Journal of Social Research & Policy, Vol. 5, Issue 2, December 2014

Perceived Risk of Victimization in Estonia and Lithuania VIVIANA ANDREESCU1 Department of Criminal Justice University of Louisville, USA

Abstract The present comparative study tries to identify individual-level factors most likely to influence perceptions of safety in two Baltic States that according to recent Eurostat data continue to have the highest rates of lethal violence in the European Union. The analysis is conducted on representative samples of residents in Estonia (N=2380) and Lithuania (N=2109) and uses recent data from the European Social Survey (Round 6/2012). Empirical tests of three theoretical approaches frequently used in fear-of-crime research (i.e., the crime-experience perspective, the vulnerability perspective, and the integrative model of fear of crime) show support for these perspectives in various degrees. Although inter-country differences do exist in terms of prior victimization, perceived safety, and the effect of fear-of-crime correlates, results of the overall sample indicate that residents who feel unsafe in their neighborhoods are more likely to be persons who directly or indirectly experienced victimization, persons who might perceive themselves as being unable to respond properly when facing potential criminals (e.g., females, persons with disabilities, people who live alone, economically-disadvantaged individuals, and ethnic minorities), and residents of large urban areas, where crime is more likely to occur. Conversely, in both countries, persons who are part of social networks and have higher levels of interpersonal trust are also more likely to feel safe in their local areas.

Keywords: Crime; Victimization; Fear of Crime; Perceived Safety; Baltic Countries; Estonia; Lithuania.

Introduction For the past five decades, in addition to examining the extent and causes of criminal behavior, researchers directed their attention to people’s subjective reaction to crime. As Gray, Jackson & Farrall (2008) noted, fear of crime has become a frequent object of scientific inquiry because people’s concerns with potential victimization may not only affect one’s quality of life, but could have detrimental effects on interpersonal relations and community life in general (Andreescu, 2013). Additionally, the levels of fear of crime in different societies have been examined because they may reflect not only individual insecurities about safety but also broader societal anxieties (see Hummelsheim et al., 2011, p. 327). Even if for a small number of individuals, who are able to convert constant worries about crime into constructive actions that would prevent victimization, fear of crime could be actually functional (see Jackson & Gray, 2010), as several researchers (Adams & Serpe, 2000; Collins, 2007; Hanslmaier, 2013) pointed out, most individuals who live in fear of becoming victims of crime have their general well-being and social life negatively affected by frequent or even occasional feelings of insecurity. Moreover, (see Maxfield, 1984) when people see the environment they live in as being unsafe, interpersonal relations change and the community’s cohesiveness decreases diminishing its capacity to act as an effective source of informal social control in the fight against crime (Andreescu, 2013); fear of crime may also obstruct the citizens’ desire to cooperate with the police and help them solve and prevent crime, as some researchers found (Ceccato & Lukyte, 2011). 1

Postal address: 202B Brigman Hall, Department of Criminal Justice, University of Louisville, Louisville, KY 40292, USA; E-mail Address: [email protected]

