We study the implications of microeconomic heterogeneity for aggregate technology, showing that the aggregate elasticity of substitution between capital and labor can be expressed as a simple function of plant level structural parameters and sufficient statistics for plant heterogeneity. This allows for a new approach to estimating the aggregate elasticity using microeconomic data and allows us to examine how the aggregate elasticity varies over time or across countries. We then use plant level data from the Census of Manufactures to construct an aggregate elasticity of substitution for the manufacturing sector, and estimate an aggregate elasticity of approximately 0.72 in 1987. We find that the aggregate elasticity has risen over time in the US and is higher in less developed countries. These differences are quantitatively important; our estimates imply that a change in the interest rate has a 50 percent larger impact on India than the US. Finally, we measure the bias of aggregate technical change using our estimates of the aggregate elasticity, and find that the bias of technical change has increased in recent years.

We develop a framework to estimate the aggregate capital‐labor elasticity of substitution by aggregating the actions of individual plants. The aggregate elasticity reflects substitution within plants and reallocation across plants; the extent of heterogeneity in capital intensities determines their relative importance. We use micro data on the cross‐section of plants to build up to the aggregate elasticity at a point in time. Interpreting our econometric estimates through the lens of several different models, we find that the aggregate elasticity for the U.S. manufacturing sector is in the range of 0.5–0.7, and has declined slightly since 1970. We use our estimates to measure the bias of technical change and assess the decline in labor's share of income in the U.S. manufacturing sector. Mechanisms that rely on changes in the relative supply of factors, such as an acceleration of capital accumulation, cannot account for the decline.

We provide a tractable, quantitatively‐oriented theory of innovation and technology diffusion to explore the role of international trade in the process of development. We model innovation and diffusion as a process involving the combination of new ideas with insights from other industries or countries. We provide conditions under which each country's equilibrium frontier of knowledge converges to a Fréchet distribution, and derive a system of differential equations describing the evolution of the scale parameters of these distributions, that is, countries' stocks of knowledge. The model remains tractable with many asymmetric countries and generates a rich set of predictions about how the level and composition of trade affect countries' frontiers of knowledge. We use the framework to quantify the contribution of bilateral trade costs to long‐run changes in TFP and individual post‐war growth miracles. For our preferred calibration, we find that both gains from trade and the fraction of variation of TFP growth accounted for by changes in trade more than double relative to a model without diffusion.

Individual producers exhibit enormous heterogeneity in many dimensions. This paper develops a theory in which the network structure of production—who buys inputs from whom—forms endogenously. Entrepreneurs produce using labor and exactly one intermediate input; the key decision is which other entrepreneur's good to use as an input. Their choices collectively determine the economy's equilibrium input–output structure, generating large differences in size and shaping both individual and aggregate productivity. When the elasticity of output to intermediate inputs in production is high, star suppliers emerge endogenously. This raises aggregate productivity as, in equilibrium, more supply chains are routed through higher‐productivity techniques.

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