3.3 Characteristics of the information set
3.3.2 Innovation inputs and output
One can distinguish between indicators that relate to the willingness to innovate and the extent of the innovation effort – innovation inputs –, and those referring to the existence of an actual innovation output as a result of the aforementioned effort.
A large amount of applied research excludes some of the different types of innova-tion input/output from their analyses. In the case of innovainnova-tion output, most of the applied work refers to new products and innovative production processes, while R&D has been the most studied innovative input. In the case of Uruguay, however, the omission of any category of innovation input or output is not in place given the particular innovation practices pursued by manufacturing firms.
Although very few firms invest in all inputs, the least preferred category among the nine defined in the surveys is chosen by 20% of firms. Regarding innovation output, until 2003 around 34% of all firms innovated in the four categories simultaneously.
The inadequacy of excluding any type of input and output from the analyses, faced to the complexities that would be introduced in the econometric models with the available detailed classification, forced us to group them in 4 and 2 categories, respec-tively29. Inputs are classified in R&D (both internal and external); Physical Capital, Hardware and Software (K+H+S); Training Programmes, including those directed to managers (TP); and Engineering & Industrial Design, Technology Transfers and Consultancy Services (EID+TT+CS). The output categories defined are Products accompanied or not by innovation processes; and Only Processes, irrespective of whether they relate to production, commercialization or organizational practices.
The frequency of firms in the here defined categorizations are depicted in Table 3.1, Table 3.2 and Figure 3.1 below.
Most innovative firms include physical capital, hardware and software among the inputs in which to invest, being training programmes the second preferred choice.
It is worth noting that investing in just one innovative input is quite rare, while investing in all categories is also less observed than other mixes.
Consequently, it is not convenient to restrict the analysis to a sole input, nor to the aggregate innovation input, as the diverse mixes chosen by firms are most likely to be very informative. Particularly, deciding on studying firms’ innovation expenditure
29The groupings were defined taking into account their theoretical adequacy, given the Uruguayan specificities (eg, TTP is not a representative category) and that the distribution of firms in the new classes is similar to that prevailing in the original categorization, both for the total sample and for the size and economic sectors strata.
focused on R&D would not be appropriate for Uruguay since although 50% of in-novative firms invest in R&D, a much higher percentage devotes its efforts to other inputs (around 80% of firms invest in capital & hardware & software, while near 70% of firms do so in training programmes). Further, if comparing the frequency of firms investing only in one input, R&D is far from being one of the most widespread practices.
Looking at the data on innovation output, a first interesting fact arising from the data is that most firms that invest in innovative inputs are able to get innovation outputs within a 3 years period, given that between 97% and 99% of innovative firms report having obtained results in the three surveys. Although these figures could include current innovation outputs that are related to having invested in in-novative inputs in previous periods, this is not the case for the samples analyzed.
The proportion of firms reporting having obtained results derived from investing in each innovative input in the corresponding 3-years period is always around 90%30. Hence, the innovative behavior of firms relative to investing and getting results may be analyzed within each survey.
Table 3.1: Distribution of firms by innovation input according to firm size, 1998-2000 - 2001-2003 - 2004-2006 (number and % of firms)
1998-2000 2001-2003 2004-2006
Total firms 494 100 494 100 494 100
Innovative firms 333 67 270 55 244 49
R&D 182 55 142 52 106 44
K+H+S 286 86 217 80 199 82
EID+TT+CS 159 48 136 50 90 37
TP 229 69 182 67 167 69
Only R&D 5 2 10 4 8 3
Only K+H+S 46 14 36 13 41 17
Only EID+TT+CS 7 2 6 2 4 2
Only TP 10 3 16 6 14 6
All Inputs 82 25 62 23 41 17
Notes: R&D includes both internal and/or external; K+H+S refers to Physical Capital and/or Hardware and/or Software; EID+TT+CS gathers Engineering & industrial design and/or Technology transfers &
Consultancy services; TP includes both management oriented and employees training programmes.
Source: own calculations based on the Innovation Surveys 1998-00; 2001-03, 2004-06; ANII/DiCyT /INE.
Two additional general comments are most in place. First, around 60% of Uruguayan innovative firms obtain innovative products as a result of their investment in inno-vative inputs, a figure that is much greater than expected, although at most 11%
are focused only in products, being the percentage around 7% on average along the whole period. Nonetheless, the above figures might overestimate the actual frequen-cies, not only as a consequence of the highly subjective character of these surveys
30These figures are obtained by counting the positive answers to the question “Have you obtained results from having invested in... (each innovative input)?”.
but also because of some evidence found in analyzing the data in depth.
On the one hand, according to the proportion of firms reporting innovative sales, product innovation should be around 7% lower than the percentage resulting from just counting the affirmative responses to the first question in the questionnaire, which asks if an innovative product has been obtained31. These 7% units did not answer to the additional questions on the sort of innovative product obtained, but instead they did report the type of innovative processes they got, in a completely consistent manner if ignoring the answer to the first question on them innovating or not in products. An additional 3% of firms reported having innovative sales, despite the fact that they declared having innovated only in processes. Those innovative sales were thus not linked to innovative products but to products resulting from the innovative processes in action. This fact suggests that in general terms it is most likely that a percentage of firms classified as innovating in products are indeed processes-innovative establishments only32.