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However, fear of crime is a subjective feeling and its intensity is not always in accordance with local crime levels (Hanslmaier, 2013). For instance, several studies published in recent years found that citizens of former communist states in Europe tend to have higher levels of fear of crime than residents of other countries in the region, despite the fact that crime levels and crime trends in these states are not significantly different from those recorded in other European countries that do not share a communist past (Andreescu, 2010; Jackson & Kuha, 2014). As international crime victimization surveys conducted on representative samples of the population between 1992 and 1996 in 40 countries of the world show, respondents in former communist countries in Eastern and Central Europe (EEC) expressed the highest level of perceived unsafety. Results indicate that almost half (49%) of the respondents in twelve EEC countries felt unsafe in their neighborhoods, while only 29% of the respondents in European Union countries shared the same worries about being victimized (van Dijk & Toornvliet, 1996). An analysis of crime victimization surveys in urban Europe (N=24) found that Vilnius, the capital city of Lithuania, had in 2000, the highest percentage of residents (67%) who felt unsafe walking alone in their neighborhoods after dark. On average, about 51% of the urban residents of EEC countries expressed a high or very high fear of victimization, while only 24% of residents in Western Europe had similar concerns about crime (Del Frate & Van Kesteren, 2004). A recent multilevel analysis of fear of crime based on data collected in 2004/2005 from representative samples in 23 European countries found the highest level of fear of crime in Estonia, the only Baltic country included in the sample, where about 40% of the residents declared they feel unsafe or very unsafe walking alone in their area after dark. With the exception of Slovenia, where only 9.7% of the population expressed high levels of perceived unsafety, all Eastern European countries included in the analysis (Hungary, Poland, the Czech Republic, and Slovakia) had the highest percentages of people feeling insecure (i.e., rates varied among these countries from 30.8% in Hungary to 39.7% in Slovakia) (Hummelsheim et al, 2011). The present inter-country comparative analysis focuses on two member states of the European Union (Estonia and Lithuania), where, as previously noted, a significant part of the residents preserved over the years quite intense feelings of insecurity. While similar to other EEC states, in both countries conventional crime rates registered a descending trend (see Clarke, 2013), especially after both states joined EU in 2004, recent accounts (see Eurostat, 2014) indicate that Lithuania and Estonia continue to have the highest rates of lethal violence in the European Union, a fact that might explain why residents in these two countries see themselves as facing a higher risk of criminal victimization. This empirical analysis will compare the inter-country levels of perceived unsafety and will also determine if there are variations in personal and vicarious victimization rates between Estonians and Lithuanians. The paper will also examine the effect of several individual-level predictors on perceived risk of victimization and will observe potential inter-country differences in the strength and direction of the fear-of-crime correlates. Visser, Scholte & Scheepers (2013, p. 279) recently noted that there is a lack of comparative research on fear of crime and feelings of unsafety in European countries. The current comparative study intends to reduce this gap in the literature. In addition to contributing to the scholarly body of cross-national research on crime victimization and fear of crime in Europe, the present study, conducted in two countries that did not benefit lately from extensive criminological research, will provide specific information that law enforcement professionals and policy makers in both Baltic states could use when trying to formulate crime prevention and safety strategies meant to target population groups that feel insecure and/or face higher victimization risks. Estonia and Lithuania: Societal similarities and differences Although Estonia and Lithuania have a lot in common in terms of geographic location (i.e., both Baltic states are located on the European Union’s most eastern borders), post-WWII history (i.e., both countries spent much of the last century incorporated in the Soviet Union; upon independence in 1991, they quickly sought to join the NATO alliance and the European Union and in 2004, they both became NATO and EU member states), economic policies (i.e., both countries have liberalized, open market economies), current government type and legal systems

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(i.e., both states are parliamentary democracies with multi-party systems; both have civil law systems), there are some socio-economic and demographic differences between them as well. Based on 2014 estimates, Lithuania, with a population of approximately 3.5 million people, is almost three times more populous than Estonia. While both countries are ethnically diverse, compared to Estonia, Lithuania appears to be more homogenous in terms of ethnic and religious characteristics. Ethnic minorities represent about 31% of the population in Estonia and about 16% in Lithuania. Ethnic Russians account for a quarter (24.8%) of the population in Estonia and only for 5.8% in Lithuania. Most residents of Lithuania (77.2%) are Roman Catholics, while more than half of Estonia’s residents (54.1%) appear to be atheists (Central Intelligence Agency/CIA, 2014a, 2014b). In 2012, when the present study was conducted, compared to Estonia, Lithuania had a lower GDP per capita ($14,432 vs. $17,490), a higher overall unemployment rate (13.2% vs. 10.1%) and youth unemployment rate (26.2% vs. 21%), a lower ‘rule of law’ index (0.81 vs. 1.13), a lower life expectancy (73.86 vs. 76.33), and a higher death rate (13.7 vs. 11.7) (World Bank, n. d.). Regarding criminal activity, its structure and prevalence, Estonia and Lithuania also share certain similarities, as well as differences. Recent crime assessments indicate that since joining the European Union and the Schengen Accord Estonia has become a growing producer of synthetic drugs and an increasingly important transshipment zone for cannabis, cocaine, opiates, and synthetic drugs (CIA, 2014a; Hanley-Giersch, 2009). Yet, analysts consider the current organized criminal activity in the country as being limited (Overseas Security Advisory Council /OSAC, 2014a). The Estonian Ministry of Justice (MOJ) indicated that 39,631 crimes were reported to the police in 2013. The clearance rate for all crime events was 52.6%, meaning that no arrests have been made in almost half of the cases. Compared to 2012, the number of thefts (16,465) committed in 2013 decreased by 12% and the number of robberies (458) dropped by 13%. In 2013, there were registered 50 homicides and almost 25% of all violent crimes were classified as domestic violence offenses (Overseas Security Advisory Council /OSAC, 2014a). Over the last two decades the calculated homicide rate, which based on the country’s legislation also included attempted murders, continued to decrease in Estonia from a high rate of 25.0 per 100,000 people in 1994 to 7.0 per 100,000 people in 2009 (Saar, 2010). Eurostat reports that include only committed murders show an average homicide rate of 5.57 per 100,000 for the years 2008-2010 (Clarke, 2013). Although homicide rate continuously decreased in the country (see Ceccato, 2008), the current homicide rate of approximately 3.97 per 100,000 people continues to be above the EU average and remains the second highest in the European Union. MOJ connects the majority of homicides in Estonia to alcohol abuse and easy access to illegal firearms and edged weapons. Tallinn, the capital city, which in the early 1990s was considered one of the world’s most violent capitals (see Hanley-Giersch, 2009), and the county that houses the Estonian/Russian border town of Narva remain the leaders in per capita criminal incidents (Overseas Security Advisory Council /OSAC, 2014a). According to a 2006 U.S. Department of State report, combating drug-related crimes was at the time a priority for the police agencies in Lithuania. The same report noted that an increase in the rate of illegal drug use has resulted in an increasing number of high-risk crimes (US Department of State, 2006). Currently, similar to Estonia, Lithuania is considered a transshipment and destination point for cannabis, cocaine, ecstasy, and opiates from Southwest Asia, Latin America, and Western Europe and is viewed as an increasingly competitive producer of high-quality amphetamines (CIA, 2014b). Different from Estonia, crime analysts consider that organized crime poses a large problem in the country and is the focus of several Lithuanian law enforcement entities (OSAC, 2014b). From 2002 to 2012, the total number of crimes reported to the police in Lithuania varied from a high 84,100 in 2004 to a low 68,000 in 2007 (Eurostat, 2014). Compared to 2012, the number of crimes reported to the police (84,715) in Lithuania in 2013 increased by 2.7% (Overseas Security Advisory Council /OSAC, 2014b). In 2012, there were registered 2,800 violent crimes and 1,923 robberies, figures still high, but lower than in previous years. Despite the fact that the average 2010-2012 homicide rate of approximately 6.9 per 100,000 inhabitants is much lower than the mean homicide rate for the years 2008-2010 (7.7 per 100,000 inhabitants) or 2005-2007

