Publication Bias in the Returns to R&amp;D Literature

Møen, Jarle; Thorsen, Helge Sandvig

doi:10.1007/s13132-015-0309-9

Cited by 14 publications

(12 citation statements)

References 59 publications

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“…The latter range from 20% to 30% in Hall et al (2010) and from16% to 28% in Weiser (2005). The closest mean values (13% with and 18% without correction for selection bias) have been reported by Møen and Thorsen (2015).…”

Section: Elasticities and Rates Of Return Beyond Selection Biassupporting

confidence: 60%

“…Most metaanalysis studies tend to estimate (6) with ordinary least squares (OLS). This is the case in the two meta-analysis studies on R&D productivity (Wieser, 2005;Møen and Thorsen, 2015); and in recent meta-analysis studies in related fields (e.g., Castellacci and Lie, 2015). However, OLS estimates from (6) would be biased if the primary-study estimates were affected by data dependence.…”

Section: Meta-analysis: Protocol and Methodsmentioning

confidence: 96%

“…This is known as the file drawer problem in meta-analysis (Card and Krueger, 1995;Sterling et al, 1995;Stanley, 2008;Stanley and Doucouliagos, 2012). Of the existing reviews, only Møen and Thorsen (2015) addresses the risk of selection bias through precision-effect tests (PET) and trim-and-fill methods. However, the selected nature of the estimates in this review and others constitutes an additional source of selection bias.…”

Section: Introductionmentioning

confidence: 99%

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R&D and Productivity in OECD Firms and Industries: A Hierarchical Meta-Regression Analysis

et al. 2015

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Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. AbstractThe relationship between R&D investment and firm/industry productivity has been investigated widely following seminal contributions by Zvi Griliches and others from late 1970s onwards. We aim to provide a systematic synthesis of the evidence, using 1,253 estimates from 65 primary studies that adopt the so-called primal approach. In line with prior reviews, we report that the average elasticity and rate-of-return estimates are positive. In contrast to prior reviews, however, we report that: (i) the estimates are smaller and more heterogeneous than what has been reported before; (ii) residual heterogeneity remains high among firm-level estimates even after controlling for moderating factors; (iii) firm-level rates of return and within-industry social returns to R&D are small and do not differ significantly despite theoretical predictions of higher social returns; and (iv) the informational content of both elasticity and rate-of-return estimates needs to be interpreted cautiously. We conclude by highlighting the implications of these findings for future research and evidence-based policy. AbstractThe relationship between R&D investment and firm/industry productivity has been investigated widely following seminal contributions by Zvi Griliches and others from late 1970s onwards. We aim to provide a systematic synthesis of the evidence, using 1,253 estimates from 65 primary studies that adopt the so-called primal approach. In line with prior reviews, we report that the average elasticity and rate-of-return estimates are positive. In contrast to prior reviews, however, we report that: (i) the estimates are smaller and more heterogeneous than what has been reported before; (ii) residual heterogeneity remains high among firm-level estimates even after controlling for moderating factors; (iii) firm-level rates of return and within-industry social returns to R&D are small and do not differ significantly despite theoretical predictions of higher social returns; and (iv) the informational content of both elasticity and rate-of-return estimates needs to be interpreted cautiously. We conclude by highlighting the implications of these findings for future research and evidence-based policy.

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Section: Elasticities and Rates Of Return Beyond Selection Biassupporting

confidence: 60%

Section: Meta-analysis: Protocol and Methodsmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

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R&D and Productivity in OECD Firms and Industries: A Hierarchical Meta-Regression Analysis

et al. 2015

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“…1. Note that recent meta-regression analyses (Møen and Thorsen 2015;Ugur et al 2016)which have combined the results coming from several primary studies on R&D investments and firm/sector productivityhave pointed out that the average returns to R&D are positive but smaller than the ones that are reported in most of the literature. This occurs because of two main biases: a publication selection and a sample selection.…”

Section: Notesmentioning

confidence: 98%

Sectoral cognitive skills, R&D, and productivity: a cross-country cross-sector analysis

Sasso

Ritzen

2018

Education Economics

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We focus on human capital measured by skills and analyse its relationship with R&D investments and productivity across 12 OECD economies and 17 industries. We compute a measure of sectoral human capital defined as the average cognitive skills of the workforce in each country-sector combination. The variation in labour productivity that can be explained by human capital is remarkably large when measured by the sectoral skills, whereas it appears statistically insignificant when measured by the sectoral school attainment. This suggests that using measures of sectoral cognitive skills can represent a major step forward in any future sectoral growth accounting exercise.

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“…However, it is noteworthy that the bias of positive relationship between R&D investment and their return appears to be particularly strong in the part of the literature due to controlling of unobserved firm fixed effects (Møen & Thorsen, 2017). Loch and Tapper (2002) claim that how a high level of uncertainty of R&D project assumptions and long lag time makes a simple model inadequate.…”

Section: Literature Review and Hypothesismentioning

confidence: 99%

Lagged Effects of R&D Investment on Corporate Market Value: Evidence from Manufacturing Firms Listed in Chinese Stock Markets

LEE¹

2020

JAFEB

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The study examines lagged economic effects of research and development (R&D) investment on the market value of manufacturing firms listed on the Shanghai Stock Exchange or the Shenzhen Stock Exchange in China. This study applies panel data analysis methods to address the following issues: 1) There might be an adjustment lag in the impact of R&D investment on corporate market value, and 2) Unobserved firm effects must be taken into account. The balanced panel data includes a total of 1,462 observations with 34 cross-sections of manufacturing firms listed on Chinese stock markets and with 27 time-specific quarterly periods from 2007 to 2017. The results indicate that the R&D investment of Chinese manufacturing firms tends to yield favorable market value of the firm with some adjustments to time. The results show that R&D investment exhibits a strong positive impact on their market value of manufacturing firms in Chinese stock markets. Moreover, R&D investment has a positive time-lag effect on the market value of the firm. Interestingly, the R&D investment of Chinese manufacturing firms generate a relatively constant positive effect on their market value, supporting the notion that the corresponding returns of R&D investment for such firms yield lagged but added market values.

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Publication Bias in the Returns to R&D Literature

Cited by 14 publications

References 59 publications

R&D and Productivity in OECD Firms and Industries: A Hierarchical Meta-Regression Analysis

R&D and Productivity in OECD Firms and Industries: A Hierarchical Meta-Regression Analysis

Sectoral cognitive skills, R&D, and productivity: a cross-country cross-sector analysis

Lagged Effects of R&D Investment on Corporate Market Value: Evidence from Manufacturing Firms Listed in Chinese Stock Markets

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