COLLATING LONGITUDINAL DATA ON CRIME, VICTIMIZATION AND SOCIAL ATTITUDES IN ENGLAND AND WALES: A NEW RESOURCE FOR EXPLORING LONG-TERM TRENDS IN CRIME

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Introduction
This article describes the availability, methodological advantages and challenges of a series of new longitudinal data sets that combine data on crime, victimization, fear of crime and social attitudes to crime, collated from a range of existing but separate sources-integrating aggregate and individual-level data.These data have enabled us to undertake a multidisciplinary long-term evaluation of the impact of Thatcherite social and economic policies on crime rates in England and Wales-an intellectual project that has been funded by the Economic and Social Research Council (ESRC) and the British Academy (see Farrall and Hay 2014 and ESRC award numbers ES/K006398/1 and RES000222688).We anticipate that the data sets will be of use to researchers working in criminology and criminal justice who wish to explore long-term trends relating to crime.Here, we outline the importance of understanding long-term trends in crime and attitudes towards crime, the contents and organization of the data and how they might be used in future research.Given that the technical documentation supplied with the data sets will focus on practical issues such as recoding and weighting of variables and the provenance of the data, our aim in this study is to outline some of the important theoretical and empirical questions that might be addressed with the data sets and also to discuss some of the limitations associated with data of this sort.

The Long View: Identifying the Long Shadow of Thatcherism on Crime
Few would doubt that Margaret Thatcher's period as Prime Minister (from May 1979 to November 1990) was one of considerable social and economic turbulence.
De-industrialization, which can be traced back to the 1960s, accelerated, vast parts of the British economy were comprehensively restructured (manufacturing declined by about a half, putting many out of work, decimating whole communities and leading to a stark rise in economic inequality); new sectors of the economy (especially banking, insurance and the service sector) became core to domestic economic output (Crafts 1991;Glennerster 1994).In addition, and as has been well-documented elsewhere, council houses were sold off, local governments' control of schooling and other public services challenged, and trade union powers were significantly contracted (Walker and Walker 1997).Rules relating to who and what could be claimed from the social security system were also modified (Walker 1993).Perhaps unsurprisingly, officially recorded crime rates-self-reported victimization rates too-rose significantly and consistently (Morgan 2014). 1 Studies have since shown that as levels of unemployment and inequality rose, so too did rates of property crime (Morgan 2014).More surprisingly, however, although Thatcher spoke out about crime and 'law and order', her government did not pass the draconian acts one might have expected given her electoral rhetoric and that of successive British governments since 1979, despite rising crime rates.In her final 1979 general election broadcast, she referred to citizens needing to feel 'safe in the streets' (cited in Riddell 1985: 193).She also repeatedly stated that she was in favour of capital punishment (Thatcher 1993: 307).
Although social science research has gone some way to broadening our understanding of the long-term impact of Thatcherite public policy, other crucial questions remain unanswered.For example, what happened to those parts of England, Wales and Scotland in which de-industrialization had been most rampant?Were rises in property crime higher in certain areas of England and Wales than others?Was fear of crime linked to the marked incidence of property crime?How did such changes alter social attitudes not just towards the treatment of offenders, but towards those associated with crime in the popular imagination, such as welfare recipients?Did these tumultuous changes create a new set of social attitudes for young people who grew up during the 1980s-and who are now a growing part of the electorate?We know relatively little beyond the national picture in terms of the economy-crime link.But what is the picture when one explores violent crime or other forms of social harm (such as non-accidental deaths and alcoholism)?Notably, scholars from related branches of social policy have also begun to conduct allied longitudinal investigations in housing policy (Dorling 2014), opiate drug-use (Morgan 2014), education policy (Berridge et al. 2001) and social attitudes (Duffy et al. 2013;Natcen 2014), highlighting the need to build an integrated model of analysis.Moreover, research has demonstrated that how individuals relate to their environment and community can impact upon their feelings about crime (Farrall et al. 2009) as well as the rate of reporting crimes (Goudriaan et al. 2006) and perception of neighbourhood disorder (Sampson and Raudenbush 2004).And finally, taking a longitudinal approach, we might expect to see lifecycle, cohort and period effects (Ryder 1965); so we asked ourselves whether or not we were witnessing the emergence of 'Thatcher's Children' 2 in terms of attitudes towards law and order and social welfare (Duffy et al. 2013;Perchard 2013).Put simply, the analyses undertaken so far provide us with few answers to these theoretically exciting and methodologically important questions.

