In many contexts, confidentiality constraints severely restrict access to unique and valuable microdata. Synthetic data which mimic the original observed data and preserve the relationships between variables but do not contain any disclosive records are one possible solution to this problem. The synthpop package for R, introduced in this paper, provides routines to generate synthetic versions of original data sets. We describe the methodology and its consequences for the data characteristics. We illustrate the package features using a survey data example.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. www.econstor.eu The Institute for the Study of Labor (IZA) in Bonn is a local and virtual international research center and a place of communication between science, politics and business. IZA is an independent nonprofit organization supported by Deutsche Post Foundation. The center is associated with the University of Bonn and offers a stimulating research environment through its international network, workshops and conferences, data service, project support, research visits and doctoral program. IZA engages in (i) original and internationally competitive research in all fields of labor economics, (ii) development of policy concepts, and (iii) dissemination of research results and concepts to the interested public. Terms of use: Documents in D I S C U S S I O N P A P E R S E R I E SIZA Discussion Papers often represent preliminary work and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be available directly from the author.IZA Discussion Paper No. 6140 November 2011 ABSTRACT Does Migration Make You Happy? A Longitudinal Study of Internal Migration and Subjective Well-BeingThe majority of modelling studies on consequences of internal migration focus almost exclusively on the labour market outcomes and the material well-being of migrants. We investigate whether individuals who migrate within the UK become happier after the move than they were before it and whether the effect is permanent or transient. Using life satisfaction responses from 12 waves of the British Household Panel Survey (BHPS) and employing a fixed-effects model, we derive a temporal pattern of migrants' subjective wellbeing (SWB) around the time of the migration event. Our findings make an original contribution by revealing for the first time that, on average, migration is preceded by a period when individuals experience a significant decline in happiness. The boost that is received through migration appears to bring people back to their initial level of happiness. As opposed to labour market outcomes of migration, SWB outcomes do not differ significantly between men and women. Perhaps surprisingly, long-distance migrants are at least as happy as short-distance migrants despite the higher social costs that are involved.JEL Classification: J61, R23

Summary. Data holders can produce synthetic versions of data sets when concerns about potential disclosure restrict the availability of the original records. The paper is concerned with methods to judge whether such synthetic data have a distribution that is comparable with that of the original data: what we term general utility. We consider how general utility compares with specific utility: the similarity of results of analyses from the synthetic data and the original data. We adapt a previous general measure of data utility, the propensity score mean-squared error pMSE, to the specific case of synthetic data and derive its distribution for the case when the correct synthesis model is used to create the synthetic data. Our asymptotic results are confirmed by a simulation study. We also consider two specific utility measures, confidence interval overlap and standardized difference in summary statistics, which we compare with the general utility results. We present two contrasting examples of data syntheses: one illustrating synthetic data that is evaluated as being useful by both general and specific measures and the second where neither is the case. For the second case we show how the general utility measures can identify the deficiencies of the synthetic data and suggest how this can inform possible improvements to the synthesis method.

We describe results on the creation and use of synthetic data that were derived in the context of a project to make synthetic extracts available for users of the UK Longitudinal Studies. A critical review of existing methods of inference from large synthetic data sets is presented. We introduce new variance estimates for use with large samples of completely synthesised data that do not require them to be generated from the posterior predictive distribution derived from the observed data and can be used with a single synthetic data set. We make recommendations on how to synthesise data based on these findings. An example of synthesising data from the Scottish Longitudinal Study is included to illustrate our results.

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Abstract. Synthetic data methods were designed to address the conflicting demands placed on data holders to unlock the research and policy potential of microdata while at the same time preserving the confidentiality of individuals. Recently, these methods have become more widely recognized in the UK and the provision of bespoke synthetic data has been approved to expand the use of one of the UK Longitudinal Studies. The process of producing useful synthetic data involves, however, a substantial investment of research time, as it always requires some customising for the characteristics of an individual data set. At the same time, a substantial part of it can be automated and this is essential when the process has to be conducted rapidly and on a regular basis. This paper describes the application of synthetic data to the UK Longitudinal Studies, details implementation process for the Scottish Longitudinal Study and presents methods used in an R package synthpop that has been developed to facilitate production of non-disclosive entirely synthetic data. A reproducible example using open data is given to illustrate the synthesising procedure and to provide insights into quality of synthetic data generated using different automated approaches.

Life satisfaction and motives for moving home are complex entanglements, reflecting multiple desires and experiences. The aim of this paper is to show that a focused analysis of satisfaction with particular life domains can prove that changing a place of residence is not only a life stressor, but also a positive means leading to enduring improvements in individual satisfaction. Using the British Household Panel Survey we examine overall life satisfaction and satisfaction in various life domains such as housing, job, social life, household income, spouse/partner and health, both prior to and after moving. A temporal pattern of movers' satisfaction for a number of years before and after the move is derived employing a fixed-effects panel data model. Our results reveal that residential relocation increases housing satisfaction considerably. The positive effect of moving on housing satisfaction is much stronger and endures longer for those with a sustained desire to relocate ahead of movement. Despite some decrease over time, five years after moving survey respondents still had significantly higher housing satisfaction than before their move. Changes in satisfaction with other life domains are much less pronounced and no lasting improvements in satisfaction are observed for them.

Scotland is often perceived as having a relatively welcoming view towards migrants and is presented as such by its politicians and policymakers. This positioning sits within a broader political context in which the Scottish Government favours immigration but has limited policy levers with which to directly influence it. This paper seeks to scrutinise the supposition that Scotland can be seen as ‘different’ to the rest of the UK in terms of how immigration is perceived in the public realm. This is pursued through the analysis of attitudinal data to explore public views on migration, the potential drivers of these perceptions and their implications for future immigration policy in the context of the 2014 referendum on the constitutional future of Scotland. The research finds that the public in Scotland does hold relatively positive views towards migration and that this could be related to Scotland's particular experience of population in and out movements. However there is evidence of some (growing) hostility towards migration on the part of the general public in Scotland and a possible link between nationalist leanings and opposition to ‘Others’. These findings have significant implications for debates regarding possible future immigration policies in Scotland.