We develop a simulation procedure to measure the effects of synthetic adjustment for census undercounts on the quality of estimated proportionate geographic population distributions. Analyzing the influences of both interstate variations in census coverage and measurement errors in national undercount estimates, we find that, over a wide range of environments, nearly two out of every three simulated applications of synthetic adjustment improve the state proportions for a majority of the national population. There is always, however, a substantial probability that adjustment will produce a much poorer geographic distribution in any particular application. We derive analytical expressions showing as precisely as possible the conditions on which improvements from census adjustment depend. Our simulation model considers two population groups, blacks and nonblacks, and 51 geographic areas, the 50 states plus the District of Columbia. We assume that both census counting errors and undercount measurement errors are lognormally distributed. From 1980 census counts, we generate true population counts according to our model and obtain, by the synthetic method, adjusted population counts. We consider several measures of adjustment success and find that whether policymakers decide to adjust may depend on which loss function they select. To assess the effects of national group undercount measurement errors, we propose four scenarios. In one there are no such errors; in another national black and white undercounts are persistently underestimated by 1% and 2.75%. Errors like the latter may arise if many illegal aliens reside in the United States. We simulate stochastic measurement errors in two alternative scenarios. National undercounts are estimated correctly on average in one, in contrast to the... [ABSTRACT FROM AUTHOR]