Crime in Lithuania: The impact of accession to the European Union

European Journal of Criminology

Volumn 6, Issue 4, 2009, Pages 337-360

  Andresen, Martin A ^a  

^a SIMON FRASER UNIVERSITY   (Canada)

Author keywords

European Union; Lithuania; Property crime

Indexed keywords

EID: 66649114236     PISSN: 14773708     EISSN: 17412609     Source Type: Journal    
DOI: 10.1177/1477370809104685     Document Type: Article

References (52)

1. Andresen, M.A. (2006). Crime measures and the spatial analysis of criminal activity. British Journal of Criminology 46, 258-85.
2. Arvanites, T.M. and DeFina, R.H. (2006). Business cycles and street crime. Criminology 44, 139-64.
3. Baltagi, B.H. (2001). Econometric analysis of panel data, 2nd edn. Chichester: John Wiley.
4. Brame, R., Bushway, S., and Paternoster, R. (1999). On the use of panel research designs and random effect models to investigate static and dynamic theories of criminal offending. Criminology 37, 599-641.
5. Cahill, M.E. and Mulligan, G.F. (2003). The determinants of crime in Tucson, Arizona. Urban Geography 24, 582-610.
6. Cantor, D. and Land, K. (1985). Unemployment and crime rates in the post World War II United States: A theoretical and empirical analysis. American Sociological Review 50, 317-32.
7. Ceccato, V. (2007). Crime dynamics at Lithuanian borders. European Journal of Criminology 4, 131-60.
8. Ceccato, V. and Haining, R. (2005). Assessing the geography of vandalism: Evidence from a Swedish city. Urban Studies 42, 1637-56.
9. Ceccato, V., Haining, R., and Signoretta, P. (2002). Exploring offence statistics in Stockholm City using spatial analysis tools. Annals of the Association of American Geographers 92, 29-51.
10. Cohen, L.E. and Felson, M. (1979). Social change and crime rate trends: A routine activity approach. American Sociological Review 44, 588-608.
11. Felson, M. and Cohen, L.E. (1980). Human ecology and crime: A routine activity approach. Human Ecology 8, 398-405.
12. Felson, M. and Cohen, L.E. (1981). Modeling crime trends: A criminal opportunity perspective. Journal of Crime and Delinquency 18, 138-61.
13. Fisher, B.S. and Wilkes, A.R.P. (2003). A tale of two ivory towers: A comparative analysis of victimization rates and risks between university students in the United States and England. British Journal of Criminology 43, 526-45.
14. Gottfredson, D.C., McNeil III, R.J., and Gottfredson, G.D. (1991). Social area influences on delinquency: A multilevel analysis. Journal of Research in Crime and Delinquency 28, 197-226.
15. Greene, W.H. (2000). Econometric analysis, 4th edn. Upper Saddle River, NJ: Prentice Hall.
16. Grennes, T. (1997). The economic transition in the Baltic countries. Journal of Baltic Studies 28, 9-24.
17. Halvorsen, R. and Palmquist, R. (1980). The interpretation of dummy variables in semilogarithmic equations. American Economic Review 70, 474-5.
18. Hausman, J.A. (1978). Specification tests in econometrics. Econometrica 46, 1251-71.
19. Hirschi, T. and Gottfredson, M. (1983). Age and the explanation of crime. American Journal of Sociology 89, 552-84.
20. Hsiao, C. (2003). Analysis of panel data, 2nd edn. Cambridge: Cambridge University Press.
21. Jakubauskas, E.B. (2000). The Lithuanian economy on the threshold of the new millennium. Journal of Baltic Studies 31, 127-35.
22. Juska, A., Johnstone, P., and Pozzuto, R. (2004). The changing character of criminality and policing in post-socialist Lithuania: From fighting organized crime to policing marginal populations? Crime, Law, & Social Change 41, 161-77.
23. Kennedy, L.W. and Forde, D.R. (1990). Routine activities and crime: An analysis of victimization in Canada. Criminology 28, 137-52.
24. Kennedy, P.E. (2003). A guide to econometrics, 5th edn. Malden, MA: Blackwell Publishing.
25. Kennedy, P.E. (1981). Estimation with correctly interpreted dummy variables in semilogarithmic equations. American Economic Review 71, 802.
26. Kim, S. and Pridemore, W.A. (2005a). Social change, institutional anomie and serious property crime in transitional Russia. British Journal of Criminology 45, 81-97.
