per 100k: 3591.583109730264
Bissendorf; Group: DE; Unemployment (%): 3.6; Offences per 100k: 4247.775638984164
Bickenbach; Group: DE; Unemployment (%): 5.1; Offences per 100k: 2901.122769608736
Beckingen; Group: DE; Unemployment (%): 4.5; Offences per 100k: 4866.748177497495
Bad Feilnbach; Group: DE; Unemployment (%): 2.8; Offences per 100k: 3799.92035168982
Altomünster; Group: DE; Unemployment (%): 3; Offences per 100k: 2696.0513037533774
Alfdorf; Group: DE; Unemployment (%): 4.2; Offences per 100k: 3701.4177573656216
Lauchringen; Group: DE; Unemployment (%): 4.2; Offences per 100k: 4213.802388404175
Waldbrunn; Group: DE; Unemployment (%): 5.2; Offences per 100k: 4865.09808433527
Butjadingen; Group: DE; Unemployment (%): 6.4; Offences per 100k: 5231.85211837726
Colditz; Group: DE; Unemployment (%): 5.8; Offences per 100k: 5045.996763119553
Drolshagen; Group: DE; Unemployment (%): 4.198; Offences per 100k: 4152.751122058846
Hemer; Group: DE; Unemployment (%): 7.43; Offences per 100k: 5948.1038902476685
Herdecke; Group: DE; Unemployment (%): 3.547; Offences per 100k: 5654.635910200625
Koenigswinter; Group: DE; Unemployment (%): 6.121; Offences per 100k: 5003.790625345822
Rethem (Aller); Group: DE; Unemployment (%): 6.5; Offences per 100k: 6491.604220179591
Memmingen; Group: DE; Unemployment (%): 3.8; Offences per 100k: 6110.39990234375
Voelklingen; Group: DE; Unemployment (%): 8.645; Offences per 100k: 9089.026231506023
Voerde (Niederrhein); Group: DE; Unemployment (%): 4.671; Offences per 100k: 5627.645124236217
Bernburg (Saale); Group: DE; Unemployment (%): 9.635; Offences per 100k: 6727.2958605086
Bad Oldesloe; Group: DE; Unemployment (%): 9.07; Offences per 100k: 4895.252131803348
Ehingen (Donau); Group: DE; Unemployment (%): 5.379; Offences per 100k: 2635.4803957421154
Moerfelden-Walldorf; Group: DE; Unemployment (%): 6.411; Offences per 100k: 4368.081696545041
Viernheim; Group: DE; Unemployment (%): 6.029; Offences per 100k: 2765.8123274330796
Münchberg; Group: DE; Unemployment (%): 3.9; Offences per 100k: 4901.780000216941
Achim; Group: DE; Unemployment (%): 3.314; Offences per 100k: 5060.378284015986
Ludwigsstadt; Group: DE; Unemployment (%): 3.8; Offences per 100k: 3129.5995042218606
Hann. Münden; Group: DE; Unemployment (%): 7.005; Offences per 100k: 7124.696672235297
Hörstel; Group: DE; Unemployment (%): 2.629; Offences per 100k: 5721.787333522244
Adenau; Group: DE; Unemployment (%): 3.9; Offences per 100k: 4760.616298037155
Nideggen; Group: DE; Unemployment (%): 4.266; Offences per 100k: 5780.117084698426
Monschau; Group: DE; Unemployment (%): 4.328; Offences per 100k: 8280.592709603201
Neustrelitz; Group: DE; Unemployment (%): 6.922; Offences per 100k: 6139.218408723683
Lütjenburg; Group: DE; Unemployment (%): 4.4; Offences per 100k: 3506.6496183264553
Wiesloch; Group: DE; Unemployment (%): 5.443; Offences per 100k: 3903.96035527006
Norderney; Group: DE; Unemployment (%): 6.5; Offences per 100k: 4679.158545885942
Barntrup; Group: DE; Unemployment (%): 5.5; Offences per 100k: 4645.267594030229
Maxhütte-Haidhof; Group: DE; Unemployment (%): 5.357; Offences per 100k: 2984.354907843978
Bobingen; Group: DE; Unemployment (%): 4.171; Offences per 100k: 2694.712169581943
Belgern-Schildau; Group: DE; Unemployment (%): 6.6; Offences per 100k: 6318.761219925585
Buchloe; Group: DE; Unemployment (%): 4.7; Offences per 100k: 2833.569170767422
Oelde; Group: DE; Unemployment (%): 5.033; Offences per 100k: 5192.489359217942
Bingen am Rhein; Group: DE; Unemployment (%): 5.531; Offences per 100k: 3878.8301510263786
Hammelburg; Group: DE; Unemployment (%): 4.626; Offences per 100k: 3060.2286233319483
Bergisch Gladbach; Group: DE; Unemployment (%): 6.441; Offences per 100k: 5755.370140244985
Neustadt b.Coburg; Group: DE; Unemployment (%): 6.7; Offences per 100k: 2886.300137330113
Amöneburg; Group: DE; Unemployment (%): 4.6; Offences per 100k: 4567.451246885361
Schortens; Group: DE; Unemployment (%): 4.86; Offences per 100k: 4524.404696696577
Dorsten; Group: DE; Unemployment (%): 5.161; Offences per 100k: 7279.033646920595
Detmold; Group: DE; Unemployment (%): 6.823; Offences per 100k: 4645.267594030229
Fulda; Group: DE; Unemployment (%): 6.134; Offences per 100k: 4424.98976529919
Frankfurt Oder; Group: DE; Unemployment (%): 8.016; Offences per 100k: 14302.975116885846
Menden Sauerland; Group: DE; Unemployment (%): 5.209; Offences per 100k: 5948.1038902476685
Willich; Group: DE; Unemployment (%): 4.065; Offences per 100k: 5596.645370093703
Stadtsteinach; Group: DE; Unemployment (%): 4; Offences per 100k: 3982.2142677367933
Friedland; Group: DE; Unemployment (%): 9; Offences per 100k: 6139.218408723683
Einbeck; Group: DE; Unemployment (%): 5.357; Offences per 100k: 5081.075917626549
Calw; Group: DE; Unemployment (%): 5.613; Offences per 100k: 3041.8416009823195
Breisach am Rhein; Group: DE; Unemployment (%): 5.724; Offences per 100k: 4288.995369792851
Bad Rodach; Group: DE; Unemployment (%): 4.3; Offences per 100k: 2886.300137330113
Pasewalk; Group: DE; Unemployment (%): 9.1; Offences per 100k: 7270.3106385248675
Wunsiedel; Group: DE; Unemployment (%): 5.2; Offences per 100k: 5778.962139789366
Perleberg; Group: DE; Unemployment (%): 8.478; Offences per 100k: 6477.941662808386
Bad Iburg; Group: DE; Unemployment (%): 4.754; Offences per 100k: 4247.775638984164
Burgbernheim; Group: DE; Unemployment (%): 2.7; Offences per 100k: 2540.502558316756
Ohrdruf; Group: DE; Unemployment (%): 5.964; Offences per 100k: 5778.206392909201
Pressath; Group: DE; Unemployment (%): 3.5; Offences per 100k: 4253.0375121031975
Herzberg am Harz; Group: DE; Unemployment (%): 6.349; Offences per 100k: 7124.696672235297
Gunzenhausen; Group: DE; Unemployment (%): 7.378; Offences per 100k: 3019.1667986694124
Möckmühl; Group: DE; Unemployment (%): 3.8; Offences per 100k: 3237.5655948253207
Bad Staffelstein; Group: DE; Unemployment (%): 5.375; Offences per 100k: 3321.5096691847607
Mainbernheim; Group: DE; Unemployment (%): 2.9; Offences per 100k: 3642.358714822483
Müllheim im Markgräflerland; Group: DE; Unemployment (%): 6.869; Offences per 100k: 4288.995369792851
Erbach; Group: DE; Unemployment (%): 4.124; Offences per 100k: 2635.4803957421154
Geisingen; Group: DE; Unemployment (%): 4.4; Offences per 100k: 2924.7699851247867
Friedberg; Group: DE; Unemployment (%): 5.562; Offences per 100k: 2121.29850953561
Falkenstein/Harz; Group: DE; Unemployment (%): 5.4; Offences per 100k: 7499.367347336046
Landau a.d.Isar; Group: DE; Unemployment (%): 14.027; Offences per 100k: 2694.1159004305437
Wiesmoor; Group: DE; Unemployment (%): 6.5; Offences per 100k: 4679.158545885942
Weißenstadt; Group: DE; Unemployment (%): 5.2; Offences per 100k: 5778.962139789366
Kappeln; Group: DE; Unemployment (%): 5.4; Offences per 100k: 4629.827908425479
Querfurt; Group: DE; Unemployment (%): 7.407; Offences per 100k: 6805.662890310275
Oppenheim; Group: DE; Unemployment (%): 5.1; Offences per 100k: 3878.8301510263786
Stadtroda; Group: DE; Unemployment (%): 4.8; Offences per 100k: 5792.997528257061
Bad Säckingen; Group: DE; Unemployment (%): 6.145; Offences per 100k: 4213.802388404175
Braunlage; Group: DE; Unemployment (%): 7.2; Offences per 100k: 6865.706961151646
Braunfels; Group: DE; Unemployment (%): 5.206; Offences per 100k: 3846.517156418996
Staufen im Breisgau; Group: DE; Unemployment (%): 3.4; Offences per 100k: 4288.995369792851
Tambach-Dietharz/Thür. Wald; Group: DE; Unemployment (%): 6.3; Offences per 100k: 5778.206392909201
Volkmarsen; Group: DE; Unemployment (%): 4.5; Offences per 100k: 3392.08127586607
Blaustein; Group: DE; Unemployment (%): 5.204; Offences per 100k: 2635.4803957421154
Rerik; Group: DE; Unemployment (%): 6; Offences per 100k: 4434.41644835201
Plau am See; Group: DE; Unemployment (%): 6.3; Offences per 100k: 5059.781250600696
Krempe; Group: DE; Unemployment (%): 5.7; Offences per 100k: 5110.33594262079
Philippsburg; Group: DE; Unemployment (%): 9.329; Offences per 100k: 3452.387214419722
Kraichtal; Group: DE; Unemployment (%): 3.553; Offences per 100k: 3452.387214419722
Golßen; Group: DE; Unemployment (%): 3.8; Offences per 100k: 10768.877976207123
Kahla; Group: DE; Unemployment (%): 4.8; Offences per 100k: 5792.997528257061
Ransbach-Baumbach; Group: DE; Unemployment (%): 3.7; Offences per 100k: 4358.454882749527
Greußen; Group: DE; Unemployment (%): 8.5; Offences per 100k: 6546.042543700689
Halver; Group: DE; Unemployment (%): 5.735; Offences per 100k: 5948.1038902476685
Bad Soden-Salmünster; Group: DE; Unemployment (%): 6.241; Offences per 100k: 4131.010135086977
Lehesten; Group: DE; Unemployment (%): 6.2; Offences per 100k: 5934.768493082263
Grebenau; Group: DE; Unemployment (%): 4.4; Offences per 100k: 4109.209888991034
Hattersheim am Main; Group: DE; Unemployment (%): 6.899; Offences per 100k: 5038.634697937388
Butzbach; Group: DE; Unemployment (%): 5.305; Offences per 100k: 3848.9311377341596
Bad Wilsnack; Group: DE; Unemployment (%): 8.2; Offences per 100k: 6477.941662808386
Franzburg; Group: DE; Unemployment (%): 9.2; Offences per 100k: 6959.940149533231
Uffenheim; Group: DE; Unemployment (%): 2.7; Offences per 100k: 2540.502558316756
Gößnitz; Group: DE; Unemployment (%): 9.2; Offences per 100k: 6464.551812405723
Peitz/Picnjo; Group: DE; Unemployment (%): 6; Offences per 100k: 7182.013043279974
Schlettau; Group: DE; Unemployment (%): 5.3; Offences per 100k: 3419.976507094983
Elsterwerda; Group: DE; Unemployment (%): 6.6; Offences per 100k: 4695.458674859902
Eschershausen; Group: DE; Unemployment (%): 7.2; Offences per 100k: 5230.1733733855845
Kreuztal; Group: DE; Unemployment (%): 6.399; Offences per 100k: 4809.285083590563
Steinheim an der Murr; Group: DE; Unemployment (%): 4.032; Offences per 100k: 4004.3035336045455
Grünsfeld; Group: DE; Unemployment (%): 3.4; Offences per 100k: 4213.443068582027
Lauterbach (Hessen); Group: DE; Unemployment (%): 3.957; Offences per 100k: 4109.209888991034
Gernsheim; Group: DE; Unemployment (%): 6.227; Offences per 100k: 4368.081696545041
Schöningen; Group: DE; Unemployment (%): 6.667; Offences per 100k: 6502.488168729981
Kelsterbach; Group: DE; Unemployment (%): 9.467; Offences per 100k: 4368.081696545041
Hirschhorn (Neckar); Group: DE; Unemployment (%): 4.5; Offences per 100k: 2765.8123274330796
Hohnstein; Group: DE; Unemployment (%): 5.3; Offences per 100k: 5168.527352907425
Rastatt; Group: DE; Unemployment (%): 6.715; Offences per 100k: 4251.5938059348955
Alsdorf; Group: DE; Unemployment (%): 7.202; Offences per 100k: 8280.592709603201
Wettin-Löbejün; Group: DE; Unemployment (%): 6.6; Offences per 100k: 6805.662890310275
Bietigheim-Bissingen; Group: DE; Unemployment (%): 4.825; Offences per 100k: 4004.3035336045455
Hartha; Group: DE; Unemployment (%): 5.5; Offences per 100k: 4161.50807439168
Zirndorf; Group: DE; Unemployment (%): 4.387; Offences per 100k: 3137.9811245423425
Owen; Group: DE; Unemployment (%): 4; Offences per 100k: 4300.02925823843
Wittichenau / Kulow; Group: DE; Unemployment (%): 6.2; Offences per 100k: 4501.92749343832
Dornstetten; Group: DE; Unemployment (%): 3.9; Offences per 100k: 3185.522884927598
Aichtal; Group: DE; Unemployment (%): 4; Offences per 100k: 4300.02925823843
St. Georgen im Schwarzwald; Group: DE; Unemployment (%): 4.368; Offences per 100k: 3454.0910471118586
Hockenheim; Group: DE; Unemployment (%): 4.816; Offences per 100k: 3903.96035527006
Middelfart; Group: DK; Unemployment (%): 2.4; Offences per 100k: 5863.39
Esbjerg; Group: DK; Unemployment (%): 2.4; Offences per 100k: 7110.12245
Guldborgsund; Group: DK; Unemployment (%): 2.8; Offences per 100k: 7074.123753
Ishøj; Group: DK; Unemployment (%): 4.6; Offences per 100k: 8575.400963
Nordfyns; Group: DK; Unemployment (%): 3.3; Offences per 100k: 5577.115423
Skive; Group: DK; Unemployment (%): 1.6; Offences per 100k: 5234.282714
Vesthimmerlands; Group: DK; Unemployment (%): 2.5; Offences per 100k: 4962.795424
Lüganuse vald; Group: EE; Unemployment (%): 4.501368; Offences per 100k: 3080
Tõrva vald; Group: EE; Unemployment (%): 3.298581; Offences per 100k: 1980
Rapla vald; Group: EE; Unemployment (%): 2.966039; Offences per 100k: 1520
Doña Mencía; Group: ES; Unemployment (%): 2.27; Offences per 100k: 4750
Oria; Group: ES; Unemployment (%): 0.4; Offences per 100k: 4750
Madrid; Group: ES; Unemployment (%): 8.83; Offences per 100k: 6953.14
Alcorcón; Group: ES; Unemployment (%): 3.9; Offences per 100k: 4021.89
Cambre; Group: ES; Unemployment (%): 4.15; Offences per 100k: 3163.71
Pulpí; Group: ES; Unemployment (%): 2.24; Offences per 100k: 4750
Premià de Mar; Group: ES; Unemployment (%): 8.81; Offences per 100k: 4815.03
Sabadell; Group: ES; Unemployment (%): 10.5; Offences per 100k: 4803.83
Arboç, L'; Group: ES; Unemployment (%): 5.07; Offences per 100k: 6350
Vielha e Mijaran; Group: ES; Unemployment (%): 1.06; Offences per 100k: 6350
Calasparra; Group: ES; Unemployment (%): 4.41; Offences per 100k: 4740
Castell d'Aro, Platja d'Aro i s'Agaró; Group: ES; Unemployment (%): 2.17; Offences per 100k: 6350
Cerceda; Group: ES; Unemployment (%): 2.66; Offences per 100k: 3540
Manlleu; Group: ES; Unemployment (%): 5.04; Offences per 100k: 2018.92
Cerdanyola del Vallès; Group: ES; Unemployment (%): 3.43; Offences per 100k: 3543.89
Albox; Group: ES; Unemployment (%): 5.2; Offences per 100k: 4750
Hernani; Group: ES; Unemployment (%): 3.87; Offences per 100k: 3571.6
Astillero, El; Group: ES; Unemployment (%): 4.6; Offences per 100k: 4310
Avilés; Group: ES; Unemployment (%): 11.17; Offences per 100k: 3097.5
Llagosta, La; Group: ES; Unemployment (%): 4.66; Offences per 100k: 6350
Vilanova del Vallès; Group: ES; Unemployment (%): 2.93; Offences per 100k: 6350
Abrera; Group: ES; Unemployment (%): 3.02; Offences per 100k: 6350
Sant Boi de Llobregat; Group: ES; Unemployment (%): 8.84; Offences per 100k: 5080.69
Zamora; Group: ES; Unemployment (%): 15.19; Offences per 100k: 3429.91
Guitiriz; Group: ES; Unemployment (%): 2.68; Offences per 100k: 3540
Caudete; Group: ES; Unemployment (%): 6.54; Offences per 100k: 4120
Alameda; Group: ES; Unemployment (%): 3.91; Offences per 100k: 4750
Pilas; Group: ES; Unemployment (%): 5.77; Offences per 100k: 4750
Navalcarnero; Group: ES; Unemployment (%): 4.31; Offences per 100k: 4604.84
Olivares; Group: ES; Unemployment (%): 7.37; Offences per 100k: 4750
Arroyo de la Luz; Group: ES; Unemployment (%): 5.9; Offences per 100k: 3460
Herencia; Group: ES; Unemployment (%): 6.62; Offences per 100k: 4120
Abanilla; Group: ES; Unemployment (%): 4.28; Offences per 100k: 4740
Sevilla la Nueva; Group: ES; Unemployment (%): 4.01; Offences per 100k: 5490
Torreperogil; Group: ES; Unemployment (%): 5; Offences per 100k: 4750
Villalbilla; Group: ES; Unemployment (%): 2.95; Offences per 100k: 5490
Arroyo de la Encomienda; Group: ES; Unemployment (%): 3.04; Offences per 100k: 6439.73
Santpedor; Group: ES; Unemployment (%): 2.34; Offences per 100k: 6350
Yebes; Group: ES; Unemployment (%): 3.97; Offences per 100k: 4120
Muro de Alcoy; Group: ES; Unemployment (%): 6.11; Offences per 100k: 5330
Morata de Tajuña; Group: ES; Unemployment (%): 5.17; Offences per 100k: 5490
Alcúdia de Crespins, l'; Group: ES; Unemployment (%): 5.79; Offences per 100k: 5330
Mejorada del Campo; Group: ES; Unemployment (%): 4.36; Offences per 100k: 4951.54
Castelló; Group: ES; Unemployment (%): 3.93; Offences per 100k: 5330
Paterna; Group: ES; Unemployment (%): 5.56; Offences per 100k: 4467.94
Linares; Group: ES; Unemployment (%): 27.59; Offences per 100k: 3240.98
Villa del Prado; Group: ES; Unemployment (%): 4.61; Offences per 100k: 5490
Porcuna; Group: ES; Unemployment (%): 1.79; Offences per 100k: 4750
Palacios y Villafranca, Los; Group: ES; Unemployment (%): 6.47; Offences per 100k: 3885.75
Eivissa; Group: ES; Unemployment (%): 7.04; Offences per 100k: 8593.18
Alcobendas; Group: ES; Unemployment (%): 3; Offences per 100k: 4523.25
Getxo; Group: ES; Unemployment (%): 3.59; Offences per 100k: 3392.95
Manacor; Group: ES; Unemployment (%): 2.01; Offences per 100k: 4715.66
Lucena; Group: ES; Unemployment (%): 5.99; Offences per 100k: 5602.654
Soto del Real; Group: ES; Unemployment (%): 3.34; Offences per 100k: 5490
Armilla; Group: ES; Unemployment (%): 22.02; Offences per 100k: 7163.94