Building an Integrated Set of Data Sets Relating to Crime, Criminal Justice and Social Attitudes
In order to explore these questions in more detail, we have created a series of data sets drawn from national-level surveys (which incorporate demographic markers such as age, education, household income, region and gender) and official statistics.Specifically, these adapt and integrate individual-and aggregate-level data sources, and can be linked through common variables, most notably the observed time period (i.e. by year) but also categories of respondent (e.g. by age, ethnicity, income, region, and employment status).Features of the content and structure of the data sets are described below (we do not report full details of the survey items, but identify some important components), and summarized in Table 1.

Individual-level variables and data sets Victimization
Officially recorded crime statistics have been held in suspicion by many criminologists (Maguire 2007).Our data incorporate self-reported data on victimization from the British Crime Survey (BCS), now known as the Crime Survey for England  1981-2013 1983-2012 2004-13 and Wales (CSEW).3This records respondents' experiences, within the preceding 12 months, of most forms of crime (albeit with some omissions). 4In addition to measures of victimization, the BCS includes a series of questions on topics such as fear of crime, perceptions of anti-social behaviour in the local area, confidence in the police and criminal justice system and attitudes towards punishment.Because over time there is drift in some response categories, such as household income and ethnicity (in the former case, inflation leads to changes in the categories, whereas in the latter, the number of categories increases over time reflecting increasing diversity of the population), the data are recoded where necessary to create continuous measures over time.This is not possible in instances where a survey question changes, for example, from a four-point to a five-point scale (as is the case with confidence in local police, which used a four-point scale between 1982 and 2003, and a five-point scale since 2003).Instead, new variables are created (with names incorporating the time period) to make these discontinuities clear to users.In total, the BCS data set consists of 599,517 respondents and over 100 variables (though not all survey items are asked in every year, and some are only asked a couple of times during the 30-year period).

Social attitudes
Our data on public attitudes toward crime and criminal justice, and other domains of social and economic life, is drawn from two main sources.Firstly, we have drawn on the 28 waves of the British Social Attitudes Survey 5 (BSA) between 1983 and 2012.This provides attitudinal data, for example, on popular attitudes towards the role of the government in society, attitudes about income inequality and redistribution, and whether benefits for the unemployed are too high or too low.The BSA also includes questions about whether the death penalty should be reinstated, the need for people to obey the law, whether or not lawbreakers should be given stiffer sentences and the degree to which welfare recipients 'fiddle' benefits.These survey items provide measures of social attitudes towards sentencing, punitiveness and the image of those on welfare.The BSA data set consists of 80 variables (not including demographic markers) and a total of 89,466 respondents over the period between 1983 and 2012.Secondly, we use the British Election Study's Continuous Monitoring Survey (BES-CMS) to construct a data set of socio-political attitudes, including perceptions of the crime situation and satisfaction with the criminal justice system, salience of the issue, evaluations of government/party handling of crime and emotions about crime.The survey also includes standard questions on political attitudes (e.g.partisanship, government and prime ministerial approval, vote intention) as well as on broader questions about social and political trust, participation and civic behaviours.This consists of a series of monthly waves over the period between 2004 and 2013, with a total of 124,110 respondents and 63 variables (not including demographic markers).

Aggregate-level and contextual variables and data sets
Many of the longitudinal processes that we are interested in require us to examine trends over time.Using individual-level data such as the BCS or BSA, it is possible to account for variation in identified dependent variables over time with simple time (typically year) control variables.However, to fully understand dynamic interrelationships between social/economic change and crime, and attitudinal shifts, it is important observe and model both rates of change and lagged processes.To do this, our individual-level data sets are also collapsed to aggregate level (and further broken down by particular demographic markers such as age, ethnicity or region).All data sets can at a minimum be aggregated at the annual level, and additionally the BCS (between 2002 and 2013) and BES-CMS (between 2004 and 2013) data sets can be aggregated to monthly intervals, to observe finer-grained trends and changes in victimization, fear of crime and attitudes towards crime.These are especially useful for looking at the impact of events and media coverage.
Many of the key contextual variables considered in longitudinal studies of crime, such as income inequality (typically measured using the Gini coefficient6 ) or unemployment, are largely treated and measured as national-level constructs.These are macrolevel indicators that predict changes in aggregated patterns of behaviour, e.g.crime rates.Our individual-level data are, therefore, integrated with indices of a range of socio-economic conditions, statistics on performance of the criminal justice system and national trends in social attitudes (especially where historical survey data have not survived in individual-level form).We have collated over a hundred time series (most at annual level but a few at quarterly and/or monthly intervals), which we describe here and are summarized in Table 2, which are integrated with both the individual-and aggregate-level BCS, BSA and BES data sets.Some of these series are disaggregated by demographic markers, which enable researchers to further explore how longitudinal processes unfold for particular subsets of the population.