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(9.69 per 100,000), Eurostat data show that Lithuania continues to have the highest homicide rate in the European Union (Eurostat, 2014). In 2012, when survey data were collected, compared to Estonia, Lithuania had a higher imprisonment rate per 100,000 people (275 vs. 252), a robbery rate per 100,000 almost twice higher than in Estonia (63.5 vs. 35.4), and a much higher homicide rate per 100,000 (6.7 vs. 5) (World Bank, n.d.). Theoretical explanations of fear of crime Given the researchers’ inability to identify consistently a positive correlation between crime rates and people’s levels of perceived unsafety, scholars focused their attention on other factors that might influence variations in personal levels of fear of crime (Jackson, 2009). Based on an extensive review of the literature, Halle (1996) concluded that the three theoretical approaches, frequently tested in studies of fear of crime, are the vulnerability perspective, the experience with victimization perspective, and the ecological perspective, which takes into account the effect of contextual factors on fear of crime or perceived risk of victimization (Andreescu, 2013). From a vulnerability perspective, it is hypothesized that persons who perceive themselves as being unable to successfully defend themselves in threatening circumstances, such as women, the elderly, persons belonging to minority groups, and/or individuals who are marginalized economically and socially, will have higher levels of fear of crime. With few exceptions, at least partial support for this theoretical perspective was generally found. In particular, if the effect of age on perceived risk of victimization varied among studies (see Andreescu, 2013 for additional details), gender was consistently able to differentiate between not-fearful and fearful groups (see Chiricos, Hogan & Gertz, 1997; De Donder, Verte & Messelis, 2005; Garofalo, 1979; Lagrange & Ferraro, 1989; Lane & Meeker, 2000; Liu et al., 2009; Reese, 2009; Scott, 2003; Taylor, Eitle & Russell, 2009; Ziegler & Mitchell, 2003). Similar to age, the variable race or ethnic minority status did not always have the predicted effect on fear of crime. While some studies (e.g., Hough, 1995; Jordan & Gabbidon, 2010; Salisbury & Upson, 2004; Skogan & Maxfield, 1981; Walker, 1994) found that ethnic/racial minorities were more fearful than the majority of the population, other researchers (Andreescu, 2013; Wyant, 2008) did not find that one’s race/ethnicity significantly impacts variations in public perceptions of safety. While several studies (Andreescu, 2013; Jordan & Gabbidon, 2010; Lane & Meeker, 2000; Lee & Ulmer, 2000; Scott, 2003; Taylor, Gottfredson & Brower, 1984) acknowledged based on research results, that persons who are economically marginalized also expressed higher levels of fear, other researchers (Clemente & Kleiman, 1977; Toseland, 1982; Wyant, 2008), did not discover a significant relationship between one’s socio-economic status and perceived risk of victimization. According to an alternative theoretical perspective, individuals who have been exposed to crime (directly or indirectly) are expected to have higher levels of fear of crime than people who did not experience personal or/and vicarious victimization. Nonetheless, empirical support for the victimization perspective is partial as well. Whereas some researchers found a significant negative relationship between victimization and one’s level of perceived safety (Andreescu, 2010, 2013; Ferraro, 1995; Kanan & Pruitt, 2002; Lee & Ulmer, 2000; Reese, 2009; Skogan & Maxfield, 1981; Taylor, Eitle & Russell, 2009; Yun, Kercher & Swindell 2010), other studies (Clemente & Kleiman, 1977; Liska, Lawrence & Sanchirico, 1982) did not find a significant relationship between victimization and fear of crime. From the ecological perspective, it is generally anticipated that in addition to individual-level characteristics there are certain contextual factors (e.g., degree of urbanization, population size of the residential area, neighborhood disorder, community cohesiveness, attitudes toward the police, and so on) that might contribute to one’s perceptions of safety. In general, researchers were able to substantiate support for this perspective. For instance, Bankston et al., (1987), Keane (1992), or Scott (2003) found a positive relationship between the degree of urbanization and fear of crime, while Clemente & Kleinman (1977) and Toseland (1982) contended that fear of crime increases with an increase in population size. Additionally, researchers found that people who live in well-integrated communities, those who trust their fellow citizens or/and have positive