Santiponce; Group: ES; Unemployment (%): 7.49; Offences per 100k: 4750
Maracena; Group: ES; Unemployment (%): 7.29; Offences per 100k: 4114.75
Muro; Group: ES; Unemployment (%): 1.29; Offences per 100k: 6580
Rojales; Group: ES; Unemployment (%): 2.91; Offences per 100k: 5330
Vegas del Genil; Group: ES; Unemployment (%): 6.17; Offences per 100k: 4750
Villanueva del Río y Minas; Group: ES; Unemployment (%): 7.59; Offences per 100k: 4750
Arenas de San Pedro; Group: ES; Unemployment (%): 5.82; Offences per 100k: 4030
Becerril de la Sierra; Group: ES; Unemployment (%): 4.42; Offences per 100k: 5490
Navia; Group: ES; Unemployment (%): 2.83; Offences per 100k: 3570
Cantillana; Group: ES; Unemployment (%): 5.44; Offences per 100k: 4750
Balaguer; Group: ES; Unemployment (%): 5.13; Offences per 100k: 6350
Carreño; Group: ES; Unemployment (%): 3.65; Offences per 100k: 3570
Baiona; Group: ES; Unemployment (%): 3.79; Offences per 100k: 3540
Ràpita, La; Group: ES; Unemployment (%): 3.72; Offences per 100k: 6350
Posadas; Group: ES; Unemployment (%): 5.36; Offences per 100k: 4750
Ribadeo; Group: ES; Unemployment (%): 3.49; Offences per 100k: 3540
Bunyola; Group: ES; Unemployment (%): 1.74; Offences per 100k: 6580
San Roque; Group: ES; Unemployment (%): 7.38; Offences per 100k: 5095.06
Binéfar; Group: ES; Unemployment (%): 2.78; Offences per 100k: 4120
Urretxu; Group: ES; Unemployment (%): 4; Offences per 100k: 4850
Chinchón; Group: ES; Unemployment (%): 5.22; Offences per 100k: 5490
Laracha, A; Group: ES; Unemployment (%): 2.51; Offences per 100k: 3540
Yecla; Group: ES; Unemployment (%): 5.2; Offences per 100k: 2728.26
Tacoronte; Group: ES; Unemployment (%): 7.04; Offences per 100k: 2824.7
Pilar de la Horadada; Group: ES; Unemployment (%): 3.07; Offences per 100k: 6830.893
Viso del Alcor, El; Group: ES; Unemployment (%): 6.92; Offences per 100k: 4750
Matanza de Acentejo, La; Group: ES; Unemployment (%): 6.67; Offences per 100k: 4800
Escorial, El; Group: ES; Unemployment (%): 3.42; Offences per 100k: 5490
Moratalla; Group: ES; Unemployment (%): 5.44; Offences per 100k: 4740
Tyrnävä; Group: FI; Unemployment (%): 9.6; Offences per 100k: 4234.9
Parkano; Group: FI; Unemployment (%): 11.7; Offences per 100k: 9332.9
Malax; Group: FI; Unemployment (%): 4.5; Offences per 100k: 4469.6
Kiuruvesi; Group: FI; Unemployment (%): 12.7; Offences per 100k: 7953.1
Inari; Group: FI; Unemployment (%): 7.6; Offences per 100k: 7813.4
Asikkala; Group: FI; Unemployment (%): 11.8; Offences per 100k: 6925.1
Mikkeli; Group: FI; Unemployment (%): 12.6; Offences per 100k: 9040.3
Äänekoski; Group: FI; Unemployment (%): 18.1; Offences per 100k: 9075.5
Kauhava; Group: FI; Unemployment (%): 7.7; Offences per 100k: 6299
Kangasala; Group: FI; Unemployment (%): 9; Offences per 100k: 5169.2
Saint-Pourçain-sur-Sioule; Group: FR; Unemployment (%): 9.176122; Offences per 100k: 5263.12519
Nilvange; Group: FR; Unemployment (%): 12.874444; Offences per 100k: 3236.4937400000003
Le Tréport; Group: FR; Unemployment (%): 19.786143; Offences per 100k: 4021.1778499999996
Grigny-sur-Rhône; Group: FR; Unemployment (%): 8.759479; Offences per 100k: 6452.98238
Blendecques; Group: FR; Unemployment (%): 11.345889; Offences per 100k: 4133.78323
Cessy; Group: FR; Unemployment (%): 7.048517; Offences per 100k: 2768.04372
Saint-Genis-Pouilly; Group: FR; Unemployment (%): 10.131832; Offences per 100k: 3636.39772
Commentry; Group: FR; Unemployment (%): 15.364696; Offences per 100k: 3423.5667599999997
Gap; Group: FR; Unemployment (%): 11.657981; Offences per 100k: 4662.06604
Mouans-Sartoux; Group: FR; Unemployment (%): 7.99439; Offences per 100k: 4536.322730000001
Annonay; Group: FR; Unemployment (%): 15.777536; Offences per 100k: 5788.1147900000005
Pamiers; Group: FR; Unemployment (%): 16.633778; Offences per 100k: 7278.48362
Narbonne; Group: FR; Unemployment (%): 18.41875; Offences per 100k: 8246.222130000002
Berre-l'Étang; Group: FR; Unemployment (%): 14.564071; Offences per 100k: 4848.34023
Gardanne; Group: FR; Unemployment (%): 10.082183; Offences per 100k: 7415.709260000001
Peypin; Group: FR; Unemployment (%): 9.47017; Offences per 100k: 4413.632609999999
Saint-Rémy-de-Provence; Group: FR; Unemployment (%): 9.302879; Offences per 100k: 5907.785900000001
Blainville-sur-Orne; Group: FR; Unemployment (%): 10.224381; Offences per 100k: 3390.1081000000004
Mézidon Vallée d'Auge; Group: FR; Unemployment (%): 8.951877; Offences per 100k: 3226.1106999999997
Ruelle-sur-Touvre; Group: FR; Unemployment (%): 12.055883; Offences per 100k: 3916.2467000000006
Saint-Pierre-d'Oléron; Group: FR; Unemployment (%): 15.841638; Offences per 100k: 5580.345420000001
Saint-Pantaléon-de-Larche; Group: FR; Unemployment (%): 8.261996; Offences per 100k: 2661.9139999999998
Talant; Group: FR; Unemployment (%): 15.247037; Offences per 100k: 3343.49551
Saint-Brieuc; Group: FR; Unemployment (%): 14.54744; Offences per 100k: 7474.55596
Bethoncourt; Group: FR; Unemployment (%): 21.419561; Offences per 100k: 4794.566949999999
Étoile-sur-Rhône; Group: FR; Unemployment (%): 6.981171; Offences per 100k: 4979.975329999999
Mesnils-sur-Iton; Group: FR; Unemployment (%): 8.503284; Offences per 100k: 3037.40553
Dreux; Group: FR; Unemployment (%): 20.554732; Offences per 100k: 6829.769179999999
Ergué-Gabéric; Group: FR; Unemployment (%): 6.212698; Offences per 100k: 2370.1913400000003
Plougastel-Daoulas; Group: FR; Unemployment (%): 9.093557; Offences per 100k: 2641.03791
Biguglia; Group: FR; Unemployment (%): 6.331025; Offences per 100k: 2499.34573
Garons; Group: FR; Unemployment (%): 10.49751; Offences per 100k: 4394.88423
Vergèze; Group: FR; Unemployment (%): 10.124725; Offences per 100k: 4520.1055
Eaunes; Group: FR; Unemployment (%): 8.846357; Offences per 100k: 3248.32122
Portet-sur-Garonne; Group: FR; Unemployment (%): 12.158788; Offences per 100k: 7586.81533
Villefranche-de-Lauragais; Group: FR; Unemployment (%): 9.103574; Offences per 100k: 5107.04701
Belin-Béliet; Group: FR; Unemployment (%): 10.114751; Offences per 100k: 2979.35651
Gujan-Mestras; Group: FR; Unemployment (%): 11.052964; Offences per 100k: 3657.0810500000007
Pauillac; Group: FR; Unemployment (%): 19.442961; Offences per 100k: 5429.68648
Marcheprime; Group: FR; Unemployment (%): 8.421743; Offences per 100k: 3444.5155999999997
Frontignan; Group: FR; Unemployment (%): 14.384796; Offences per 100k: 4882.03468
Pézenas; Group: FR; Unemployment (%): 18.387486; Offences per 100k: 8037.960539999999
La Grande-Motte; Group: FR; Unemployment (%): 15.103339; Offences per 100k: 16354.13069
Gévezé; Group: FR; Unemployment (%): 6.22931; Offences per 100k: 3240.64625
Redon; Group: FR; Unemployment (%): 15.852099; Offences per 100k: 6244.81841
Le Poinçonnet; Group: FR; Unemployment (%): 6.502549; Offences per 100k: 2743.74987
Saint-Pierre-des-Corps; Group: FR; Unemployment (%): 19.231771; Offences per 100k: 6683.7634499999995
Eybens; Group: FR; Unemployment (%): 9.263311; Offences per 100k: 7741.835419999999
Saint-Ismier; Group: FR; Unemployment (%): 5.665707; Offences per 100k: 3891.2103899999997
Vienne; Group: FR; Unemployment (%): 11.68102; Offences per 100k: 6143.53935
Dax; Group: FR; Unemployment (%): 16.144281; Offences per 100k: 9647.04743
Mer; Group: FR; Unemployment (%): 13.531694; Offences per 100k: 5271.32471
Roanne; Group: FR; Unemployment (%): 16.70855; Offences per 100k: 6575.29026
Villerest; Group: FR; Unemployment (%): 7.170839; Offences per 100k: 2522.6624699999998
La Chapelle-sur-Erdre; Group: FR; Unemployment (%): 8.352658; Offences per 100k: 4179.39822
Le Loroux-Bottereau; Group: FR; Unemployment (%): 5.238999; Offences per 100k: 2484.27033
Saint-Brevin-les-Pins; Group: FR; Unemployment (%): 8.618231; Offences per 100k: 4708.26444
Les Sorinières; Group: FR; Unemployment (%): 6.712713; Offences per 100k: 4774.38154
Fleury-les-Aubrais; Group: FR; Unemployment (%): 13.906139; Offences per 100k: 6212.286300000001
Villemandeur; Group: FR; Unemployment (%): 13.854913; Offences per 100k: 3924.099149999999
Baugé-en-Anjou; Group: FR; Unemployment (%): 9.193807; Offences per 100k: 3092.0809799999997
Montrevault-sur-Èvre; Group: FR; Unemployment (%): 6.493456; Offences per 100k: 2636.1719200000002
Lys-Haut-Layon; Group: FR; Unemployment (%): 7.672229; Offences per 100k: 2140.4394300000004
Châlons-en-Champagne; Group: FR; Unemployment (%): 15.371551; Offences per 100k: 7292.868019999999
Laval; Group: FR; Unemployment (%): 12.738452; Offences per 100k: 6899.830920000001
Longuyon; Group: FR; Unemployment (%): 16.260915; Offences per 100k: 3574.5770699999994
Vandœuvre-lès-Nancy; Group: FR; Unemployment (%): 17.801604; Offences per 100k: 4916.14154
Hennebont; Group: FR; Unemployment (%): 11.877584; Offences per 100k: 4498.16096
Pontivy; Group: FR; Unemployment (%): 13.688922; Offences per 100k: 5616.121630000001
Fameck; Group: FR; Unemployment (%): 15.703423; Offences per 100k: 3508.60567
Mondelange; Group: FR; Unemployment (%): 11.419646; Offences per 100k: 3981.2380500000004
Cosne-Cours-sur-Loire; Group: FR; Unemployment (%): 15.349425; Offences per 100k: 5055.4832400000005
Bondues; Group: FR; Unemployment (%): 7.318225; Offences per 100k: 5281.63402
Douchy-les-Mines; Group: FR; Unemployment (%): 19.368986; Offences per 100k: 4309.95551
Halluin; Group: FR; Unemployment (%): 12.676581; Offences per 100k: 4767.44765
Lys-lez-Lannoy; Group: FR; Unemployment (%): 12.060681; Offences per 100k: 4599.98519
Petite-Forêt; Group: FR; Unemployment (%): 13.541004; Offences per 100k: 7348.073160000002
Templeuve-en-Pévèle; Group: FR; Unemployment (%): 7.020422; Offences per 100k: 3008.7352199999996
Chambly; Group: FR; Unemployment (%): 10.675518; Offences per 100k: 6460.169679999998
Pont-Sainte-Maxence; Group: FR; Unemployment (%): 15.272627; Offences per 100k: 4960.08205
Avion; Group: FR; Unemployment (%): 18.987591; Offences per 100k: 5271.484990000001
Courcelles-lès-Lens; Group: FR; Unemployment (%): 15.206649; Offences per 100k: 3847.1610999999994
Isbergues; Group: FR; Unemployment (%): 13.031605; Offences per 100k: 3909.84155
Nœux-les-Mines; Group: FR; Unemployment (%): 17.8021; Offences per 100k: 5230.313970000001
Wimereux; Group: FR; Unemployment (%): 10.450625; Offences per 100k: 2783.6783699999996
Lezoux; Group: FR; Unemployment (%): 11.074721; Offences per 100k: 2957.4437000000003
Hendaye; Group: FR; Unemployment (%): 13.111163; Offences per 100k: 5965.533979999999
Bagnères-de-Bigorre; Group: FR; Unemployment (%): 11.983226; Offences per 100k: 7033.06951
Perpignan; Group: FR; Unemployment (%): 22.439923; Offences per 100k: 9926.75147
Brumath; Group: FR; Unemployment (%): 7.943715; Offences per 100k: 3898.94884
Obernai; Group: FR; Unemployment (%): 9.814774; Offences per 100k: 4047.4248099999995
Blotzheim; Group: FR; Unemployment (%): 10.025591; Offences per 100k: 3085.8259
Rixheim; Group: FR; Unemployment (%): 11.596892; Offences per 100k: 3254.66349
Chaponost; Group: FR; Unemployment (%): 6.703409; Offences per 100k: 5222.934209999999
Vindry-sur-Turdine; Group: FR; Unemployment (%): 6.075851; Offences per 100k: 2897.88424
Chassieu; Group: FR; Unemployment (%): 9.02729; Offences per 100k: 7980.97236
Gray; Group: FR; Unemployment (%): 15.147593; Offences per 100k: 7381.293299999998
Montceau-les-Mines; Group: FR; Unemployment (%): 19.668145; Offences per 100k: 5442.52322
Sablé-sur-Sarthe; Group: FR; Unemployment (%): 16.019667; Offences per 100k: 6525.29758
Allinges; Group: FR; Unemployment (%): 7.651608; Offences per 100k: 1764.9320500000001
Marignier; Group: FR; Unemployment (%): 7.115068; Offences per 100k: 2590.82818
Thyez; Group: FR; Unemployment (%): 8.163212; Offences per 100k: 2976.0485400000002
Déville-lès-Rouen; Group: FR; Unemployment (%): 15.019423; Offences per 100k: 4307.30159
Mont-Saint-Aignan; Group: FR; Unemployment (%): 13.030308; Offences per 100k: 5476.51668
Avon; Group: FR; Unemployment (%): 11.853546; Offences per 100k: 4359.4643399999995
Dammarie-les-Lys; Group: FR; Unemployment (%): 14.937701; Offences per 100k: 4913.59965
Mitry-Mory; Group: FR; Unemployment (%): 12.125771; Offences per 100k: 8752.457199999999
Provins; Group: FR; Unemployment (%): 17.961728; Offences per 100k: 8348.279569999999
Villenoy; Group: FR; Unemployment (%): 9.168315; Offences per 100k: 4396.94865
Le Chesnay-Rocquencourt; Group: FR; Unemployment (%): 8.167993; Offences per 100k: 3611.36456
Louveciennes; Group: FR; Unemployment (%): 7.514184; Offences per 100k: 4688.3969
Orgeval; Group: FR; Unemployment (%): 7.78642; Offences per 100k: 5218.87359
Vélizy-Villacoublay; Group: FR; Unemployment (%): 6.44559; Offences per 100k: 5763.3662300000005
Moncoutant-sur-Sèvre; Group: FR; Unemployment (%): 6.412061; Offences per 100k: 2362.81977
Aussillon; Group: FR; Unemployment (%): 16.149504; Offences per 100k: 2850.11545
Nègrepelisse; Group: FR; Unemployment (%): 11.701559; Offences per 100k: 2591.6111899999996
La Farlède; Group: FR; Unemployment (%): 9.664408; Offences per 100k: 6465.64957
Le Pradet; Group: FR; Unemployment (%): 9.032897; Offences per 100k: 4371.82038
Trans-en-Provence; Group: FR; Unemployment (%): 10.936845; Offences per 100k: 4844.64693
Mazan; Group: FR; Unemployment (%): 9.089023; Offences per 100k: 3340.70349
Aubigny-Les Clouzeaux; Group: FR; Unemployment (%): 6.490428; Offences per 100k: 2130.8481699999998
Mouilleron-le-Captif; Group: FR; Unemployment (%): 5.740532; Offences per 100k: 2271.3427199999996
Migné-Auxances; Group: FR; Unemployment (%): 8.014594; Offences per 100k: 3032.1524
Panazol; Group: FR; Unemployment (%): 9.686311; Offences per 100k: 2696.5917700000005
Sens; Group: FR; Unemployment (%): 20.430716; Offences per 100k: 6777.17482
Crosne; Group: FR; Unemployment (%): 8.876336; Offences per 100k: 3895.88306
Limours; Group: FR; Unemployment (%): 6.200552; Offences per 100k: 3498.4893500000007
Paray-Vieille-Poste; Group: FR; Unemployment (%): 8.94828; Offences per 100k: 5285.62923
Villebon-sur-Yvette; Group: FR; Unemployment (%): 8.195252; Offences per 100k: 5572.055010000001
Clamart; Group: FR; Unemployment (%): 9.292606; Offences per 100k: 5276.30415
Puteaux; Group: FR; Unemployment (%): 9.393803; Offences per 100k: 11937.951860000001
Le Bourget; Group: FR; Unemployment (%): 17.120632; Offences per 100k: 7300.39814
Noisy-le-Grand; Group: FR; Unemployment (%): 12.204388; Offences per 100k: 6242.764359999999
Villetaneuse; Group: FR; Unemployment (%): 19.49758; Offences per 100k: 6184.47366
Gentilly; Group: FR; Unemployment (%): 12.52602; Offences per 100k: 5260.6355300000005
Saint-Maurice; Group: FR; Unemployment (%): 10.483889; Offences per 100k: 4900.256909999999
Bessancourt; Group: FR; Unemployment (%): 8.27096; Offences per 100k: 3988.1271699999993
Franconville; Group: FR; Unemployment (%): 11.556597; Offences per 100k: 4236.32021
Montmagny; Group: FR; Unemployment (%): 12.607014; Offences per 100k: 5575.3398
Taverny; Group: FR; Unemployment (%): 10.166998; Offences per 100k: 4627.037130000001
Vasilikón; Group: GR; Unemployment (%): 13.517; Offences per 100k: 1825.430627
Rethymno; Group: GR; Unemployment (%): 10.271; Offences per 100k: 1711.09977
Palaió Fáliro; Group: GR; Unemployment (%): 11.991; Offences per 100k: 3126.1903026367236
Néa Artáki; Group: GR; Unemployment (%): 12.513; Offences per 100k: 1825.430627
Megalópoli; Group: GR; Unemployment (%): 18.846; Offences per 100k: 2291.534776
Kos; Group: GR; Unemployment (%): 8.341; Offences per 100k: 2444.073435
Karpenísi; Group: GR; Unemployment (%): 15.451; Offences per 100k: 1825.430627
Igoumenítsa; Group: GR; Unemployment (%): 14.929; Offences per 100k: 1296.052286
Ekáli; Group: GR; Unemployment (%): 6.564; Offences per 100k: 2926.701365
Asíni; Group: GR; Unemployment (%): 12.015; Offences per 100k: 2291.534776
Almyrós; Group: GR; Unemployment (%): 12.783; Offences per 100k: 1243.71339
Véroia; Group: GR; Unemployment (%): 16.635; Offences per 100k: 1389.023643
Platý; Group: GR; Unemployment (%): 22.156; Offences per 100k: 1389.023643
Litóchoro; Group: GR; Unemployment (%): 15.678; Offences per 100k: 1389.023643
Fíliro; Group: GR; Unemployment (%): 13.725; Offences per 100k: 2414.583262
Alexándreia; Group: GR; Unemployment (%): 21.845; Offences per 100k: 1389.023643
