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Does cash flow cause investment and R&D: an exploration using panel data for French, Japanes and United States scientific firms

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  • Bronwyn H. Hall
  • Jacques Mairesse
  • Benoit Mulkay

Abstract

The role of financial institutions and corporate governance in the conduct and performance of industrial firrm, especially in the area of technological innovation and international competition has been hotly debated in the recent past. The results presented here are a contribution to the empirical evidence on the behavior of individual firms that exist in somewhat different institutional environments. Using a Panel Data version of the Vertor Auto Regressive (VAR) methodology, we test for causal relationship among sales and cash flow on the one hand and investment and R and D on the other, using three large panels of firms in the scientific (high technology) sectors in the United States, Rance, and Japan. Our findings are that both invest- ment and R and D are more highly sensitive to cash flow and sales in the United States than in Rance and Japan. Correspondingly, both investment and R and D predict both cash flow and sales positively in the United States, while the impact is somewhat more mixed in the other countries.

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Bibliographic Info

Paper provided by Institute for Fiscal Studies in its series IFS Working Papers with number W98/11.

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Date of creation: Oct 1998
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Handle: RePEc:ifs:ifsewp:98/11

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References

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  1. Griliches, Zvi & Mairesse, Jacques, 1983. "Comparing productivity growth: An exploration of french and U.S. industrial and firm data," European Economic Review, Elsevier, vol. 21(1-2), pages 89-119.
  2. Jacques Mairesse & Alan K. Siu, 1984. "An Extended Accelerator Model of R&D and Physical Investment," NBER Chapters, in: R & D, Patents, and Productivity, pages 271-298 National Bureau of Economic Research, Inc.
  3. Keane, Michael P & Runkle, David E, 1992. "On the Estimation of Panel-Data Models with Serial Correlation When Instruments Are Not Strictly Exogenous," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(1), pages 1-9, January.
  4. Bronwyn H. Hall & Jacques Mairesse, 2000. "Univariate Panel Data Models and GMM Estimators: An Exploration Using Real and Simulated Data," Econometric Society World Congress 2000 Contributed Papers 1114, Econometric Society.
  5. Richard Blundell & Steve Bond, 1995. "Initial conditions and moment restrictions in dynamic panel data models," IFS Working Papers W95/17, Institute for Fiscal Studies.
  6. Arellano, Manuel & Bond, Stephen, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Wiley Blackwell, vol. 58(2), pages 277-97, April.
  7. Hoshi, Takeo & Kashyap, Anil & Scharfstein, David, 1990. "The role of banks in reducing the costs of financial distress in Japan," Journal of Financial Economics, Elsevier, vol. 27(1), pages 67-88, September.
  8. Pesaran, M. H. & Shin, Y. & Smith, R. P., 1997. "Pooled Estimation of Long-run Relationships in Dynamic Heterogeneous Panels," Cambridge Working Papers in Economics 9721, Faculty of Economics, University of Cambridge.
  9. Alexander, Ian & Mayer, Colin, 1990. "Banks and Securities Markets: Corporate Financing in Germany and the UK," CEPR Discussion Papers 433, C.E.P.R. Discussion Papers.
  10. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1988. "Estimating Vector Autoregressions with Panel Data," Econometrica, Econometric Society, vol. 56(6), pages 1371-95, November.
  11. Bronwyn H. Hall & Jacques Mairesse, 1992. "Exploring the Relationship Between R&D and Productivity in French Manufacturing Firms," NBER Working Papers 3956, National Bureau of Economic Research, Inc.
  12. Zvi Griliches, 1998. "R&D and Productivity Growth: Comparing Japanese and U.S. Manufacturing Firms," NBER Chapters, in: R&D and Productivity: The Econometric Evidence, pages 187-210 National Bureau of Economic Research, Inc.
  13. W. Carl Kester, 1992. "Governance, Contracting, And Investment Horizons: A Look At Japan And Germany," Journal of Applied Corporate Finance, Morgan Stanley, vol. 5(2), pages 83-98.
  14. Crepon, Bruno & Kramarz, Francis & Trognon, Alain, 1997. "Parameters of interest, nuisance parameters and orthogonality conditions An application to autoregressive error component models," Journal of Econometrics, Elsevier, vol. 82(1), pages 135-156.
  15. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
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