27. Kim, S. and Pridemore, W.A. (2005b). Poverty, socioeconomic change, institutional anomie, and homicide. Social Science Quarterly 86, 1377-98.
28. Kim, S. and Pridemore, W.A. (2005c). Social support and homicide in transitional Russia. Journal of Criminal Justice 33, 561-72.
29. Levitt, S.D. (2001). Alternative strategies for identifying the link between unemployment and crime. Journal of Quantitative Criminology 17, 377-90.
30. Linsky, A. and Straus, M. (1986). Social stress in the United States: Links to regional patterns in crime and illness. Dover, MA: Auburn House.
31. Miethe, T.D., Stafford, M.C., and Long, J.S. (1987). Social differentiation in criminal victimization: A test of routine activities/ lifestyle theories. American Sociological Review 52, 184-94.
32. Moulton, B.R. (1986). Random group effects and the precision of regression estimates. Journal of Econometrics 32, 385-97.
33. Moulton, B.R. (1987). Diagnostics for group effects in regression analysis. Journal of Business and Economic Statistics 5, 275-82.
34. Nagin, D.S. and Paternoster, R. (1991). On the relationship of past to future participation in delinquency. Criminology 29, 163-289.
35. Paternoster, R., Bushway, S., Brame, R., and Apel, R. (2003). The effect of teenage employment on delinquency of problem behaviors. Social Forces 82, 297-335.
36. Pridemore, W.A. (2005). Social structure and homicide in post-Soviet Russia. Social Science Research 34, 732-56.
37. Pridemore, W.A. and Kim, S. (2007). Socioeconomic change and homicide in a transitional society. Sociological Quarterly 48, 229-51.
38. Pridemore, W.A. and Shkolnikov, V.M. (2004) Education and marriage as protective factors against homicide mortality: Methodological and substantive findings from Moscow. Journal of Quantitative Criminology 20, 173-87.
39. Rice, K.J. and Smith, W.R. (2002). Socioecological models of automotive theft: Integrating routine activity and social disorganization approaches. Journal of Research in Crime and Delinquency 39, 304-36.
40. Sampson, R.J. and Groves, W.B. (1989). Community structure and crime: Testing social-disorganization theory. American Journal of Sociology 94, 774-802.
41. Sampson, R.J. and Wooldredge, J.D. (1987). Linking the micro- and macro-level dimensions of lifestyle-routine activity and opportunity models of predatory victimization. Journal of Quantitative Criminology 3, 371-393.
42. Shaw, C.R. (1929). Delinquency areas. Chicago, IL: University of Chicago Press.
43. Shaw, C.R. and McKay, H.D. (1942). Juvenile delinquency and urban areas: A study of rates of delinquency in relation to differential characteristics of local communities in American cities. Chicago, IL: University of Chicago Press.
44. Simcha-Fagan, O. and Schwartz, J.E. (1986). Neighborhood and delinquency: An assessment of contextual effects. Criminology 27, 27-55.
45. Smith, W.R., Frazee, S.G., and Davison, E.L. (2000). Furthering the integration of routine activity and social disorganization theories: Small units of analysis and the study of street robbery as a diffusion process. Criminology 38, 489-523.
46. Stark, R. (1996). Deviant places: A theory of the ecology of crime. In P. Cordella and L. J. Seigel (eds) Readings in contemporary criminological theory, 128-42. Boston, MA: Northeastern University Press.
47. Trefler, D. (2004). The long and short of the Canada-U.S. Free Trade Agreement. American Economic Review 94, 870-95.
48. Tseloni, A., Osborn, D.R., Trickett, A., and Pease, K. (2002). Modelling property crime using the British Crime Survey: What have we learnt? British Journal of Criminology 42, 109-28.
49. Tseloni, A., Wittebrood, K., Farrell, G., and Pease, K. (2004). Burglary victimization in England and Wales, the United States and the Netherlands. British Journal of Criminology 4, 66-91.
50. Van Wilsem, J. (2004). Criminal victimization in cross-national perspective. European Journal of Criminology 1, 89-109.
51. Wooldridge, J.M. (2002). Econometric analysis of cross section and panel data. Cambridge, MA: MIT Press.
52. Worrall, J.L. and Pratt, T.C. (2004). On the consequences of ignoring unobserved heterogeneity when estimating macro-level models of crime. Social Science Research 33, 79-105.