Comparing and Combining List and Endorsement Experiments: Evidence from Afghanistan

List and endorsement experiments are becoming increasingly popular among social scientists as indirect survey techniques for sensitive questions. When studying issues such as racial prejudice and support for militant groups, these survey methodologies may improve the validity of measurements by reducing nonresponse and social desirability biases. We develop a statistical test and multivariate regression models for comparing and combining the results from list and endorsement experiments. We demonstrate that when carefully designed and analyzed, the two survey experiments can produce substantively similar empirical findings. Such agreement is shown to be possible even when these experiments are applied to one of the most challenging research environments: contemporary Afghanistan. We find that both experiments uncover similar patterns of support for the International Security Assistance Force (ISAF) among Pashtun respondents. Our findings suggest that multiple measurement strategies can enhance the credibility of empirical conclusions. Open‐source software is available for implementing the proposed methods.     

Digital Britain – the final report

The final Digital Britain report was published in June as to set out the Government's final proposals and updating an interim version that has been published in January this year. This article builds upon an earlier article in [2009] 25 CLSR 263, which analysed the interim report in depth. The intention is not to repeat that earlier analysis, but rather update it and draw the reader's attention to those key areas of change.