We estimate a dynamic network technology where new knowledge in the form of publications in STEM (science, technology, engineering, and mathematics) is an intermediate product. Knowledge is produced in the first stage of production and is used in the second stage of production to produce a final output of real consumption, which equals gross domestic product minus investment spending on physical capital minus research and development expenditures. Knowledge also spills over between producers as it becomes disseminated. The two stages of production are linked between periods as investments in research capital and physical capital enhance future production possibilities. Our model combines several theories of production: dynamic data envelopment analysis (DEA) and two-stage network DEA. Using pooled data on 53 countries during 1999–2012, the model estimates indicate that dynamic efficiency averages about 70%. Countries could increase final consumption by about 25% via greater technical efficiency in production and by another 5% via an optimal intertemporal reallocation of investment spending.
Sources and uses of knowledge in a dynamic network technology / Bostian, M.; Daraio, C.; Grosskopf, S.; Ruocco, G.; Weber, W. L.. - In: INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH. - ISSN 0969-6016. - 27:4(2020), pp. 1821-1844. [10.1111/itor.12741]
Sources and uses of knowledge in a dynamic network technology
Bostian M.
;Daraio C.
;Ruocco G.
;
2020
Abstract
We estimate a dynamic network technology where new knowledge in the form of publications in STEM (science, technology, engineering, and mathematics) is an intermediate product. Knowledge is produced in the first stage of production and is used in the second stage of production to produce a final output of real consumption, which equals gross domestic product minus investment spending on physical capital minus research and development expenditures. Knowledge also spills over between producers as it becomes disseminated. The two stages of production are linked between periods as investments in research capital and physical capital enhance future production possibilities. Our model combines several theories of production: dynamic data envelopment analysis (DEA) and two-stage network DEA. Using pooled data on 53 countries during 1999–2012, the model estimates indicate that dynamic efficiency averages about 70%. Countries could increase final consumption by about 25% via greater technical efficiency in production and by another 5% via an optimal intertemporal reallocation of investment spending.File | Dimensione | Formato | |
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Note: https://onlinelibrary.wiley.com/doi/full/10.1111/itor.12741
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