Patras; Group: GR; Unemployment (%): 18.133523194041295; Offences per 100k: 2022.8108534805192
Tatabánya; Group: HU; Unemployment (%): 3.6252122009; Offences per 100k: 324.46485
Szentgotthárd; Group: HU; Unemployment (%): 2.8053204353; Offences per 100k: 1568.009511
Sárbogárd; Group: HU; Unemployment (%): 4.4648829431; Offences per 100k: 1743.827677
Őrbottyán; Group: HU; Unemployment (%): 4.5701357466; Offences per 100k: 1557.179145
Maglód; Group: HU; Unemployment (%): 3.7823683445; Offences per 100k: 1557.179145
Kisbér; Group: HU; Unemployment (%): 2.8782028782; Offences per 100k: 1491.335352
Hatvan; Group: HU; Unemployment (%): 4.749953523; Offences per 100k: 2461.680059
Dunavarsány; Group: HU; Unemployment (%): 3.4195162636; Offences per 100k: 1557.179145
Cegléd; Group: HU; Unemployment (%): 4.414390046; Offences per 100k: 1557.179145
Baja; Group: HU; Unemployment (%): 4.7604590443; Offences per 100k: 1970.127746
Tiszaújváros; Group: HU; Unemployment (%): 4.0665434381; Offences per 100k: 1877.474723
Sándorfalva; Group: HU; Unemployment (%): 4.216011369; Offences per 100k: 3139.348528
Nagyecsed; Group: HU; Unemployment (%): 8.8750913075; Offences per 100k: 1838.052371
Kondoros; Group: HU; Unemployment (%): 4.2764578834; Offences per 100k: 1885.956915
Hajdúszoboszló; Group: HU; Unemployment (%): 5.3770889254; Offences per 100k: 1212.776061
Egyek; Group: HU; Unemployment (%): 8.6880973067; Offences per 100k: 1212.776061
Abony; Group: HU; Unemployment (%): 5.1814203021; Offences per 100k: 1557.179145
Carrigaline; Group: IE; Unemployment (%): 5.5; Offences per 100k: 4380.5
Trim; Group: IE; Unemployment (%): 7.9; Offences per 100k: 4566
Wicklow; Group: IE; Unemployment (%): 9.3; Offences per 100k: 4566
Balbriggan; Group: IE; Unemployment (%): 11; Offences per 100k: 7773.6
Monasterevin; Group: IE; Unemployment (%): 9.1; Offences per 100k: 4566
Linguaglossa; Group: IT; Unemployment (%): 12.9074616943931; Offences per 100k: 3976.5
Almese; Group: IT; Unemployment (%): 6.00752877340521; Offences per 100k: 5866.3
Castiglione Torinese; Group: IT; Unemployment (%): 5.30879561897133; Offences per 100k: 5866.3
Luserna San Giovanni; Group: IT; Unemployment (%): 8.12009471879148; Offences per 100k: 5866.3
San Maurizio Canavese; Group: IT; Unemployment (%): 4.94303059533742; Offences per 100k: 5866.3
Gattinara; Group: IT; Unemployment (%): 4.72937303081166; Offences per 100k: 2830.4
Romentino; Group: IT; Unemployment (%): 5.43326338800613; Offences per 100k: 3554
Ceva; Group: IT; Unemployment (%): 5.5891406445452; Offences per 100k: 2489.3
Nizza Monferrato; Group: IT; Unemployment (%): 6.29741971760594; Offences per 100k: 3048.9
Imperia; Group: IT; Unemployment (%): 7.12857004264296; Offences per 100k: 4764.3
Quiliano; Group: IT; Unemployment (%): 4.7801246774091; Offences per 100k: 4333.4
Sant'Olcese; Group: IT; Unemployment (%): 4.23030941927335; Offences per 100k: 4865
Arcisate; Group: IT; Unemployment (%): 11.3774607031924; Offences per 100k: 3777.9
Ferno; Group: IT; Unemployment (%): 5.17885989096727; Offences per 100k: 3777.9
Origgio; Group: IT; Unemployment (%): 3.94907367274578; Offences per 100k: 3777.9
Appiano Gentile; Group: IT; Unemployment (%): 5.46121493181781; Offences per 100k: 3085.6
Inverigo; Group: IT; Unemployment (%): 4.14517636000186; Offences per 100k: 3085.6
Uggiate con Ronago; Group: IT; Unemployment (%): 9.49727796516372; Offences per 100k: 3085.6
Bresso; Group: IT; Unemployment (%): 5.98619092441505; Offences per 100k: 6989
Cinisello Balsamo; Group: IT; Unemployment (%): 6.54504500225245; Offences per 100k: 6989
Lacchiarella; Group: IT; Unemployment (%): 5.38316269439856; Offences per 100k: 6989
Pantigliate; Group: IT; Unemployment (%): 4.45537613656732; Offences per 100k: 6989
Rozzano; Group: IT; Unemployment (%): 6.53388741580016; Offences per 100k: 6989
Truccazzano; Group: IT; Unemployment (%): 4.4344307337617; Offences per 100k: 6989
Almenno San Salvatore; Group: IT; Unemployment (%): 3.69679048630284; Offences per 100k: 3415.1
Calusco d'Adda; Group: IT; Unemployment (%): 5.55566474571751; Offences per 100k: 3415.1
Gorlago; Group: IT; Unemployment (%): 4.59265641099573; Offences per 100k: 3415.1
Romano di Lombardia; Group: IT; Unemployment (%): 5.79138523992426; Offences per 100k: 3415.1
Verdellino; Group: IT; Unemployment (%): 7.55391719242493; Offences per 100k: 3415.1
Calvisano; Group: IT; Unemployment (%): 3.8502364154906; Offences per 100k: 3527.3
Desenzano del Garda; Group: IT; Unemployment (%): 5.87173356659449; Offences per 100k: 3527.3
Montichiari; Group: IT; Unemployment (%): 4.81202582641917; Offences per 100k: 3527.3
Rezzato; Group: IT; Unemployment (%): 4.8460621032578; Offences per 100k: 3527.3
Belgioioso; Group: IT; Unemployment (%): 5.78338762847613; Offences per 100k: 4101.9
Rivanazzano Terme; Group: IT; Unemployment (%): 5.95103814688574; Offences per 100k: 4101.9
Pandino; Group: IT; Unemployment (%): 4.66956529895676; Offences per 100k: 2885.3
Marcaria; Group: IT; Unemployment (%): 3.69151166702156; Offences per 100k: 3079
Volta Mantovana; Group: IT; Unemployment (%): 3.37341979716576; Offences per 100k: 3079
Malles Venosta; Group: IT; Unemployment (%): 2.89854051542348; Offences per 100k: 3362.8
Lavis; Group: IT; Unemployment (%): 3.75555842054345; Offences per 100k: 2952.9
Bovolone; Group: IT; Unemployment (%): 4.87463670641533; Offences per 100k: 4150.9
Lavagno; Group: IT; Unemployment (%): 3.9271402590867; Offences per 100k: 4150.9
Sant'Ambrogio di Valpolicella; Group: IT; Unemployment (%): 4.68411762464426; Offences per 100k: 4150.9
Bassano del Grappa; Group: IT; Unemployment (%): 4.9385745140607; Offences per 100k: 3278.9
Malo; Group: IT; Unemployment (%): 4.10490664112318; Offences per 100k: 3278.9
Sarcedo; Group: IT; Unemployment (%): 4.05038603561224; Offences per 100k: 3278.9
Belluno; Group: IT; Unemployment (%): 3.35306045182556; Offences per 100k: 2511.3
Casale sul Sile; Group: IT; Unemployment (%): 3.69346436181613; Offences per 100k: 2351.9
Loria; Group: IT; Unemployment (%): 3.97404465445234; Offences per 100k: 2351.9
Quinto di Treviso; Group: IT; Unemployment (%): 5.36477878809844; Offences per 100k: 2351.9
Treviso; Group: IT; Unemployment (%): 5.92; Offences per 100k: 2351.9
Concordia Sagittaria; Group: IT; Unemployment (%): 4.78058963220032; Offences per 100k: 4984.6
Portogruaro; Group: IT; Unemployment (%): 5.60612201809878; Offences per 100k: 4984.6
Brugine; Group: IT; Unemployment (%): 5.37305064155642; Offences per 100k: 3795.1
Legnaro; Group: IT; Unemployment (%): 4.39493846746869; Offences per 100k: 3795.1
Rubano; Group: IT; Unemployment (%): 4.61643892895311; Offences per 100k: 3795.1
Villa del Conte; Group: IT; Unemployment (%): 4.27929404358508; Offences per 100k: 3795.1
Campoformido; Group: IT; Unemployment (%): 4.50260207118194; Offences per 100k: 2980.5
Pozzuolo del Friuli; Group: IT; Unemployment (%): 4.68821751241926; Offences per 100k: 2980.5
Monfalcone; Group: IT; Unemployment (%): 5.97214885655827; Offences per 100k: 3293.3
Piacenza; Group: IT; Unemployment (%): 4.4; Offences per 100k: 3540.1
Lesignano de' Bagni; Group: IT; Unemployment (%): 3.56892619070637; Offences per 100k: 4213.8
Brescello; Group: IT; Unemployment (%): 4.70930314321799; Offences per 100k: 3924.8
Novellara; Group: IT; Unemployment (%): 5.74422769719618; Offences per 100k: 3924.8
Castelvetro di Modena; Group: IT; Unemployment (%): 3.82186158337867; Offences per 100k: 4293.8
San Felice sul Panaro; Group: IT; Unemployment (%): 5.25866085295101; Offences per 100k: 4293.8
Castello d'Argile; Group: IT; Unemployment (%): 4.68974467964037; Offences per 100k: 6108.1
Monte San Pietro; Group: IT; Unemployment (%): 5.4067807005237; Offences per 100k: 6108.1
Argenta; Group: IT; Unemployment (%): 6.39477069674775; Offences per 100k: 4290.5
Alfonsine; Group: IT; Unemployment (%): 5.53119260489603; Offences per 100k: 4071.4
Castrocaro Terme e Terra del Sole; Group: IT; Unemployment (%): 4.71929693620548; Offences per 100k: 3643.7
Fermignano; Group: IT; Unemployment (%): 4.81788825242439; Offences per 100k: 2664.7
Chiaravalle; Group: IT; Unemployment (%): 6.03873450370377; Offences per 100k: 2662.9
Civitanova Marche; Group: IT; Unemployment (%): 7.24026996423179; Offences per 100k: 2630.3
Castel di Lama; Group: IT; Unemployment (%): 5.95641979956018; Offences per 100k: 2922.8
Borgo a Mozzano; Group: IT; Unemployment (%): 5.29986251661058; Offences per 100k: 3752
Massa e Cozzile; Group: IT; Unemployment (%): 7.75921492053023; Offences per 100k: 3410.7
Campi Bisenzio; Group: IT; Unemployment (%): 5.15646858678046; Offences per 100k: 6566.8
Pontassieve; Group: IT; Unemployment (%): 5.08266535345959; Offences per 100k: 6566.8
Cecina; Group: IT; Unemployment (%): 7.28609221043227; Offences per 100k: 4900.4
Pomarance; Group: IT; Unemployment (%): 5.27618749088511; Offences per 100k: 4293.7
Capolona; Group: IT; Unemployment (%): 4.63530462108134; Offences per 100k: 3244.6
Laterina Pergine Valdarno; Group: IT; Unemployment (%): 4.93263564414318; Offences per 100k: 3244.6
Torrita di Siena; Group: IT; Unemployment (%): 5.02874853610245; Offences per 100k: 3041.7
Città di Castello; Group: IT; Unemployment (%): 4.72666111137393; Offences per 100k: 3554.6
Spoleto; Group: IT; Unemployment (%): 6.58117102504689; Offences per 100k: 3554.6
Montefiascone; Group: IT; Unemployment (%): 7.25411056932575; Offences per 100k: 3079.2
Anguillara Sabazia; Group: IT; Unemployment (%): 10.0235232385305; Offences per 100k: 6434.1
Frascati; Group: IT; Unemployment (%): 8.44799917199498; Offences per 100k: 6434.1
Morlupo; Group: IT; Unemployment (%): 10.3958117443939; Offences per 100k: 6434.1
Trevignano Romano; Group: IT; Unemployment (%): 10.2967253522875; Offences per 100k: 6434.1
Gaeta; Group: IT; Unemployment (%): 12.2044842416784; Offences per 100k: 3658.7
Arce; Group: IT; Unemployment (%): 9.87119466395598; Offences per 100k: 2620.3
Sant'Elia Fiumerapido; Group: IT; Unemployment (%): 9.94076527442226; Offences per 100k: 2620.3
Casaluce; Group: IT; Unemployment (%): 13.8162419685461; Offences per 100k: 3435.6
Piedimonte Matese; Group: IT; Unemployment (%): 9.83185369748194; Offences per 100k: 3435.6
Teano; Group: IT; Unemployment (%): 10.6648574569; Offences per 100k: 3435.6
Telese Terme; Group: IT; Unemployment (%): 9.26939407950794; Offences per 100k: 2234
Casalnuovo di Napoli; Group: IT; Unemployment (%): 12.9635419164129; Offences per 100k: 4489.4
Grumo Nevano; Group: IT; Unemployment (%): 13.3882715384238; Offences per 100k: 4489.4
Pimonte; Group: IT; Unemployment (%): 13.6105625638577; Offences per 100k: 4489.4
Sant'Agnello; Group: IT; Unemployment (%): 9.37796347093067; Offences per 100k: 4489.4
Santa Maria la Carità; Group: IT; Unemployment (%): 11.5883060017604; Offences per 100k: 4489.4
Serino; Group: IT; Unemployment (%): 11.8986615308532; Offences per 100k: 2706.4
Castel San Giorgio; Group: IT; Unemployment (%): 10.3439826615249; Offences per 100k: 3247.1
Polla; Group: IT; Unemployment (%): 9.38914041049918; Offences per 100k: 3247.1
Vietri sul Mare; Group: IT; Unemployment (%): 12.0923591367967; Offences per 100k: 3247.1
Corropoli; Group: IT; Unemployment (%): 7.91998923601971; Offences per 100k: 3244.3
Collecorvino; Group: IT; Unemployment (%): 9.19778602128414; Offences per 100k: 3728.4
Ortona; Group: IT; Unemployment (%): 8.15964525420684; Offences per 100k: 2851.8
Foggia; Group: IT; Unemployment (%): 11.83; Offences per 100k: 3913.3
Vico del Gargano; Group: IT; Unemployment (%): 13.5324536880802; Offences per 100k: 3913.3
Corato; Group: IT; Unemployment (%): 11.741681461276; Offences per 100k: 3341.2
Ruvo di Puglia; Group: IT; Unemployment (%): 9.95849489047488; Offences per 100k: 3341.2
Leporano; Group: IT; Unemployment (%): 12.4721194013082; Offences per 100k: 2809.2
Brindisi; Group: IT; Unemployment (%): 14.15; Offences per 100k: 2802.6
San Vito dei Normanni; Group: IT; Unemployment (%): 11.794003980992; Offences per 100k: 2802.6
Corigliano d'Otranto; Group: IT; Unemployment (%): 10.3348944054997; Offences per 100k: 2813.2
Monteroni di Lecce; Group: IT; Unemployment (%): 12.3431984864296; Offences per 100k: 2813.2
Taurisano; Group: IT; Unemployment (%): 10.4499179937484; Offences per 100k: 2813.2
Picerno; Group: IT; Unemployment (%): 11.33772903116; Offences per 100k: 1994.9
Scanzano Jonico; Group: IT; Unemployment (%): 9.27833880874048; Offences per 100k: 2668.6
Paola; Group: IT; Unemployment (%): 13.9317961923835; Offences per 100k: 2458.1
Borgia; Group: IT; Unemployment (%): 11.2670151938072; Offences per 100k: 3338.3
Cittanova; Group: IT; Unemployment (%): 10.9238145018335; Offences per 100k: 2824.8
Villa San Giovanni; Group: IT; Unemployment (%): 11.9273147813748; Offences per 100k: 2824.8
Petrosino; Group: IT; Unemployment (%): 14.641299999013; Offences per 100k: 3052.1
Corleone; Group: IT; Unemployment (%): 13.8066945373268; Offences per 100k: 3945.9
Trabia; Group: IT; Unemployment (%): 17.2803125790349; Offences per 100k: 3945.9
Taormina; Group: IT; Unemployment (%): 11.9578677675469; Offences per 100k: 2665.8
Menfi; Group: IT; Unemployment (%): 14.4860163594696; Offences per 100k: 2475.7
Niscemi; Group: IT; Unemployment (%): 14.8688793273365; Offences per 100k: 2952.9
Aci Catena; Group: IT; Unemployment (%): 16.6216968091591; Offences per 100k: 3976.5
Mascalucia; Group: IT; Unemployment (%): 12.9058991165458; Offences per 100k: 3976.5
Santa Venerina; Group: IT; Unemployment (%): 14.8848664441408; Offences per 100k: 3976.5
Santa Croce Camerina; Group: IT; Unemployment (%): 12.3446720913028; Offences per 100k: 2857
Solarino; Group: IT; Unemployment (%): 15.9703588009003; Offences per 100k: 3895.5
Roveredo in Piano; Group: IT; Unemployment (%): 4.43614202735082; Offences per 100k: 2405.5
Casatenovo; Group: IT; Unemployment (%): 4.30210613995203; Offences per 100k: 2901.6
Lodi; Group: IT; Unemployment (%): 5.36049691269106; Offences per 100k: 3121.4
Verucchio; Group: IT; Unemployment (%): 7.02224985054061; Offences per 100k: 6041.9
Petilia Policastro; Group: IT; Unemployment (%): 6.18736918970904; Offences per 100k: 2861.6
Agrate Brianza; Group: IT; Unemployment (%): 4.93932189761178; Offences per 100k: 3641.3
Cogliate; Group: IT; Unemployment (%): 4.59827381090456; Offences per 100k: 3641.3
Seveso; Group: IT; Unemployment (%): 5.22952375548703; Offences per 100k: 3641.3
Monte Urano; Group: IT; Unemployment (%): 5.9551225133085; Offences per 100k: 3185.7
Ittiri; Group: IT; Unemployment (%): 9.90610976646309; Offences per 100k: 3124.6
Nuoro; Group: IT; Unemployment (%): 8.94298666932144; Offences per 100k: 2437.6
Assemini; Group: IT; Unemployment (%): 11.1441964734261; Offences per 100k: 2794.1
Uta; Group: IT; Unemployment (%): 11.3412367927845; Offences per 100k: 2794.1
Motobu; Group: JP; Unemployment (%): 5.62; Offences per 100k: 728.3
Tōon; Group: JP; Unemployment (%): 3.235; Offences per 100k: 544.4
Kunitachi; Group: JP; Unemployment (%): 3.66; Offences per 100k: 700.7
Nanyō; Group: JP; Unemployment (%): 3.192; Offences per 100k: 315.6
Aki-takata; Group: JP; Unemployment (%): 2.34; Offences per 100k: 542.9
Miyawaka; Group: JP; Unemployment (%): 4.564; Offences per 100k: 757.6
Gotō; Group: JP; Unemployment (%): 3.493; Offences per 100k: 336.2
Kōshū; Group: JP; Unemployment (%): 3.068; Offences per 100k: 416.2
Tamba-Sasayama; Group: JP; Unemployment (%): 2.803; Offences per 100k: 747.6
Shōwa; Group: JP; Unemployment (%): 4.617; Offences per 100k: 416.2
Yoshino-chō; Group: JP; Unemployment (%): 4.505; Offences per 100k: 487.5
Yamakita; Group: JP; Unemployment (%): 3.919; Offences per 100k: 542.6
Urayasu; Group: JP; Unemployment (%): 3.03; Offences per 100k: 655.337823
Tsu; Group: JP; Unemployment (%): 3.186; Offences per 100k: 624.9
Toki; Group: JP; Unemployment (%): 3.318; Offences per 100k: 670.5
Tamano; Group: JP; Unemployment (%): 3.665; Offences per 100k: 560.7
Takahama; Group: JP; Unemployment (%): 1.977; Offences per 100k: 443.3
Sugito; Group: JP; Unemployment (%): 3.94; Offences per 100k: 729.3
Shimoda; Group: JP; Unemployment (%): 3.792; Offences per 100k: 506.3
Sasaguri; Group: JP; Unemployment (%): 5.219; Offences per 100k: 757.6
