Declining survey response rates in federal surveys have led to concerns of increasing nonresponse bias in key government statistics. A potential solution is to leverage administrative data from federal agencies and third party data when constructing survey weights. This project performs initial research on incorporating administrative data into the weighting algorithm for the Survey of Income and Program Participation (SIPP). Specifically, we match income data from IRS tax forms and demographic data from the Social Security Administration and the Decennial Census to both respondents and nonrespondents. We then use this matched data in the household nonresponse adjustment of the SIPP weighting algorithm, which adjusts the weights of respondents to account for differential nonresponse rates among subpopulations and reduces nonresponse bias in survey estimates. We show how these new experimental weights affect estimates of wealth, income, poverty, health insurance coverage, and participation in government assistance programs and their impact on nonresponse bias compared to the traditional weights. Overall, the new experimental weights are associated with a small increase in estimated economic wellbeing.