Reaching the Hard to Reach with Intermediaries: The Kansas City Fed’s LMI Survey

Reaching hard-to-reach individuals is a common problem in survey research. The low- and moderate-income (LMI) population, for example, is generally hard to reach. The Kansas City Fed’s Low- and Moderate-Income Survey addresses this problem by sampling a database of organizations to serve as proxies for the LMI population. In this paper, I describe why the LMI population can be hard to reach. I then explore potential problems with using a nonrandom survey sample and address the empirical validity of the Kansas City Fed’s LMI Survey. I compare results from the survey using the standard sample to results from the survey using a random sample. I find that the results of the surveys using the standard and random samples are not significantly different and conclude that the use of a nonrandom sample is not a significant problem for the LMI Survey. I find that the series of responses from the LMI Survey are correlated with the things they should be correlated with, suggesting that the survey is empirically valid and does a good job of measuring economic conditions in LMI communities.