The match between workers and jobs is fundamentally important to economic prosperity, as it directly influences labor productivity, wage equality, and overall economic growth. An efficient worker-job assignment not only enhances individual job satisfaction and performance but also drives organizational efficiency and innovation. This dissertation comprises three essays that analyze the efficient match between workers and jobs from different perspectives. Chapter 1 investigates the non-parametric identification of matching games without individual-level data and applies this framework to the analysis of matching mechanism design in government recruitment. To address challenge posed by the non-availability of individual-level data, I build a many-to-one Non-transferable Utility job matching model with two-sided heterogeneity and demonstrate the non-parametric identification of the model using only position-level data based on instruments. I apply the framework to analyze the National Civil Service Exam (NCSE), a primary method for recruiting entry-level government officials in China. The NCSE is a mechanism where each candidate applies to \textit{one} position and subsequently takes a meritocratic exam determining admission. In the counterfactual analysis, I introduce a strategy-proof mechanism as an alternative. A strategy-proof mechanism may not be ideal when candidates differ in multiple dimensions while one dimension is relevant for matching output but is unobservable by the hiring party. In Chapter 2, my coauthor and I explore how subjective beliefs impact job search. We document how job seekers update perceived job-finding prospects by unemployment duration and by learning about aggregate unemployment. We find that job seekers perceive an 18% decline in their job-finding probability for each additional month of unemployment, but perceive a higher job-finding probability when the aggregate unemployment rate is unexpectedly low. We develop a job search model with learning and updating to quantify the impact of perceived aggregate unemployment on subjective job-finding probabilities, revealing an overreaction to news about aggregate conditions. These beliefs can potentially offset a non-trivial part of the negative consequences of moral hazard in job search. In Chapter 3, my coauthor and I consider efficient assignment of workers and jobs within organizations. In a firm with multiple hierarchical levels, efficient promotion decisions can require information concerning worker ability levels to be shared within the firm. We explore practices that improve intra-firm employer learning and reduce talent hoarding given heterogeneous worker visibility. We find that firms can employ managerial bonuses and job rotation to improve intra-firm employer learning and avoid talent hoarding, but the presence of visible workers can increase the likelihood of talent hoarding. Also, when equilibrium is characterized by talent hoarding, less visible workers are disadvantaged in hiring and promotion. We compare our theoretical results to findings in the empirical literature.