Intangible Investment and Firm Performance

Article
  • 14 Downloads

Abstract

We combine survey and administrative data for about 13,000 New Zealand firms from 2005 to 2013 to study intangible investment and firm performance. We find that firm size and moderate competition is associated with higher intangible investment, while firm age is associated with lower intangible investment. Examining firm performance, we find that higher investment is associated with higher labour and capital input, higher revenue, and higher firm-reported employee and customer satisfaction, but not with higher productivity or profitability. The evidence suggests that intangible investment is associated with growth and ‘soft’ performance objectives, but not with productivity or profitability.

Keywords

Firm performance Industrial policy Intangible investment Productivity 

JEL Classification

D22 D24 L21 

Notes

Acknowledgements

This research is partially funded by the Productivity Hub under the Productivity Partnership programme, and by Queensland University of Technology. We would like to thank Lawrence J. White and an anonymous referee for valuable feedback. We also thank participants at an internal Motu seminar, as well as participants at a Productivity Commission of New Zealand workshop for helpful comments.

References

  1. Aghion, P., Bloom, N., Blundell, R., Griffith, R., & Howitt, P. (2002). Competition and innovation: An inverted U relationship (Working Paper No. 9269). National Bureau of Economic Research.Google Scholar
  2. Andrews, D., Criscuolo, C., & Menon, C. (2014). Do resources flow to patenting firms? (OECD Economics Department Working Papers). Paris: Organisation for Economic Co-operation and Development.Google Scholar
  3. Andrews, D., & de Serres, A. (2012). Intangible assets, resource allocation and growth (OECD Economics Department Working Papers). Paris: Organisation for Economic Co-operation and Development.Google Scholar
  4. Balasubramanian, N., & Sivadasan, J. (2010). What Happens When Firms Patent? New Evidence from U.S. Economic Census Data. Review of Economics and Statistics, 93(1), 126–146.CrossRefGoogle Scholar
  5. Bontempi, M. E., & Mairesse, J. (2015). Intangible capital and productivity at the firm level: a panel data assessment. Economics of Innovation and New Technology, 24(1–2), 22–51.CrossRefGoogle Scholar
  6. Corrado, C., Hulten, C., & Sichel, D. (2005). Measuring capital and technology: An expanded framework. In Measuring capital in the new economy (pp. 11–46). University of Chicago Press.Google Scholar
  7. Corrado, C., Hulten, C., & Sichel, D. (2009). Intangible Capital and U.S. Economic Growth. Review of Income and Wealth, 55(3), 661–685.CrossRefGoogle Scholar
  8. Corrado, C. A., Haskel, J., Iommi, M., & Jona Lasinio, C. (2012). Intangible capital and growth in advanced economies: Measurement and comparative results. Discussion Paper No. 6733, Institute for the Study of Labour (IZA), Bonn.Google Scholar
  9. Crass, D., & Peters, B. (2014). Intangible assets and firm-level productivity. Centre for European Research Discussion Paper No. 14-120.Google Scholar
  10. Crepon, B., Duguet, E., & Mairessec, J. (1998). Research, Innovation and Productivity: An Econometric Analysis At The Firm Level. Economics of Innovation and New Technology, 7(2), 115–158.CrossRefGoogle Scholar
  11. Elnasri, A., & Fox, K. J. (2017). The contribution of research and innovation to productivity. Journal of Productivity Analysis, 47(3), 291–308.CrossRefGoogle Scholar
  12. Fabling, R. (2011). Keeping it together: Tracking firms on New Zealand’s longitudinal business database. Motu Economic and Public Policy Research Working Papers 11_01.Google Scholar
  13. Fabling, R., & Maré, D. C. (2015a). Production function estimation using New Zealand’s longitudinal business database. Motu Economic and Public Policy Research Working Papers 15_15.Google Scholar
  14. Fabling, R., & Maré, D. C. (2015b). Addressing the absence of hours information in linked employer-employee data. Motu Economic and Public Policy Research Working Papers 15_17.Google Scholar
  15. Fabling, R., & Sanderson, L. (2016.). A rough guide to New Zealand’s longitudinal business database, 2nd edn. Motu Economic and Public Policy Research Working Papers 16_03.Google Scholar
  16. Firpo, S., Fortin, N. M., & Lemieux, T. (2009). Unconditional quantile regressions. Econometrica, 77(3), 953–973.CrossRefGoogle Scholar
  17. Griliches, Z. (1979). Issues in assessing the contribution of research and development to productivity growth. The Bell Journal of Economics, 10, 92–116.CrossRefGoogle Scholar
  18. Lin, H. L., & Lo, M. L. (2015). The portfolio of intangible investments and their performance: Evidence from Taiwanese Manufacturing Firms. Unpublished manuscript. Retrieved from http://homepage.ntu.edu.tw/~josephw/20151112_Intangible20151106v1.pdf.
  19. Maré, D. C. (2016). Urban productivity estimation with heterogeneous prices and labour. Motu Economic and Public Policy Research Working Papers 16_21.Google Scholar
  20. Machado, J. A. F., Parente, P. M., & Silva, J. S. (2015). QREG2: Stata module to perform quantile regression with robust and clustered standard errors. Statistical Software Components.Google Scholar
  21. Montresor, S., & Vezzani, A. (2016). Intangible investments and innovation propensity: Evidence from the Innobarometer 2013. Industry and Innovation, 1–22.Google Scholar
  22. Pakes, A., & Griliches, Z. (1984). Patents and R&D at the firm level: A first look. In Z. Griliches (Ed.), R&D, patents, and productivity (ch. 3). Chicago: University of Chicago Press.Google Scholar
  23. Scherer, F. M. (1982). Inter-industry technology flows and productivity growth. The Review of Economics and Statistics, 64, 627–634.CrossRefGoogle Scholar
  24. Scherer, F. M. (1983). The propensity to patent. International Journal of Industrial Organization, 1(1), 107–128.CrossRefGoogle Scholar
  25. Scherer, F. M. (1986). Innovation and growth: Schumpeterian perspectives. MIT Press Books, Cambridge 1.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Motu Economic and Public Policy ResearchWellingtonNew Zealand
  2. 2.Motu Economic and Public Policy Research, Te Pūnaha MatatiniQueensland University of TechnologyWellingtonNew Zealand

Personalised recommendations