Sabae; Group: JP; Unemployment (%): 2.533; Offences per 100k: 443.3
Ōme; Group: JP; Unemployment (%): 4.442; Offences per 100k: 1732.130153
Odawara; Group: JP; Unemployment (%): 3.678; Offences per 100k: 577.159317
Nishihara; Group: JP; Unemployment (%): 5.336; Offences per 100k: 728.3
Nakanojō; Group: JP; Unemployment (%): 3.309; Offences per 100k: 808.6
Murakami; Group: JP; Unemployment (%): 3.462; Offences per 100k: 462.5
Minano; Group: JP; Unemployment (%): 4.519; Offences per 100k: 729.3
Maizuru; Group: JP; Unemployment (%): 3.144; Offences per 100k: 492
Kotohira; Group: JP; Unemployment (%): 3.999; Offences per 100k: 690.7
Kiyosu; Group: JP; Unemployment (%): 3.274; Offences per 100k: 757.6
Kawaguchi; Group: JP; Unemployment (%): 3.965; Offences per 100k: 743.259843
Kanoya; Group: JP; Unemployment (%): 3.798; Offences per 100k: 551
Kagoshima; Group: JP; Unemployment (%): 4.136; Offences per 100k: 551
Itami; Group: JP; Unemployment (%): 4.181; Offences per 100k: 778.245465
Iiyama; Group: JP; Unemployment (%): 2.96; Offences per 100k: 406.9
Hirado; Group: JP; Unemployment (%): 3.251; Offences per 100k: 336.2
Hamada; Group: JP; Unemployment (%): 2.733; Offences per 100k: 338.5
Ginoza; Group: JP; Unemployment (%): 3.404; Offences per 100k: 728.3
Chizu; Group: JP; Unemployment (%): 3.374; Offences per 100k: 573.4
Ashikaga; Group: JP; Unemployment (%): 4.171; Offences per 100k: 884.307684
Seirō; Group: JP; Unemployment (%): 5.175; Offences per 100k: 462.5
Imabari; Group: JP; Unemployment (%): 3.929; Offences per 100k: 544.4
Tōgane; Group: JP; Unemployment (%): 5.133; Offences per 100k: 639.5
Shikama; Group: JP; Unemployment (%): 2.863; Offences per 100k: 500.9
Nihommatsu; Group: JP; Unemployment (%): 4.165; Offences per 100k: 497.6
Marumori; Group: JP; Unemployment (%): 3.985; Offences per 100k: 500.9
Kakuda; Group: JP; Unemployment (%): 4.223; Offences per 100k: 500.9
Gojōnome; Group: JP; Unemployment (%): 6.048; Offences per 100k: 295.1
Yūbari; Group: JP; Unemployment (%): 7.274; Offences per 100k: 478.9
Shimizu; Group: JP; Unemployment (%): 2.343; Offences per 100k: 478.9
Noboribetsu; Group: JP; Unemployment (%): 4.249; Offences per 100k: 478.9
Kuriyama; Group: JP; Unemployment (%): 2.914; Offences per 100k: 478.9
Hirosaki; Group: JP; Unemployment (%): 3.992; Offences per 100k: 514.050313
Ashoro; Group: JP; Unemployment (%): 2.382; Offences per 100k: 478.9
Kasumigaura; Group: JP; Unemployment (%): 4.656; Offences per 100k: 686.8
Rittō; Group: JP; Unemployment (%): 3.043; Offences per 100k: 618.3
Kahoku; Group: JP; Unemployment (%): 2.982; Offences per 100k: 489.6
Hidaka; Group: JP; Unemployment (%): 4.396; Offences per 100k: 729.3
Komagane; Group: JP; Unemployment (%): 2.576; Offences per 100k: 406.9
Nikaho; Group: JP; Unemployment (%): 3.696; Offences per 100k: 295.1
Kaizu; Group: JP; Unemployment (%): 3.075; Offences per 100k: 670.5
Habikino; Group: JP; Unemployment (%): 4.594; Offences per 100k: 539.839612
Buzen; Group: JP; Unemployment (%): 4.501; Offences per 100k: 757.6
Kanmaki; Group: JP; Unemployment (%): 5.555; Offences per 100k: 487.5
亀田郡七飯町; Group: JP; Unemployment (%): 9.2; Offences per 100k: 280.03979512878146
上川郡当麻町; Group: JP; Unemployment (%): 3; Offences per 100k: 165.18004625041294
新冠郡新冠町; Group: JP; Unemployment (%): 2.2; Offences per 100k: 279.3853522251048
厚岸郡厚岸町; Group: JP; Unemployment (%): 2.4; Offences per 100k: 536.9127516778524
北津軽郡中泊町; Group: JP; Unemployment (%): 7.5; Offences per 100k: 148.66730381225443
紫波郡矢巾町; Group: JP; Unemployment (%): 3.7; Offences per 100k: 435.7798165137615
柴田郡柴田町; Group: JP; Unemployment (%): 5.9; Offences per 100k: 459.6625471360546
山本郡八峰町; Group: JP; Unemployment (%): 3.8; Offences per 100k: 131.44922773578705
東田川郡三川町; Group: JP; Unemployment (%): 2.5; Offences per 100k: 328.1495220430875
東白川郡矢祭町; Group: JP; Unemployment (%): 4.1; Offences per 100k: 349.8542274052478
東茨城郡城里町; Group: JP; Unemployment (%): 3.6; Offences per 100k: 496.95053083352155
那須郡那須町; Group: JP; Unemployment (%): 3.7; Offences per 100k: 1367.2616786935055
邑楽郡大泉町; Group: JP; Unemployment (%): 7.7; Offences per 100k: 1058.7472691042663
三郷市; Group: JP; Unemployment (%): 3.8; Offences per 100k: 854.057477
児玉郡上里町; Group: JP; Unemployment (%): 4.8; Offences per 100k: 864.7232230592859
香取郡神崎町; Group: JP; Unemployment (%): 5.3; Offences per 100k: 408.23571175008874
港区; Group: JP; Unemployment (%): 2.7; Offences per 100k: 1323.4744939876018
板橋区; Group: JP; Unemployment (%): 4.1; Offences per 100k: 603.1984025261092
横浜市保土ケ谷区; Group: JP; Unemployment (%): 3.9; Offences per 100k: 404.03342772290904
川崎市高津区; Group: JP; Unemployment (%): 3.3; Offences per 100k: 506.55940540703665
足柄下郡湯河原町; Group: JP; Unemployment (%): 5.3; Offences per 100k: 439.97756977095287
能美市; Group: JP; Unemployment (%): 3.1; Offences per 100k: 263.5602768388862
南都留郡富士河口湖町; Group: JP; Unemployment (%): 4.2; Offences per 100k: 250.78369905956112
下伊那郡阿智村; Group: JP; Unemployment (%): 2; Offences per 100k: 387.14021208550747
不破郡関ケ原町; Group: JP; Unemployment (%): 4.4; Offences per 100k: 407.4979625101874
浜松市天竜区（再編後）; Group: JP; Unemployment (%): 3.626543; Offences per 100k: 269.6719661903804
名古屋市中村区; Group: JP; Unemployment (%): 4.1; Offences per 100k: 757.6
海部郡蟹江町; Group: JP; Unemployment (%): 3.1; Offences per 100k: 757.6
南牟婁郡御浜町; Group: JP; Unemployment (%): 2.6; Offences per 100k: 345.7548981943911
京都市右京区; Group: JP; Unemployment (%): 4.4; Offences per 100k: 369.9039823705336
大阪市浪速区; Group: JP; Unemployment (%): 7.4; Offences per 100k: 3064.581435367952
大阪市中央区; Group: JP; Unemployment (%): 3.8; Offences per 100k: 5188.135150836483
泉南郡田尻町; Group: JP; Unemployment (%): 3.1; Offences per 100k: 1426.2140499764262
朝来市; Group: JP; Unemployment (%): 4.3; Offences per 100k: 490.0194566548966
磯城郡三宅町; Group: JP; Unemployment (%): 9.2; Offences per 100k: 487.5
日高郡印南町; Group: JP; Unemployment (%): 2.5; Offences per 100k: 448.4
西伯郡伯耆町; Group: JP; Unemployment (%): 3.2; Offences per 100k: 226.7126663380976
広島市中区; Group: JP; Unemployment (%): 4; Offences per 100k: 542.9
熊毛郡平生町; Group: JP; Unemployment (%): 4; Offences per 100k: 260.51358392259027
さぬき市; Group: JP; Unemployment (%): 4.4; Offences per 100k: 419.4101199603139
高岡郡佐川町; Group: JP; Unemployment (%): 3.7; Offences per 100k: 321.8975010588734
福岡市城南区; Group: JP; Unemployment (%): 4.9; Offences per 100k: 865.0668425060248
鞍手郡小竹町; Group: JP; Unemployment (%): 7.6; Offences per 100k: 682.1480406386066
神埼市; Group: JP; Unemployment (%): 3.3; Offences per 100k: 410.8000662580752
熊本市西区; Group: JP; Unemployment (%): 4.1; Offences per 100k: 617.8796854027311
上益城郡嘉島町; Group: JP; Unemployment (%): 3.7; Offences per 100k: 916.7154281256095
東諸県郡綾町; Group: JP; Unemployment (%): 5; Offences per 100k: 191.5991156963891
熊毛郡屋久島町; Group: JP; Unemployment (%): 3.8; Offences per 100k: 551
中頭郡嘉手納町; Group: JP; Unemployment (%): 7.5; Offences per 100k: 728.3
성북구; Group: KR; Unemployment (%): 4; Offences per 100k: 2171.36679
송파구; Group: KR; Unemployment (%): 2.5; Offences per 100k: 2817.497055
사상구; Group: KR; Unemployment (%): 3.4; Offences per 100k: 3642.550981
옹진군; Group: KR; Unemployment (%): 0.3; Offences per 100k: 3060
성남시; Group: KR; Unemployment (%): 4.1; Offences per 100k: 3212.411231
상록구; Group: KR; Unemployment (%): 3.6; Offences per 100k: 3030
기흥구; Group: KR; Unemployment (%): 3.9; Offences per 100k: 3030
제천시; Group: KR; Unemployment (%): 1.1; Offences per 100k: 2738.080379
당진시; Group: KR; Unemployment (%): 1; Offences per 100k: 3427.4942
영천시; Group: KR; Unemployment (%): 2.2; Offences per 100k: 2870
진주시; Group: KR; Unemployment (%): 1.2; Offences per 100k: 3511.120541
합천군; Group: KR; Unemployment (%): 0.7; Offences per 100k: 2940
화천군; Group: KR; Unemployment (%): 0.9; Offences per 100k: 2990
순창군; Group: KR; Unemployment (%): 0.3; Offences per 100k: 2880
Raseiniai; Group: LT; Unemployment (%): 11.3; Offences per 100k: 1312
Kelmė; Group: LT; Unemployment (%): 11.2; Offences per 100k: 1460.6
Utenos municipality; Group: LT; Unemployment (%): 7.2; Offences per 100k: 940.7
Kauno municipality; Group: LT; Unemployment (%): 9.7; Offences per 100k: 1666.2
Balvi; Group: LV; Unemployment (%): 8.9; Offences per 100k: 1931
Preiļi; Group: LV; Unemployment (%): 8.2; Offences per 100k: 1482
Beek; Group: NL; Unemployment (%): 3.2; Offences per 100k: 4230
Twenterand; Group: NL; Unemployment (%): 2.9; Offences per 100k: 2310
Leusden; Group: NL; Unemployment (%): 3; Offences per 100k: 2570
Sluis; Group: NL; Unemployment (%): 2.9; Offences per 100k: 3110
Arnhem; Group: NL; Unemployment (%): 4.2; Offences per 100k: 6970
Gooise Meren; Group: NL; Unemployment (%): 3.4; Offences per 100k: 4240
Kampen; Group: NL; Unemployment (%): 3; Offences per 100k: 2670
Westerwolde; Group: NL; Unemployment (%): 3.3; Offences per 100k: 4010
Dantumadiel; Group: NL; Unemployment (%): 3.2; Offences per 100k: 1800
Hattem; Group: NL; Unemployment (%): 2.8; Offences per 100k: 2840
Tiel; Group: NL; Unemployment (%): 3.6; Offences per 100k: 5450
Waddinxveen; Group: NL; Unemployment (%): 3; Offences per 100k: 3140
Maasdriel; Group: NL; Unemployment (%): 2.8; Offences per 100k: 2550
Midden-Delfland; Group: NL; Unemployment (%): 2.7; Offences per 100k: 3610
Venlo; Group: NL; Unemployment (%): 4; Offences per 100k: 6010
Bergen (L.); Group: NL; Unemployment (%): 3.1; Offences per 100k: 3320
Deurne; Group: NL; Unemployment (%): 2.9; Offences per 100k: 3160
Laarbeek; Group: NL; Unemployment (%): 2.9; Offences per 100k: 2530
Veldhoven; Group: NL; Unemployment (%): 3.1; Offences per 100k: 3410
Drechterland; Group: NL; Unemployment (%): 2.9; Offences per 100k: 2240
Medemblik; Group: NL; Unemployment (%): 3; Offences per 100k: 2410
Borne; Group: NL; Unemployment (%): 2.9; Offences per 100k: 2770
Averøy; Group: NO; Unemployment (%): 1.9; Offences per 100k: 4090
Færder; Group: NO; Unemployment (%): 1.8; Offences per 100k: 4290
Hå; Group: NO; Unemployment (%): 1.3; Offences per 100k: 3500
Indre Fosen; Group: NO; Unemployment (%): 1.7; Offences per 100k: 3600
Lier; Group: NO; Unemployment (%): 1.8; Offences per 100k: 4270
Modum; Group: NO; Unemployment (%): 2.2; Offences per 100k: 4230
Oppdal; Group: NO; Unemployment (%): 1; Offences per 100k: 4700
Rauma; Group: NO; Unemployment (%): 1.2; Offences per 100k: 4860
Sør-Varanger; Group: NO; Unemployment (%): 1.7; Offences per 100k: 6000
Time; Group: NO; Unemployment (%): 1.5; Offences per 100k: 4920
Verdal; Group: NO; Unemployment (%): 2.4; Offences per 100k: 4590
Warkworth; Group: NZ; Unemployment (%): 1.7; Offences per 100k: 5491.63
Te Awamutu; Group: NZ; Unemployment (%): 2.4; Offences per 100k: 4311.9
Waitara; Group: NZ; Unemployment (%): 4; Offences per 100k: 3467.26
Motueka; Group: NZ; Unemployment (%): 1.9; Offences per 100k: 2512.52
Wanaka; Group: NZ; Unemployment (%): 1.2; Offences per 100k: 4113.38
Zdzieszowice; Group: PL; Unemployment (%): 3.9; Offences per 100k: 1520
Wola; Group: PL; Unemployment (%): 2; Offences per 100k: 1392
Twardogóra; Group: PL; Unemployment (%): 5.9; Offences per 100k: 1480
Szamotuły; Group: PL; Unemployment (%): 2.9; Offences per 100k: 1584
Strzegom; Group: PL; Unemployment (%): 5.9; Offences per 100k: 1973
Skoczów; Group: PL; Unemployment (%): 2.9; Offences per 100k: 1737
Pszczyna; Group: PL; Unemployment (%): 2.7; Offences per 100k: 1392
Piła; Group: PL; Unemployment (%): 3.7; Offences per 100k: 1982.9999999999998
Olkusz; Group: PL; Unemployment (%): 5.6; Offences per 100k: 1982
Murowana Goślina; Group: PL; Unemployment (%): 1.1; Offences per 100k: 1306
Łodygowice; Group: PL; Unemployment (%): 2.7; Offences per 100k: 2201
Krosno Odrzańskie; Group: PL; Unemployment (%): 3.4; Offences per 100k: 1932.9999999999998
Kłodawa; Group: PL; Unemployment (%): 2.8; Offences per 100k: 1580
Jarocin; Group: PL; Unemployment (%): 4; Offences per 100k: 1250
Głuszyca; Group: PL; Unemployment (%): 3.7; Offences per 100k: 2968
Czechowice-Dziedzice; Group: PL; Unemployment (%): 2.6; Offences per 100k: 1107
Buk; Group: PL; Unemployment (%): 1.2; Offences per 100k: 1306
Zwoleń; Group: PL; Unemployment (%): 7.6; Offences per 100k: 1270
Szczebrzeszyn; Group: PL; Unemployment (%): 6.5; Offences per 100k: 1188
Rakszawa; Group: PL; Unemployment (%): 6.8; Offences per 100k: 1264
Opole Lubelskie; Group: PL; Unemployment (%): 6.6; Offences per 100k: 1507
Mońki; Group: PL; Unemployment (%): 4.5; Offences per 100k: 1602
Korczyna; Group: PL; Unemployment (%): 3.5; Offences per 100k: 856
Grójec; Group: PL; Unemployment (%): 2.6; Offences per 100k: 2205
Brzozów; Group: PL; Unemployment (%): 10; Offences per 100k: 948
Białystok; Group: PL; Unemployment (%): 4.6; Offences per 100k: 1708
Chełmża; Group: PL; Unemployment (%): 6.6; Offences per 100k: 1289
Ełk; Group: PL; Unemployment (%): 5.3; Offences per 100k: 1609
Hajnówka; Group: PL; Unemployment (%): 6.3; Offences per 100k: 1339
Kłodzko; Group: PL; Unemployment (%): 7.3; Offences per 100k: 2142
Łaziska Górne; Group: PL; Unemployment (%): 2.9; Offences per 100k: 2181
Lubawa; Group: PL; Unemployment (%): 2.7; Offences per 100k: 1798
Nowa Ruda; Group: PL; Unemployment (%): 7.1; Offences per 100k: 2142
Ozorków; Group: PL; Unemployment (%): 6.4; Offences per 100k: 1555
Puławy; Group: PL; Unemployment (%): 5; Offences per 100k: 1669.0000000000002
Sandomierz; Group: PL; Unemployment (%): 5.8; Offences per 100k: 1422
Starachowice; Group: PL; Unemployment (%): 7.1; Offences per 100k: 2072
Toruń; Group: PL; Unemployment (%): 3.1; Offences per 100k: 2405
Żagań; Group: PL; Unemployment (%): 2.5; Offences per 100k: 2560
Porto; Group: PT; Unemployment (%): 3.45; Offences per 100k: 5240
Santa Marta de Penaguião; Group: PT; Unemployment (%): 2.88; Offences per 100k: 1550
Castanheira de Pera; Group: PT; Unemployment (%): 2.8; Offences per 100k: 2310
Mora; Group: PT; Unemployment (%): 1.79; Offences per 100k: 3250
Murtosa; Group: PT; Unemployment (%): 1.48; Offences per 100k: 3080
Miranda do Corvo; Group: PT; Unemployment (%): 1.86; Offences per 100k: 1370
Monção; Group: PT; Unemployment (%): 1.59; Offences per 100k: 2100
Ponte da Barca; Group: PT; Unemployment (%): 1.63; Offences per 100k: 3680
Alfândega da Fé; Group: PT; Unemployment (%): 2.53; Offences per 100k: 2310
Freixo de Espada à Cinta; Group: PT; Unemployment (%): 4.63; Offences per 100k: 2470
Loulé; Group: PT; Unemployment (%): 1.74; Offences per 100k: 4960
Alcobaça; Group: PT; Unemployment (%): 1.69; Offences per 100k: 2290
Peso da Régua; Group: PT; Unemployment (%): 3.63; Offences per 100k: 1960
Almeirim; Group: PT; Unemployment (%): 1.59; Offences per 100k: 3830
Borba; Group: PT; Unemployment (%): 2.7; Offences per 100k: 2700
Peniche; Group: PT; Unemployment (%): 2.19; Offences per 100k: 3030
São Brás de Alportel; Group: PT; Unemployment (%): 1.55; Offences per 100k: 3570
Penamacor; Group: PT; Unemployment (%): 1.87; Offences per 100k: 4320
Mullsjö; Group: SE; Unemployment (%): 8.5; Offences per 100k: 6658
Järfälla; Group: SE; Unemployment (%): 14; Offences per 100k: 15104
Österåker; Group: SE; Unemployment (%): 8; Offences per 100k: 8653
Gävle; Group: SE; Unemployment (%): 14.9; Offences per 100k: 12732
Örebro; Group: SE; Unemployment (%): 12.6; Offences per 100k: 13915
Öckerö; Group: SE; Unemployment (%): 5.4; Offences per 100k: 5696
Gällivare; Group: SE; Unemployment (%): 5.4; Offences per 100k: 9090
Strömstad; Group: SE; Unemployment (%): 9.3; Offences per 100k: 12242
Falköping; Group: SE; Unemployment (%): 10.9; Offences per 100k: 10351
Tranås; Group: SE; Unemployment (%): 11.9; Offences per 100k: 10355
Tierp; Group: SE; Unemployment (%): 11.5; Offences per 100k: 10567
Hultsfred; Group: SE; Unemployment (%): 12.3; Offences per 100k: 11526
Salem; Group: SE; Unemployment (%): 9.8; Offences per 100k: 9376
Olofström; Group: SE; Unemployment (%): 13.9; Offences per 100k: 11546
Duplek; Group: SI; Unemployment (%): 11.7; Offences per 100k: 2089
Koper/Capodistria; Group: SI; Unemployment (%): 9.8; Offences per 100k: 2590
Metlika; Group: SI; Unemployment (%): 14.6; Offences per 100k: 3208
Rače - Fram; Group: SI; Unemployment (%): 12.2; Offences per 100k: 2089
Šentjur; Group: SI; Unemployment (%): 11.2; Offences per 100k: 1924
Zreče; Group: SI; Unemployment (%): 10.1; Offences per 100k: 1924
Želiezovce; Group: SK; Unemployment (%): 3.44; Offences per 100k: 700