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attitudes toward the institution meant to protect them against crime tend to feel safer and worry less about neighborhood crime (see Andreescu, 2010, 2013; Dowler & Sparks, 2008; Gibson et al., 2002; Hawdon & Ryan, 2003; Tewksbury & West, 2001; Weitzer & Tuch, 2005). Hypotheses Based on the theoretical perspectives previously described, it is hypothesized that in both countries, individuals with real or perceived vulnerabilities, such as females, persons with disabilities, persons who live alone, ethnic minorities, and those who are economically marginalized will express higher levels of fear of crime. Additionally, residency in large urban areas and experience with victimization are expected to be positively related to perceived unsafety. At the same time, it is anticipated that persons who socialize more and trust people in general, as well as those who have confidence in an institution meant to prevent and fight crime will feel safer than, respectively, individuals who tend to be socially isolated, those with lower interpersonal trust, and persons who express low trust in the police. In addition to individual-level predictors, country-specific socio-economic contextual factors should be considered as well when examining variations in people’s fear of crime. To reiterate, in 2012, when the ESS6 survey was conducted, Lithuanians, more than Estonians, were facing not only more economic problems, such as higher unemployment rates, but also higher levels of lethal violence, higher robbery rates, and more intense organized criminal activities. Taking into account these inter-country differences in societal conditions, it is anticipated that residents of Lithuania, who might consider themselves as being more vulnerable socially and economically, will also feel less safe and at a higher risk of criminal victimization than residents of Estonia. 2 Data & methods The analysis presented in this paper is based on data collected in 2012 from representative samples of residents in Estonia (N = 2380) and Lithuania (N = 2109), who participated at the European Social Survey (ESS Round 6, 2012, 2014). In order to identify the individual-level factors more likely to explain variations in perceived safety and to see if there are inter-country differences regarding the effects of the fear-of-crime correlates, several statistical models have been created. To facilitate further potential inter-country comparisons, the variable selection and coding procedures are similar to those used in prior cross-national studies examining fear of crime at the country level in Europe (see Andreescu, 2010, 2013). The dependent variable, perceived unsafety is based on the only question (i.e., “How safe do you feel of walking alone in local area after dark?”) used in ESS6 to measure respondents’ fear of crime. Several prior studies made use of this standard measure of safety as a proxy for fear of crime (Baumer, 1985; Maxfield, 1984; Skogan & Maxfield, 1981). The variable3 has been recoded into a dummy variable and respondents who declared they feel ‘unsafe’ and ‘very unsafe’ were coded 1, while the others were coded zero. 2

