How much can firms know?

There are two key stylised facts about the extinction patterns of firms. First, the probability of extinction is highest at the start of the firm"s existence, but soon becomes more or less invariant to the age of the firm. Second, the relationship between the size and frequency of firm extinctions is closely approximated by a power law. An agent based model of firm evolution and extinction has been developed which has properties which conform closely to the stylised facts. We examine the effects of allowing firms different amounts of knowledge about the effects of strategy in the context of this agent-based evolutionary model. There are very considerable returns in the model to acquiring knowledge. As both the amount of knowledge available to firms increases and as the number of firms capable of acquiring such knowledge rises, the lifespan of agents approaches the full information paradigm in which agents live for ever. However, even with relatively low levels of knowledge and numbers of agents capable of acquiring it, the model ceases to have properties which are compatible with the two key stylised facts on firm extinctions. The clear implication is that firms have very limited capacities to acquire knowledge about the true impact of their strategies.agent based evolutionary model; heterogenous agents; learning

Economic impact of infrastructure

This paper looks at the need for and criteria used to invest in infrastructure. This term can cover a wide variety of assets. One element of the infrastructure of the UK is its language and its institutions, which are arguably among the most important elements in our continued success and some commentators would like to see us invest more effort into them. However, for the purposes of this paper, I shall concentrate on assets which have a physical dimension

Building bridges - some lessons from the Middle Ages on the long-term economic impact of bridges over the Thames

This study was inspired by the proposed Thames Gateway Bridge between Beckton and Woolwich and addresses the problem of calculating the long term economic impact of major capital projects, such as bridges. The study of medieval crossings of the Thames reveals that of 18 medieval bridges, only one was allowed to fall into neglect and disappear; the others, once built, remained, and were improved and enlarged and in most cases they or their successors are still present. The conclusion is that in the long term, perhaps the very long term, such capital projects rarely fail to be economically advantageous

Inflation/Unemployment Regimes and the Instability of the Phillips Curve

From a theoretical standpoint, Friedman (1968) argued that in the long‐run there is no connection between inflation and the state of demand. In so far as there is consensus on these matters amongst economists, this is it. However, the ‘long run ’ is a theoretical concept, and economic theory offers no guidance as to how long the long run might be in practice (though see Atkinson (1969) for

Computational modelling for decision-making: where, why, what, who and how

In order to deal with an increasingly complex world, we need ever more sophisticated computational models that can help us make decisions wisely and understand the potential consequences of choices. But creating a model requires far more than just raw data and technical skills: it requires a close collaboration between model commissioners, developers, users and reviewers. Good modelling requires its users and commissioners to understand more about the whole process, including the different kinds of purpose a model can have and the different technical bases. This paper offers a guide to the process of commissioning, developing and deploying models across a wide range of domains from public policy to science and engineering. It provides two checklists to help potential modellers, commissioners and users ensure they have considered the most significant factors that will determine success. We conclude there is a need to reinforce modelling as a discipline, so that misconstruction is less likely; to increase understanding of modelling in all domains, so that the misuse of models is reduced; and to bring commissioners closer to modelling, so that the results are more useful

Inflation/Unemployment Regimes and the Instability of the Phillips Curve

Using the statistical technique of fuzzy clustering, regimes of inflation and unemployment are explored for the United States, the United Kingdom and Germany between 1871 and 2009. We identify for each country three distinct regimes in inflation/unemployment space. There is considerable similarity across the countries in both the regimes themselves and in the timings of the transitions between regimes. However, the typical rates of inflation and unemployment experienced in the regimes are substantially different. Further, even within a given regime, the results of the clusterings show persistent fluctuations in the degree of attachment to that regime of inflation/unemployment observations over time. The economic implications of the results are that, first, the inflation/unemployment relationship experiences from time to time major shifts. Second, that it is also inherently unstable even in the short run. It is likely that the factors which govern the inflation/unemployment trade off are so multi‐dimensional that it is hard to see that there is a way of identifying periods of short run Phillips curves which can be assigned to particular historical periods with any degree of accuracy or predictability. The short run may be so short as to be meaningless. The analysis shows that reliance on any kind of trade off between inflation and unemployment for policy purposes is entirely misplaced. 1