and participants in several seminar and conference presentations for useful comments and feedback. We thank Emily Breza and Cynthia Kinnan for their help with the Indian NSS data. We thank Ana Danieli for her outstanding assistance in a revision of an earlier draft. Comin acknowledges the generous support of the National Science Foundation, the Institute for New Economic Thinking and the European Commission through the H2020 grant to the FRAME project. Mestieri acknowledges the generous support of the Agence Nationale de la Recherche (JJCC-GRATE program) while at TSE. All remaining errors are our own. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.

We study the lags with which new technologies are adopted across countries, and their long-run penetration rates once they are adopted. Using data from the last two centuries, we document two new facts: there has been convergence in adoption lags between rich and poor countries, while there has been divergence in penetration rates. Using a model of adoption and growth, we show that these changes in the pattern of technology diffusion account for 80% of the Great Income Divergence between rich and poor countries since 1820.

This chapter discusses different approaches pursued to explore three broad questions related to technology diffusion: what general patterns characterize the diffusion of technologies, and how have they changed over time; what are the key drivers of technology, and what are the macroeconomic consequences of technology. We prioritize in our discussion unified approaches to these three questions that are based on direct measures of technology.

We present a new multi‐sector growth model that features nonhomothetic, constant elasticity of substitution preferences, and accommodates long‐run demand and supply drivers of structural change for an arbitrary number of sectors. The model is consistent with the decline in agriculture, the hump‐shaped evolution of manufacturing, and the rise of services over time. We estimate the demand system derived from the model using household‐level data from the United States and India, as well as historical aggregate‐level panel data for 39 countries during the postwar period. The estimated model parsimoniously accounts for the broad patterns of sectoral reallocation observed among rich, miracle, and developing economies. Our estimates support the presence of strong nonhomotheticity across time, income levels, and countries. We find that income effects account for the bulk of the within‐country evolution of sectoral reallocation.

This chapter discusses different approaches pursued to explore three broad questions related to technology diffusion: what general patterns characterize the diffusion of technologies, and how have they changed over time; what are the key drivers of technology, and what are the macroeconomic consequences of technology. We prioritize in our discussion unified approaches to these three questions that are based on direct measures of technology.