Modeling life outcomes

How well can we determine ex ante individuals’ life outcomes? Traditional low dimensional models employed in the social sciences prove of limited effectiveness when given such objective. We seek to improve the performance of such models by applying modern machine learning methods on CBS microdata. Neural network models for natural language processing (eg. BERT and GPT-3) have proven to have extraordinary power when trained on large language corpora. Thus by analogy, we believe that models trained on large and rich datasets of individual life courses for millions of individuals could have great explanatory power for a variety of social outcomes that exceeds that of standard social science models.