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Business Cycles with Costly Search and Recruiting

Quarterly Journal of Economics 1988 103(1), 147
A business cycle model is developed in which output is traded on Lucas-Phelps islands and labor services on each island are exchanged through costly search and recruiting with transactions externalities. The model exhibits persistent involuntary unemployment and inefficient equilibria, even though there are no nominal rigidities and no unexploited privately attainable gains from trade. It also exhibits employment fluctuations without any real-wage fluctuations. It yields a Lucas aggregate-supply curve (to a linear approximation). It also implies that the natural rate of unemployment depends positively upon the variability and persistence of relative price shocks.

Stability of Equilibria with Externalities

Quarterly Journal of Economics 1988 103(2), 261
It is shown that, in a class of models with multiple externalities (one positive and one negative), all stationary equilibria may be locally stable to perturbations, in the sense that there exist perfect foresight trajectories leading back to the equilibrium. Thus, scale diseconomies (arising, for example, out of a common resource pool) generally overturn the Liviatan-Samuelson result, that equilibria are either saddlepoints or sources.

Competition and Innovation: An Inverted-U Relationship*

Quarterly Journal of Economics 2005 120(2), 701-728
This paper investigates the relationship between product market competition and innovation. We find strong evidence of an inverted-U relationship using panel data. We develop a model where competition discourages laggard firms from innovating but encourages neck-and-neck firms to innovate. Together with the effect of competition on the equilibrium industry structure, these generate an inverted-U. Two additional predictions of the model-that the average technological distance between leaders and followers increases with competition, and that the inverted-U is steeper when industries are more neck-and-neck-are both supported by the data.