This dissertation is composed of three chapters. In the first two chapters, I study how micro-level heterogeneity affects aggregate fluctuations in an economy. The third chapter develops a novel computational method that solves the nonlinear dynamic stochastic general equilibrium with heterogeneous agents. In the first chapter, I study how heterogeneous firm-level lumpy investments affect the business cycle. I develop a heterogeneous-firm business cycle model where large firms’ lumpy investments closely follow the empirical patterns. In the model, synchronized large-scale investments of large firms significantly amplify productivity-driven aggregate fluctuations and lead to investment cycles even in the absence of aggregate shocks. In the second chapter, I study how the pass-through businesses of top income earners affect the aggregate fluctuations in the U.S. economy. Using a heterogeneous-household real business cycle model with endogenous labor supply and occupational choice, I argue that the business-income-driven top income inequality has made the following changes in the productivity-driven aggregate fluctuations: 1) lower volatility of aggregate output and 2) stronger negative correlation between labor hour and productivity. In the third chapter, I develop and test a novel algorithm that solves heterogeneous-agent models with aggregate uncertainty. This method computes the nonlinear dynamic stochastic general equilibrium with a high degree of accuracy. And the computational gain compared to existing methods is significant when a non-trivial market-clearing condition is present in the model.