@inbook {10360, title = {Can Internet Match High-quality Traditional Surveys? Comparing the Health and Retirement Study and its Online Version}, booktitle = {The Econometrics of Complex Survey Data}, series = {Advances in Econometrics}, volume = {39}, year = {2019}, pages = {3 - 33}, publisher = {Emerald Publishing Limited}, organization = {Emerald Publishing Limited}, abstract = {Abstract We examine sample characteristics and elicited survey measures of two studies, the Health and Retirement Study (HRS), where interviews are done either in person or by phone, and the Understanding America Study (UAS), where surveys are completed online and a replica of the HRS core questionnaire is administered. By considering variables in various domains, our investigation provides a comprehensive assessment of how Internet data collection compares to more traditional interview modes. We document clear demographic differences between the UAS and HRS samples in terms of age and education. Yet, sample weights correct for these discrepancies and allow one to satisfactorily match population benchmarks as far as key socio- demographic variables are concerned. Comparison of a variety of survey outcomes with population targets shows a strikingly good fit for both the HRS and the UAS. Outcome distributions in the HRS are only marginally closer to population targets than outcome distributions in the UAS. These patterns arise regardless of which variables are used to construct post-stratification weights in the UAS, confirming the robustness of these results. We find little evidence of mode effects when comparing the subjective measures of self-reported health and life satisfaction across interview modes. Specifically, we do not observe very clear primacy or recency effects for either health or life satisfaction. We do observe a significant social desirability effect, driven by the presence of an interviewer, as far as life satisfaction is concerned. By and large, our results suggest that Internet surveys can match high-quality traditional surveys.}, keywords = {internet survey comparison}, isbn = {978-1-78756-726-9, 978-1-78756-725-2/0731-9053}, url = {https://doi.org/10.1108/S0731-905320190000039001}, author = {Marco Angrisani}, editor = {Finley Brian} }