Many people derive a sense of impact or purpose from their jobs – they consider work to be a source of meaning. But how to make work meaningful? Theoretical models suggest that meaning can be created through social and non-social impact. We exploit rich panel data to empirically assess these models, and estimate a nonlinear production function for work meaning that allows for noisy and complementary inputs. We find that social impact is the most effective pathway to meaning, and estimate a direct output elasticity of about 0.55. We also find evidence of a negative interaction with non-social impact. A standard deviation increase in social impact is twice as effective in creating meaning for individuals that perceive their jobs as having little non-social impact, compared to those with high perceived non-social impact.

We introduce a teacher time allocation model in which teachers allocate their available instruction time among individual, group, and classroom instruction to maximize a function of pupils' test scores. We consider two variants of the model, one with knowledge spillovers, the other with instruction spillovers. We evaluate both variants and find that the variant with instruction spillovers performs better, but requires more assumptions. We also derive teachers' marginal social welfare weights for their pupils and examine the influencing factors. The weights are predominantly positive, indicating teacher efficiency, decrease with higher math scores, suggesting inequality aversion, and show no significant correlation with gender, home language, or mother's education, implying anonymity. These results appear robust regardless of the presence and type of spillover effects.