Although differences in contextual factors at the country level may affect the way independent variables relate to the dependent variable in each country, the present analysis is conducted only at one level of analysis, the individual level, and such impact cannot be directly estimated. Further research based on multilevel analyses, however, should examine the effect on people’s feelings of unsafety of macro-level indicators characterizing larger units of analysis, such as neighborhoods, cities, or regions. 3 The original variable was an ordinal-level indicator (Likert-type scale) with four categories. However, in both subsamples there were persons (about 3% of the entire sample) who had no opinion or were undecided, negatively affecting the normal distribution of the variable, if these response categories would have been placed in the middle of the scale (no safe/no unsafe)], limiting the number of statistical procedures that could be used to analyze the data without violating statistical assumptions. Taking into account the fact that the main objective of the analysis was to determine what characteristics have those individuals who feel unsafe and very unsafe vs. those who do feel safe or do not seem to worry about crime, a dichotomy was created. Information was not lost and all cases could be preserved in the analysis. Logistic regression, a statistical procedure that can be successfully applied when there is an unequal split in the sample has been used in multivariate analyses.

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This empirical study examined the simultaneous effect on the dependent variable of a set of predictors selected in accordance with three theoretical approaches frequently used when examining fear of crime (see Halle, 1996): the crime-experience perspective, the vulnerability hypothesis, and the integrative model of fear-of-crime correlates. The independent variables are: experience with victimization (coded 1 if the respondent or other household member had been a victim of burglary or assault during the last five years and coded zero otherwise), gender (coded 1 for females and zero for males), disability status (coded 1 if the respondent declared that he/she is all the time hampered in daily activities by illness/disability/infirmity/mental problem and zero otherwise), economic disadvantage (coded 1 if the respondent declared that it is very difficult to live on present income, and zero otherwise), ethnic minority status (coded 1 for respondents belonging to ethnic minority groups and zero otherwise), household size (respondents living alone were coded 1 and those in households with two or more members were coded zero), and residency (coded 1 for people living in large cities and zero otherwise). Due to relatively high correlations between age and disability status, particularly in the Lithuanian subsample where the bivariate correlation coefficient Pearson’s r was .54 (p = .000), the respondent’s age was not used in the analysis. Moreover, two composite measures have been created to determine if one’s level of social integration is influencing perceptions of safety. Interpersonal trust is based on three questions (i.e., Most people can be trusted or you can’t be too careful; Most people try to be fair or try take advantage of you; Most of the time people are helpful or mostly looking for themselves), each with scores that varied from 0 (complete distrust) to 10 (complete trust). A factor of interpersonal trust has been computed through principal component analysis. Only one factor has been extracted (Eigenvalue = 2.095; variance explained = 69.8%). The factor loadings varied from .814 to .845 and the Cronbach’s reliability coefficient Alpha for this index was .783. Social capital is an index created by combining responses at two questions (“How often do you meet socially with friends, relatives, or colleagues?” and “How often do you take part in social activities compared to others of the same age?”). The Cronbach’s reliability coefficient Alpha for this index was .569 and when principal component analysis has been used only one factor has been extracted (Eigenvalue = 1.451; variance explained = 72.6%), with factor loadings equal to .852. Lastly, the analysis also examined the respondent’s perceived trust in the police on one’s sense of safety. The variable takes values from zero (complete distrust) to ten (complete trust). Results Table 1 presents the descriptive statistics (means and standard deviations) for each subsample. It can be observed that about four out of ten people in Lithuania (44%) and one third of Estonians (33%) feel (very) unsafe when walking alone at night in their neighborhoods. Table 1: Descriptive statistics (N = 4489) Lithuania (N=2109) Estonia Mean SD Mean Perceived unsafety .44 .49 .33 Experience with victimization .11 .31 .21 Health problems/disability .32 .47 .29 Financial difficulties .10 .29 .11 Gender (female) .58 .49 .58 Household size (lives alone) .23 .42 .24 Ethnic minority .06 .24 .20 Residential area (big city) .34 .48 .27 Interpersonal trust .00 1.00 .00 Social capital .04 1.03 -.03 Police trust 5.52 2.50 5.90 Variable

