Innovation and Productivity: What can we learn from the CIS III Results for Portugal?

1. Innovation and Productivity: What can we learn from the CIS III Results for Portugal? Pedro Morais Martins de Faria pedro.faria@dem.ist.utl.pt Orientador: Doutor Pedro Filipe Teixeira da Conceição Co-Orientadora: Doutora Elsa Beatriz Padilla 23 December 2004 The research reported in this thesis was partially supported by Observatorio da Ciencia e do Ensino Superior (OCES) [Obervatory of Science and Higher Education, Ministry for Science and Higher Education, Portugal]

2. Introduction • Two issues associated with the relationship between productivity and innovation: • the impact of technological breakthroughs on productivity; • 2) the time frame within which that impact occurs. • The relationship between innovation and productivity growth is expected to be positive in the long run and at the macro level (countries and regions). • But in the short run and at the firm level, the relationship between innovation and productivity growth may be negative.

3. Theories Arguments Main References Innovation - new skills - productivity decrease New skills necessary to adopt correctly new technologies Jovanovic and Nyarko (1996) Time and costs of the adoption process not Learning Ahn (1999, 2001) neglegetable - learning cost Innovation implies the execution of non-productivity activities - drop in productivity in the short run More productive firms have difficulties to change technology negative relationship between innovation and levels of productivity When technologies appear perform less effectively than the technologies already diffused Technology transfer imply a change on management techniques in order to synchronize the firm Leonard-Barton (1988, 1992) characteristics with the innovation Utterback (1994) Christensen and Bower (1996) More productive firms may be reluctant to switch to Christensen (1997) new technologies that would imply significant Technology and Organizational Rigidities Young (1991, 1993) productivity losses Benner and Tushman (2002) More productive firms are those that stick more Tripsas and Gavetti (2002) closely to existing routines Decision not to innovate - level of productivity and level of organizational rigidity Periods of adoption of new technologies - adjustment costs and decrease of levels of output May be a lag between the growth in investment and its benefits Bessen (2001) Adjustment costs - Bernstein et al. (1999) costs related to setting up new equipment, training of and innovation Adjustment Costs positive relationship between levels of productivity Hall (2002) employees (resources used to fully utilize the capital) Leung (2004) During the introduction of the innovation stage, innovative firms will have a lower rate of productivity growth than non-inovative firms More productive firms are those that are more capable to deal with adjustments costs and liquidity constrains Three general explanations that predict a negative relationship between productivity growth and innovation in the short run.

4. Data The CIS III is a nation-wide firm-level survey that measured directly innovation by asking whether firms have introduced any new process or product in the context of the firm. The CIS III inquired a representative sample of the Portuguese firms. The CIS III provides information at the firm level for the period 1998-2000.

5. Model and Methods (I) The model was constructed assuming that innovation and productivity change are simultaneously determined in the CIS III sample. Thus, in order to avoid possible biases that result from this fact, the proposed model, that builds on the Conceição et al. (2003) approach, is a system of two equations: one predicting innovation and other predicting productivity growth.

6. Model and Methods (II) Where: Prdg –Productivity Growth Measure – log (Turnover / nº Workers) Inov –Innovation Dummy Variable Exp –Exports / Turnover NF –Dummy Variable that indicates if the firm is new (1998-2000) GP –Dummy Variable that indicates if the firm is part of a group ED –Share of the Workforce engaged in specialized tasks CS –Gross Investments in Capital Goods S –Sector Dummy Variables Log_Turn_Inic –Critical Identification Variable - log (Turnover 1998)

7. Model and Methods (III) 1) Endogeneity: Hausman Test OLS – inconsistent 2)Equation System: 3)Covariance Correction: Murphy-Topel Method - two step estimation method for mixed models that include limited dependent variables

8. Model and Methods (IV) A novelty of this study is the inclusion of a new variable that measures partially the management and strategy of firms. Although the productivity literature states that management and investment strategy influence the level and the dynamics of productivity, these aspects of firm behavior are exceptionally difficult factors to quantify and to measure. This variable can bring new light to the understanding of the productivity/innovation relationship. To measure goods (CS), a variable that exposes the investment strategy of the influence of management and investment strategy in productivity, we considered the log of the gross investments in tangible the firm. This variable is an indicator of a firm’s strategy towards enhancing productivity since productivity growth is often linked to investments in capital goods.

9. Results (I) Note: * Significant at 10%; ** 5%; *** 1%; Sector Dummies Variables included but not reported

10. Results (II) Note: * Significant at 10%; ** 5%; *** 1%; Sector Dummies Variables included but not reported

11. In the sample of Portuguese firms surveyed by the CIS III, innovative firms have a lower degree of productivity growth when compared with non-innovative firms Conclusions (I) The more productive firms are more innovative – this is coherent with the Adjustment Costs Theory The inclusion of the new variable Gross Investment in Capital Goods gives robustness to the model

12. Conclusions (II) Policy implications: The evaluation of innovation impacts cannot be done only in the short run: technology adoption is a complex process that does not render results instantaneously. Therefore, when evaluating a new technology, decision makers at the firm and state level have to consider this time lag between adoption and productivity growth: a technology that is inefficient in the short run can raise productivity in the long run. Further Work: Case studies could be conducted in Portuguese firms aiming at capturing possible differences between sectors. International comparisons could be done with data from the CIS from other countries.

13. Innovation and Productivity: What can we learn from the CIS 3 Results for Portugal? Pedro Morais Martins de Faria pedro.faria@dem.ist.utl.pt Orientador: Doutor Pedro Filipe Teixeira da Conceição Co-Orientadora: Doutora Elsa Beatriz Padilla 23 December 2004