Firms in Scottish High Technology Clusters: software, life sciences, microelectronics, optoelectronics and digital media – preliminary evidence and analysis on firm size, growth and optimality

This paper reports on: (a) new primary source evidence on; and (b) statistical and econometric analysis of high technology clusters in Scotland. It focuses on the following sectors: software, life sciences, microelectronics, optoelectronics, and digital media. Evidence on a postal and e-mailed questionnaire is presented and discussed under the headings of: performance, resources, collaboration & cooperation, embeddedness, and innovation. The sampled firms are characterised as being small (viz. micro-firms and SMEs), knowledge intensive (largely graduate staff), research intensive (mean spend on R&D GBP 842k), and internationalised (mainly selling to markets beyond Europe). Preliminary statistical evidence is presented on Gibrat’s Law (independence of growth and size) and the Schumpeterian Hypothesis (scale economies in R&D). Estimates suggest a short-run equilibrium size of just 100 employees, but a long-run equilibrium size of 1000 employees. Further, to achieve the Schumpeterian effect (of marked scale economies in R&D), estimates suggest that firms have to grow to very much larger sizes of beyond 3,000 employees. We argue that the principal way of achieving the latter scale may need to be by takeovers and mergers, rather than by internally driven growth.

Baysian Model Averaging, Learning and Model Selection

Agents have two forecasting models, one consistent with the unique rational expectations equilibrium, another that assumes a time-varying parameter structure. When agents use Bayesian updating to choose between models in a self-referential system, we find that learning dynamics lead to selection of one of the two models. However, there are parameter regions for which the non-rational forecasting model is selected in the long-run. A key structural parameter governing outcomes measures the degree of expectations feedback in Muth's model of price determination.

Anticipation, Learning and Welfare: the Case of Distortionary Taxation

We study the impact of anticipated fiscal policy changes in a Ramsey economy where agents form long-horizon expectations using adaptive learning. We extend the existing framework by introducing distortionary taxes as well as elastic labour supply, which makes agents. decisions non-predetermined but more realistic. We detect that the dynamic responses to anticipated tax changes under learning have oscillatory behaviour that can be interpreted as self-fulfilling waves of optimism and pessimism emerging from systematic forecast errors. Moreover, we demonstrate that these waves can have important implications for the welfare consequences of .scal reforms. (JEL: E32, E62, D84)

Directed Search over the Life Cycle

We develop a life-cycle model of the labor market in which different worker-firm matches have different quality and the assignment of the right workers to the right firms is time consuming because of search and learning frictions. The rate at which workers move between unemployment, employment and across different firms is endogenous because search is directed and, hence, workers can choose whether to seek low-wage jobs that are easy to find or high-wage jobs that are hard to find. We calibrate our theory using data on labor market transitions aggregated across workers of different ages. We validate our theory by showing that it predicts quite well the pattern of labor market transitions for workers of different ages. Finally, we use our theory to decompose the age profiles of transition rates, wages and productivity into the effects of age variation in work-life expectancy, human capital and match quality.