Publications

Lia Majid had spent nearly a year and a half searching for a business to acquire and thought she’d finally found a deal worth pursuing. She spent months negotiating with the firm’s sellers and believed she was on the verge of a purchase. However, at the last minute, her backers and mentors at the Search Fund Accelerator (SFA) wanted her to completely restructure the deal.

Majid was part of the first cohort of SFA. SFA was the brainchild of Timothy Bovard who founded the accelerator to help search fund entrepreneurs vet deals, review proposals, and provide emotional support during the search. Through SFA’s leads, Majid had identified a target company that was willing to sell one of its divisions, but she still needed Bovard’s input before drafting a Letter of Intent (LOI) for the seller. Bovard, however, was concerned about the proposed carve-out acquisition, a complex task for even a seasoned CEO, let alone a first time CEO.

Faced with Bovard’s concerns and SFA’s new deal structure, Majid had to decide whether to reengage the target firm with this new deal or to move on to investigate other prospects.

We investigate the use of the inclusive value based approach for estimating dynamic discrete choice models of demand with aggregate data. The inclusive value sufficiency (IVS) approach approximates a multi-dimensional state space with a single “sufficient statistic” in order to mitigate the curse of dimensionality and tractability estimate model primitives. Although in widespread use, the conditions under which IVS is appropriate have not been examined. Theoretically, we show that the estimator is biased and inconsistent. We then use Monte Carlo simulations (of a simple model of dynamic durable goods adoption) to demonstrate the degree of bias associated with the inclusive value approximation estimator under an array of parameterizations and data generating processes. In our examination, we show that the estimator performs better when the discount factor is smaller and/or when the price sensitivity of the consumer is larger. Examining how the bias impacts economic quantities of interest, we find that the IVS method under estimates the true long-run own-price elasticities and over estimates the change in profits as prices change. Theses findings highlight the importance of correctly specifying how consumers form expectations. As a result, researchers should consider how to empirically support their assumption for the underlying consumer belief structure.