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Input Diffusion and the Evolution of Production Networks

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  • Vasco M. Carvalho
  • Nico Voigtländer

Abstract

The adoption and diffusion of inputs in the production network is at the heart of technological progress. What determines which inputs are initially considered and eventually adopted by innovators? We examine the evolution of input linkages from a network perspective, starting from a stylized model of network formation. Producers direct their search for new inputs along vertical linkages, screening the network neighborhood of existing suppliers to identify potentially useful inputs. A subset of these is then adopted, following a tradeoff between the benefits from input variety and the costs of customizing new inputs. Guided by this framework, we document a novel stylized fact at both the sector and the firm level: producers are more likely to adopt inputs that are already used – directly or indirectly – by their current suppliers. In particular, using disaggregated input-output data, we show that initial network proximity of a sector in 1967 significantly increases the likelihood of adoption throughout the subsequent four decades. A one-standard deviation decrease in network distance is associated with an increase in the adoption probability by one third to one half. Similarly, U.S. firms are significantly more likely to develop new input linkages among their suppliers’ network neighborhood. Our results imply that the existing production network plays a crucial role in the diffusion of inputs and the evolution of technology.

Suggested Citation

  • Vasco M. Carvalho & Nico Voigtländer, 2014. "Input Diffusion and the Evolution of Production Networks," NBER Working Papers 20025, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:20025
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    Cited by:

    1. Gualdi, Stanislao & Mandel, Antoine, 2016. "On the emergence of scale-free production networks," Journal of Economic Dynamics and Control, Elsevier, vol. 73(C), pages 61-77.
    2. Nikolay Chernyshev, 2018. "From Productivity Shifts to Economic Growth: Intersectoral Linkage as an Amplifying Factor," CDMA Working Paper Series 201801, Centre for Dynamic Macroeconomic Analysis.
    3. Charles D. Brummitt & Kenan Huremovic & Paolo Pin & Matthew H. Bonds & Fernando Vega-Redondo, 2017. "Contagious disruptions and complexity traps in economic development," Papers 1707.05914, arXiv.org.
    4. Harald Fadinger & Christian Ghiglino & Mariya Teteryatnikova, 2015. "Income Differences and Input-Output Structure," Vienna Economics Papers 1510, University of Vienna, Department of Economics.

    More about this item

    JEL classification:

    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • D57 - Microeconomics - - General Equilibrium and Disequilibrium - - - Input-Output Tables and Analysis
    • E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General
    • L23 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Organization of Production
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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