Matching with Phantoms

By Bruno Decreuse

Searching for partners involves informational persistence that reduces future traders’ matching probability. In this paper, traders that are no longer available but who left tracks on the market are called phantoms. I examine a discrete-time matching market in which phantom traders are a by-product of search activity, no coordination frictions are assumed, and non-phantom traders may lose time trying to match with phantom traders. The resulting aggregate matching technology features increasing returns to scale in the short run, but has constant returns to scale in the long run. I discuss the labor market evidence and argue that there is observational equivalence between phantom unemployed and on-the-job seekers.

Those involved in faculty searches can very well relate with this paper. The fact that it takes time to process candidate files leads to obsolete information about the availability of candidates, with potentially high costs of deal with a file of someone who has already found a job. Similarly, candidates may put effort in an application for a position that has already been filled. While the academic job search may dramatize such effects, they may still apply and be macroeconomically relevant for other labor markets.

One Response to Matching with Phantoms

  1. Sometimes small imperfections have far reaching consequences, from a practical and a theoretical viewpoint. This paper is a nice illustration of such a principle: job seekers frequently answer to job offers and are told that the job is already filled, though the add can still be found in the newspapers (or websites). Apparently, nobody cares about that, and few efforts are made to deal with such a problem. Though, one may imagine that searching for a job could be much more efficient if such ‘phantom’ job offers were withdrawn from the newspapers. Thus, after having introduced the reader to ‘phantom job offers’ and ‘phantom job seekers’, the paper analyzes several scenarios where phantom job offers may arise and highlighting how and why they matter for the whole economy.

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