This paper studies the economics of match formation using a novel dataset obtained from a major online dating service. Online dating takes place in a new market environment that has become a common means to find a date or a marriage partner. According to comScore (2006), 17 percent of all North American and 18 percent of all European Internet users visited an online personals site in July 2006. In the United States, 37 percent of all single Internet users looking for a partner have visited a dating Web site (Mary Madden and Amanda Lenhart 2006). The Web site we study provides detailed information on the users' attributes and interactions, which we use to estimate a rich model of mate preferences. Based on the preference estimates, we then examine whether an economic matching model can explain the observed online matching patterns, and we evaluate the efficiency of the matches obtained on the Web site. Finally, we explore whether the estimated preferences and a matching model are helpful in understanding sorting patterns observed "offline," among dating and married couples.Two distinct literatures motivate this study. The first is the market design literature, which focuses on designing and evaluating the performance of market institutions. A significant branch of this literature is devoted to matching markets (Alvin E. Roth and Marilda A. O. Sotomayor 1990), with the goal of understanding the allocation mechanism in a particular market, and assessing whether an alternative mechanism with better theoretical properties (typically in terms
Mate preferences, Dating, Marriage, C78, J12,
This paper develops a model of dynamic advertising competition, and applies it to the problem of optimal advertising scheduling through time. In many industries we observe advertising “pulsing”, whereby firms systematically switch advertising on and off at a high-frequency. Hence, we observe periods of zero and non-zero advertising, as opposed to a steady level of positive advertising. Previous research has rationalized pulsing through two features of the sale response function: an S-shaped response to advertising, and long-run effects of current advertising on demand. Despite considerable evidence for advertising carry-over, existing evidence for non-convexities in the shape of the sales-response to advertising has been limited and, often, mixed. We show how both features can be included in a discrete choice based demand system and estimated using a simple partial maximum likelihood estimator. The demand estimates are then taken to the supply side, where we simulate the outcome of a dynamic game using the Markov perfect equilibrium (MPE) concept. Our objective is not to test for the specific game generating observed advertising levels. Rather, we wish to verify whether the use of pulsing (on and off) can be justified as an equilibrium advertising practice. We solve for the equilibrium using numerical dynamic programming methods. The flexibility provided by the numerical solution method allows us to improve on the existing literature, which typically considers only two competitors, and places strong restrictions on the demand models for which the supply side policies can be obtained. We estimate the demand model using data from the Frozen Entree product category. We find evidence for a threshold effect, which is qualitatively similar to the aforementioned S-shaped advertising response. We also show that the threshold is robust to functional form assumptions for the marginal impact of advertising on demand. Our estimates, which are obtained without imposing any supply side restrictions, imply that firms should indeed pulse in equilibrium. Predicted advertising in the MPE is higher, on average, than observed advertising. On average, the optimal advertising policies yield a moderate profit improvement over the profits under observed advertising. Copyright Springer Science + Business Media, Inc. 2005advertising, dynamic oligopoly, Markov perfect equilibrium, pulsing,
The conventional wisdom in economic theory holds that switching costs make markets less competitive. This paper challenges this claim. We formulate an empirically realistic model of dynamic price competition that allows for differentiated products and imperfect lock-in. We calibrate this model with data from frequently purchased packaged goods markets. These data are ideal in the sense that they have the necessary variation to separately identify switching costs from consumer heterogeneity. Equally important, consumers exhibit inertia in their brand choices, a form of psychological switching cost. This makes our results applicable to the broad range of products that are distinctly identified (i.e. branded) rather than just to those products for which there is a product adoption cost or explicit switching fee. In our simulations, prices are as much as 18 per cent lower with than without switching costs.
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