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In developing countries, mobile telecom networks have emerged as major providers of financial services, bypassing the sparse retail networks of traditional banks. We analyze a large individual-level data set of mobile money transactions in Tanzania to provide evidence of the impact of mobile money on alleviating financial exclusion in developing countries. We identify three types of transactions: (i) money transfers to others, (ii) short-distance money self-transportation, and (iii) money storage for short to medium periods of time. We utilize a natural experiment of an unanticipated increase in transaction fees to identify the demand for these transactions. Using the demand estimates, we find that the willingness to pay to avoid walking with cash an extra kilometer (shortdistance self-transportation) and to avoid storing money at home (money storage) for an extra day are 1.25% and 0.8% of an average transaction, respectively, which demonstrates that mobile money ameliorates significant amounts of crime-related risk. We explore the implications of these estimates for pricing and demonstrate the profitability of incentivecompatible price discrimination based on type of service, consumer location, and distance between transaction origin and destination. We show that differential pricing based on the features of a transaction delivers a Pareto improvement. History: K. Sudhir served as the editor-in-chief and Juanjuan Zhang served as associate editor for this article. Funding: The authors thank the Bill and Melinda Gates Foundation for financial support and the University of Chicago, Using Mobile Phones as a Platform for Banking [Award 035250-002].

This study examines mergers in two-sided markets using a structural supply-and-demand model that employs data from the 1996–2006 merger wave in the US radio industry. In particular, it identifies the conflicting incentives for merged firms to exercise market power on both listener and advertiser sides of the market, and disaggregates the effects of mergers into changes in product variety and advertising quantity. Specifically, it finds 0.2 percent listener welfare increase (+0.3 percent from increased product variety, and −0.1 percent from decreased ad quantity) and 21 percent advertiser welfare decrease (−17 percent from changes in product variety, and −5 percent from decreased ad quantity). (JEL G34, L13, L82, L88, M37)

This article estimates fixed-cost efficiencies from mergers using a dynamic oligopoly model in which mergers and repositioning of products are endogenous. The inference is based on revealed preference approach selecting cost synergies that rationalize observed merger decisions. The estimates can be used to assess the total welfare impact of retrospective and counterfactual mergers. The framework is applied to estimate cost efficiencies after the 1996 deregulation of U.S. radio industry. Within the period of 1996 to 2006 the cost savings resulting from mergers amount to $1.2 billion per year (equally split across economies of scale and within-format cost synergies). as well as participants at numerous seminars.1 In this article, I use the terms merger and acquisition interchangeably to mean any change of ownership of a part of or a whole company. 816Copyright C 2014, RAND. JEZIORSKI / 817 one I infer that the presumed cost efficiencies are too large. On the other hand, when the model predicts no merger, but the data indicate one, I infer the presumed cost efficiencies are too small.Implementing the proposed cost estimator requires robust long-run predictions of gains from mergers, which are obtained using a dynamic model with endogenous mergers and product characteristics. In contrast, previous empirical work analyzes mergers in a static framework and treats market structure as given (see Nevo, 2000;Pinkse and Slade, 2004;Ivaldi and Verboven, 2005). Such static models are useful in addressing the short-run impacts of mergers but do not account for resulting long-run changes in the market structure. Benkard, Bodoh-Creed, and Lazarev (2008) evaluate a longer-run effect of a merger on market structure but still treat it as an exogenous one-time event. The proposed dynamic framework builds on the above methods accounting for dynamic processes such as self-selection of mergers, follow-up mergers leading to merger waves, and postmerger product repositioning.Modelling and estimating models with endogenous mergers pose econometric and computational challenges. To evaluate a potential merger, both acquirer and acquiree must take into account the ownership structure and characteristics of all active products. Because the number of such variables is usually large, one has to deal with the curse of dimensionality, which increases data requirements and poses computational challenges. In this article, I overcome these issues by using a data set on thousands of mergers within one industry, and by applying recent advancements in the estimation of dynamic games (see Bajari, Benkard, and Levin, 2007; hereafter "BBL"). Moreover, modelling of mergers in a dynamic framework introduces several conceptual issues including simultaneous merger bids for a single product and multiproduct bids by a single acquirer. This study addresses the former issue by modelling players' moves as sequential with bigger owners moving first, and the latter issue by approximating multiproduct mergers with a series of highly correlated product-by-product acq...