Dick Wittink Prize

The Dick Wittink Prize Committee is pleased to announce the 2022 winner of the 16th Annual Dick Wittink prize for the best paper published in the Quantitative Marketing and Economics journal.

WINNER

Selling mechanisms for perishable goods: An empirical analysis of an online resale market for event tickets

by Caio Waisman

This paper assesses the value of the availability of menus of different selling mechanisms to agents in an online platform in the context of scarce perishable goods. By analyzing the choice between auctions and posted prices in the context of National Football League tickets offered on eBay, it estimates a structural model in which heterogeneous, forward-looking sellers optimally choose which selling mechanism to use and its features. Counterfactual results suggest that sellers would experience an average 87.37% decrease in expected revenues if auctions were removed and just a 4.34% decrease if posted prices were. In turn, buyers would benefit from an auction-only platform since the expected number of transactions would increase and expected transaction prices would decrease. These results suggest that while sellers benefit from menus of different selling mechanisms, the same does not hold for buyers. Thus, the implications for a platform, which should take into account both sides of the market, are ambiguous.

The Dick Wittink Prize Committee is pleased to announce the 2021 winner of the 15th Annual Dick Wittink prize for the best paper published in the Quantitative Marketing and Economics journal.

WINNER 

Displaying things in common to encourage friendship formation: A large randomized field experiment

by Tianshu Sun & Sean J. Taylor

Friendship formation is of central importance to online social network sites and to society, but can suffer from significant and unequal frictions. In this study, we demonstrate that social networks and policy makers may use an IT-facilitated intervention – displaying things in common (TIC) between users (mutual hometown, interest, education, work, city) – to encourage friendship formation, especially among people who are different from each other. Displaying TIC may update an individual’s belief about the shared similarity with another and reduce information friction that may be hard to overcome in offline communication. In collaboration with an online social network, we design and implement a randomized field experiment, which randomly varies the prominence of different types of things in common information when a user (viewer) is browsing a non-friend’s profile. The dyad-level exogenous variation, orthogonal to any (un)observed structural factors in viewer-profile’s network, allows us to cleanly isolate the role of individuals’ preference for TIC in driving network formation and homophily. We find that displaying TIC to viewers may significantly increase their probability of sending a friend request and forming a friendship, and is especially effective for pairs of people who have little in common. Such findings suggest that information intervention is a very effective and zero-cost approach to encourage the formation of weak ties, and also provide the first experimental evidence on the crucial role of individuals’ preference (versus structural embeddedness) in network formation. We further demonstrate that displaying TIC could improve friendship formation for a wide range of viewers with different demographics and friendship status, and is more effective when the TIC information is more surprising to the viewer. Our study offers actionable insights to social networks and policy makers on the design of information intervention to encourage friendship formation and improve the diversity of the friendship, at both an aggregate and an individual level.

RUNNER-UP

The Effect of Sales Assistance on Purchase Decisions: An analysis using retail video data

by Aditya Jain, Sanjog Misra, and Nils Rudi

We investigate the role of sales assistance in driving customer’s purchase decision using unique observational video data from a cosmetics retail chain. The data contain visual descriptors of customers and their in-store activities including the time they spent in interacting with salespersons (sales assistance), and are linked to their purchase decisions. Our empirical specification is based on the process of customer deciding to engage in sales assistance to acquire information meaningful toward purchase decision. Thus, we treat sales assistance as endogenous construct, and employ a control function approach to correct for this endogeneity using instruments pertaining to the supply of sales assistance. Our analysis quantifies the role of sales assistance in driving a customer’s purchase decision, and it shows that the effectiveness of sales assistance diminishes with its amount. In addition to highlighting the importance of sales assistance towards purchase decisions, our results also quantify how the retailer can influence sales assistance by increasing the availability of salespersons. We also examine the effect of sales assistance on in-store search carried out by the customer. Finally, we offer number of context specific insights into the heterogeneity of customers’ shopping and purchasing behavior.

The Dick Wittink Prize Committee is pleased to announce the 2020 winners of the 14th Annual Dick Wittink prize for the best paper published in the Quantitative Marketing and Economics journal.