Secondly, the design of the questionnaire is such that the first question the respon-dent faces relates to innovative products, an expression that in Spanish is very much similar to innovative output. This observation may explain why only when going ahead with the survey do respondents end answering correctly, differentiating inno-vative products from innoinno-vative output33.
Innovation processes are the most frequent type of innovation output obtained, as around 90% of firms innovate in at least one process. The figures are still high if restricted to each type of innovative process, being those related to production the category with the highest proportion of firms (80% on average) while those linked to commercialization practices have the lowest frequency (45% on average). Further, the percentage of firms that innovate only in at least one type of process is similar to the lower bound of the individual groups.
31The dataset here used already contains the figures corrected by us.
32We did not correct many of these cases at this stage, despite having quite strong evidence on them being misreported, due to time restrictions. We will probably be able to do so together with the INE in the months to follow.
33“Output” and “product” in Spanish are both translated as “producto”.
Figure 3.1: Frequency of firms according to different types of innovation output (Average percentage over all three surveys) The displayed figures do not add up to unity, given that they refer to the average percentage number of firms in each category, over all three surveyed periods.
Source: own calculations based on data from the Innovation Surveys 1998-00; 2001-03, 2004-06; ANII/DiCyT/INE.
The results are consistent with the stylized fact reported in the applied literature regarding the innovation behavior of firms in non-developed countries relative to what is generally seen in central economies.
From the above description, it is possible to state that the innovation behavior of manufacturing firms in Uruguay is more intensive in processes than in products, ob-tained by means of investing mainly in physical capital and training programmes for their employees. The most noteworthy result, however, relates to most Uruguayan firms obtaining a combined innovation output, both when new products are involved or not, by also combining inputs. This stylized fact thus strongly suggests the ex-istence of complementarities among inputs and types of output. Nonetheless, the mix most frequently analyzed in the literature – products and production processes (TTP) – is surprisingly among the least observed (9% on average). This result sup-port the hypothesis of developed and non developed countries displaying intrinsically different innovation behaviors.
The comparative statics analysis of the frequency of innovative output in time is not clear-cut. The only fact suggested by the data refers to product and production
process innovation being increasing in time, its intensity especially going up with the recovery of the economy in 2004.
Table 3.2: Distribution of firms of different sizes by innovation output, 1998-2000 - 2001-2003 - 2004-2006 (Number and % firms)
1998-2000 2001-2003 2004-2006
Innovative firms 333 100 270 100 244 100
Firms with innovative output 322 97 266 99 240 98
Production Processes 268 83 224 84 171 71
Organizational Processes 212 66 182 68 104 43
Commercialization Processes 170 53 145 55 57 24
Processes 309 96 253 95 214 89
Products 206 64 172 64 136 57
Only Processes 116 36 94 36 104 43
Only Production Processes 34 10 20 7 43 18
Only Non- Production Processes 26 8 24 9 32 13
Only Products 13 4 13 5 26 11
Products & Production Processes 34 10 36 13 11 5 Products & Non-Production Processes 15 5 5 2 11 5
All Outputs 107 33 90 34 27 11
Notes: ‘Production Processes’ refer to new or improved productive methods. ‘Only Processes’ refers to inno-vating in at least one process and not in products, while ‘Processes’ include firms that innovate in at least one process, irrespective of whether they also innovate in products or not. ‘Products’ includes all firms innovating in products only and those that also innovate in any process. Thus, the categories ‘Only Processes’ and ‘Pro-ducts’ add up to 100% and so do the categories ‘Processes’ and ‘Only Pro‘Pro-ducts’.
Source: Own calculations based on data from the Innovation Surveys 1998-00; 2001-03 and 2004-06, ANII/DiCyT/INE.
The data only includes three data points on its time dimension, them being three three-year-periods: 1998-2000, 2001-2003 and 2004-2006. Although from a statistical point of view these constitute only three data points, they still mirror a full period of eight years. In addition, the period in question displays three very well defined moments of the country’s economic cycle. The first period finds the Uruguayan business cycle at a peak, while during the second period the country faced one of its worse crises, reaching a trough in September 2002. In the third period the Uruguayan business cycle was undergoing a middle recovery. One could hence argue that given the three periods in time considered, firms’ innovation behavior can be seen in the light of how they relate to the business cycle.
According to the analyzed dataset, firms seem to combine an increasing trend in product innovation with innovative production processes. This behavior appears to be pro-cyclical, which might be linked to the size and market structure in innovative economic sectors after the economic crisis. Similarly, regarding innovation inputs, an apparent decreasing trend is found in R&D investment and a not very pronounced pro-cyclical behavior of innovative investment in capital, hardware and software.
Finally, the data reveal an apparent negative time trend in the percentage of inno-vative firms. However, those that succeed in obtaining an innovation output are a
constant share of innovative firms. As such, the result cannot bea priori associated to institutional obstacles for carrying on the activities, although the existence of re-strictions for investing in innovation inputs cannot be discarded. Alternatively, this may just be reflecting the life-cycle of firms given that a large extent of the sample is fixed. Also, the decrease in the share of firms pursuing innovation may be linked to the changes in the composition of the firm sample that took place after 2002. If compared to previous periods with respect to the degree of market concentration or to the share of firms of specific sizes the firm landscape changed substantially, with more small sized firms and less concentrated markets. To shed light on possible underlying causes explaining the innovative behavior of firms, in what follows we add other dimensions to our descriptive analysis.