The Impact of Innovative Activity in Economic Performance: An ...

600 International Conference on Applied Economics – ICOAE 2008
a The cut value is ,500
Observed
Classification Table(a)
Predicted
DE96_05 Percentage Correct
,00 1,00
Step 1 DE96_05 ,00 23 8 74,2
1,00 7 13 65,0
Overall Percentage 70,6
Variables in the Equation
B S.E. Wald df Sig. Exp(B)
Step 1(a) Innovation 2,575 1,150 5,011 1 ,025 13,125
Size ,736 ,357 4,253 1 ,039 2,087
Ownership -,599 ,924 ,420 1 ,517 ,550
DF96_05 ,000 ,000 ,064 1 ,800 1,000
Constant -6,341 2,557 6,149 1 ,013 ,002
a Variable(s) entered on step 1: Innovation, Size, Ownership, DF96_05.
In order to avoid any possible bias in the analysis by considering both IPRs and R&D activity as innovative activity for the firms, and
attribute to them as one variable, we chose to proceed further to the analysis, segregating and include them in the model as separate variables.
The reason was that the latter is real in-house R&D process, while the former includes the acquisitions of intellectual Property Rights or the
‘third parties production’ the so-called as «FASON». As we can see from the results apposed in the following summarised table, only R&D is
really a critical factor concerning higher rates of growth, not IPRs. That is a truly interesting finding, confirming that in-house innovative
process is what firms (especially smaller and independent) should focus on, in order to survive and grow.
5. Conclusions
Table 10: Summarised Process’ Results
Dependent: Sales Dependent: Employment
Nagelkerke ,339 Nagelkerke ,283
R Square
R Square
Percentage 76,5 (0: 82,1
Percentage 76,5 (0: 80,6
Correct
1: 69,6)
Correct
1: 70,0)
DF96_05 ,083 (Exp(B):1,003) DF96_05 ,861 (Exp(B):1,000)
Ownership ,331 (Exp(B):2,747) Ownership ,352 (Exp(B): ,399
Size ,476 (Exp(B): ,773) Size ,086 (Exp(B): 1,804)
RandD ,033 (Exp(B): 4,577) RandD ,019 (Exp(B):5,254)
IPRs ,773 (Exp(B): 1,245) IPRs ,909 (Exp(B): ,918)
In the present survey, we tried to approach a very important sector of the economy, the pharmaceutical industry, which affects not only
the overall economic indices, but also the quality of life. Through the proper transformation of our data set and the development of an
econometric model (logistic regression), we manage to include economic and non-economic factors in the same analysis, trying to cover a
broader research field. The use of such methodology, although not common in economic analysis, proved to be very useful for data sets
consisting of both economic and non-economic data, with dichotomous dependent variables.
Our scope was to examine the role of innovative activity in firms’ growth (in terms of sales and employment), among other factors such
as investment in tangible assets, size of the firms and ownership status (subsidiary company or independent). Our findings seem to confirm
that innovative activity proves to be (in pharmaceutical sector), the most important factor for firms’ better performance.
Furthermore, segregating R&D and IPRs and attributing them as two different explanatory variables, we isolated the effect of active inhouse
innovative process from the acquisition of foreign know-how, and find that only the former can interpret the achievement of high rates
of growth. As subsidiary companies control the major part of the market-share in Greek pharmaceutical industry and achieve higher net
profits’ ratio, the only factor that seems to be able to help the other firms in the sector to survive, is active innovative process. The latter
should be considered thoroughly, from Greek firms which seem to present low rates in that kind of expenses.
References
Autio, E., and Parhankangas, A., (1998), ‘Employment Generation Potential of New, Technology-Based Firms During a Reccessionary
Period: The Case of Finland’, Small Business Economics, 11:113-123.