Watch the recording of the 2020 Wittink Prize announcement

Winner

Dynamic effects of price promotions: field evidence, consumer search, and supply-side implications

by Andrés Elberg, Pedro M. Gardete, Rosario Macera and Carlos Noton

This paper investigates the dynamic effects of price promotions in a retail setting through the use of a large-scale field experiment varying the promotion depths of 170 products across 17 categories in 10 supermarkets of a major retailer in Chile. In the intervention phase of the experiment, treated customers were exposed to deep discounts (approximately 30%), whereas control customers were exposed to shallow discounts (approximately 10%). In the subsequent measurement phase, the promotion schedule held discount levels constant across groups. We find that treated customers were 22.4% more likely to buy promoted items than their control counterparts, despite facing the same promotional deals. Strikingly, the magnitude of the dynamic effects of price promotions (when promotional depths are equal across conditions) is 61% of the promotional effects induced by offering shallow vs. deep discounts during the intervention phase. The result is robust to other concurrent dynamic forces, including consumer stockpiling behavior and state dependence. We use the experimental variation and historical promotional activities to inform a demand-side model in which consumers search for deals, and a supply-side model in which firms compete for those consumers. We find that small manufacturers can benefit from heightened promotion sensitivity by using promotions to induce future consideration. However, when unit margins are high, heightened promotion sensitivity leads to fierce competition, making all firms worse off.

Runner-Up

A study into mechanisms of attitudinal scale conversion: A randomized stochastic ordering approach

by Zvi Gilula, Robert E. McCulloch, Yaacov Ritov & Oleg Urminsky 

This paper considers the methodological challenge of how to convert categorical attitudinal scores (like satisfaction) measured on one scale to a categorical attitudinal score measured on another scale with a different range. This is becoming a growing issue in marketing consulting and the common available solutions seem too few and too superficial. A new methodology for scale conversion is proposed, and tested in a comprehensive study. This methodology is shown to be both relevant and optimal in fundamental aspects. The new methodology is based on a novel algorithm named minimum conditional entropy, that uses the marginal distributions of the responses on each of the two scales to produce a unique joint bivariate distribution. In this joint distribution, the conditional distributions follow a stochastic order that is monotone in the categories and has the relevant optimal property of maximizing the correlation between the two underlying marginal scales. We show how such a joint distribution can be used to build a mechanism for scale conversion. We use both a frequentist and a Bayesian approach to derive mixture models for conversion mechanisms, and discuss some inferential aspects associated with the underlying models. These models can incorporate background variables of the respondents. A unique observational experiment is conducted that empirically validates the proposed modeling approach. Strong evidence of validation is obtained.

Runner-Up

Firms’ reactions to public information on business practices: The case of search advertising 

by Justin M. Rao and Andrey Simonov 

We use five years of bidding data to examine the reaction of advertisers to widely disseminated press on the lack of effectiveness of brand search advertising (queries that contain the firm’s name) found in a large experiment run by eBay (Blake et al. 2015). We estimate that 11% of firms that did not face competing ads on their brand name keywords, matching the case of eBay, discontinued the practice of brand search advertising. In contrast, firms did not react to the information pertaining to the high value and ease of running experiments—we observe no change in the experiment-like variation in advertising levels. Further, while 72% of firms had sharp changes in advertising suitable for estimating causal effects, we find no correlation between firm-level advertising effects and the propensity to advertise in the future. We discuss how a principal-agent problem within the firm would lead to these learning dynamics.

The Dick Wittink Prize Committee is pleased to announce the 2019 winner of the 13th Annual Dick Wittink prize for the best paper published in the Quantitative Marketing and Economics journal.

