Optimal "Induced" Technical Change

Kamien, Morton I.; Schwartz, Nancy L.

doi:10.2307/1909600

Cited by 108 publications

(52 citation statements)

References 11 publications

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“…However, in other studies, researchers found that the size of the firm had a negligible positive effect on R&D intensity (i.e., R&D expenditures normalized by a measure of total output), and after controlling for industry belonging, the size effect disappeared (Cohen et al 1987). Indeed, the link between a firm's size and R&D investment depends to a great extent on the technological characteristics of the sector to which it belongs (Kamien and Schwartz 1982;Dosi 1988). For instance, in a study by Scherer and Ross (1990), it is shown that R&D increases proportionally with size in most industries; as far as the remaining sectors are concerned, industries in which R&D spending increases more than proportionally with size slightly outnumber those characterized by the opposite pattern.…”

Section: The Reference Literaturementioning

confidence: 94%

R&D in SMEs: a paradox?

2009

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Section: The Reference Literaturementioning

confidence: 94%

R&D in SMEs: a paradox?

2009

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“…R&D-based technological change has a long-running theoretical foundation beginning with the early work by Kennedy (1964), Kamien and Schwartz (1968), and Binswanger and Ruttan (1978) in developing the innovation possibility frontier (IPF) and the theory behind induced technological change. More recent work by Acemoglu (2002) addresses how the trade-off between innovation in different directions inherent in the IPF results endogenously from a firm's dynamic optimization.…”

Section: Randd-induced Technological Changementioning

confidence: 99%

Energy, the Environment, and Technological Change

Popp

Newell

Jaffe

2010

Handbook of the Economics of Innovation

320

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“…Although two early contributions by Kamien and Schwartz (1968) and Kmenta A and α when varying the elasticity of substitution. Klump and de La Grandville (2000) show that choosing a particular baseline point k 0 corresponds to the following normalisation of the ACMS parameters, with y 0 as output per capita at k 0 and π 0 as income share of capital under remuneration at marginal product at k 0 1 :…”

Section: The Meaning Of the Baseline Pointmentioning

confidence: 98%

Calibration of Normalised Ces Production Functions in Dynamic Models

Klump

Saam

2006

SSRN Journal

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Die Dis cus si on Pape rs die nen einer mög lichst schnel len Ver brei tung von neue ren For schungs arbei ten des ZEW. Die Bei trä ge lie gen in allei ni ger Ver ant wor tung der Auto ren und stel len nicht not wen di ger wei se die Mei nung des ZEW dar.Dis cus si on Papers are inten ded to make results of ZEW research prompt ly avai la ble to other eco no mists in order to encou ra ge dis cus si on and sug gesti ons for revi si ons. The aut hors are sole ly respon si ble for the con tents which do not neces sa ri ly repre sent the opi ni on of the ZEW.Download this ZEW Discussion Paper from our ftp server:ftp://ftp.zew.de/pub/zew-docs/dp/dp06078.pdf Non-technical summaryBasic models of economic dynamics are used to analyse how capital accumulation and technology influence economic growth and income distribution. A central element of such a model is the production function. It relates the economy's input of capital and labour to its total output. The production function with a constant elasticity of substitution (CES) represents a commonly used functional form. The elasticity of substitution is a parameter that can be thought to reflect an economy's overall flexibility. It has been estimated in a number of empirical studies. The CES function has two more parameters. Current practice of choosing them in applications of dynamic models can lead to arbitrary and inconsistent results. Based on the concept of normalisation introduced by Klump and de La Grandville (2000), we develop a method that chooses them using empirical values of the income share of capital, the ratio of capital to output, and the elasticity of substitution. We illustrate the method with an example from the Ramsey growth model. Abstract Normalising CES production functions in the calibration of basic dynamic models allows to choose technology parameters in an economically plausible way. When variations in the elasticity of substitution are considered, normalisation is necessary in order to exclude arbitrary effects. As an illustration, the effect of the elasticity of substitution on the speed of convergence in the Ramsey model is computed with different normalisations. Calibration of Normalised CES Production Functions in Dynamic Models

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Optimal "Induced" Technical Change

Cited by 108 publications

References 11 publications

R&D in SMEs: a paradox?

R&D in SMEs: a paradox?

Energy, the Environment, and Technological Change

Calibration of Normalised Ces Production Functions in Dynamic Models

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