Criminal justice system
For comparison against the BCS data on victimization, and also for enabling a longerterm view of crime that dates to earlier than the 1970s, our data include official recorded statistics on the annual number of different categories of crimes for England and Wales as reported in the Home Office's (2012;2014)

Socio-economic indicators
A large amount of data on the state of economy and society are included in our aggregate-level data set.This includes standard measures of inflation and unemployment rates, the claimant count and rate, economic inactivity, average earnings, labour disputes and GDP drawn from official statistics of the Office for National Statistics (www. ons.gov.uk).Data are also included on levels of inequality, poverty and incomes from the Institute for Fiscal Studies (www.ifs.org.uk).Data on annual benefits expenditure (and specific categories of benefits) are taken from the Department of Work and Pensions (2014).We have collated data on truancy from the Youth Cohort Study 7 from around 1985 and school expulsions from the late 1990s.In addition, we have included data from the Home Office Addicts Index, which records new heroin addicts notified to the police (for the period from 1977 to 1997), suicide rates (from Office for National Statistics 2012) and council house sales (from Department for Communities and Local Government 2013, with the latter also disaggregated by region).To complete our measures of social conditions, we have data on the number of children in care dating back to the 1960s.

Policy and politics
Our data sets also include measures of political attention and on policy action on crime.We draw on data from the UK Policy Agendas Project (www.policyagendas.org.uk) to capture the amount of attention given to crime, and law and order, in the statement 7 The Youth Cohort Study commenced in 1985.It represents a key piece of longitudinal research designed to monitor behaviour of young people as they reach the minimum school leaving age and either stay on in education or enter the labour market.The sample is based on representative samples of young people aged 16 years onwards completing postal questionnaires. of policy intentions set out in the Queen's Speech and in Acts of Parliament (between 1945 and 2012).We have generated our own data on the frequency of mention of crime rates and specific crime-related issues (such as anti-social behaviour) in all parliamentary debates over the period between 1900 and 2004 using the Hansard Prototype archive of parliamentary debates (http://hansard.millbanksystems.com/).

Public opinion
Finally, we have been able to collect a number of aggregate-level measures of public opinion over an extended time period, enabling a long-term view of attitudinal shifts.
Firstly, this includes survey data on the 'most important problem' facing the country, as collected by the Gallup Organization between 1944 and 2001 (and the 'most important issue', as collected by Ipsos-MORI between 1974 and2014).This measure indicates the prominence of crime as an issue on the public's mind (see Jennings and Wlezien 2011).
In addition, we include data on the public's preferences for left or right public policy ('public policy mood'), from Bartle et al. (2011), and have constructed our own measure of public punitiveness using survey items on capital punishment, sentencing and other aspects of criminal justice, using a method developed by Stimson (1991) and applied by Enns (2014) in the US.
The data have been collated and stored in a manner we hope conducive to its use by other researchers.It has been 'preserved' so that it is possible to use at both individual and aggregate levels.This should provide users with flexibility to adapt the data sets for their own purposes-either integrating additional contextual variables or collapsing the data by specific demographic markers.Each survey can be analyzed as a large 'stand-alone' data set.The BCS has almost 600,000 respondents over the period from 1981 to 2013 (the oldest year of birth is 1885), allowing for robust analyses of particular items where responses or subgroups may be rare, for example, male victims of domestic violence (Gadd et al. 2002).It is also possible to 'collapse' these survey responses into annual aggregate observations (e.g. the rate of crime per capita, average fear of crime in the population) to measure trends over time and to undertake time-series modelling of the data (interpolating missing years in the BCS and BSA).This aggregate data can also be merged with contextual variables, so for example, survey items from the BSA can be used to explore the degree to which social attitudes shift as crime rises and falls, based on self-reported rates of victimization from the BCS.
Another potential use of the data is to repeat the above analyses disaggregating regions of England and Wales. 8This allows one to check for the structural invariance of national-level processes at the regional level-and may highlight unique behavioural or cultural processes taking place in particular localities.A further technique that can be employed with this longitudinal data is age-period-cohort analysis (Ryder 1965;Grasso 2014), which allows exploration of the unique contributions of three types of timerelated variations, namely age, period and cohort effects.Distinguishing these variations is critical for testing individual or social mechanisms that may influence variation in behaviour and attitudes across age groups of the population.Specifically, age effects represent developmental changes in the life course; period effects arise via cultural and economic changes that are exclusive to the study period, whereas cohort effects are the core of social change and represent the effects of formative experiences (Ryder 1965).

