My research lies at the intersection of macroeconomics and labor economics, with a particular focus on the demand side of the labor market. Broadly, my work can be characterized as that of an applied macroeconomist studying labor economic issues by applying macroeconomic models and applied labor tools. I combine rich empirical analyses with models of heterogeneous workers that incorporate labor market dynamics, firm dynamics, and macroeconomic outcomes to investigate the research questions. I discuss three chapters of my ongoing projects in this dissertation. In the first chapter, using worker surveys and online job posting data, I document that the U.S. economy has seen a substantial increase in the mixing of skill requirements from 2005-2018, both for incumbent jobs and newly posted vacancies. American workers increasingly work in occupations that demand mixtures of analytical, computer, and interpersonal skills rather than specializing in one of them, even within granular occupations. This change occurred primarily in low- to medium-wage occupations, and workers in occupations that increasingly mix non-routine skills, or those with a broader set of these skills earn a wage premium. In the second chapter, I build a multi-dimensional directed search and matching model with two-sided heterogeneity and endogenous choices to understand the sources of skill mixing shifts,. In this framework, firms optimally choose occupa- tions’ skill intensities before producing with a worker. Simultaneously, workers make decisions about their jobs as well as their life-time skill development trajectories. Counterfactual analysis shows that the rise in the complementarity of skills in production and in the cost of skills for occupation operation are the main drivers of skill mixing shifts and the corresponding wage and employment dynamics in this period. In the third chapter, I study the spatial general equilibrium and redistribution effects of e-commerce on different local labor markets from a trade perspective based on the production technology change in the retail sector. Using a panel of products and retailers on Amazon, I document that online retailers are more agglomerated in space, particularly for those using Amazon’s distribution and fulfillment centers, and their agglomeration is related to higher trade flows of the upstream goods. I then incorporate consumer search and retailer location choices into a multi-sector gravity trade model with an elastic supply of heterogeneous workers. The model implies that the increase in online shopping efficiency, the rise in online retailer agglomeration, and the reduction in shipping friction will induce greater industrial and occupational specialization. Quantitative analysis shows that the growth of Amazon from 2007-2017 had led to overall declines in retail prices, but also worker reallocation out of manufacturing sector, resulting in a 1 percent decrease in welfare. Non-employment increases by 2.3 percentage points and the Gini index on employment across regions increases by near 20 percent, exacerbating regional inequality.