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Against the background of renewed interest in vertical support policies targeting specific industries or technologies, we investigate the effects of vertical vs. horizontal policies in a combinatorial model of economic development. In the framework we propose, an economy develops by acquiring new capabilities allowing for the production of an ever greater variety of products with an increasing complexity. Innovation policy can aim to expand the number of capabilities (vertical policy) or the ability to combine capabilities (horizontal policy). The model shows that for low-income countries, the two policies are complementary. For high-income countries that are specialised in the most complex products, focusing on horizontal policy only yields the highest returns. We reflect on the model results in the light of the contemporary debate on vertical policy.

We propose a statistical framework to quantify location and co-location associations of economic activities using information-theoretic measures. We relate the resulting measures to existing measures of revealed comparative advantage, localization and specialization and show that they can all be seen as part of the same framework. Using a Bayesian approach, we provide measures of uncertainty of the estimated quantities. Furthermore, the information-theoretic approach can be readily extended to move beyond pairwise co-locations and instead capture multivariate associations. To illustrate the framework, we apply our measures to the co-location of occupations in US cities, showing the associations between different groups of occupations.

We propose a combinatorial model of economic development. An economy develops by acquiring new capabilities allowing for the production of an ever greater variety of products of increasingly complex products. Taking into account that economies abandon the least complex products as they develop over time, we show that variety first increases and then decreases in the course of economic development. This is consistent with the empirical pattern known as 'the hump'. Our results question the common association of variety with complexity. We further discuss the implications of our model for future research.

Understanding how spatial configurations of economic activity emerge is important when formulating spatial planning and economic policy. Not only micro-simulation and agent-based model such as UrbanSim, ILUMAS and SIMFIRMS, but also Simon's model of hierarchical concentration have widely applied, for this purpose. These models, however, have limitations with respect to simulating structural changes in spatial economic systems and the impact of proximity. The present paper proposes a model of firm development that is based on behavioural rules such as growth, closure, spin-off and relocation. An important aspect of the model is that locational preferences of firms are based on agglomeration advantages, accessibility of markets and congestion, allowing for a proper description of concentration and deconcentration tendencies. By comparing the outcomes of the proposed model with real world data, we will calibrate the parameters and assess how well the model predicts existing spatial configurations and decide. The model is implemented as an agent-based simulation model describing firm development in the Netherlands in 21 industrial sectors from 1950 to 2004., Comment: 16 pages

Understanding how spatial configurations of economic activity emerge is important when formulating spatial planning and economic policy. A simple model was proposed by Simon, who assumed that firms grow at a rate proportional to their size, and that new divisions of firms with certain probabilities relocate to other firms or to new centres of economic activity. Simon's model produces realistic results in the sense that the sizes of economic centres follow a Zipf distribution, which is also observed in reality. It lacks realism in the sense that mechanisms such as cluster formation, congestion (defined as an overly high density of the same activities) and dependence on the spatial distribution of external parties (clients, labour markets) are ignored. The present paper proposed an extension of the Simon model that includes both centripetal and centrifugal forces. Centripetal forces are included in the sense that firm divisions are more likely to settle in locations that offer a higher accessibility to other firms. Centrifugal forces are represented by an aversion of a too high density of activities in the potential location. The model is implemented as an agent-based simulation model in a simplified spatial setting. By running both the Simon model and the extended model, comparisons are made with respect to their effects on spatial configurations. To this end a series of metrics are used, including the rank-size distribution and indices of the degree of clustering and concentration., Comment: Conference Proceeding in European Regional Science Association, Liverpool, England, August, 2008

Using entropy statistics we analyse scaling patterns in terms of changes in the ratios among product characteristics of 143 designs in civil aircraft. Two allegedly dominant designs, the piston propeller DC3 and the turbofan Boeing 707, are shown to have triggered a scaling trajectory at the level of the respective firms. Along these trajectories different variables have been scaled at different moments in time: this points to the versatility of a dominant design which allows a firm to react to a variety of user needs. Scaling at the level of the industry took off only after subsequently reengineered models were introduced, like the piston propeller Douglas DC4 and the turbofan Boeing 767. The two scaling trajectories in civil aircraft corresponding to the piston propeller and the turbofan paradigm can be compared with a single, less pronounced scaling trajectory in helicopter technology for which we have data during the period 1940-1996. Management and policy implications can be specified in terms of the phases of codification at the firm and the industry level.

In this chapter, we elaborate on the topic of European integration in science. We will not deal with questions related to the effects of European integration, but only with the scientometric question how one can quantitatively indicate integration of the European science system. Our study is intended to facilitate and supplement debates rather than to provide a final answer to the questions whether European integration 'exists'. In this chapter, we first discuss the use of scientometric indicators in research evaluation from a historical perspective in (section 2). A discussion of European science policy follows (section 3). Then, we introduce a number of indicators of integration and discuss our empirical results concerning the evolution of the European science system in the 1980s and 1990s (section 4). We close the chapter with a discussion of possible avenues of future research for enhancing research evaluation (section 5).