# 5 Concluding Remarks

We extended the model by Aghion and Howitt (1992) to take into account the role of intellectualproperty institutions in the process of innovation. Our model consists of two sectors that operate simultaneously, one relying on costly imitation and the other on innovation. Firms or entrepreneurs decide endogenously whether to participate in innovative or imitative activities. The enforcement of intellectual property rights aects the incentives of labor to move between the two sectors. That is, institutions determine the risk-adjusted relative discount rate between employment in the two sectors. A second theoretical result is that an increase in the endowment of human capital increases the share of labor devoted to R&D activities under strong protection of IPRs.

Perhaps more importantly, the model predicts that aggregate patterns of the R&D shares across countries depend on complex interactions between IPRs and human capital. In spite of these complex interactions, the model also predicts, under fairly nonrestrictive assumptions, that IPRs provide incentives for the allocation of human capital into R&D activities. Economies with lax IPRs may not experience increases in the incidence of R&D over GDP as a result of increases in the stock of human capital. The model suggests that a minimum level of protection of IPRs can ensure that human capital accumulation increases the share of R&D. Thus, the model yields a testable prediction, namely that the share of R&D in GDP is a non-linear function of IPRs and human capital. While existing theories predict dierential eects of IPRs on poor versus rich countries, the existing empirical literature has focused exclusively on log-linear functions of R&D determinants (e.g., Varsakelis 2001; Chen and Puttitanum 2005). The analyses here thus contributed to both micro-founded theory and evidence by highlighting an ignored aspect of the role of IPRs as institutions shaping incentives for human capital to be allocated to R&D within countries.

The empirical section of the paper focused on international data on R&D shares of GDP, years of schooling of the adult population, and the Ginarte and Park (1997) data on de jure intellectual property rights. The data on educational attainment and IPRs were safely treated as being predetermined. Preliminary and descriptive estimations of the quasi-elasticity of R&D over GDP as a function of schooling suggested that in fact the data do seem to behave as if the underlying data generation process were unpredictably non-linear, and highlighting a new stylized fact: at low levels of IPRs, marginal increases in the stock of education have negligible eects on R&D.

We estimated basic models of the determinants of R&D expenditures as a share of GDP to test for non-linearities and interactions between the schooling of the labor force and the quality and enforcement of intellectual property rights, while also controlling for unobserved international heterogeneity with country specic eects. Non-parametric estimators cannot estimate such functions, and thus the applied literature has focused on polynomial and trigonometric approximations to non-linear functional forms.

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