Trenčín; Group: SK; Unemployment (%): 7.71; Offences per 100k: 900
Šahy; Group: SK; Unemployment (%): 4.68; Offences per 100k: 900
Nové Zámky; Group: SK; Unemployment (%): 3.53; Offences per 100k: 1000
Kysucké Nové Mesto; Group: SK; Unemployment (%): 4.93; Offences per 100k: 700
Fiľakovo; Group: SK; Unemployment (%): 9.31; Offences per 100k: 800
Bánovce nad Bebravou; Group: SK; Unemployment (%): 3.24; Offences per 100k: 700
Sečovce; Group: SK; Unemployment (%): 6.64; Offences per 100k: 800
Humenné; Group: SK; Unemployment (%): 5.36; Offences per 100k: 600
Manor Park; Group: UK; Unemployment (%): 3.8; Offences per 100k: 10401.764377621668
New Stevenston; Group: UK; Unemployment (%): 3.2; Offences per 100k: 10017.736167243329
Leicester Forest East; Group: UK; Unemployment (%): 3.4; Offences per 100k: 5920.584292516064
Primrose Place; Group: UK; Unemployment (%): 4.7; Offences per 100k: 7479.789505796217
Woodford Green; Group: UK; Unemployment (%): 5.3; Offences per 100k: 7426.431446529134
Wilmslow; Group: UK; Unemployment (%): 2.7; Offences per 100k: 6098.533579556513
Wheatley; Group: UK; Unemployment (%): 2.4; Offences per 100k: 4064.037834728702
West Bromwich; Group: UK; Unemployment (%): 5.5; Offences per 100k: 9587.690046911208
Wardle; Group: UK; Unemployment (%): 4.8; Offences per 100k: 10459.71107271577
Tynemouth; Group: UK; Unemployment (%): 3.6; Offences per 100k: 8175.793512382282
Timperley; Group: UK; Unemployment (%): 3.1; Offences per 100k: 7485.945441344259
Swadlincote; Group: UK; Unemployment (%): 3.1; Offences per 100k: 5272.654541121598
Stowmarket; Group: UK; Unemployment (%): 4; Offences per 100k: 4661.70232630907
Stevenage; Group: UK; Unemployment (%): 5.83; Offences per 100k: 9378.473205918886
Southgate; Group: UK; Unemployment (%): 5.3; Offences per 100k: 8522.938973961165
Shrewsbury; Group: UK; Unemployment (%): 3.3; Offences per 100k: 4756.433201485916
Scalby; Group: UK; Unemployment (%): 2.6; Offences per 100k: 5139.877038585607
Saint Blazey; Group: UK; Unemployment (%): 4; Offences per 100k: 6273.048180233126
Royston; Group: UK; Unemployment (%): 3; Offences per 100k: 4953.316666788142
Redditch; Group: UK; Unemployment (%): 4.55; Offences per 100k: 6382.115899061153
Preston; Group: UK; Unemployment (%): 4; Offences per 100k: 9865.900383
Polesworth; Group: UK; Unemployment (%): 3; Offences per 100k: 6123.634847
Palmers Green; Group: UK; Unemployment (%): 5.3; Offences per 100k: 8522.938973961165
Norwich; Group: UK; Unemployment (%): 4.22; Offences per 100k: 10999.07
Newport; Group: UK; Unemployment (%): 3.4; Offences per 100k: 7298.215889605618
Narborough; Group: UK; Unemployment (%): 3; Offences per 100k: 5920.584292516064
Milford; Group: UK; Unemployment (%): 2.5; Offences per 100k: 3750.260641625212
Maldon; Group: UK; Unemployment (%): 3.3; Offences per 100k: 4478.453949747582
Longdendale; Group: UK; Unemployment (%): 5.27; Offences per 100k: 9644.345964622376
Lincoln; Group: UK; Unemployment (%): 4.45; Offences per 100k: 11662.226451
Larbert; Group: UK; Unemployment (%): 3.5; Offences per 100k: 5520
Kingston upon Hull; Group: UK; Unemployment (%): 6.34; Offences per 100k: 12147.014717
Kendal; Group: UK; Unemployment (%): 1.5; Offences per 100k: 5284.030820365614
Ingleby Greenhow; Group: UK; Unemployment (%): 2.4; Offences per 100k: 4736.568703071136
Hounslow; Group: UK; Unemployment (%): 4.5; Offences per 100k: 8739.112429197392
Histon; Group: UK; Unemployment (%): 3.4; Offences per 100k: 4689.81824925816
Heighington; Group: UK; Unemployment (%): 2.8; Offences per 100k: 3907.959630270764
Harwich; Group: UK; Unemployment (%): 5.1; Offences per 100k: 7972.747976192754
Halstead; Group: UK; Unemployment (%): 3.5; Offences per 100k: 5325.494205862305
Great Wyrley; Group: UK; Unemployment (%): 3; Offences per 100k: 5079.398372704788
Gorebridge; Group: UK; Unemployment (%): 2.1; Offences per 100k: 4990
Gedling; Group: UK; Unemployment (%): 3.7; Offences per 100k: 5320.626314042271
Forres; Group: UK; Unemployment (%): 3; Offences per 100k: 4410.062099
Farnham Royal; Group: UK; Unemployment (%): 2.9; Offences per 100k: 5885.263432307766
Enderby; Group: UK; Unemployment (%): 3; Offences per 100k: 5920.584292516064
Eastleigh; Group: UK; Unemployment (%): 3.25; Offences per 100k: 5496.281474537021
Droylsden; Group: UK; Unemployment (%): 4.8; Offences per 100k: 9644.345964622376
Denny; Group: UK; Unemployment (%): 3.5; Offences per 100k: 5523.059618
Crumlin; Group: UK; Unemployment (%): 3.3; Offences per 100k: 8533.627342888645
Cosham; Group: UK; Unemployment (%): 2.7; Offences per 100k: 11274.210180057018
Clevedon; Group: UK; Unemployment (%): 2.8; Offences per 100k: 8179.340808093401
Chesham; Group: UK; Unemployment (%): 2.9; Offences per 100k: 5885.263432307766
Caterham; Group: UK; Unemployment (%): 5.3; Offences per 100k: 5391.561609961805
Callington; Group: UK; Unemployment (%): 2.7; Offences per 100k: 6273.048180233126
Brundall; Group: UK; Unemployment (%): 4.8; Offences per 100k: 3484.44161352664
Bridgwater; Group: UK; Unemployment (%): 2.8; Offences per 100k: 8408.064888973497
Borehamwood; Group: UK; Unemployment (%): 5.4; Offences per 100k: 7185.242986244692
Bishopstoke; Group: UK; Unemployment (%): 2.7; Offences per 100k: 5496.281474537021
Bexley; Group: UK; Unemployment (%): 4.4; Offences per 100k: 6002.26
Bath; Group: UK; Unemployment (%): 2.5; Offences per 100k: 7904.393384926111
Banchory; Group: UK; Unemployment (%): 4.5; Offences per 100k: 2937.603742
Armadale; Group: UK; Unemployment (%): 3; Offences per 100k: 5527.247372
Aberystwyth; Group: UK; Unemployment (%): 3.5; Offences per 100k: 5513.850053
Didsbury; Group: UK; Unemployment (%): 3.1; Offences per 100k: 14267.302050299319
King's Cross; Group: UK; Unemployment (%): 5; Offences per 100k: 17325.749159917585
Calcot; Group: UK; Unemployment (%): 2.4; Offences per 100k: 5498.0861475846705
Chelmsley Wood; Group: UK; Unemployment (%): 5.5; Offences per 100k: 7952.377939089322
Knotty Ash; Group: UK; Unemployment (%): 3.5; Offences per 100k: 12408.809319378106
Charlton; Group: UK; Unemployment (%): 4.9; Offences per 100k: 9025.867364653723
Aldridge; Group: UK; Unemployment (%): 4.7; Offences per 100k: 9294.570445
Attleborough; Group: UK; Unemployment (%): 3.7; Offences per 100k: 4909.971355
Barry (Vale of Glamorgan); Group: UK; Unemployment (%): 3.6; Offences per 100k: 6083.554953109921
Bidford-on-Avon; Group: UK; Unemployment (%): 3.1; Offences per 100k: 5610.549001
Boston Spa; Group: UK; Unemployment (%): 4; Offences per 100k: 11461.933366
Broad Blunsdon; Group: UK; Unemployment (%): 5; Offences per 100k: 6956.432599
Bursledon; Group: UK; Unemployment (%): 2.4; Offences per 100k: 5496.281475
Catterick Garrison; Group: UK; Unemployment (%): 2; Offences per 100k: 4736.568703
Clayton-le-Moors; Group: UK; Unemployment (%): 4.2; Offences per 100k: 9696.94857
Cowes; Group: UK; Unemployment (%): 4.9; Offences per 100k: 7606.946209
Culcheth; Group: UK; Unemployment (%): 2.8; Offences per 100k: 7036.505704
Driffield; Group: UK; Unemployment (%): 2.6; Offences per 100k: 5139.877039
Elland; Group: UK; Unemployment (%): 7.1; Offences per 100k: 10340.920404
Four Marks; Group: UK; Unemployment (%): 2.8; Offences per 100k: 4339.296018
Great Harwood; Group: UK; Unemployment (%): 4.2; Offences per 100k: 9696.94857
Haxby; Group: UK; Unemployment (%): 2.5; Offences per 100k: 6570.441613
Hexham; Group: UK; Unemployment (%): 3.4; Offences per 100k: 6930.480961
Hornsea; Group: UK; Unemployment (%): 5.2; Offences per 100k: 5139.877039
Kearsley; Group: UK; Unemployment (%): 5.3; Offences per 100k: 9797.31364
Leatherhead; Group: UK; Unemployment (%): 2.1; Offences per 100k: 5435.7506
Llanharan and Brynna; Group: UK; Unemployment (%): 6.2; Offences per 100k: 7654.995096
Marchwood; Group: UK; Unemployment (%): 3.2; Offences per 100k: 5285.720775
Milnrow; Group: UK; Unemployment (%): 7.2; Offences per 100k: 10459.711073
New Ollerton and Ollerton; Group: UK; Unemployment (%): 3.7; Offences per 100k: 6844.377023
Odiham; Group: UK; Unemployment (%): 2.9; Offences per 100k: 5816.831375
Penistone; Group: UK; Unemployment (%): 2.6; Offences per 100k: 9507.089804
Pool and Illogan; Group: UK; Unemployment (%): 4; Offences per 100k: 6273.04818
Ringwood; Group: UK; Unemployment (%): 3.2; Offences per 100k: 5285.720775
Sandown; Group: UK; Unemployment (%): 4.9; Offences per 100k: 7606.946209
Shepton Mallet; Group: UK; Unemployment (%): 2.8; Offences per 100k: 8408.064889
Sleaford; Group: UK; Unemployment (%): 2.8; Offences per 100k: 3907.95963
Stone Cross; Group: UK; Unemployment (%): 2.9; Offences per 100k: 4105.25559
Thirsk; Group: UK; Unemployment (%): 2; Offences per 100k: 4736.568703
Uckfield; Group: UK; Unemployment (%): 2.9; Offences per 100k: 4105.25559
Warminster; Group: UK; Unemployment (%): 2.7; Offences per 100k: 4925.720833
Whickham; Group: UK; Unemployment (%): 6.8; Offences per 100k: 8777.372263
Worsbrough; Group: UK; Unemployment (%): 2.6; Offences per 100k: 9507.089804
Kendall; Group: US; Unemployment (%): 3.26957; Offences per 100k: 2740.1
Folkston; Group: US; Unemployment (%): 27.406765; Offences per 100k: 548.754749
Aspen Hill; Group: US; Unemployment (%): 7.00598; Offences per 100k: 3458
Stratford; Group: US; Unemployment (%): 4.704705; Offences per 100k: 1242.496161
Spring; Group: US; Unemployment (%): 3.719982; Offences per 100k: 1705.29
East Norwalk; Group: US; Unemployment (%): 5.211715; Offences per 100k: 1023.673781
North Haven; Group: US; Unemployment (%): 2.009474; Offences per 100k: 2662.284306
Wethersfield; Group: US; Unemployment (%): 3.415055; Offences per 100k: 1429.468474
Amesbury; Group: US; Unemployment (%): 3.649995; Offences per 100k: 669.769554
Charlton; Group: US; Unemployment (%): 4.3; Offences per 100k: 453.481568
Easton; Group: US; Unemployment (%): 3.8; Offences per 100k: 921.32146
Hull; Group: US; Unemployment (%): 3.959152; Offences per 100k: 727.449079
Medway; Group: US; Unemployment (%): 3; Offences per 100k: 350.500715
North Reading; Group: US; Unemployment (%): 3.6; Offences per 100k: 471.840784
Southborough; Group: US; Unemployment (%): 3.4; Offences per 100k: 282.485876
Webster; Group: US; Unemployment (%): 8.936043; Offences per 100k: 1437.681808
Gorham; Group: US; Unemployment (%): 2.360656; Offences per 100k: 419.755778
Minnetonka Mills; Group: US; Unemployment (%): 2.991742; Offences per 100k: 1397.865912
Litchfield; Group: US; Unemployment (%): 3.2; Offences per 100k: 164.435048
Bloomfield; Group: US; Unemployment (%): 4.3; Offences per 100k: 1584.452784
South Plainfield; Group: US; Unemployment (%): 5.600951; Offences per 100k: 2048.364154
Edinboro; Group: US; Unemployment (%): 0.398883; Offences per 100k: 890.39987
Jamestown; Group: US; Unemployment (%): 3.2; Offences per 100k: 342.342342
Morristown; Group: US; Unemployment (%): 2; Offences per 100k: 1727.574751
Los Alamos; Group: US; Unemployment (%): 0.78972; Offences per 100k: 453.873221
City of Sammamish; Group: US; Unemployment (%): 3.505208; Offences per 100k: 304.974711
Albertville; Group: US; Unemployment (%): 5.9965; Offences per 100k: 1996.385853
Clanton; Group: US; Unemployment (%): 7.1264; Offences per 100k: 3621.621622
Greenville; Group: US; Unemployment (%): 6.5995; Offences per 100k: 4420.049112
Lincoln; Group: US; Unemployment (%): 3.5482; Offences per 100k: 2666.666667
Opp; Group: US; Unemployment (%): 5.1924; Offences per 100k: 2263.313609
Satsuma; Group: US; Unemployment (%): 5.0059; Offences per 100k: 828.488372
Valley; Group: US; Unemployment (%): 3.4751; Offences per 100k: 4218.338053
Buckeye; Group: US; Unemployment (%): 4.9067; Offences per 100k: 937.884782
Goodyear; Group: US; Unemployment (%): 4.1775; Offences per 100k: 1645.108305
Queen Creek; Group: US; Unemployment (%): 4.2911; Offences per 100k: 941.444112
Alma; Group: US; Unemployment (%): 7.5587; Offences per 100k: 1486.866017
Clarksville; Group: US; Unemployment (%): 5.3842; Offences per 100k: 2500
Jonesboro; Group: US; Unemployment (%): 6.3117; Offences per 100k: 3764.645072
Pocahontas; Group: US; Unemployment (%): 5.5895; Offences per 100k: 3129.890454
Warren; Group: US; Unemployment (%): 8.4374; Offences per 100k: 1361.602801
Arcata; Group: US; Unemployment (%): 11.8964; Offences per 100k: 2271.418852
Bell Gardens; Group: US; Unemployment (%): 5.8988; Offences per 100k: 1864.31479
Calimesa; Group: US; Unemployment (%): 1.2572; Offences per 100k: 1851.690863
Chula Vista; Group: US; Unemployment (%): 8.0172; Offences per 100k: 1508.163437
Corona; Group: US; Unemployment (%): 5.4682; Offences per 100k: 1973.022944
Diamond Bar; Group: US; Unemployment (%): 4.8806; Offences per 100k: 1940.304346
Emeryville; Group: US; Unemployment (%): 6.4143; Offences per 100k: 14718.648883
Fountain Valley; Group: US; Unemployment (%): 5.6499; Offences per 100k: 1962.710323
Gridley; Group: US; Unemployment (%): 11.4654; Offences per 100k: 1631.862813
Holtville; Group: US; Unemployment (%): 9.4005; Offences per 100k: 415.087529
La Cañada Flintridge; Group: US; Unemployment (%): 4.9723; Offences per 100k: 1606.947839
La Puente; Group: US; Unemployment (%): 6.2251; Offences per 100k: 1700.133126
Los Alamitos; Group: US; Unemployment (%): 9.1634; Offences per 100k: 2185.01465
Maywood; Group: US; Unemployment (%): 7.7865; Offences per 100k: 1920.450666
Moreno Valley; Group: US; Unemployment (%): 7.083; Offences per 100k: 1938.374668
Oceanside; Group: US; Unemployment (%): 5.292; Offences per 100k: 2130.686028
Paradise; Group: US; Unemployment (%): 4.8903; Offences per 100k: 978.693037
Pomona; Group: US; Unemployment (%): 6.5679; Offences per 100k: 3469.100928
Richmond; Group: US; Unemployment (%): 8.3485; Offences per 100k: 3685.482022
San Buenaventura (Ventura); Group: US; Unemployment (%): 4.812194; Offences per 100k: 2616.474577
San Pablo; Group: US; Unemployment (%): 8.4676; Offences per 100k: 3134.887325
Scotts Valley; Group: US; Unemployment (%): 2.9239; Offences per 100k: 1903.952401
South Pasadena; Group: US; Unemployment (%): 5.0893; Offences per 100k: 2723.164738
Tulare; Group: US; Unemployment (%): 8.6007; Offences per 100k: 2414.596382
Waterford; Group: US; Unemployment (%): 7.8616; Offences per 100k: 1065.303079
Yuba City; Group: US; Unemployment (%): 6.9589; Offences per 100k: 2082.111437
Cherry Hills Village; Group: US; Unemployment (%): 4.3807; Offences per 100k: 1430.408229
Fort Collins; Group: US; Unemployment (%): 5.4121; Offences per 100k: 2428.024327
Lakewood; Group: US; Unemployment (%): 4.5356; Offences per 100k: 5880.616932
Salida; Group: US; Unemployment (%): 1.5854; Offences per 100k: 787.533512
Danbury; Group: US; Unemployment (%): 6.5193; Offences per 100k: 1518.717321
West Haven; Group: US; Unemployment (%): 7.2729; Offences per 100k: 1342.54002
Atlantic Beach; Group: US; Unemployment (%): 3.1808; Offences per 100k: 1194.616664
Coconut Creek; Group: US; Unemployment (%): 5.0379; Offences per 100k: 1205.400192864031
Flagler Beach; Group: US; Unemployment (%): 2.8156; Offences per 100k: 1162.790698
Jacksonville; Group: US; Unemployment (%): 4.581; Offences per 100k: 3965.9371143341746
Maitland; Group: US; Unemployment (%): 4.7932; Offences per 100k: 1455.332863
Ocala; Group: US; Unemployment (%): 5.8585; Offences per 100k: 2861.8288462340333
Pensacola; Group: US; Unemployment (%): 6.3175; Offences per 100k: 3277.7
Satellite Beach; Group: US; Unemployment (%): 5.8068; Offences per 100k: 613.927381
Tequesta; Group: US; Unemployment (%): 6.1716; Offences per 100k: 253.284787
Atlanta; Group: US; Unemployment (%): 5.8811; Offences per 100k: 3840.1791842780244
Chamblee; Group: US; Unemployment (%): 2.1616; Offences per 100k: 4179.132098
Eastman; Group: US; Unemployment (%): 4.0421; Offences per 100k: 5669.916938
Hiram; Group: US; Unemployment (%): 3.8462; Offences per 100k: 5171.158048
Marietta; Group: US; Unemployment (%): 3.8296; Offences per 100k: 2108.785554
Rincon; Group: US; Unemployment (%): 9.4733; Offences per 100k: 616.918786
Stone Mountain; Group: US; Unemployment (%): 6.9918; Offences per 100k: 2413.528055
Urban Honolulu; Group: US; Unemployment (%): 4.832386; Offences per 100k: 1974.776756
Moscow; Group: US; Unemployment (%): 7.9082; Offences per 100k: 1034.327687
