Bart Verspagen

We build on the interpretation of the Economic Complexity method as Correspondence Analysis (CA), and propose that the Canonical form of CA (CCA), which originated in the ecology literature, can be used to calculate multi-dimensional economic complexity. The traditional (CA) way of calculating economic complexity includes no "external" information such as countries' development characteristics to facilitate interpretation of "complexity". This has led to a wide range of fairly ad hoc interpretations of economic complexity on the basis of ex-post correlation to a long list of other variables. By the ex-ante inclusion of a number of country variables in the construction of the complexity indicators, CCA enables better interpretation, also in the case of multi-dimensional indicators. The analysis is further facilitated by another element of the ecologists' toolbox, the so-called biplots, which are CCA-based graph embeddings that represent a lower-dimensional product-space in which products and countries are positioned together, in mutual correspondence to each other. We show that in this way, CCA provides a richer account of development in many of its aspects, especially economic growth.

We aim to contribute to the literature on product space and diversification by proposing a number of extensions of the current literature: (1) we propose that the alternative but related idea of a country space also has empirical and theoretical appeal; (2) we argue that the loss of comparative advantage should be an integral part of (testing the empirical relevance of) the product space idea; (3) we propose several new indicators for measuring relatedness in product space; and (4) we propose a non-parametric statistical test based on bootstrapping to test the empirical relevance of the product space idea.

Despite the fact that research and development (R&D) activities are carried out in most countries in public research institutes such as universities and public research organizations, there have been few studies that attempted to estimate the economic impact of such public investment in R&D. In this paper, we analyze the relations between total factor productivity (TFP) and public and private R&D as well as gross domestic product for a set of 17 Organisation for Economic Cooperation and Development (OECD) countries using a vector-error-correction model. We find that for the period 1975–2014, investment in public R&D has had a clearly positive effect on TFP growth in the majority of countries analyzed. In simulations allowing for a permanent positive shock to public R&D, we observe a strong dynamic complementarity between the public and private (domestic) stocks of R&D for several countries. In countries where this complementarity is strong, the TFP effect of extra public R&D investments is also strong. A discriminant analysis shows that in countries with high complementarity between private and public R&D, the share of foreign funding of R&D performed in the business sector combined with a high business R&D intensity tends to be low. At the same time, the share of basic R&D in business R&D combined with a higher public R&D intensity tends to be higher in countries with strong complementarity.

The recent literature on the economic effects of machine learning, robotization and artificial intelligence suggests that there may be an upcoming wave of substitution of human labor by machines. We argue that these new technologies may lead to so-called perpetual growth, i.e. growth of per capita income with a non-progressing state of technology. We specify an exact parameter threshold beyond which perpetual growth emerges, and argue that ongoing technological change may bring the threshold in reach. We also show that in a state of perpetual growth, factor-eliminating technological progress reduces the role of labor in the production process and that this leads to a rising wage rate but ever-declining share of wage income. We present simulation experiments on several policy options to combat this inequality, including a universal basic income as well as an option in which workers become owners of ‘robots’.