(N=2380) SD .47 .41 .45 .31 .49 .42 .40 .45 1.00 .97 2.50

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Although the percentage of those who fear crime is higher in Lithuania than in Estonia, the percentage of those who actually experienced victimization (directly or/and indirectly) in Lithuania (11%) is almost twice lower than in Estonia (21%). Results of an independent-samples t-test (t = 5.003; p = .000) indicate that the level of trust citizens have in their police, while moderate in both countries, is significantly higher in Estonia than in Lithuania. While there is no inter-country difference in the level of interpersonal trust, the level of social capital, is significantly higher in Lithuania than in Estonia (t = 2.188; p = .029). Table 2 presents the results of the logistic regression, the statistical procedure used to estimate the simultaneous effect of the selected set of predictors on fear of crime in the overall sample and comparatively in the two subsamples. It can be noticed that, when controlling for the rest of predictors included in the model, the level of perceived unsafety is significantly higher in Lithuania when compared to Estonia. The value of the odds ratio is more than twice higher [Exp(B)=2.358; p =.000] in Lithuania compared to the reference category, Estonia, suggesting that Lithuanians are 136% more likely than Estonians to feel unsafe at night in their local areas. Ethnic minorities [Exp (B) =2.469; p =.000], victims of crime [Exp (B) =2.206; p =.000], and women [Exp (B) =2.171; p =.000] are more than twice more likely to feel unsafe than, respectively, the ethnic majority, those who did not experience victimization, and men. Table 2: Logit estimates for fear of crime in the Baltic region Total (N=4489) Lithuania (N=2109) Estonia (N=2380) B Exp p B Exp p B Exp p Variables (SE) (B) (SE) (B) (SE) (B) Country .858 2.358 .000 (Lithuania) (.075) .791 2.206 .000 1.687 5.403 .000 .404 1.498 .001 Victimization (.095) (.182) (.124) -.225 .798 .000 -.180 .835 .001 -.261 .770 .000 Interpersonal trust (.038) (.055) (.056) -.206 .814 .000 -.174 .840 .001 -.179 .836 .001 Social capital (.037) (.053) (.055) .037 1.038 .015 .131 1.140 .000 -.052 .950 .020 Police trust (.015) (.022) (.022) .904 2.469 .000 .346 1.413 .104 .872 2.392 .000 Ethnic minority (.109) (.213) (.131) Health problems .210 1.234 .008 .525 1.690 .000 -.010 .990 .930 (disability) (.079) (.119) (.113) Financial .243 1.276 .000 .194 1.214 .005 .283 1.327 .000 difficulties (.074) (.069) (.068) .775 2.171 .000 .491 .1.634 .000 1.079 2.941 .000 Gender (female) (.074) (.105) (.111) Household size .205 1.228 .017 .100 1.105 .440 .250 1.283 .038 (lives alone) (.086) (.129) (.120) Residential area .674 1.962 .000 .185 1.203 .005 1.048 2.851 .000 (big city) (.077) (.109) (.114) .063 .000 .121 .000 .081 .000 Constant 2.770 2.114 2.513 (.169) (.217) (.244) Pseudo R2 .197 .178 .249 (Nagelkerke) As hypothesized, persons who live alone, those who are in poor health, those who experience serious financial difficulties and residents of large urban areas tend to have significantly higher levels of fear of crime. On the other hand, persons who socialize frequently and those who trust their fellow citizens tend to feel safer and express significantly lower levels of fear of crime.

