It is often necessary to estimate a frequency function or certain points on a frequency function from very limited data. A usual procedure for this estimation involves two steps. From the set of “well-known” frequency functions, e.g., the normal, poisson, binomial, etc., one chooses that function which seems likely to best “fit” and then uses the available data to estimate the parameters of the chosen distribution. If no one “well-known” function can be chosen a priori, then perhaps several likely candidates are tried and the one which fits best according to some criterion is chosen. For many purposes, this procedure is quite unobjectionable.

This article studies the determinants of the success of industry consolidations using a unique sample of firms established at the time of their initial public offering: roll-up IPOs. In these transactions, small, private firms merge into a shell company, which goes public at the same time. These firms deliver poor stock returns; their operating performance mimics that of comparable firms but does not justify their high initial valuations. However, if the managers and owners of the firms included in the transaction remain involved in the business as shareholders and directors, operating and stock price performance improve, and future acquisitions are better received by the market. Higher ownership by the sponsor of the transaction leads to a reduction in performance, consistent with the view that the sponsor's compensation is excessive. These findings highlight the impact of corporate governance on performance.