This paper argues that microeconomic shocks can lead to aggregate fluctuations through intersectoral input-output linkages. It shows that as the economy becomes more disaggregated, the rate at which aggregate volatility decays depends on the structure of these linkages. The paper characterizes how sectoral shocks propagate through the economy, generating significant aggregate effects. It highlights that sizable aggregate volatility arises from sectoral shocks only if there is significant asymmetry in sectoral roles as suppliers. The paper also shows that the sparseness of the input-output matrix is unrelated to aggregate fluctuations. The paper introduces a mathematical framework to analyze the propagation of shocks through the economy. It shows that sectoral shocks may propagate throughout the economy, affecting other sectors and generating aggregate effects. The paper provides three key theorems characterizing the rate of convergence of aggregate volatility in terms of the structural properties of the intersectoral network. The results show that aggregate volatility decays at a slower rate than the standard diversification argument predicts, due to first-order and higher-order interconnections. The paper also shows that the structure of the intersectoral network has a defining effect on aggregate fluctuations, even when the law of large numbers holds. The paper uses empirical data from the U.S. economy to illustrate the implications of its results. It shows that the empirical distributions of first-order and second-order degrees appear to have Pareto tails, with the latter exhibiting a heavier tail. The paper estimates that the second-order degree parameter is 1.18, implying that aggregate volatility in the U.S. economy decays at a rate slower than n^0.15. This suggests that sizable aggregate fluctuations may originate from idiosyncratic shocks to different sectors in the economy. The paper is closely related to Gabaix (2011), who shows that firm-level idiosyncratic shocks translate into aggregate fluctuations when the firm size distribution is sufficiently heavy-tailed. The paper also relates to the literature on the role of sectoral shocks in macro fluctuations. The paper provides a more comprehensive and tractable framework for the analysis of such interactions and characterizes the extent to which such interactions will impact aggregate volatility. It also shows how cascade effects may play a central role in translating idiosyncratic shocks into aggregate volatility. The paper concludes that the structure of the intersectoral network has a defining effect on aggregate fluctuations, and that the nature of aggregate fluctuations resulting from sectoral shocks is not related to the sparsity or cyclicality of the input-output matrix, but rather to the extent of asymmetry between different sectors.This paper argues that microeconomic shocks can lead to aggregate fluctuations through intersectoral input-output linkages. It shows that as the economy becomes more disaggregated, the rate at which aggregate volatility decays depends on the structure of these linkages. The paper characterizes how sectoral shocks propagate through the economy, generating significant aggregate effects. It highlights that sizable aggregate volatility arises from sectoral shocks only if there is significant asymmetry in sectoral roles as suppliers. The paper also shows that the sparseness of the input-output matrix is unrelated to aggregate fluctuations. The paper introduces a mathematical framework to analyze the propagation of shocks through the economy. It shows that sectoral shocks may propagate throughout the economy, affecting other sectors and generating aggregate effects. The paper provides three key theorems characterizing the rate of convergence of aggregate volatility in terms of the structural properties of the intersectoral network. The results show that aggregate volatility decays at a slower rate than the standard diversification argument predicts, due to first-order and higher-order interconnections. The paper also shows that the structure of the intersectoral network has a defining effect on aggregate fluctuations, even when the law of large numbers holds. The paper uses empirical data from the U.S. economy to illustrate the implications of its results. It shows that the empirical distributions of first-order and second-order degrees appear to have Pareto tails, with the latter exhibiting a heavier tail. The paper estimates that the second-order degree parameter is 1.18, implying that aggregate volatility in the U.S. economy decays at a rate slower than n^0.15. This suggests that sizable aggregate fluctuations may originate from idiosyncratic shocks to different sectors in the economy. The paper is closely related to Gabaix (2011), who shows that firm-level idiosyncratic shocks translate into aggregate fluctuations when the firm size distribution is sufficiently heavy-tailed. The paper also relates to the literature on the role of sectoral shocks in macro fluctuations. The paper provides a more comprehensive and tractable framework for the analysis of such interactions and characterizes the extent to which such interactions will impact aggregate volatility. It also shows how cascade effects may play a central role in translating idiosyncratic shocks into aggregate volatility. The paper concludes that the structure of the intersectoral network has a defining effect on aggregate fluctuations, and that the nature of aggregate fluctuations resulting from sectoral shocks is not related to the sparsity or cyclicality of the input-output matrix, but rather to the extent of asymmetry between different sectors.