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Significant bivariate correlations between interpersonal trust and perceived safety indicate that lower levels of fear of crime might in turn positively impact people’s trust in their fellow citizens, the relationship between the two variables being bi-directional. Contrary to the expectations, in the overall model, trust in the police is significantly and positively associated with feelings of insecurity. Two additional statistical models examine the effects of the independent variables separately in each subsample. It can be noticed that the explanatory power of the model is higher for the Estonian subsample (Pseudo R2 /Nagelkerke = .25) when compared to the Lithuanian subsample (Pseudo R2 /Nagelkerke = .18), suggesting that the selected predictors tend to explain better variations in perceived safety in Estonia than in Lithuania. While in the Estonian subsample only one predictor (health impairment) is not significantly associated with the dependent variable at a probability level lower than .05, in the Lithuanian subsample two independent variables (ethnic minority status and household size/living alone) are not significantly associated with perceived unsafety at p < .05. Results (see Table 2) show similarities and differences between the two Baltic countries. Although in both countries persons who have been victimized directly or indirectly tend to express significantly higher levels of fear of crime, the effect of prior victimization is much stronger in Lithuania than it is in Estonia. While an Estonian who experienced victimization is 1.5 times more likely to be afraid of walking alone at night than a fellow citizen who was not a victim of crime [Exp (B) = 1.498; p = .001], a Lithuanian who was a victim of crime would be 5.4 times more afraid of being victimized again [Exp (B) = 5.403; p = .000] than a resident who was not a victim of crime in the recent past. Conversely, gender and residency, while they are significant predictors in both subsamples, they have a much stronger effect in Estonia than they do in Lithuania. In other words, compared to an Estonian man, an Estonian woman is almost three times more afraid of walking alone at night in her neighborhood [Exp (B) = 2.941; p = .000], while a Lithuanian woman feels 1.6 times less safe walking after dark than a Lithuanian man does [Exp (B) = 1.634; p = .000]. Compared to persons who live in small towns, in suburban or in rural areas, Estonians who are living in big cities are almost three times more afraid of being victimized [Exp (B) = 2.851; p = .000], while Lithuanians who reside in large urban areas are only 1.2 times more afraid of walking alone at night in their city [Exp (B) = 1.203; p = .005]. In both subsamples economic insecurity is significantly related to fear of crime and in both countries persons who appear to be well integrated socially feel significantly safer than persons who do not socialize much and those who think people are generally untrustworthy. Inter-country comparisons show that the effects of these independent variables on perceived safety are quite similar. While trust in the police has a significant relationship with the dependent variable in both subsamples, the effect is positive in one country and negative in the other country. If Estonians who have confidence in their police tend to feel safer, Lithuanians who appear to trust the police are also more afraid of being victimized when walking alone at night. Household size appears to have a significant impact only in Estonia. Persons living alone in Lithuania are not significantly more afraid of victimization than persons living in larger households, but Estonians in one-person households feel significantly less safe. In Estonia, ethnic minorities appear to be 2.4 times more afraid of victimization [Exp (B) = 2.392; p = .000] than persons belonging to the majority group, while in Lithuania, ethnic minorities do not feel significantly less safe than the rest of the population. Discussion and conclusions Compared to data collected in previous rounds of the European Social Survey, the perceived risk of victimization slightly decreased in recent years, but remains relatively large in both countries. About 44% of the residents in Lithuania and about 33% of Estonians continued to fear victimization in 2012. Findings show support for all three theoretical perspectives simultaneously tested here. Different from other studies that did not identify a significant relationship between victimization and fear of crime, but consistent with other body of research

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(Andreescu, 2010, 2013; Ferraro, 1995; Kanan & Pruitt, 2002; Lee & Ulmer, 2000; Reese, 2009; Skogan & Maxfield 1981; Taylor, Eitle & Russell, 2009; Yun, Kercher & Swindell, 2010) in Estonia and Lithuania, fear of crime appears to be a reflection of actual victimization experiences. However, the impact of victimization on perceived unsafety is approximately three times higher in Lithuania compared to Estonia. At the same time, in concordance with actual crime rates, it should be reiterated that the proportion of Lithuanians who experienced personal and vicarious victimization is approximately twice lower than the proportion of Estonians who shared similar experiences. As hypothesized, when controlling for all the variables in the model, Lithuanians have a significantly higher level of fear of crime than Estonians do, suggesting that societal conditions, not accounted for in the model, might have indirectly affected Lithuanians’ feelings of safety more than their actual experience with victimization did. Without knowing the type of crimes respondents witnessed or experienced directly, and without having additional details about each case (e.g., one’s personal experiences with law enforcement agencies; proportion of persons directly victimized; violent vs. property crimes experienced; national media’s portrayals of criminal activity, media consumption, and so on) it is difficult to isolate the impact of the social environment from one’s personal experiences with crime and clearly explain why Lithuanians feel less safe than Estonians do, despite lower victimization rates and why they are more affected by crime than their Estonian counterparts. Nevertheless, it should be noted that even if significant decreases in violent crimes rates and lethal violence occurred in the country over the past decade, the 2010-2012 average national homicide rate continued to be higher in Lithuania than in any other EU country (see Eurostat, 2014), a fact that might have increased one’s overall perception of unsafety and risk of victimization. Additionally, the measure perceived unsafety was based on a question that asked respondents “how safe they feel walking alone at night in their local area” and as recorded in OSAC’s (2014b) crime and safety report for Lithuania, most incidents of violence recorded in the country typically occurred late at night. Moreover, Lithuanian residents of large cities appear to have a significantly higher victimization rate (Pearson’s r = .14; p< .05) than Lithuanians who live in smaller cities, suburban, or rural areas, while Estonians living in big cities were not victimized at a rate significantly different from the rest of the population (Pearson’s r = -.02; NS). It should be noted that in the overall sample the proportion of Lithuanians living in large urban areas is higher than the percentage of Estonians living in big cities, a fact that might have contributed to inter-country differences in perceived unsafety. Although in both countries living in large urban areas is associated with higher levels of fear of crime, it is possible that in Lithuania the “expressive” fear of crime (having anxiety about crime without having a real reason to feel at risk of victimization) increased the effect of the “experiential” fear of crime (see Farrall, Jackson & Gray, 2009), which was expressed more often by people living in big cities. Similar to results obtained in other studies, in both countries, bivariate correlations (not presented) indicate that persons who tend to be more afraid of potential victimization, such as women, the elderly, persons with disabilities, the poor, and those living alone experienced victimization significantly less or no differently than, respectively, men, younger persons, people in good health, better-off individuals, and those living in larger households. Although the vulnerability hypothesis is generally supported by the findings, inter-country variations in terms of the strength of the effects can be observed. As found in most studies that examined the fear of crime correlates, females had significantly higher levels of fear of victimization than their male counterparts and gender had the strongest effect on fear of crime in the Estonian subsample. Also, in both samples, persons who appear to be economically marginalized perceive themselves as being at a higher risk of victimization, even if in both countries persons who experienced financial difficulties were not victimized significantly more than the rest of the population. In the Lithuanian subsample, but not in the Estonian subsample, as hypothesized and consistent with prior research (Taylor, Eitle & Russell, 2009), persons with physical limitations and in poor health expressed higher levels of fear than individuals in good health. Estonians living alone feel significantly less safe than persons in larger households, but not Lithuanians living in one-person households.

