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Linking ICT related Innovation Adoption and Productivity: results from micro-aggregated data versus firm-level data

  • Van Leeuwen, George
  • Polder, Michael

E-business systems are increasingly considered as important examples of ICT related innovations embodied in software applications, the adoption of which is essential for capturing the potential fruits of several ICT externalities. For analysing the importance of this type of embodied technological progress several routes are open. One route is to look at the data that can be used. In this paper we apply the same modelling strategy to two different types of data: 1) cross-country-industry micro-aggregated data obtained after applying Distributed Micro data Analysis (DMD) and 2) firm-level data, in this case for the Netherlands. Today, the econometric analysis based on firm-level data is often more advanced and more complicated from an econometric point of view than the analysis on aggregated data. We show that DMD can be extended to enable the estimation of more complicated models that feature recent directions in micro-econometric analysis on firm-level data. Our application concerns the innovative use of E-business systems by firms. Using a rich set of cross-country-industry data constructed and tailored by DMD for this purpose, we analyse the adoption of three E-business systems (Eterprise Resourc Planning, Customer Relationship Management, Supply Chain Management). We investigate the complementarities in joint adoption and the productivity effects of adopting systems simultaneously or in isolation. The same exercise is repeated on firm-level data for the Netherlands. Our example illustrates that international benchmarking with more elaborate models on cross-country-industry panel data is feasible after using DMD to tailor the underlying firm-level data for specific research questions. This is an important result in the light of the restrictions on pooling cross-country micro data due to confidentiality rules. We find that the results are more diverging for the estimation of complementarities at the adoption stage than for the productivity effects of (joint) adoption. This result implies that measurement error and unobservable heterogeneity plays a greater role when explaining adoption pattern at the firm-level than at the aggregate level.

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Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 46479.

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Date of creation: 31 Mar 2013
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Handle: RePEc:pra:mprapa:46479
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  1. Arthur Lewbel, 2007. "Coherency And Completeness Of Structural Models Containing A Dummy Endogenous Variable," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(4), pages 1379-1392, November.
  2. Cappellari, Lorenzo & Jenkins, Stephen P., 2006. "Calculation of Multivariate Normal Probabilities by Simulation, with Applications to Maximum Simulated Likelihood Estimation," IZA Discussion Papers 2112, Institute for the Study of Labor (IZA).
  3. Tobias Kretschmer & Eugenio J. Miravete & Jose C. Pernias, 2012. "Competitive Pressure and the Adoption of Complementary Innovations," American Economic Review, American Economic Association, vol. 102(4), pages 1540-70, June.
  4. Elie Tamer, 2003. "Incomplete Simultaneous Discrete Response Model with Multiple Equilibria," Review of Economic Studies, Wiley Blackwell, vol. 70(1), pages 147-165, January.
  5. Michael Polder & George van Leeuwen & Pierre Mohnen & Wladimir Raymond, 2010. "Product, Process and Organizational Innovation: Drivers, Complementarity and Productivity Effects," CIRANO Working Papers 2010s-28, CIRANO.
  6. Pierre Mohnen & Lars-Hendrik Röller, 2000. "Complementarities in Innovation Policy," CIG Working Papers FS IV 00-18, Wissenschaftszentrum Berlin (WZB), Research Unit: Competition and Innovation (CIG).
  7. Lorenzo Cappellari & Stephen P. Jenkins, 2003. "Multivariate probit regression using simulated maximum likelihood," United Kingdom Stata Users' Group Meetings 2003 10, Stata Users Group.
  8. Milgrom, Paul & Roberts, John, 1995. "Complementarities and fit strategy, structure, and organizational change in manufacturing," Journal of Accounting and Economics, Elsevier, vol. 19(2-3), pages 179-208, April.
  9. Heckman, James J, 1978. "Dummy Endogenous Variables in a Simultaneous Equation System," Econometrica, Econometric Society, vol. 46(4), pages 931-59, July.
  10. Eugenio J. Miravete & Jos� C. Pern�As, 2006. "INNOVATION COMPLEMENTARITY AND SCALE OF PRODUCTION -super-* ," Journal of Industrial Economics, Wiley Blackwell, vol. 54(1), pages 1-29, 03.
  11. Elie Tamer, 2003. "Incomplete Simultaneous Discrete Response Model with Multiple Equilibria," Review of Economic Studies, Oxford University Press, vol. 70(1), pages 147-165.
  12. Ilsoon Shin, 2006. "Adoption of Enterprise Application Software and Firm Performance," Small Business Economics, Springer, vol. 26(3), pages 241-256, 04.
  13. Cappellari, Lorenzo & Jenkins, Stephen P., 2006. "Calculation of multivariate normal probabilities by simulation, with applications to maximum simulated likelihood estimation," ISER Working Paper Series 2006-16, Institute for Social and Economic Research.
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