Algonquin; Group: US; Unemployment (%): 4.1434; Offences per 100k: 1238.073228
Bethalto; Group: US; Unemployment (%): 4.0486; Offences per 100k: 876.712329
Carol Stream; Group: US; Unemployment (%): 3.9125; Offences per 100k: 780.301269
Clinton; Group: US; Unemployment (%): 3.6962; Offences per 100k: 2123.327516
Downers Grove; Group: US; Unemployment (%): 4.0338; Offences per 100k: 984.525995
Forest Park; Group: US; Unemployment (%): 4.451; Offences per 100k: 3246.656761
Grayslake; Group: US; Unemployment (%): 5.4314; Offences per 100k: 706.684745
Hillsboro; Group: US; Unemployment (%): 2.924; Offences per 100k: 783.426184
Lake Bluff; Group: US; Unemployment (%): 4.3691; Offences per 100k: 871.301507
Lockport; Group: US; Unemployment (%): 4.7247; Offences per 100k: 659.967002
Midlothian; Group: US; Unemployment (%): 5.3241; Offences per 100k: 1764.92399
Mundelein; Group: US; Unemployment (%): 2.649; Offences per 100k: 771.740494
Oak Park; Group: US; Unemployment (%): 5.5842; Offences per 100k: 3931.314076
Peru; Group: US; Unemployment (%): 2.4825; Offences per 100k: 1890.281488
Rochelle; Group: US; Unemployment (%): 8.1652; Offences per 100k: 913.865546
Shiloh; Group: US; Unemployment (%): 1.7146; Offences per 100k: 809.364548
Sugar Grove; Group: US; Unemployment (%): 5.2924; Offences per 100k: 358.929737
Westchester; Group: US; Unemployment (%): 5.2273; Offences per 100k: 681.130172
Woodridge; Group: US; Unemployment (%): 4.2389; Offences per 100k: 877.587085
Bluffton; Group: US; Unemployment (%): 2.7553; Offences per 100k: 912.634281
Danville; Group: US; Unemployment (%): 2.0681; Offences per 100k: 811.496196
Griffith; Group: US; Unemployment (%): 3.7572; Offences per 100k: 1116.486788
Logansport; Group: US; Unemployment (%): 4.3244; Offences per 100k: 1285.926252
North Vernon; Group: US; Unemployment (%): 7.0588; Offences per 100k: 1342.896383
Speedway; Group: US; Unemployment (%): 5.7502; Offences per 100k: 2776.020803
Algona; Group: US; Unemployment (%): 1.9651; Offences per 100k: 226.500566
Clarinda; Group: US; Unemployment (%): 6.4565; Offences per 100k: 1305.334847
Fort Dodge; Group: US; Unemployment (%): 6.027; Offences per 100k: 4256.795364
Marshalltown; Group: US; Unemployment (%): 5.2505; Offences per 100k: 2070.641137
Red Oak; Group: US; Unemployment (%): 2.9102; Offences per 100k: 1218.386561
Winterset; Group: US; Unemployment (%): 2.976; Offences per 100k: 911.967244
Fort Scott; Group: US; Unemployment (%): 6.3298; Offences per 100k: 1980.720982
Lenexa; Group: US; Unemployment (%): 2.7935; Offences per 100k: 1530.464915
Prairie Village; Group: US; Unemployment (%): 2.9763; Offences per 100k: 1140.833989
Berea; Group: US; Unemployment (%): 4.1922; Offences per 100k: 935.853734
Fort Mitchell; Group: US; Unemployment (%): 2.4111; Offences per 100k: 812.347685
Lebanon; Group: US; Unemployment (%): 3.6674; Offences per 100k: 1122.062168
Nicholasville; Group: US; Unemployment (%): 3.6229; Offences per 100k: 1609.566117
Versailles; Group: US; Unemployment (%): 2.959; Offences per 100k: 825.909763
DeRidder; Group: US; Unemployment (%): 10.0711; Offences per 100k: 1744.247137
Plaquemine; Group: US; Unemployment (%): 3.7802; Offences per 100k: 4506.329114
Augusta; Group: US; Unemployment (%): 5.6723; Offences per 100k: 4341.473596
South Portland; Group: US; Unemployment (%): 2.619; Offences per 100k: 1433.292488
District Heights; Group: US; Unemployment (%): 6.7895; Offences per 100k: 2461.431791
Mount Airy; Group: US; Unemployment (%): 2.2361; Offences per 100k: 1344.571543
Boston; Group: US; Unemployment (%): 6.1008; Offences per 100k: 2649.6
Holyoke; Group: US; Unemployment (%): 7.7368; Offences per 100k: 5273.06968
Pittsfield; Group: US; Unemployment (%): 7.0221; Offences per 100k: 1750.904634
Adrian; Group: US; Unemployment (%): 5.346; Offences per 100k: 2968.229503
Brighton; Group: US; Unemployment (%): 2.9039; Offences per 100k: 1339.066339
Eastpointe; Group: US; Unemployment (%): 12.9228; Offences per 100k: 2991.759226
Grand Ledge; Group: US; Unemployment (%): 4.5732; Offences per 100k: 706.850019
Houghton; Group: US; Unemployment (%): 10.3241; Offences per 100k: 794.021485
Marquette; Group: US; Unemployment (%): 4.321; Offences per 100k: 696.634502
Novi; Group: US; Unemployment (%): 4.2527; Offences per 100k: 754.90462
Saginaw; Group: US; Unemployment (%): 10.1447; Offences per 100k: 4160.447761
Trenton; Group: US; Unemployment (%): 3.2781; Offences per 100k: 576.336309
Anoka; Group: US; Unemployment (%): 4.7519; Offences per 100k: 1431.58362
Champlin; Group: US; Unemployment (%): 3.5722; Offences per 100k: 1251.553346
Elko New Market; Group: US; Unemployment (%): 0; Offences per 100k: 0
International Falls; Group: US; Unemployment (%): 7.7441; Offences per 100k: 1569.830386
Medina; Group: US; Unemployment (%): 1.0877; Offences per 100k: 661.599099
Oakdale; Group: US; Unemployment (%): 3.2406; Offences per 100k: 1942.29815
St. Cloud; Group: US; Unemployment (%): 6.0479; Offences per 100k: 3323.448777
Waseca; Group: US; Unemployment (%): 2.7665; Offences per 100k: 1160.646491
Cleveland; Group: US; Unemployment (%): 7.882; Offences per 100k: 3226.758485
Kosciusko; Group: US; Unemployment (%): 5.5224; Offences per 100k: 1803.399852
Richland; Group: US; Unemployment (%): 5.058; Offences per 100k: 1082.01977
Blue Springs; Group: US; Unemployment (%): 3.4886; Offences per 100k: 2684.300118
Columbia; Group: US; Unemployment (%): 4.0178; Offences per 100k: 2665.050555
Glendale; Group: US; Unemployment (%): 0.2594; Offences per 100k: 382.631842
Kirkwood; Group: US; Unemployment (%): 3.1103; Offences per 100k: 1609.242831
Nevada; Group: US; Unemployment (%): 5.7143; Offences per 100k: 5315.935726
Pleasant Hill; Group: US; Unemployment (%): 5.1873; Offences per 100k: 821.664159
Savannah; Group: US; Unemployment (%): 2.3898; Offences per 100k: 590.783773
Waynesville; Group: US; Unemployment (%): 5.1436; Offences per 100k: 1391.177009
Laurel; Group: US; Unemployment (%): 2.3785; Offences per 100k: 4147.529576
Grand Island; Group: US; Unemployment (%): 4.5628; Offences per 100k: 2128.105472
Scottsbluff; Group: US; Unemployment (%): 2.5662; Offences per 100k: 3371.22697
Winnemucca; Group: US; Unemployment (%): 5.6609; Offences per 100k: 2020.447907
Asbury Park; Group: US; Unemployment (%): 5.6134; Offences per 100k: 4044.755964
Butler borough; Group: US; Unemployment (%): 4.1192; Offences per 100k: 539.180446
Eatontown borough; Group: US; Unemployment (%): 6.668424; Offences per 100k: 2108.389013
Garfield; Group: US; Unemployment (%): 6.7412; Offences per 100k: 1949.953213
Highland Park borough; Group: US; Unemployment (%): 4.765994; Offences per 100k: 1369.593709
Linwood; Group: US; Unemployment (%): 7.3521; Offences per 100k: 732.653354
Morris Plains borough; Group: US; Unemployment (%): 5.0209; Offences per 100k: 1186.465505
Ocean City; Group: US; Unemployment (%): 3.1919; Offences per 100k: 2178.358673
Pleasantville; Group: US; Unemployment (%): 10.6505; Offences per 100k: 1876.909646
Roselle borough; Group: US; Unemployment (%): 8.0133; Offences per 100k: 1310.466139
Tenafly borough; Group: US; Unemployment (%): 6.839908; Offences per 100k: 472.461329
Wildwood; Group: US; Unemployment (%): 7.4479; Offences per 100k: 5275.498242
Edgewood; Group: US; Unemployment (%): 5.1017; Offences per 100k: 1635.858008
Taos; Group: US; Unemployment (%): 10.6131; Offences per 100k: 6915.39182
Bronxville; Group: US; Unemployment (%): 3.7832; Offences per 100k: 356.921167
Floral Park; Group: US; Unemployment (%): 3.1119; Offences per 100k: 445.783889
Ilion; Group: US; Unemployment (%): 2.2057; Offences per 100k: 1885.039161
Medina; Group: US; Unemployment (%): 3.2682; Offences per 100k: 1019.021739
Ossining; Group: US; Unemployment (%): 6.0153; Offences per 100k: 720.57945
Rye Brook; Group: US; Unemployment (%): 6.2027; Offences per 100k: 283.314783
Wappingers Falls; Group: US; Unemployment (%): 7.3519; Offences per 100k: 247.443088
Black Mountain; Group: US; Unemployment (%): 3.9317; Offences per 100k: 1237.739374
Cornelius; Group: US; Unemployment (%): 2.4493; Offences per 100k: 1139.499688
Gibsonville; Group: US; Unemployment (%): 3.3446; Offences per 100k: 1101.985653
Kernersville; Group: US; Unemployment (%): 2.7038; Offences per 100k: 3376.34107
Mint Hill; Group: US; Unemployment (%): 4.1151; Offences per 100k: 934.215648
Rockingham; Group: US; Unemployment (%): 11.3248; Offences per 100k: 4450.26178
Thomasville; Group: US; Unemployment (%): 4.6278; Offences per 100k: 2626.702997
Dickinson; Group: US; Unemployment (%): 3.1579; Offences per 100k: 2003.211562
Athens; Group: US; Unemployment (%): 8.1775; Offences per 100k: 1059.592097
Bowling Green; Group: US; Unemployment (%): 5.6944; Offences per 100k: 1026.8432
Centerville; Group: US; Unemployment (%): 3.3719; Offences per 100k: 1046.383319
Delaware; Group: US; Unemployment (%): 2.6302; Offences per 100k: 1136.535185
Forest Park; Group: US; Unemployment (%): 4.96; Offences per 100k: 1971.616827
Harrison; Group: US; Unemployment (%): 1.4864; Offences per 100k: 848.145143
Lakewood; Group: US; Unemployment (%): 5.0194; Offences per 100k: 1282.675759
Massillon; Group: US; Unemployment (%): 4.4092; Offences per 100k: 2133.931039
Newark; Group: US; Unemployment (%): 3.7503; Offences per 100k: 1908.783126
Ontario; Group: US; Unemployment (%): 6.3225; Offences per 100k: 3609.022556
Reminderville; Group: US; Unemployment (%): 4.1989; Offences per 100k: 300.582378
Springdale; Group: US; Unemployment (%): 5.3297; Offences per 100k: 3857.245854
Troy; Group: US; Unemployment (%): 4.2165; Offences per 100k: 1255.183649
Wauseon; Group: US; Unemployment (%): 4.5143; Offences per 100k: 1197.846568
Youngstown; Group: US; Unemployment (%): 11.8886; Offences per 100k: 3440.951572
Clinton; Group: US; Unemployment (%): 2.0452; Offences per 100k: 1941.282205
Henryetta; Group: US; Unemployment (%): 10.8028; Offences per 100k: 1498.929336
Norman; Group: US; Unemployment (%): 5.7456; Offences per 100k: 2526.763646
Stillwater; Group: US; Unemployment (%): 6.444; Offences per 100k: 1733.119615
Baker City; Group: US; Unemployment (%): 7.2177; Offences per 100k: 1667.4889
Grants Pass; Group: US; Unemployment (%): 5.3069; Offences per 100k: 3308.362948
Milton-Freewater; Group: US; Unemployment (%): 7.2502; Offences per 100k: 1994.219653
Seaside; Group: US; Unemployment (%): 8.1032; Offences per 100k: 4007.820137
Aliquippa; Group: US; Unemployment (%): 6.8422; Offences per 100k: 2022.572354
Bradford; Group: US; Unemployment (%): 5.2174; Offences per 100k: 3547.048588
Clarks Summit borough; Group: US; Unemployment (%): 0.9865; Offences per 100k: 517.582585
Duquesne; Group: US; Unemployment (%): 9.1129; Offences per 100k: 1854.066986
Glenolden borough; Group: US; Unemployment (%): 7.642626; Offences per 100k: 2293.38554
Kennett Square borough; Group: US; Unemployment (%): 3.1032; Offences per 100k: 713.118407
Media borough; Group: US; Unemployment (%): 4.217791; Offences per 100k: 1793.95182
New Cumberland borough; Group: US; Unemployment (%): 3.984998; Offences per 100k: 489.417989
Pittston; Group: US; Unemployment (%): 5.586; Offences per 100k: 561.577641
Shamokin; Group: US; Unemployment (%): 2.0826; Offences per 100k: 1153.675492
Tyrone borough; Group: US; Unemployment (%): 5.8299; Offences per 100k: 1400.984476
York; Group: US; Unemployment (%): 10.6821; Offences per 100k: 2392.355156
Cayce; Group: US; Unemployment (%): 5.3098; Offences per 100k: 3514.822424
Gaffney; Group: US; Unemployment (%): 10.5511; Offences per 100k: 4403.580934
Mauldin; Group: US; Unemployment (%): 4.8971; Offences per 100k: 1600.411241
Tega Cay; Group: US; Unemployment (%): 2.1702; Offences per 100k: 325.124516
Rapid City; Group: US; Unemployment (%): 2.5677; Offences per 100k: 4511.036723
Brownsville; Group: US; Unemployment (%): 8.6326; Offences per 100k: 3540.587219
East Ridge; Group: US; Unemployment (%): 5.257; Offences per 100k: 2407.932011
Jefferson City; Group: US; Unemployment (%): 6.0841; Offences per 100k: 2230.483271
McMinnville; Group: US; Unemployment (%): 9.0354; Offences per 100k: 2306.520635
Newport; Group: US; Unemployment (%): 0.5926; Offences per 100k: 4992.867332
Signal Mountain; Group: US; Unemployment (%): 2.3873; Offences per 100k: 526.021265
Alice; Group: US; Unemployment (%): 4.0857; Offences per 100k: 3757.076686
Austin; Group: US; Unemployment (%): 4.687; Offences per 100k: 3708.8
Bonham; Group: US; Unemployment (%): 9.4235; Offences per 100k: 788.686429
Burleson; Group: US; Unemployment (%): 3.4581; Offences per 100k: 1259.7636
Clute; Group: US; Unemployment (%): 8.5536; Offences per 100k: 2124.289574
Dallas; Group: US; Unemployment (%): 4.9128; Offences per 100k: 4010.1
El Campo; Group: US; Unemployment (%): 6.3952; Offences per 100k: 2313.732041
Fort Stockton; Group: US; Unemployment (%): 2.2296; Offences per 100k: 412.551569
Glenn Heights; Group: US; Unemployment (%): 5.2621; Offences per 100k: 1078.651685
Hempstead; Group: US; Unemployment (%): 2.3555; Offences per 100k: 1936.136396
Huntsville; Group: US; Unemployment (%): 10.9269; Offences per 100k: 2044.654775
Katy; Group: US; Unemployment (%): 7.4077; Offences per 100k: 3480.261739
La Joya; Group: US; Unemployment (%): 4.9389; Offences per 100k: 1241.738434
Liberty; Group: US; Unemployment (%): 4.1828; Offences per 100k: 2394.539555
McKinney; Group: US; Unemployment (%): 3.674; Offences per 100k: 932.771115
Mission; Group: US; Unemployment (%): 7.7575; Offences per 100k: 1337.480206
Orange; Group: US; Unemployment (%): 7.7399; Offences per 100k: 1643.044619
Pleasanton; Group: US; Unemployment (%): 2.9767; Offences per 100k: 2260.135432
River Oaks; Group: US; Unemployment (%): 6.0268; Offences per 100k: 1413.670052
San Antonio; Group: US; Unemployment (%): 6.1847; Offences per 100k: 5217.8
Sinton; Group: US; Unemployment (%): 8.4427; Offences per 100k: 1848.196662
Terrell Hills; Group: US; Unemployment (%): 4.2501; Offences per 100k: 1757.851076
Waco; Group: US; Unemployment (%): 4.6089; Offences per 100k: 2552.129623
Wilmer; Group: US; Unemployment (%): 14.4167; Offences per 100k: 2333.481022
Ephraim; Group: US; Unemployment (%): 10.4636; Offences per 100k: 573.339704
Murray; Group: US; Unemployment (%): 3.8056; Offences per 100k: 3596.815468
Roosevelt; Group: US; Unemployment (%): 6.0625; Offences per 100k: 1682.496608
Tooele; Group: US; Unemployment (%): 3.8441; Offences per 100k: 1705.361121
Ashland; Group: US; Unemployment (%): 4.8996; Offences per 100k: 2695.179046
Fairfax; Group: US; Unemployment (%): 3.2682; Offences per 100k: 2987.176636
Marion; Group: US; Unemployment (%): 4.7619; Offences per 100k: 2618.364419
South Boston; Group: US; Unemployment (%): 5.2489; Offences per 100k: 2977.955395
Arlington; Group: US; Unemployment (%): 4.2026; Offences per 100k: 2559.000463
Centralia; Group: US; Unemployment (%): 5.6921; Offences per 100k: 3007.558539
Ephrata; Group: US; Unemployment (%): 6.1129; Offences per 100k: 3107.085531
Lake Forest Park; Group: US; Unemployment (%): 4.3998; Offences per 100k: 1748.360912
Mukilteo; Group: US; Unemployment (%): 3.1331; Offences per 100k: 1822.979132
Pullman; Group: US; Unemployment (%): 8.2851; Offences per 100k: 951.517898
Snoqualmie; Group: US; Unemployment (%): 2.6374; Offences per 100k: 1115.718055
Washougal; Group: US; Unemployment (%): 7.7427; Offences per 100k: 1314.548456
Fairmont; Group: US; Unemployment (%): 6.6901; Offences per 100k: 1843.241448
Antigo; Group: US; Unemployment (%): 4.5325; Offences per 100k: 1436.130008
Cottage Grove; Group: US; Unemployment (%): 0.8658; Offences per 100k: 567.346081
Fox Point; Group: US; Unemployment (%): 0.3818; Offences per 100k: 594.7842
Kenosha; Group: US; Unemployment (%): 4.5195; Offences per 100k: 1152.050137
Middleton; Group: US; Unemployment (%): 3.0002; Offences per 100k: 997.730484
Onalaska; Group: US; Unemployment (%): 3.3821; Offences per 100k: 2328.508496
River Falls; Group: US; Unemployment (%): 3.3239; Offences per 100k: 990.041349
Tomah; Group: US; Unemployment (%): 4.3154; Offences per 100k: 2050.138092
Wisconsin Rapids; Group: US; Unemployment (%): 6.5768; Offences per 100k: 2424.470487

