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Employment Effects of Innovation at the Firm Level

Explore the impact of innovation on employment, focusing on product vs. process innovations. Utilize panel data to distinguish effects and categories of innovations. Investigate theoretical and empirical contributions, along with the complex employment adjustment process. Consider endogeneity issues and potential IV strategies. Results suggest positive effects of innovations on employment growth, with process innovations showing higher impact. No additional effects for R&D-based innovations, but patent-related product innovations show added benefits. Further research recommended on adjustment process dynamics.

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Employment Effects of Innovation at the Firm Level

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  1. Employment Effects of Innovation at the Firm Level Stefan Lachenmaier*, Horst Rottmann♦ 3. Konferenz für Sozial- und Wirtschaftsdaten, Mai 2006, Wiesbaden * Ifo Institute for Economic Research at the University of Munich ♦ University of Applied Sciences Amberg-Weiden and Ifo Institute

  2. The Research Question • Do innovations have a significant effect on employment? • Concentrate on the analysis of long-term effects

  3. Motivation • Theoretical contributions show different results • Product innovations: increase demand  increase employment level  decrease competition increase market power reduce output decrease employment • Process innovations: increase labour productivity  decrease employment level  lower costs  lower prices  higher demand  stimulate emplyoment  Overall effect is depending on elasticity of demand • Empirical evidence is necessary • Panel studies are rare due to the lack of appropriate data

  4. Main Idea • Exploit long innovation panel data set • Distinguish between product and process innovations • Introduce different innovation categories

  5. Related Literature • Theoretical Contributions: • Petit (1995) • Stoneman (1984), Hamermesh (1993) • Empirical Contributions: • Chennels / Van Reenen (1999) • Cross-Sectional Analyses: Zimmermann (1991), König et al. (1995) • Employment Growth Analyses: Brouwer et al. (1993), Blanchflower/ Burgess (1999), Blechinger et al. (1998) • Panel Analyses: Smolny (1998), van Reenen (1997), Rottmann/Ruschinski (1998)

  6. Database • Ifo Innovation Survey • Panel Structure: 1982-2003 (unbalanced) • German Manufacturing Sector • ~1300 observations per year • Contains information on: • Innovation: Product and Process Innovation, Innovations introduced, Innovation expenditure • Firm characteristics: firm size, NACE, German states, turnover • Control variables added on sector level (2digit NACE)

  7. Empirical Model • Modelling employment adjustment process is complex, esp. for small firms (e.g. Hamermesh / Pfann 1996) • Labour demand reacts slowly to changes in innovation behaviour • Estimating long-term effects: Following Blanchard / Wolfers (2000), Nickell (1997, 2003) • Calculating averages for 4-(and 5-year periods) • Use period averages for panel analysis (time index t indicates period)

  8. Estimation Level Equation: L: Labour demand T: Technology Q: Product quality X: Controls Linear Equation in differenced log values: • transformed into growth rates • allows to introduce innovation variables • Eliminates unobservable firm effect

  9. Estimation Equation: IPc: Process Innovation (proxy for Dt) IPd: Product Innovation (proxy for Dq) Dw: Growth of Real Hourly Wage Rate (sectoral) Dg: Growth of Real Gross Value Added (sectoral) eit: log of employment start level • Remember: • Variables are expressed in averages over periods

  10. The problem of endogeneity • Potential contemporaneous correlation of innovation and error term resulting from a shock simultaneously affecting employment and innovation • IV Strategy • So far we tested Innovation Impulses, Innovation Obstacles, lagged values • No robust results: Either instruments are not good (low significance in first stage) or not valid (Sargan test)

  11. Descriptive Statistics Until 1990: Former West Germany, since 1991: Germany Unbalanced panel: 9142 „observations“, 4567 different firms, 5 time categories

  12. Regressions I

  13. Regressions II

  14. Regressions III

  15. Regressions IV

  16. Summary • Innovations show positive effects on employment growth • True for product as well as process innovations. Process innovations show even higher effect • No additional effect for R&D based innovations • Additional effect for product innovations which involved patent applications • Further Research: Dynamics of adjustment process

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