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Interestingly, even if minority status and victimization were positively and significantly associated only in the Lithuanian subsample (Pearson’s r = .06; p < .05), being part of an ethnic minority group influenced significantly variations in fear of crime only in Estonia. Additional analyses revealed quite a strong correlation between ethnic minority status and perceptions of discrimination in Estonia (Pearson’s r = .47; p < .05). Additionally, 30.4% of the respondents who declared that Russian is the language most often spoken at home acknowledged discrimination, while only 3.2% of those whose first language is Estonian shared similar feelings. This suggests that ethnic minorities’ fear of crime could be in fact an expression of broader societal anxieties, possibly related to an inadequate level of integration in the Estonian society of certain minority groups, such as ethnic Russians. Although this analysis recognizes the merit of the vulnerability perspective, it offers a stronger support for the integrative model of fear of crime. Regarding the effect of contextual factors, residency in large urban areas was associated significantly with higher levels of fear of crime in both subsamples. However, Estonian urban residents tend to be much more afraid of victimization (r = .54; p < .05) than urban Lithuanians (r = .47; p < .05), even if only in Lithuania residency in large urban area and experience with victimization were positively and significantly correlated. As hypothesized, in both subsamples, social capital and collective efficacy are negatively related to fear of crime. Persons who socialize more, who live in areas where people are fair, trustworthy, and help each other tend to have significantly lower levels of fear of crime. Although in both subsamples, interpersonal trust and trust in the police are significantly and positively related (Estonia: r = .37; p < .05; Lithuania: r = .23; p<. 05), in multivariate analyses only in Estonia trust in the police and fear of crime are significantly and negatively related, as hypothesized and consistent with prior research (Andreescu, 2010; Dowler & Sparks, 2008; Hawdon & Ryan, 2003; Tewksbury & West, 2001; Weitzer & Tuch, 2005). Surprisingly, Lithuanians who trust the police appear to also express higher levels of perceived unsafety, suggesting that police actions, even if they are seen as effective and legitimate might not be able to change the Lithuanians’ perceptions of unsafety, especially if they reflect a generalized sense of insecurity at the societal level. Almost two decades ago, the Chamber of Local Authorities of the Council of Europe debated and approved a resolution stressing the fact that “crime, fear of crime and urban insecurity in Europe are of major public, professional and political concern and that finding satisfactory solutions to them is one of the main keys to civic peace and stability (Council of Europe, 1997, p. 1).” Even if inter-country differences exist regarding the strength and the direction of the selected predictors’ effects on perceived risk of victimization, the results of this analysis suggest that local authorities and law enforcement agencies in Estonia and Lithuania should continue their efforts of identifying effective crime deterrent mechanisms and should also try to build trust within communities. As this study shows, increased public confidence in the police might positively impact the citizens’ perceptions of safety at local and national levels and could also improve the communities’ capacity to control crime and reduce victimization risks. References 1.

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