Abstract
We study the economic value of both embodied technological change and Research and Development (R&D) investment as proxies for the inputs of innovative activities conducted by Vietnamese firms. Our main focus is on the profitability of young innovative companies (YICs), private innovative companies (PICs), and small and young companies (SYCs). In particular, we test whether YICs could prove successful in fostering economic development through their technological change activities. Results show that (a) although YICs are more R&D intensive and innovative than PICs and SYCs, in general they do not produce equivalent performance; however those specific YICs focusing on technological change potentially outperform their counterparts, and (b) PICs are more capable than the other types of firms in translating their innovative effort to higher profitability.
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Notes
Technological change is “embodied” when it takes the form of newer capital input (tangible internal investments in new machinery, equipment, and work-in-progress), whereas it is “disembodied” when resulting in intangible accumulation of knowledge.
NTBFs are independently owned firms, are less than 25 years old, and belong to a high-tech sector (Storey and Tether 1998).
We adopt the Statistical Classification of Economic Activities of the European Community at the three-digit level to aggregate manufacturing industries according to their technical intensity and classify them into high-technology (office, accounting and computing machines; radio, television, and communication equipment; medical, precision, and optical instruments), medium high-technology (chemicals and chemical products; machinery and equipment, and motor vehicles; trailers and semitrailers), medium low-technology, and low-technology industries.
The participation of private sector actors in the innovation process has also been found to be preferable in European countries (Autio et al. 2007).
The data consist of 40,411 firms in 2000; 49,115 firms in 2001; 59,908 firms in 2002; 68,214 firms in 2003; 86,009 firms in 2004; and 104,835 firms in 2005.
We apply the standard Heckman selection model to control for firm survival bias. Particularly, we address (1) whether firms engaging in R&D activities are more likely to exit the market and (2) whether surviving firms have higher profit margin than other firms, consistent with the finding above. In the first stage, we estimate the probability of firm survival using the probit model (survival stage). Heckman’s inverse Mills ratio computed from the first stage is included in the second stage to estimate the profitability of surviving firms (performance stage). We use average ROS and average firm size of the industry as the exclusion restrictions in the Heckman selection model. However, the insignificant Mills ratio indicates the absence of survival bias in our estimation model even at the 10 % significant level. Therefore, we are confident that our estimation results do not overestimate the economic value of firms’ R&D activities. The results can be obtained from the authors upon request.
The rationales for using ROS rather than the widely used logarithm of profit or return on assets are as follows: (1) logarithm of profit excludes firms operating at loss (negative profit) from the analysis, and (2) sales is generally expressed in current monetary terms, whereas assets normally carry book values and require a longer time frame of availability (Geringer et al. 1989).
In this paper, R&D expenditure is constructed from the direct question of “what are the costs for research and for technological development?” Innovation investment has three components: (1) construction and assembly works, (2) machinery and equipment, and (3) technology renovation. Therefore, it is largely a measure of technological change embodied in intermediate and capital goods, and it has been shown to be a major determinant of the overall innovation activity by SMEs (Santarelli and Sterlacchini 1990). Whereas R&D reflects the internal input, embodied technological change represents the external input into the innovation process.
White/Koenker nR2 test statistic: \( \chi^{2} (81) \) = 327.967; p value = 0.000.
Wooldridge first-order serial correlation test: F (1,62074) = 1.079; p value = 0.299.
H0: “Innovation investment rate” is exogenous
Durbin–Wu–Hausman \( \chi^{2} \) test
\( \chi^{2} (1) \) = 10.639
p value = 0.001
H0: “R&D intensity” is exogenous.
Durbin–Wu–Hausman \( \chi^{2} \) test
\( \chi^{2} (1) \) = 0.013
p value = 0.907
Under-identification test \( \chi^{2} (1) = 4.121;p\;{\text{value}} = 0.01 \)
Over-identification test (Hansen J statistic) \( \chi^{2} (1) = 0.027;p\;{\text{value}} = 0.869 \)
Extending the work of Arellano and Bond (1991), they propose a system estimator that uses moment conditions in which lagged differences are employed as instruments for the level equation aside from the moment conditions of lagged levels as instruments for the differenced equation.
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Acknowledgments
We thank Zoltan Acs, David Audretsch, Carlos Carreira, Erik Lehmann, Georg Licht, conference participants and two anonymous reviewers for their useful comments. Enrico Santarelli acknowledges financial support from the Italian Ministry of Education, FIRB 2012 #RBFR1269_003, project leader Roberto Patuelli.
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Santarelli, E., Tran, H.T. Young innovative companies: Are they high performers in transition economies? Evidence for Vietnam. J Technol Transf 42, 1052–1076 (2017). https://doi.org/10.1007/s10961-016-9475-6
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DOI: https://doi.org/10.1007/s10961-016-9475-6