This dissertation consists of two chapters, each representing an individual research paper. In the first chapter, I analyze how a firm's labor market power shapes, and is shaped by, its workforce, and I evaluate the implications for welfare and inequality. Using matched worker-firm panel data from Norway (1995-2018), I develop, identify, and estimate an equilibrium model of the labor market where firms compete with one another for workers who are heterogeneous in both their skills and preferences over wages versus non-wage job amenities. I allow the wage-amenity trade-offs to be correlated with skills, while also varying among equally skilled workers. When a firm adjusts its wages, the composition of its workforce shifts, and these compositional changes, in turn, affect the labor supply curve to the firm. As a result, the firm's wage-setting power varies based on which types of workers it employs. I find that this variation leads to large allocative inefficiency, with welfare losses from imperfect competition estimated at 9.5% relative to the competitive benchmark. In the second chapter, I explore how identity influences group behavior through social interactions. I study a discrete choice model where people wish to conform to the actions of some members of their network, while deviating from the actions of others. Under this generalized framework, I explore what aggregate outcomes arise from noncooperative decisionmaking. I characterize the uniqueness and stability of equilibria, and I discuss implications of negative spillovers for welfare and inefficiency. Additionally, I demonstrate how the model may be taken to data. I introduce a novel identification strategy that accounts for unobserved network effects by leveraging within-network variation in individual characteristics. I also construct internal instruments to overcome the issue of measurement error, which is a primary source of endogeneity in network-based models with incomplete information. Finally, I apply this methodology using data from the large-scale education experiment Project STAR, where I find robust evidence of gender differences in peer effects.