Comparative Cross National Electoral Research (CCNER)
A four year project funded by the British Economic & Social Research Council
Cross-national electoral researchers face the same challenges as cross-national researchers in other areas: translation, equivalence of measures, reliability and validity. However, neither cross-national electoral researchers, nor researchers in other subfields and other disciplines, have paid close attention to the issues of the non-random selection of country cases in large N comparative research, the impact of multiple-levels of analysis, the timing of fieldwork and the effects of these on the validity and reliability of measures of political attitudes and behaviours. For addressing data and case selection issues, we will develop approaches based on weighting, selection bias models and draw on the logic of small N comparative research. Whereas most large-scale survey research projects try to address data quality issues through harmonization of implementation procedures, we will develop techniques for addressing data quality for secondary sources. The substantive research question that motivates our programme examines how these methodological issues have affected the study of electoral competitiveness.
Our programme of training and secondary analysis will build on and extend that progress in methodology and content, helping to set comparative research on an even more sound and secure footing. The aims of our training programme in Comparative Cross-National Electoral Research (CCNER) are three-fold:
á Build capacity in the UK for world leading research in comparative cross-national electoral research;
Develop methods and techniques for resolving issues related to data quality in secondary sources, case selection bias, and the multi-level structure of data.
Develop training programmes
CCNER Launch and Workshop
Exeter September 8-9 2011
To meet the aims of the research and training programme, we will:
á Provide high quality research methods training in the collection, management and analysis of cross-national survey and macro data; -In a series of workshops address issues of data and case selection bias, data quality and multi-level data structures
Produce instructional materials (podcasts, powerpoint presentations and datasets) using existing cross-national data sets [CSES, EES, ESS, WVS, ISSP]
Disseminate instructional materials via a web portal, encouraging high quality UG and PG students to undertake research in this area;
Draw on expertise of investigators in management of large scale cross-national research projects and in cross-national research to develop and deliver workshops;
Develop new measures of electoral competitiveness and new methods of analysing its causes and consequences taking into consideration problems of levels and units of analysis; case selection, and non-response.
For further information contact Jeffrey Karp at firstname.lastname@example.org.