The Dick Wittink Prize Committee is pleased to announce the 2017 winner of the 11th Annual Dick Wittink prize for the best paper published in the Quantitative Marketing and Economics journal.
Costly Search and Consideration Sets in Storable Goods Markets, (PDF) by Tiago Pires
Costly search can result in consumers restricting their attention to a subset of products–the consideration set–before making a final purchase decision. The search process is usually not observed, which creates econometric challenges. I show that inventory and the availability of different package sizes create new sources of variation to identify search costs in storable goods markets. To evaluate the importance of costly search in these markets, I estimate a dynamic choice model with search frictions using data on purchases of laundry detergent. My estimates show that consumers incur significant search costs, and ignoring costly search overestimates the own-price elasticity for products more often present in consideration sets and underestimates the elasticity of frequently excluded products. Firms employ marketing devices, such as product displays and advertising, to influence consideration sets. These devices have direct and strategic effects, which I explore using the estimates of the model. I find that using marketing devices to reduce a product’s search cost during a price promotion has modest effects on the overall category revenues, and decreases the revenues of some products.
Identification and semiparametric estimation of a finite horizon dynamic discrete choice model with a terminating action (PDF) by Patrick Bajari,Chenghuan Sean Chu, Denis Nekipelov, Minjung Park
We study identification and estimation of finite-horizon dynamic discrete choice models with a terminal action. We first demonstrate a new set of conditions for the identification of agents’ time preferences. Then we prove conditions under which the per-period utilities are identified for all actions in the agent’s choice-set, without having to normalize the utility for one of the actions. Finally, we develop a computationally tractable semiparametric estimator. The estimator uses a two-step approach that does not use either backward induction or forward simulation. Our methodology can be implemented using standard statistical packages without the need to write specialized computational routines, as it involves linear (or nonlinear) projections only. Monte Carlo studies demonstrate the superior performance of our estimator compared with existing two-step estimation methods. Monte Carlo studies further demonstrate that the ability to identify the per-period utilities for all actions is crucial for counterfactual predictions. As an empirical illustration, we apply the estimator to the optimal default behavior of subprime mortgage borrowers, and the results show that the ability to identify the discount factor, rather than assuming an arbitrary number as typically done in the literature, is also crucial for obtaining correct counterfactual predictions. These findings highlight the empirical relevance of key identification results of the paper.
Advertising Competition in Presidential Elections, (PDF) by Brett R. Gordon and Wesley R. Hartmann
Presidential candidates purchase advertising based on each state’s potential to tip the election. The structure of the Electoral College concentrates spending in battleground states, such that a majority of voters are ignored. We estimate an equilibrium model of multimarket advertising competition between candidates that allows for endogenously determined budgets. In a Direct Vote counterfactual, we find advertising would be spread more evenly across states, but total spending levels can either decrease or increase depending on the contestability of the popular vote. Spending would increase by 13 % in the extremely narrow 2000 election, but would decrease by 54 % in 2004. These results suggest that the Electoral College greatly increases advertising spending in typical elections.