Abstract
In this paper we investigate the innovative patterns of Chilean productive sectors applying multivariate analysis methods such as factor and cluster analysis. Three main patterns are detected in our sample according to the type of innovation introduced and the motivation behind it: product strategy innovators, cost strategy innovators and non-innovators. Starting on this clustering, we analyze the relationship between innovative pattern (or type of innovation introduced) and wage for professional category. We found a positive impact of product innovations on wages for all professional groups except unskilled manual workers. Controlling for unobserved firm heterogeneity through a fixed effect panel estimator, coefficients are not significant anymore for all professional categories. Only for innovations in marketing we can still register a wage premium earned by high skilled workers. Finally, we do not register a polarization effect as the one detected for Europe by recent literature.
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Notes
Compared to our dataset, Laaksonen et al. have the possibility to exploit a worker-establishment data base containing information on workers characteristics, such as age, level of education, technical science education.
For the description of the questionnaire, please make reference to the Appendix.
Monetary values are expressed in miles of Chilean Pesos and deflated to 2009 values.
StataCorp 2009. Stata: Release 11. Statistical Software. College Station, TX: StataCorp LP, p. 310.
In order to check the stability of our results, we provide further estimations of factor scores applying other techniques such as principal component, maximum likelihood, iterative principal factors and principal component factors.
Competing wage.
We decide to use labour costs instead of wages, due to the large number of missing values in the sample for wages. We found the same procedure also in Goos and Konings (2000).
The two factors election is also supported by the iterated principal factors and by the maximum likelihood methods. In both cases, the eigenvalue of the first two factors is greater than one. Results are available upon request.
Even if Chile is one of most dynamic country in LAC region in terms of innovation, it is not surprising that the majority of firms declare to not introduce innovations.
We apply the standard formula for dummy variables with dependent variable expressed in logarithms \( \left( {e^{0.1274} - 1} \right)*100 = 13.58 \).
\( H_{0} : \) Random effects are orthogonal to the regressors.
Recently, Peters (2009), “Persistence of innovation: stylized facts and panel data evidence”, The Journal of Technology Transfer, Vol. 34, Issue 2, shows that past innovation experience is an important determinant for firms in manufacturing and services.
The first wave of ELE has been perceived as quite difficult by entrepreneurs, particularly the section on innovations. Actually, some questions have been changed in the second wave in order to facilitate the comprehension.
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Cirillo, V. Patterns of innovation and wage distribution. Do “innovative firms” pay higher wages? Evidence from Chile. Eurasian Bus Rev 4, 181–206 (2014). https://doi.org/10.1007/s40821-014-0010-0
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DOI: https://doi.org/10.1007/s40821-014-0010-0