Issues in Assessing the Contribution of Research and Development to Productivity Growth

Griliches, Zvi

doi:10.2307/3003321

“…MAR-spillovers lead to learning processes like those described in the preceding paragraph, where knowledge spills over between individuals working to solve similar or at least related problems. MAR-spillovers are, therefore, intra-industrial phenomena and allow the exploitation of regional economies of scale: the relatively small technological distance (Griliches 1979) between individuals and firms implies low barriers for knowledge spillovers and is seen as a condition for sustained growth. A testable hypothesis deduced from this approach would, therefore, state that regions characterised by a higher concentration of firms employing similar production technologies ought to, ceteris paribus, have higher income growth rates than regions with a lower concentration of similar firms.…”

Section: Knowledge Spillovers Agglomeration and Regional Economic Grmentioning

confidence: 99%

What do we know about geographical knowledge spillovers and regional growth?: A survey of the literature

Döring¹,

2006

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. with persistently different levels of growth. This paper provides a survey of theoretical and empirical findings on this. Terms of use: Documents in• The theoretical concept of knowledge spillovers is outlined by discussing the different types of knowledge, the spatial dimension of knowledge spillovers, and the geographical mechanisms and structural conditions of knowledge diffusion. Such spillovers lead to dynamic externalities, and to agglomeration effects in the geographical dimension. Both effects constitute path dependencies in the economic growth of regions.• Existing recent empirical studies mainly support the theoretically derived hypotheses. This applies especially to the importance of knowledge spillovers for regional productivity and innovative behaviour.• In addition to the large number of surveyed contributions, the paper refers also to unanswered questions, i.e. the normative question whether the theoretical considerations and empirical evidence warrant any economic policy measures actively encouraging knowledge spillovers.Thomas Döring, University of Kassel and Philipps-University Marburg Jan Schnellenbach, Philipps-University Marburg What Do We Know About Geographical Knowledge Spillovers and Regional Growth? -A Survey of the LiteratureThomas Döring University of Kassel and Philipps-University Marburg and Jan Schnellenbach * Philipps-University Marburg AbstractModern (endogenous) growth theory tells us that knowledge spillovers are crucial for the growth of high-income economies. Against this background the paper provides a survey of theoretical and empirical findings highlighting the question of how geographically limited knowledge diffusion can help to explain clusters of regions with persistently different levels of growth. The paper discusses this topic in two steps: First, the theoretical concept of knowledge spillovers is outlined by discussing the different types of knowledge, the spatial dimension of knowledge spillovers, and the geographical mechanisms and structural conditions of knowledge diffusion. This discussion shows that the literature on knowledge spillovers focuses on the hypotheses that such spillovers lead to dynamic externalities and -in the geographical dimension -to agglomeration effects, both of which constitute path dependence in the economic growth of regions. Second, the paper analyses the empirical evidence for these theoretical findings. Existing empirical work mainly supports the theoretically derived hypothes...

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“…Aggregate output in the consumption good sector is nominal GDP net of R&D investment as reported in the BEA-NSF satellite account, de‡ated by the implied GDP de ‡ator. Outputs Y Rt and Y Ct are obtained by dividing real R&D investment and real aggregate output in the consumption good sector by the population 24 Previous studies also indicate that most variation in total hours is due to variation in employment than variation in individual hours (e.g. Hansen (1985), Castro and Coen-Pirani (2008)), especially at annual frequencies.…”

Section: Other Variables Used In the Analysismentioning

confidence: 99%

R&D and Aggregate Fluctuations

Artuç

¹

,

Pourpourides

²

2012

SSRN Journal

0

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Abstract Using US data for the period 1959-2007, we identify sectoral productivity shocks and capital investment-speci…c shocks by employing a Vector Autoregression whose shock structure is disciplined by a general equilibrium model. Controlling for real and nominal factors, we …nd that capital investment-speci…c shocks explain 70 percent of ‡uctuations of R&D investment while R&D technology shocks explain 30 percent of the variation of aggregate output net of R&D investment (i.e. the output of the non-R&D sector). Technology shocks jointly explain almost all the variation of output in the R&D sector and 78 percent of the variation of output in the non-R&D sector. Terms of use: Documents in

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“…The R&D stock is constructed by using a perpetual inventory method (Griliches, 1979). For each firm, the R&D stock at time t is defined by:…”

Section: Datamentioning

confidence: 99%

“…OLS-FD estimates the model specified in (log) first-differences to remove the unobserved time-invariant firms fixed effects. However, OLS estimates produce biased and inconsistent results in the presence of endogeneity and simultaneity (Griliches, 1979). GMM-FD and GMM-SYS models allow controlling for firms' permanent unobserved specific effects, and taking into account the possible endogeneity or simultaneity issue of the explanatory variables with the error term 2 .…”

Section: Empirical Frameworkmentioning

confidence: 99%