Van Leeuwen, George and Polder, Michael (2013): Linking ICT related Innovation Adoption and Productivity: results from micro-aggregated data versus firm-level data.
Preview |
PDF
MPRA_paper_46479.pdf Download (569kB) | Preview |
Abstract
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.
Item Type: | MPRA Paper |
---|---|
Original Title: | Linking ICT related Innovation Adoption and Productivity: results from micro-aggregated data versus firm-level data. |
English Title: | Linking ICT related Innovation Adoption and Productivity: results from micro-aggregated data versus firm-level data. |
Language: | English |
Keywords: | DMD, ICT, innovation, innovation complementarities, productivity |
Subjects: | D - Microeconomics > D2 - Production and Organizations D - Microeconomics > D2 - Production and Organizations > D24 - Production ; Cost ; Capital ; Capital, Total Factor, and Multifactor Productivity ; Capacity D - Microeconomics > D8 - Information, Knowledge, and Uncertainty L - Industrial Organization > L2 - Firm Objectives, Organization, and Behavior L - Industrial Organization > L2 - Firm Objectives, Organization, and Behavior > L21 - Business Objectives of the Firm |
Item ID: | 46479 |
Depositing User: | Dr George van Leeuwen |
Date Deposited: | 24 Apr 2013 10:51 |
Last Modified: | 28 Sep 2019 22:00 |
References: | Aral, S., E. Brynjolfsson, and D.J. Wu (2006), “Which Came First, IT Or Produc-tivity? The Virtuous Cycle Of Investment And Use In Enterprise Systems”, Twenty Seventh International Conference on Information Systems, Milwaukee 2006. Athey, Susan and Scott Stern,1998, “An Empirical Framework for Testing Theories About Complementarity in Organizational Design”. National Bureau of Economic Research Working Paper 6600. Bharadway, Anandhi S., 2000, “A Resource-Based Perspective on Information Technology Capability and Firm Performance: An Empirical Investigation”, MIS Quarterly, Vol. 24, No 1, pp 169-196. Bartelsman, E. J., 2004, “The Analysis of Microdata from an International Perspec-tive”, STD/CSSTAT (2004), 12 OECD. Cappellari, Lorenzo and Stephen P. Jenkins, 2003, “Multivariate Probit regression using Simulated maximum likelihood”. The StataJournal, Vol.3, No3, pp 278–294. Cappellari, Lorenzo and Stephen P. Jenkins, 2006, “Calculation of multivariate normal probabilities by simulation, with applications to maximum simulated likeli-hood estimation”. The Stata Journal, Vol.6, No 2, pp 156–189. Davenport, T.H., 1998 ,”Putting the enterprise into the enterprise system”, Har-vard Business Review, 76, 121–131. Falk, Martin. (2013),”ICT linked firm reorganization and productivity gains”. Technovation (forthcoming), Gourieroux, Christian, Alain Monfort, Eric Renault and Alain Trognon, 1987, “Generalized Residuals”. Journal of Econometrics, Vol. 34, pp. 5–32. Heckman, James, J., 1978, “Endogenous variables in a Simultaneous Equation System”, Econometrica, Vol. 46, No 4, pp 931–959. Hitt, Lorin M., D. J. Wu and X. Zhou., 2002, “Investment in Enterprise Resource Planning: Business Impact and Productivity Measures”, Journal of Management Information Systems, Vol. 19, No 1, pp 71-98. Kodde, David, A. and Franz Palm, 1986, “Wald Criteria for Jointly Testing Equal-ity and Inequality Restrictions”.Econometrica, Vol. 54, No. 5, pp. 1243–1248. Kretschmer, Tobias, Eugenio J. Miravete and José C. Pernías (2012), “Competitive pressure and the adoption of innovations”. American Economic Review, Vol 102, No. 4, pp.1540-1570. Lewbel, Arthur, 2007, “Coherency and Completeness of Structural Models containing a Dummy Endogenous Variable”. International Economic Review, Vol. 48, No 4, pp 1379–1392. Milgrom, Paul and John Roberts, 1990, “The economics of modern manufacturing, technology, strategy and organizations”. American Economic Review, Vol. 80, pp. 511–528. Milgrom, Paul and John Roberts, 1995, “Complementarities and fit. Strategy, structure and organizational change in manufacturing”. Journal of Accounting & Economics, Vol. 19,pp. 179–208. Miravete, E. and J. Pernías (2006). “Innovation complementarity and scale of production”. Journal of Industrial Economics, Vol. 54, pp. 1-29. Mohnen, Pierre and Lars-Hendrik Röller, 2005, “Complementarities in innovation policies”. European Economic Review, Vol. 49, pp. 1431–1450. Polder, Michael, George van Leeuwen, Pierre Mohnen and Wladimir Raymond, 2010, “Product- process and organizational innovation: drivers, complementarity and productivity effects”.UNU-MERIT Working Paper 2010-035, UNU-MERIT, Maastricht. Polder, Michael, Fardad Zand, George van Leeuwen and Cees van Beers, 2012, “Complementarities between Information Technologies and Innovation Modes in the Adoption and Outcome Stage: A Micro Econometric Analysis for the Nether-lands”, Paper presented at the CAED Conference 2012, Nuremberg. Shin, Ilsoon, 2006, ”Adoption of Enterprise Application Software and Firm Perfor-mance”, Small Business Economics, 26, 241–256. Tamer, Elie. 2003, “Incomplete Simultaneous Discrete Response Model with Multiple Equilibria”.The Review of Economic Studies. Vol. 70, No 1, pp 147–165. Train, Kenneth, 2003, “Discrete Choice Methods with Simulations. Cambridge University Press, Cambridge UK. Van Leeuwen, George and Pierre Mohnen, 2013, “Revisting The Porter Hypothesis, An Empirical Analysis of Green Innovation For The Netherlands”, UNU-MERIT Working Paper 2013-02, UNU-MERIT, Maastricht. Wooldridge, J. M., 2002, “Econometric Analysis of Cross Section and Panel Data”. The MIT Press, Cambridge Massachusetts, Cambridge USA. Zand, F. (2011), “Information Technology and Firm Performance: The Role of Innovation”, PhD. Thesis, Technical University of Delft. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/46479 |