Innovation and market value: a quantile regression analysis

By Alex Coad, Rekha Rao. 2006

135 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/c27f7ce064a8fd0a4dc7945332ca89b81febdf72

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Citations in the corpus

Innovation and firm growth: Does firm age play a role? (2016, unknown): “Quantile regression has been frequently applied to analyse issues related to the distribution of returns to innovation (Coad and Rao, 2006; Coad and Rao, 2008; Goedhuys and Sleuwaegen, 2009; Hölzl, 2009; Kaiser, 2009; Love et al., 2009; Ebersberger et al., 2010; Segarra and Teruel, 2011; Falk,…”
The firm-level employment effects of innovations in high-tech US manufacturing industries (2011, result): “We observe that this indicator does not appear to perform as well when we scale down innovative activity by a firm’s total sales (compare the results here with those in Coad and Rao (2006) and Coad and Rao (2008)).”
Pricing determinants in the hotel industry: Quantile regression analysis (2010, methodology): “It is also applied to industry analysis (Görg et al., 2000; Girma and Görg, 2007; Yasar et al., 2006) and finance (Dimelis and Louri, 2002; Fattouh et al., 2005; Coad and Rao, 2006; Somers and Whittaker, 2007).”
Firm Growth : a Survey (2007, unknown): “it is quite common for theoretically-minded authors to consider this to be a ‘stylised fact’ for the purposes of constructing and validating economic models (see for example Cooley and Quadrini (2001), Gomes (2001) and Clementi and Hopenhayn (2006)).”
Innovation and firm growth in high-tech sectors: A quantile regression approach (2008, methodology): “11Further evidence of the discrepancies between patent statistics and R&D statistics is presented in the regression results in Tables 5 and 6 of Coad and Rao (2006a).”
Firm growth and R&D expenditure (2010, background): “Still others have focused on the influence of institutional factors on firm-level R&D investment levels, including such factors as patent protection, human capital and international openness (Falk 2006). 2. Another strand of the literature on R&D investment, which we will not survey in any detail he”
‘Better late than never’: the interplay between green technology and age for firm growth (2017, methodology): “3.3 Variables Our dependent variable is the growth rate of employees (Growthit), calculated as the difference between the logarithm of firm i’s employees in year t and the logarithm of employees in year t − 1 (Coad and Rao 2006; Coad 2010) (see Online Appendix A3 for details).”
Political stability and growth: An application of dynamic GMM and quantile regression (2017, background): “Furthermore, advantage is that while conventional regression focuses on the mean, quantile regressions are able to describe the entire conditional distribution of the dependent variable (Coad and Rao, 2006).”
Services and services innovation (2009, background): “1 See Coad and Rao (2006) for a recent discussion of the implications of this for statistical analysis of innovation and growth rates.”