Technical change and the von Neumann coefficient of uniform expansion |
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| Institution: | 1. Department of Economics, Oregon State University, Corvallis, OR, USA;2. Department of Applied Economics, University of Maryland, College Park, MD, USA;3. Department of Economics, Southern Illinois University, Carbondale, IL, USA;4. Department of Accounting, Economics and Finance, Southeast Missouri State University, Cape Girardeau, MO, USA;1. School of Economic Mathematics and Collaborative Innovation Center of Financial Security, Southwestern University of Finance and Economics, Chengdu 611130, China;2. School of Economic Mathematics, Southwestern University of Finance and Economics, Chengdu 611130, China;3. Department of Mathematics, Imperial College, London SW7 2BZ, UK;1. Department of Logistics Management, School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China;2. Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Special Administrative Region;1. Instituto de Matemática y Ciencias Afines, Lima, Peru;2. Instituto de Telecomunicações and CIDMA, Universidade de Aveiro, Aveiro, Portugal;3. Laboratoire Informatique d’Avignon, Avignon Université, Avignon,France;1. Universidad Pontificia Comillas, ICADE. c/ Alberto Aguilera 23, 28015 Madrid, Spain;2. Department of Economics, Universidad Carlos III de Madrid. Calle Madrid, 126, Getafe, E-28903 Madrid, Spain;1. Department of Mathematics, Technische Universität Kaiserslautern, Germany;2. School of Mathematics and Natural Sciences, University of Wuppertal, Germany;3. Department of Mathematical Sciences, Clemson University, SC, USA |
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| Abstract: | We study technical change for multi-product technologies to examine its effect on economic growth for 27 OECD (Organization for Economic Cooperation and Development) countries during 1951–2014. We review the Malmquist index and reexamine von Neumann’s model of an expanding economy. We estimate the coefficient of uniform expansion via DEA (Data Envelopment Analysis) and use it to measure technical change via a Solow residual and an alternative von Neumann technical change index which equals the difference between the growth rates of the slowest growing output and the fastest growing input. We also exploit a property of constant returns to scale in order to examine technical change of the average technology. During 2005–2014 the Solow residual shows relatively fast technical change. In contrast, the Malmquist, average technology and alternative von Neumann technical change indexes show negative or stagnant technical change. |
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