Michael Polder

Product, Process and Organizational Innovation: Drivers, Complementarity and Productivity Effects

We propose a model where both R&D and ICT investment feed into a system of three innovation output equations (product, process and organizational innovation), which ultimately feeds into a productivity equation. We find that ICT investment and usage are important drivers of innovation in both manufacturing and services. Doing more R&D has a positive effect on product innovation in manufacturing. The strongest productivity effects are derived from organizational innovation. We find positive effects of product and process innovation when combined with an organizational innovation. There is evidence that organizational innovation is complementary to process innovation.

Micro Moments Database for Cross-Country Analysis of ICT, Innovation, and Economic Outcomes

This paper provides technical documentation to a database built up from firm-level sources titled Micro moments database (MMD) that is made available for researchers through Eurostat. The MMD is an internationally harmonized research database of statistical moments collected from linked longitudinal firm-level data in a large selection of EU national statistical offices. The underlying sources for the database are business registers, firm-level surveys on production, usage of Information and Communications Technologies (ICT) and innovative activities, as well as recorded information on trade and worker education, all linked at the firm level. The unit of observation in the MMD represents groups of firms within industries and allows research that bridges micro and macro analysis. The paper delineates the type of research questions that uniquely can be addressed with the MMD, and the advantages and disadvantages of using MMD for questions where alternative datasets are available. The paper next presents the methodology underlying construction of the MMD and provides documentation of the rich set of features. Finally, the paper provides descriptive statistics that highlight the unique character of the data and reviews some of the cross-country analytical work already conducted using the MMD.

CDM using a cross-country micro moments database†

ABSTRACT This note starts with a retrospective view of the CDM model [Crépon, Bruno, Emmanuel Duguet, and Jacques Mairesse. 1998. “Research, Innovation and Productivity: An Econometric Analysis at the Firm Level.” Economics of Innovation and New Technology 7 (2): 115–158.] as an econometric framework for studying innovation and growth. A narrative interpretation of CDM describes the chain from innovative activity at firms to increases in welfare and makes links to the policy environment. Filling in missing pieces of the innovation to productivity puzzle has a heavy data burden. The paper makes use of the micro moments database (MMD) that allows observing micro-level behavior and macro-level impacts of innovation and production in a large selection of European countries. Two examples are given of research using the MMD. First, we estimate a simplified system of innovation and production equations that can be applied to average firm choices and outcomes, as well as to industry or aggregate outcomes. We find that innovative activity contributes to aggregate productivity even while the average effect at the firm level is insignificant. Next, a cross-country exploration is made that shows heightened productivity effects of combined use by firms of various enterprise-level information and communications technologies.

ICT, R&D, and Organizational Innovation: Exploring Complementarities in Investment and Production

This paper examines whether there are complementarities between investments in ICT, R&D and organizational innovation, and the effects of different investment profiles on total factor productivity growth on Dutch firm-level data. We estimate an integrated model of investment profile adoption and total factor productivity growth. We find that the three investment decisions are complementary, in the sense that investing in one increases the probability of investing in another one because joint investments lead to higher TFP growth than individual investments. ICT earns on average an expected rate of return of 9.7%, followed by 6% to 7% on organizational innovation and a modest 1.4% to 1.8% on R&D in services and manufacturing respectively.