We estimate the impact of the employment rate of peers and neighborhood characteristics on an individual’s probability of employment. Nonrandom location choice and unobserved heterogeneity at the individual and neighborhood levels complicate the estimation of this causal impact. Our identification strategy rests on using a hedonic pricing model to control for neighborhood-level unobserved heterogeneity and on using a fixed-effects estimator to account for individual time-invariant characteristics. Using a unique dataset assembled composed of a household panel survey, regional employment statistics, and data from an online real-estate platform, we estimate that a one-percentage-point increase in the employment rate within a neighborhood will lead to a 0.6–1.1% increase in one’s own employment probability. The share of highly educated individuals and the share of foreigners in the neighborhood, as well as unobservable neighborhood characteristics, do not influence the individual employment probability. These results are robust to subsamples by sex, urbanity, region, citizenship, and educational attainment.