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Working Paper
Updates to the Sampling of Wealthy Families in the Survey of Consumer Finances
Participation in household surveys has fallen over time, making it harder to produce a household survey-like the Survey of Consumer Finances (SCF)-in a timely manner. To address these challenges, the reference year of the sampling frame data for the 2016 SCF wealthy oversample was shifted back one year, allowing the oversample to be selected earlier than the past. In implementing this change, though, we risk identifying an outdated set of families and introducing variability in the sampling process. However, we show that the set of families selected in the new frame are observationally ...
Working Paper
Lining Up : Survey and Administrative Data Estimates of Wealth Concentration
The Survey of Consumer Finances (SCF) has a dual-frame sample design that supplements a standard area-probability frame with a sample of observations drawn from statistical records derived from tax returns. The tax-based frame is stratified on the basis of a "wealth index" constructed largely from observed income flows, with the intent of heavily oversampling wealthy households. Although the SCF is not specifically designed to estimate wealth concentration, the design arguably provides sufficient support to enable such analysis with a reasonable level of credibility. Similar estimates may ...
Working Paper
LLM on a Budget: Active Knowledge Distillation for Efficient Classification of Large Text Corpora
Large Language Models (LLMs) are highly accurate in classification tasks, however, substantial computational and financial costs hinder their large-scale deployment in dynamic environments. Knowledge Distillation (KD) where a LLM ""teacher"" trains a smaller and more efficient ""student"" model, offers a promising solution to this problem. However, the distillation process itself often remains costly for large datasets, since it requires the teacher to label a vast number of samples while incurring significant token consumption. To alleviate this challenge, in this work we explore the ...