Restricciones

What are the characteristics of enterprises that export high-tech goods? In order to answer this question we have to look at the binary logistic regression models in Table B3.4 where the dummy high-tech goods exporter is the dependent variable.

Table B3.4

Binary logistic regression (dependent variable: high tech good exporter) Regression models

(1) (2) (3) (4) (5) (6)

Constant –2.480*** –2.937*** –2.584*** –2.784*** –2.843*** –2.933***

(–0.060) (0.074) (0.066) (0.070) (0.075) (0.077) Size of enterprise (ref. medium-sized)

small –1.083*** –0.818*** –1.090*** –0.895*** –0.900*** –0.817*** (0.105) (0.109) (0.105) (0.108) (0.108) (0.109) large 0.642*** 0.409*** 0.615*** 0.511*** 0.499*** 0.409*** (0.116) (–0.120) (0.116) (0.118) (0.118) (0.120) very large 1.138*** 1.010*** 1.145*** 1.142*** 1.153*** 1.008*** (0.185) (0.192) (0.186) (0.189) (0.189) (0.193) Manufacturing sector (ref. services and

other sectors) 0.369*** 0.240 –0,022

(0.091) (0.093) (0.101)

Foreign controlled (ref. Dutch controlled) 0.907*** 1.011*** 0.976*** 0.909***

(0.095) (0.093) (0.094) (0.096)

R&D-activities (ref. without

R&D-activities) 0.911*** 0.919***

(0.101) (0.108)

N 9,935 9,935 9,935 9,935 9,935 9,935

Nagelkerke R Square 0.068 0.117 0.072 0.097 0.099 0.117

*** p < 0.01; ** p < 0.05; * p < 0.1

Regarding enterprise size class the same conclusion as in the previous part about innovators applies. The coefficients for all size class dummies are very significant. Small enterprises are less likely to be exporters of high-tech goods than medium- sized enterprises. Large and very large enterprises are more often innovators than medium-sized enterprises. The main difference with the regression models on the innovator dependent variable in Table B3.3 is that the coefficients for very large enterprises are relatively high compared with large enterprises in the regression on high-tech good exporter. This indicates that exporters of high-tech goods are more likely to be very large enterprises compared with innovators. An explanation for this observation may be that R&D and innovation is often a requirement for starting to export high-tech goods. A high level of R&D is needed to come up with innovations and develop high-tech products.

The coefficients for the manufacturing enterprises are not robust and not significant in all models. So we cannot characterise high-tech goods exporters in terms of the sector in which they are active. One may expect high-tech good exporters to be active in the manufacturing sector, which is the most technology-intensive. However, part of the high-tech exports could be sourced to wholesale enterprises.

In particular, enterprises with R&D and innovation as their core business may want to focus on their core business, and leave the production, marketing and sales to others. This could explain why we do not find significant results for the manufacturing sector in all the regression models.

Foreign controlled enterprises are more often exporters of high-tech goods than Dutch controlled enterprises. Probably the fact that foreign controlled enterprises in the Netherlands are more productive than Dutch controlled enterprises is the underlying reason for this observation.

The regression models show that enterprises with R&D activities are more often exporters of high-tech goods compared with enterprises that do not invest in R&D. Many enterprises that export high-tech goods are probably also producers and developers of high-tech goods. This implies that they conduct R&D activities. An exception to this observation is the group of wholesale enterprises that are hired by R&D enterprises to export their products.

In sum, enterprises that export high-tech goods can be characterised as (very) large in size, relatively often under foreign control, and often have their own R&D activities.

3.6 Summary and conclusion

Both export and R&D increase productivity. A certain level of productivity (and future profit expectations) is needed in order to start exporting or investing in R&D, because fixed costs are high. Once enterprises reach a certain productivity level, the odds of them becoming exporters or R&D enterprises increase. This is referred to as the self-selection effect. Productive enterprises become even more productive because they start exporting or start up R&D activities. This suggests that it is important for enterprises to achieve the initial productivity level that triggers them to start exporting or to start up R&D activities.

In order to innovate, creation and combination of knowledge are essential. Trade often includes the transfer of technologies and knowledge. So innovation diffusion is fostered by (international) trade and is regarded as an important source of productivity growth. Increasing international trade and increasing foreign direct investment are, among other things, inherent to globalisation. We argued in this paper that the international trade aspect of globalisation increases and accelerates the pace of innovation diffusion. While the increasing exports of high-tech goods by enterprises in the Dutch business sector indicate that industrial “upgrading” is taking place, increasing imports of high-tech goods shows that more enterprises are importing (valuable) knowledge into the Netherlands. The inflow of knowledge

from abroad yields spillover advantages in the Netherlands, which add directly or indirectly to productivity growth. In addition, the inflow of knowledge in combination with knowledge already available offers opportunities for creating new knowledge. Therefore, globalisation offers an open economy like the Netherlands opportunities to attract and use foreign knowledge.

The binary logistics regressions show that innovating enterprises are generally large enterprises in the manufacturing industry. They are relatively often foreign controlled, are exporters of goods and invest in R&D. In particular, the relationship between investing in R&D and being an innovator is strong. An indirect indicator that is not taken up in the models is productivity. Probably and according to the literature there is a correlation between the innovator dependent variable and several independent variables. Controlling for size class, locus of control and sector we can state that exporters are more innovative than non-exporters. However, due to indirect relations and intrinsic aspects of R&D activities and international trade, such as time lags and risk factors, it is difficult to study the causality between export and innovation.

Exporters of high-tech goods can be characterised as (very) large in size, relatively often foreign controlled, and with their own R&D activities.

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B4 Wage and employee differences