Limitations of the Data
It is important, however, to acknowledge the limitations of any data set of this kind.'Big Data', to adopt the phrase in vogue at present, no matter how big or how well-honed, is not a magic bullet (cf.Savage and Burrows 2007;Manovich 2011).There are some factors that are relevant and likely important for understanding changes in victimization and social attitudes over this period (such as the experiences of homeless people and the growth of CCTV surveillance), but for which no quantitative data exists-and cannot be retrospectively constructed.As such, the experiences, behaviours and attitudes that researchers are able to analyze reflect preoccupations and concerns (not to mention question wording and research design) of an earlier generation of researchers.This is a perennial problem for secondary data analysis (Dale 2004).In our case, it means that, to return to the example we cite above, the degree to which homeless people were abused by passers-by in the street or had their possessions stolen cannot be subjected to analysis using the data that we have collated.A further consequence is that the choice of data and method will shape the story we can deduct-in this instance, for example, the unintended consequences of the 'right to buy' policies promoted by the Thatcher governments following the 1980 Housing Act (see Carlen 1996 for a more thorough exploration of this matter).Analogously, the psychological damage done to a young man's sense of 'self' and of their place in society when facing long-term unemployment and the alternative ways in which they chose to assert their masculinity (Gadd and Farrall 2004), unfortunately, cannot be explored using this sort of data.Even though our collation of data provide a substantial overview of changes in victimization, fear of crime and social attitudes-as well as broader changes in the economy, society and politics-it does not offer an exhaustive appreciation of lived realities of social exclusion and engagement in crime.
In sum, the priorities of researchers-past may limit the validity of conclusions drawn from today's 'Big Data', which lack the 'thick'9 descriptive accounts that ethnographic or qualitative data can provide.This is especially important given the emphasis that government and research councils increasingly place on maximizing the value and use of data and conducting secondary analysis.This trend towards the collection and use of large and integrated data sets will continue, providing opportunities for new empirical and methodological inroads.It also has the potential to facilitate strong interdisciplinary connections as researchers from related fields become aware of data that is relevant to them.But we must also be cautious about the intrinsic assumptions, values and biases involved in historical data and the knowledge that can be extracted from it.

Future Possibilities
Our project is funded by the ESRC (award No. ES/K006398/1). 10 All of the data that we have collated will be deposited at the UK Data Archive at the end of the project (in the autumn of 2015) for use by other researchers.We hope that the data sets we have generated will form the basis of projects undertaken by other researchers, which either supplements our data with additional variables, or with equivalent data collated from other countries for comparative analyses.These data sets can also be updated as new sweeps of the annual surveys are released.The data are designed to be a platform for others to build upon, modifying for their own research projects, PhD studentships and teaching purposes.
Recorded Crime Statistics for England and Wales 1898-2001/02 and Recorded Crime Statistics for England and Wales 2002/03-2013/14 data sets.There is also annual data on the number of convictions (plus the per capita and per crime conviction rates), obtained from Mitchell's (2003) British Historical Statistics, combined with data from the Annual Abstract of Statistics for later time periods.Annual data on the size of the prison population are taken from the Ministry of Justice's (2013) caseload statistics.

Table 1
Summary of individual-level data

Table 2
Summary of aggregate data