This research was financed by The Bank of Sweden Tercentenary Foundation (Riksbankens Jubileumsfond) - Grant J2004-0142:1, 2005-2007

Aim of the project and research strategy

The aim of this project was to study patterns of offence rates over time and space in the three Baltic States of Estonia, Latvia and Lithuania. This involved the display and analysis of the changing levels and composition of a selected group of offences covering the transition period during the 1990’s from planed to market economy and including the years of preparation for the integration into the European Union.  

The study dealt with three different spatial scales.

The first was the macro scale, involving comparisons at the level of the nation state in the 1990s. The analysis was first devoted to the assessment of differences in crime composition and levels across the three countries.

The second was the meso scale, involving the analysis of regional patterns of crime within the three countries in the 1990s. Here we accessed how these countries differ internally on their level and geography of crime and how these patterns relate to some of their regional socio-economic indicators.

Finally, the micro scale focused on the analysis of intra-urban patterns of crime using a fine detailed geographical database for Tallinn (Estonia) and Vilnius (Lithuania). The focus here was on the relationship between intra-urban crime levels and individual’s differences in accessing social and economic rights. We assessed here whether or not the vulnerability to crime in Eastern European cities follows similar processes to the ones found in Western European urban centres.

The novelty of this project referred to the inclusion of the spatial dimension of crime in different spatial scales, which has often been neglected in the recent. Until recently, spatial crime analysis in these nations in transition was rare simply because data was not systematically available for all regions or data quality was still a major limiting factor.

Main findings

• Since the mid 1990s, crime rates in the Baltic countries have tended to become more like those found in Western European countries. Although acquisitive and expressive crimes (with the exception of homicide) increased significantly in the Baltic countries after the independence according to official statistics, no significant changes were found in the levels and composition of offences declared by victims in the same period. Possible causes for this mismatch are: (1) the growth in crime reporting to police, (2) changes in the socio-economic composition of the victims of crime (3) political and administrative changes, inclusive within the police (this does not include changes in penal code).

Homicide rates per 10000 inhabitants, 1993-2000, in relation to other EU countries

By incorporating the spatial dimension using GIS, this study allowed an assessment of how social contexts and land use structures interact at regional and local levels to produce different patterns of crime: 

• Both expressive and acquisitive crimes are concentrated in urban areas or densely populated regions in the Baltic countries. Economically leading regions are often large urban areas or capital cities, where both the positive and negative sides of the new market economy are experienced: an increase in investment creates new jobs and increases the supply of goods (targets) but also exacerbates income disparities through wage differentials and selective unemployment (increasing the pool of motivated offenders). (papers 1 and 4).

Standardised theft ratios for Estonia, Latvia and Lithuania

• Indicators of regions’ social structure (e.g., divorce rate), more strongly predict the variation of 2000’s crime ratios than land use and economic covariates. One of the mechanisms that links divorce/broken families to offending is the increase in poverty, particularly after the family splits up. Divorce rates had a strong increase between 1990 and 2000 in the Baltic countries. For instance, in Estonia they rose from 49 per hundred new marriages to 77 (the highest within the EU). (papers 1 and 4).
• There was no evidence that social institutions work as ‘moderators’ of poor socio-economic conditions on crime in Estonia, Latvia and Lithuania, as previously suggested in the literature (papers 1 and 4).

Quartile maps of the residuals from the final regression models: (i) Drug related offences; (ii) robbery; (iii) thefts; (iv) car related thefts. 

• Organised crime in the region has been assessed by taking Lithuania as a case study. Lithuania’s location in relation to Belarus and Kaliningrad oblast also accounts for the high percentage of Lithuania-based organized crime groups dealing in various goods, including illegal weapons, human smuggling and contraband products such as cigarettes, clothes, furniture and technology. Marijampole county, for instance, bordering Poland and Kaliningrad oblast, is known as an important ‘transit’ region of Lithuania owing to its well-developed transport infrastructure and links both north to south and west to east. In the particular case of Lithuania, there are variations in the level and geography of offences between border regions and the rest of the country. Despite the fact that the highest average increases in recorded criminal offences were found in two border regions, non-border regions had a higher average increase in the 1990s. This partially explains why, out of the six selected offences, only assault shows an increase owing to the ‘border effect’. (paper 2)

 

 

 

 

 

 

 

Seized goods per 1000 passengers travelling through Lithuanian borders. Source: State Border Guard database, 1995-2004.

• We examined whether or not levels and patterns of robbery in Tallinn, Estonia, followed similar processes to the ones found in Cologne, Germany. Although robbery rates in Tallinn are higher than in Cologne, their geography and the factors that underlie such geography, are similar for both cities. Robbery is a phenomenon typical of central urban areas or areas of mixed land use. Clusters of robbery are concentrated in the inner city areas for both Cologne and Tallinn, and particularly in the case of Tallinn, they follow main roads, stations and local centres. In both cities, the geography of robbery is more associated with covariates of routine activities (e.g., pubs and clubs) than social disorganisation variables (e.g., welfare recipients) which, however, also have a significant contribution. Results show also that are no major differences between significant covariates in the day and night time distribution of robbery. Thus, the results presented in this paper provide support for the generalisibility of spatial theories of crime from the 'West' to Eastern European cities. (papers 3 and 5)

Robbery by hour: Cologne and Tallinn

Clusters of Robbery: Tallinn

Cluster of robbery - Tallinn
 

 

 

 

 

 

 

 

 

 

 

 

Cluster of vandalism - Tallinn