Where it breaks down

The first breakdown is geographic grain. Spain’s full coefficient of +0.010 combines 378 municipality rows at +0.040 with 47 city-grain rows at -0.354. The smaller city subset is too limited to replace the headline, but the reversal shows that the pooled Spanish estimate depends on which administrative units are included. Germany’s district-grain rows are +0.251 and its 37 city-grain rows +0.389; repeated district outcomes still prevent 3,040 rows from acting like independent city observations.

The United Kingdom illustrates a different failure. Twenty-two rows use city unemployment from 2018 and three use 2023 regional_context; all pair with 2024 crime. The city-only coefficient is -0.147, while the full 62-row coefficient is +0.301. Neither small estimate is stable enough to support relocation advice.

City size is a competing correlate, not an explanation. Lithuania provides the clearest contrast: unemployment is +0.029 while population is +0.638 on the same 30 places. Spain is +0.010 for unemployment and +0.195 for population; Canada is +0.081 and -0.248. Belgium and the Netherlands are positive on both. No single size adjustment can turn these patterns into one mechanism.

The table requires a technical correction in interpretation. Population is missing for 114 US rows and one UK row, but the packet carries each country’s full-sample unemployment coefficient beside the smaller population-complete n. Recalculating both coefficients on identical rows gives +0.325 for US unemployment versus +0.263 for population, and -0.109 for UK unemployment versus +0.229 for population. The US conclusion is unchanged; the UK comparison becomes even less stable.

A rank-based population sensitivity also leaves heterogeneity intact. After residualising unemployment and crime ranks on population within complete rows, coefficients remain +0.686 in Sweden, +0.682 in Belgium, +0.523 in the Netherlands and +0.304 in the United States; Germany falls to +0.196 and Spain to -0.100. This is not causal adjustment—only a one-variable robustness check.

What this means if you are moving

In Sweden, the Netherlands and Belgium, unemployment is a meaningful contextual companion to recorded crime in this packet; Denmark also shows a moderate alignment. In the United States it is a weaker screen, and Germany, though its coefficient is stronger, is limited by district-grain outcomes. In Spain, Portugal, Canada, Lithuania and the UK, the coefficient is too close to zero or too sample-sensitive to carry much decision weight.

