AN APPLICATION OF SEQUENTIAL REGRESSION MULTIPLE IMPUTATION ON PANEL DATA

The relatively new sequential regression multiple imputation (SRMI) method is introduced, with the process of SRMI laid out in detail. The Project for Statistics on Living Standards and Development and the follow‐up KwaZulu‐Natal Income Dynamics Study provide the real panel data on which the methods reviewed are applied. The SRMI process is used to create multiple datasets completed with values imputed for data originally missing, and using the error component model estimation procedures and Rubin's rules, inferences on the panel data are made. Conclusions are drawn as to the applicability of the SRMI process to these data and as to the results of the regression analyses completed.