Export-market dynamics and the probability of firm closure: Evidence for the UK

This study presents the first empirical analysis of the determinants of firm closure in the UK with an emphasis on the role of export-market dynamics, using panel data for a nationally representative group of firms operating in all-market based sectors during 1997-2003. Our findings show that the probability of closure is (cet. par.) significantly lower for exporters, particularly those experiencing export-market entry and exit. Having controlled for other attributes associated with productivity (such as size and export status), the following factors are found to increase the firm’s survival prospects: higher capital intensity and TFP, foreign ownership, young age, displacement effects (through relatively high rates of entry of firms in each industry), and belonging to certain industries. Interestingly, increased import penetration (a proxy for lower trade costs) leads to a lower hazard rate for exporting entrants and continuous exporters, whilst inducing a higher hazard rate for domestic producers or those that quit exporting.

Separating Myth from Probability: the Origins and Evolution of QWERTY

We use basic probability theory and simple replicable electronic search experiments to evaluate some reported “myths” surrounding the origins and evolution of the QWERTY standard. The resulting evidence is strongly supportive of arguments put forward by Paul A. David (1985) and W. Brian Arthur (1989) that QWERTY was path dependent with its course of development strongly influenced by specific historical circumstances. The results also include the unexpected finding that QWERTY was as close to an optimal solution to a serious but transient problem as could be expected with the resources at the disposal of its designers in 1873.

Suppliers of Priors: A Theory of Retailing Inspired by the Market for Chinese Antiquities

Adverse selection may thwart trade between an informed seller, who knows the probability p that an item of antiquity is genuine, and an uninformed buyer, who does not know p. The buyer might not be wholly uninformed, however. Suppose he can perform a simple inspection, a test of his own: the probability that an item passes the test is g if the item is genuine, but only f < g if it is fake. Given that the buyer is no expert, his test may have little power: f may be close to g. Unfortunately, without much power, the buyer's test will not resolve the difficulty of adverse selection; gains from trade may remain unexploited. But now consider a "store", where the seller groups a number of items, perhaps all with the same quality, the same probability p of being genuine. (We show that in equilibrium the seller will choose to group items in this manner.) Now the buyer can conduct his test across a large sample, perhaps all, of a group of items in the seller's store. He can thereby assess the overall quality of these items; he can invert the aggregate of his test results to uncover the underlying p; he can form a "prior". There is thus no longer asymmetric information between seller and buyer: gains from trade can be exploited. This is our theory of retailing: by grouping items together - setting up a store - a seller is able to supply buyers with priors, as well as the items themselves. We show that the weaker the power of the buyer�s test (the closer f is to g), the greater the seller�s profit. So the seller has no incentive to assist the buyer � e.g., by performing her own tests on the items, or by cleaning them to reveal more about their true age. The paper ends with an analysis of which sellers should specialise in which qualities. We show that quality will be low in busy locations and high in expensive locations.

Prior selection for panel vector autoregressions

There is a vast literature that specifies Bayesian shrinkage priors for vector autoregressions (VARs) of possibly large dimensions. In this paper I argue that many of these priors are not appropriate for multi-country settings, which motivates me to develop priors for panel VARs (PVARs). The parametric and semi-parametric priors I suggest not only perform valuable shrinkage in large dimensions, but also allow for soft clustering of variables or countries which are homogeneous. I discuss the implications of these new priors for modelling interdependencies and heterogeneities among different countries in a panel VAR setting. Monte Carlo evidence and an empirical forecasting exercise show clear and important gains of the new priors compared to existing popular priors for VARs and PVARs.