Even in the stronger countries, do not translate the association into a story about unemployed residents or assume unemployment reduction would change crime. Use it to flag where two place-level conditions overlap, then inspect the actual variables relevant to a move: job availability by sector, offence categories, neighbourhood patterns, reporting year and the geographic boundary behind each rate.

Compare shortlisted places only within the same source system, period and grain where possible. A current city-level offence series and a current local labour measure are more useful than a national coefficient built from mismatched years. The pairing is context, not a substitute for direct city evidence.

Limits

This is a bivariate, ecological, cross-sectional analysis. It cannot establish causation in either direction and does not measure deprivation, policing intensity, reporting propensity, urban form, tourism, commuting, age structure, housing conditions or any other mechanism that could shape both variables.

Definitions and dates are not harmonised. Belgium’s 14-year pairing and Portugal’s roughly four-year mismatch are especially important. Crime-recording systems differ even within the UK, while unemployment sources range from registers to surveys. The coefficients describe ordering inside each assembled sample, not synchronized city conditions.

Rows are not fully independent. German district outcomes repeat across cities; nearby places may share police jurisdictions, economic conditions or source methodology. Spain mixes municipality and city grain. Standard p-values and the apparent precision of large n do not correct those dependencies.

Coverage is uneven: 4,457 US rows versus 30 in Lithuania, 40 in Canada and 61 in Poland. The 20-place floor prevents the thinnest country estimates from being reported, but it does not make small samples stable or the packet representative of all destinations.

Recorded offences may omit unreported incidents and reflect enforcement or publication choices. Unemployment may omit discouraged workers or use administrative eligibility rules. Neither variable is an individual-risk measure, and neither supports cross-country level rankings.

Method

We calculated Spearman’s rank correlation between unemployment percentage and recorded offences per 100,000 separately within each country. A country required at least 20 complete rows. Eighteen countries passed, yielding 16,342 rows; the pooled +0.447 uses all 16,353 rows only to demonstrate the aggregation problem.

Spearman is primary because it asks whether higher unemployment ranks tend to accompany higher recorded-crime ranks without requiring a linear relationship in raw units. Pearson is retained as a shape diagnostic. Coefficients are descriptive; no population weighting, missing-value imputation, cross-country standardisation or causal model was applied.

Quartile ratios use the within-country 25th- and 75th-percentile unemployment cutoffs, retain all rows tied at each boundary, and divide the high-unemployment group’s median crime rate by the low-unemployment group’s median. The population sensitivity ranks all three variables, removes the linear rank association with population and correlates the residuals. It controls one observed ranking only and cannot identify a mechanism.

The unadjusted two-sided Spearman p-values ignore spatial dependence and repeated administrative outcomes and are reported only as a sensitivity check. Grain-specific estimates were recalculated for Germany, Spain and the UK. Parent-municipality values inherited by subdivisions were excluded before analysis.

FAQ

Does unemployment cause crime?

This analysis cannot answer causation. It compares city-level unemployment and recorded-crime ranks at one point or period, without measuring policing, reporting, deprivation, urban form or other possible influences. It also cannot say anything about an individual unemployed person’s behaviour; doing so would be the ecological fallacy.

Where is the unemployment–crime relationship strongest?

The strongest reportable Spearman coefficients are Sweden at +0.683, the Netherlands at +0.647 and Belgium at +0.646. Germany follows at +0.583. These are within-country rankings under each country’s own unemployment and recorded-crime definitions, not evidence that their national levels are higher or directly comparable.

Where is the coefficient closest to zero?

Spain is +0.010 across 427 places, Lithuania +0.029 across 30, Portugal +0.044 across 280, Canada +0.081 across 40 and Italy -0.099 across 2,371. These are sample coefficients near zero, not proof that the underlying relationship is exactly zero.

Does city population explain the unemployment–crime result?

No single size explanation fits all countries. Lithuania has a +0.638 population–crime coefficient but only +0.029 for unemployment; Belgium and the Netherlands are positive on both; Portugal is slightly positive for unemployment and negative for population. Population is a competing correlate, not a demonstrated mechanism.

How should movers use these figures?

Use the pairing only as a country-specific screening clue. Check each shortlisted city’s observation year, geographic grain, offence definition and unemployment definition, then compare places covered by the same source system. Direct neighbourhood, offence-category and labour-market evidence is more useful than assuming one national coefficient applies everywhere.

Sources

The packet contains 2,264 source records. The publisher-level ledger below is generated from sources.csv; each link opens one representative record from that publisher family.

api.scb.se — 1 source record; grade A; checked 2026-07-14.
api.stat.gov.lv — 1 source record; grade A; checked 2026-07-14.
BBSR; Bundeskriminalamt (BKA), Polizeiliche Kriminalstatistik — All recorded crimes per 100,000 residents in the BBSR/PKS Kreis indicator. — 1 source record; grade A; checked 2026-07-16.
Belgian Federal Police / DGR/DRI/BIPOL — Belgian Federal Police — recorded total offences by municipality, Q4 2025 — 425 source records; grade B; checked 2026-07-26.
Budapest Police Headquarters / Budapest Municipality — BRFK — Report on 2025 activity and Budapest public safety — 1 source record; grade A; checked 2026-07-29.
Bundesagentur für Arbeit (BA), Statistik — Arbeitslosenquoten — Länder, Kreise und Gemeinden, Gesamt, 2024 annual average — 1 source record; grade A; checked 2026-07-26.
Bundesagentur für Arbeit, Statistik — 1 source record; grade A; checked 2026-08-05.
Bundesamt für Kartographie und Geodäsie (BKG) — 1 source record; grade A; checked 2026-08-05.
Bundesamt für Statistik (BFS) — Reproducible density from BFS STATPOP permanent population at 31.12.2024 divided by the exact official BFS municipality area denominator (2013-2018; FJ=2013; area observed_at=2013). — 1 source record; grade A; checked 2024-12-31.
Bundeskriminalamt (BKA) — PKS 2024 T01 Grundtabelle - Fälle mit Häufigkeitszahl (HZ) - Städte — 1 source record; grade A; checked 2026-07-16.

Show 105 more sources

Bundeskriminalamt / Statistik Austria — Bundeskriminalamt and Statistik Austria — 2025 Vienna offences and 2026 population — 1 source record; grade A; checked 2026-07-29.
California Department of Water Resources, Division of Integrated Regional Water Management (BIOS) — 1 source record; grade A; checked 2026-08-05.
CBS — CBS Kerncijfers wijken en buurten 2025, municipality-grain passenger-car universe (Personenauto's totaal) divided by the same-table municipality population. — 1 source record; grade A; checked 2026-07-15.
Census Reporter — Census Reporter mirror of ACS 2024 5-year tables — 98 source records; grade C; checked 2026-07-26.
Census Reporter (underlying U.S. Census ACS) — 189 source records; grade B; checked 2026-08-03.
Census Reporter / U.S. Census Bureau — 404 source records; grade B; checked 2026-08-03.
Centraal Bureau voor de Statistiek (CBS), Netherlands — CBS labour market in figures 2024 — unemployment by municipality — 1 source record; grade A; checked 2026-07-26.
Central Statistical Bureau of Latvia — CSB Latvia RIG090 — share of unemployed persons among economically active population aged 15-74 — 2 source records; grade A; checked 2026-07-26.
Czech Statistical Office — ČSÚ — Unemployment in Prague in 2025 — 2 source records; grade A; checked 2026-07-29.
Czech Statistical Office (CZSO) — CZSO official Prague statistical material — 1 source record; grade A; checked 2026-07-18.
Danmarks Statistik — DST KOM kommunekode source register; exact municipality row keyed by kommunekode. — 2 source records; grade A; checked 2026-07-12 to 2026-07-14.
Danmarks Statistik (DST) — Derived municipality density from DST population and ARE207 registered municipal area. — 1 source record; grade A; checked 2026-01-01.
data.gov.lv — 1 source record; grade A; checked 2026-07-14.
Destatis — Official municipality population divided by official municipality area from the same Destatis row. — 1 source record; grade A; checked 2024-12-31.
dst_by1_2025 — Statistics Denmark official Population 1 January by municipality, age and sex; summed over all ages and sexes. — 1 source record; grade A; checked 2026-07-14.
Eurostat — 3 source records; grade A; checked 2026-07-30 to 2026-08-05.
Eurostat (ESTAT) — Unemployment rate — 3 source records; grade A; checked 2026-07-16.
Eurostat GISCO / Eurostat Urban Audit — 1 source record; grade B; checked 2026-08-02.
FBI Crime Data Explorer / Uniform Crime Reporting — 1 source record; grade A; checked 2026-08-04.
FBI Crime Data Explorer, Crime in the United States 2024, Table 8 — 1 source record; grade A; checked 2026-08-05.
get.data.gov.lt — 1 source record; grade A; checked 2026-07-14.
GUS BDL / GUGiK — Reproducible gmina density for Warszawa: population_total_2024 / official area_2024, rounded to the metric contract precision 0. — 1 source record; grade A; checked 2024-12-31.
Hungarian Central Statistical Office — Population by type of settlement, 1 January — 1 source record; grade A; checked 2026-07-29.
Hungarian Central Statistical Office (KSH) — KSH official table for population_density_per_km2 — 1 source record; grade A; checked 2026-07-18.
Hungarian Central Statistical Office and official public authorities — KSH official data — 1 source record; grade A; checked 2026-07-18.
INE — Official INE 2024 municipality population divided by official INE 2024 municipality area. — 1 source record; grade A; checked 2024-01-01.
INE Portugal — Official INE municipality profile: population density for Lisboa municipality, reference year 2022. — 2 source records; grade A; checked 2026-07-15.
INE Portugal / reproducible local derivation — Reproducible derived density from the same-period INE populationTotal divided by areaKm2; no external density number was substituted. — 1 source record; grade B; checked 2026-07-15.
Information Centre of the Ministry of the Interior / Central Statistical Bureau of Latvia — Official Statistics Portal Latvia — NOR023 recorded crimes and crime rates 2021–2025 — 2 source records; grade A; checked 2026-07-29 to 2026-07-30.
Information Technology and Communications Department, Lithuania — Information Technology and Communications Department Lithuania — crime statistics — 1 source record; grade A; checked 2026-07-29.
Instituto do Emprego e Formação Profissional (IEFP), Portugal — IEFP — registered unemployment by municipality, June 2026 — 1 source record; grade B; checked 2026-07-26.
Instituto Nacional de Estadística (INE), Spain — INE Urban Indicators — unemployment rate by city — 1 source record; grade A; checked 2026-07-26.
Instituto Nacional de Estatística (INE), Portugal — INE — Taxa de criminalidade (‰) por Localização geográfica (NUTS 2013) e Categoria de crime; Anual, indicador 0008074, categoria Total, ano 2022 — 1 source record; grade A; checked 2026-07-31.
ISTAT — Official SITUAS report 74 (Comuni - Dimensione): exact municipality surface in km2, with annual area vintage. — 1 source record; grade A; checked 2026-07-15.
Istituto Nazionale di Statistica (ISTAT) — Resident population by age and sex, 1 January 2026 estimate — 1 source record; grade A; checked 2026-07-29.
Kantonspolizei Bern / Bundesamt für Statistik — Kantonspolizei Bern / BFS — Bern Gemeinde PKS 2025 total — 1 source record; grade A; checked 2026-07-29.
Metropolitan Police Department of the District of Columbia / U.S. Census Bureau — Population denominator used in MPD 2024 crime-rate table — 1 source record; grade A; checked 2026-07-16.
Ministerio del Interior / Secretaría de Estado de Seguridad — MIR 2024 Q4 exact III. TOTAL INFRACCIONES PENALES, enero-diciembre 2024; INE 29005 denominator. — 1 source record; grade A; checked 2026-07-16.
National Records of Scotland — 1 source record; grade A; checked 2026-08-05.
no_ssb_07459_population — SSB table 07459 — Population by region, 1 January 2026 — 1 source record; grade A; checked 2026-07-14.
Norwegian Labour and Welfare Administration (NAV) — NAV HL301 — fully unemployed by county and municipality, June 2026 — 1 source record; grade A; checked 2026-07-26.
Office for National Statistics — 1 source record; grade A; checked 2026-08-04.
Office for National Statistics (ONS) — 1 source record; grade A; checked 2026-08-06.
Office for National Statistics via Nomis — 1 source record; grade A; checked 2026-08-05.
official authority — Belgium official denominator source — 972 source records; grade A; checked 2026-07-14.
Police of the Czech Republic / Czech Statistical Office — Czech Police and CZSO — Prague 2025 registered criminal offences and population — 1 source record; grade A; checked 2026-07-29.
Polizei Berlin — Polizei Berlin Kriminalitätsatlas — HZ 2024 Berlin (PKS gesamt) — 1 source record; grade A; checked 2026-07-29.
pt_pordata_Q1000037 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q1000041 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q1003126 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q1005090 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q1005121 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q1005138 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q1006385 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q1013094 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q1013140 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q174800 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q368867 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q425410 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q438263 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q449526 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q492475 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q551649 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q551684 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q552580 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q635165 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q641715 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q647467 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q700311 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q769062 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q861589 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q985519 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q986093 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q988863 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
pt_pordata_Q995188 — area_km2 at municipality; reference 2025. — 1 source record; grade B; checked 2026-07-14.
Roma Capitale, Ufficio di Statistica / Istat — Roma Capitale — Annuario statistico 2024, Chapter 15, Table 15.1 — 1 source record; grade A; checked 2026-07-29.
Secretaría de Estado de Seguridad, Ministerio del Interior, Spain — Balance de Criminalidad 2024 Q4 — III. Total infracciones penales, municipal rows — 1 source record; grade A; checked 2026-07-26.
Servicio Público de Empleo Estatal (SEPE), Spain — SEPE — registered unemployment by municipality, June 2026 — 1 source record; grade B; checked 2026-07-26.
Spanish Ministry of Interior / Criminality Statistics Portal — 1 source record; grade A; checked 2026-08-05.
Statbel / Belgian Census 2011 — Statbel be.STAT — unemployment rate of 15–64-year-olds by municipality, Census 2011 — 1 source record; grade B; checked 2026-07-26.
Statbel / Statistics Belgium — Official resident population by Belgian municipality on 1 January 2026; Total column. — 1 source record; grade A; checked 2026-01-01.
State Data Agency of Lithuania (LSD) — 1 source record; grade A; checked 2026-08-05.
State Data Agency of Lithuania (Statistics Lithuania) — Statistics Lithuania OSP — resident population by county and municipality — 1 source record; grade A; checked 2026-07-26.
State Data Agency of Lithuania (Statistics Lithuania) and Employment Service — Statistics Lithuania / OSP — registered unemployment by county and municipality — 1 source record; grade A; checked 2026-07-26.
Statistics Austria — Population and citizenship by administrative unit, 1 January 2026 — 1 source record; grade A; checked 2026-07-29.
Statistics Canada — Statistics Canada — Police-reported Crime Severity Index and crime rate, by census metropolitan area, 2024 — 40 source records; grades A, B; checked 2021-05-11 to 2026-07-26.
Statistics Denmark — StatBank Denmark STRAF11 — reported criminal offences, municipality, all offence types — 3 source records; grade A; checked 2026-07-26 to 2026-07-29.
Statistics Denmark and official Danish public authorities — DK official material for crime_incidents_per_100k — 2 source records; grade A; checked 2026-07-18.
Statistics Finland — Statistics Finland municipal offences recorded, table 13ex — 2 source records; grade A; checked 2026-07-26.
Statistics Netherlands (CBS) — CBS StatLine 83648NED — registered crime by municipality, total, 2024 — 2 source records; grade A; checked 2026-07-26 to 2026-07-29.
Statistics Norway — Statistics Norway — offences reported to the police, national and Oslo comparator — same-period scope evidence repair — 1 source record; grade A; checked 2026-07-29.
Statistics Norway (SSB) — SSB 11342 ArealKm2 — 1 source record; grade A; checked 2026-07-15.
Statistics Poland — Population by territorial unit, 2021 — 1 source record; grade A; checked 2026-07-29.
Statistics Poland, Statistical Office in Warsaw — Statistics Poland — Statistical Yearbook of Warsaw 2024, Table 1 (31) — 2 source records; grade A; checked 2026-07-16 to 2026-07-29.
Statistics Sweden (SCB) — SCB labour-market variables by municipality, 2022–2024 — 4 source records; grades A, B; checked 2025-12-31 to 2026-07-29.
STATISTIK AUSTRIA — STATISTIK AUSTRIA — Wirtschaftsatlas, Österreich und seine Bundesländer — 1 source record; grade A; checked 2026-07-29.
Statistik Austria — Reproducible Gemeinde density from archived official population_total 2025-01-01 divided by official 2025 Gemeinde geometry area. — 1 source record; grade A; checked 2025-01-01.
Statistisches Bundesamt (Destatis) — 3 source records; grade A; checked 2026-08-03 to 2026-08-05.
Statistisches Bundesamt (Destatis) / Statistical Offices of the Länder — Zensus 2022 regional tables — Germany municipalities — 2 source records; grade A; checked 2026-07-26.
Swedish National Council for Crime Prevention (Brå) — Brå — reported offences by municipality, 2025 — 1 source record; grade A; checked 2026-07-26.
U.S. Census Bureau (Population Estimates Program) — 2 source records; grade A; checked 2026-08-03.
U.S. Census Bureau, Population Estimates Program — 2 source records; grade A; checked 2026-08-03 to 2026-08-05.
U.S. Census Bureau, TIGERweb Census 2020 — 2 source records; grade A; checked 2026-08-05.
Unknown publisher — Information Technology and Communications Department under the Ministry of the Interior of the Republic of Lithuania — 4 source records; grade A; checked 2026-08-04.
Užimtumo tarnyba prie Lietuvos Respublikos socialinės apsaugos ir darbo ministerijos — 1 source record; grade A; checked 2026-08-05.

How to cite

Streltcoff, M. (2026). The unemployment–crime link changes sharply by country. ImmigrationDB. https://immigrationdb.com/research/unemployment-recorded-crime/

Free to reuse under CC BY 4.0 with this credit; each figure keeps the terms of the publishers linked under its sources.