Winner

Cross channel effects of search engine advertising on brick & mortar retail sales: Meta analysis of large scale field experiments on Google.com

by Kirthi Kalyanam, John McAteer, Jonathan Marek, James Hodges, and Lifeng Lin

We investigate the cross channel effects of search engine advertising on Google.com on sales in brick and mortar retail stores. Obtaining causal and actionable estimates in this context is challenging: Brick and mortar store sales vary widely on a weekly basis; offline media dominate the marketing budget; search advertising and demand are contemporaneously correlated; and estimates have to be credible to overcome agency issues between the online and offline marketing groups. We report on a meta-analysis of a population of 15 independent field experiments, in which 13 well-known U.S. multi-channel retailers spent over $4 Million in incremental search advertising. In test markets category keywords were maintained in positions 1-3 for 76 product categories with no search advertising on these keywords in the control markets. Outcomes measured include sales in the advertised categories, total store sales and Return on Ad Spending. We estimate the average effect of each outcome for this population of experiments using a Hierarchical Bayesian (HB) model. The estimates from the HB model provide causal evidence that increasing search engine advertising on broad keywords on Google.com had a positive effect on sales in brick and mortar stores for the advertised categories for this population of retailers. There also was a positive effect on total store sales. Hence the increase in sales in the advertised categories was incremental to the retailer net of any sales borrowed from non-advertised categories. The total store sales increase was a meaningful improvement compared to the baseline sales growth rates. The average Return on Ad Spend (ROAS) is positive, but does not breakeven on average although several retailers achieved or exceeded break-even based only on brick and mortar sales. We examine the robustness of our findings to alternative assumptions about the data specific to this set of experiments. Our estimates suggest online and offline are linked markets, that media planners should account for the offline effects in the planning and execution of search advertising campaigns, and that these effects should be adjusted by category and retailer. Extensive replication and a unique research protocol ensure that our results are general and credible.

Winner 

The effect of the WIC program on consumption patterns in the cereal category

by Romana Khan, Ting Zhu, and Sanjay Dhar

The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) is a federally-funded food assistance program for low income participants who are at nutritional risk. Beneficiaries receive vouchers for specific foods and brands, selected for their nutritional value. While the program is designed to improve nutrition, it may also induce changes in consumption behavior that persist beyond participation in the program. In this paper, we study how participation in WIC impacts the consumption patterns and preferences during and after the program. Our analysis focuses on the cereal category, in which the subsidized brands must meet certain nutritional guidelines. As expected, during the program households increase cereal consumption volume and shift their choices towards the WIC-approved brands. More interesting is that once households exit the program, the higher category consumption rate and elevated share of WIC brands persist. To understand the behavioral mechanism underlying these consumption patterns, we estimate a choice model and find an increased preference for WIC brands after controlling for state dependence. The evidence suggests that this targeted food subsidy program is effective in creating behavior change that persists even after the incentive is withdrawn.

The Dick Wittink Prize Committee is pleased to announce the 2018 winner of the 12th Annual Dick Wittink prize for the best paper published in the Quantitative Marketing and Economics journal.

Winner

The Dick Wittink Prize Committee is pleased to announce the 2018 winner of the 12th Annual Dick Wittink prize for the best paper published in the Quantitative Marketing and Economics journal.

Super Returns to Super Bowl Ads? by Seth Stephens-Davidowitz, Hal Varian, and Michael D. Smith

This paper uses a natural experiment—the Super Bowl—to study the causal effect of advertising on demand for movies. Identification of the causal effect rests on two points: 1) Super Bowl ads are purchased before advertisers know which teams will play; 2) home cities of the teams that are playing will have proportionally more viewers than viewers in other cities. We find that the movies in our sample experience on average incremental opening weekend ticket sales of about $8.4 million from a $3 million Super Bowl advertisement.

Runner-Up

The Impact of Advertising Along the Conversion Funnel, by Stephan Seiler and Song Yao

We assemble a unique data set that combines information on supermarket feature advertising with path-tracking data on consumers’ movement within the store as well as purchase information. Using these novel data, we trace out how advertising affects consumer behavior along the path-to-purchase. We find advertising has no significant effect on the number of consumers visiting the category being advertised. The null effect is precisely estimated. At the upper bound of the confidence interval, a one-standard-deviation shift in advertising increases category traffic by only 1.3%. We do find a significant effect at the lower end of the conversion funnel. A one-standard-deviation change in advertising (evaluated at the point estimate) increases category-level sales by 10%. We further decompose the impact on sales and find the increase is driven by the same number of consumers buying a larger number of products of the same brand. We find no evidence of spillover effects of advertising between categories that are stocked in proximity of each other, nor between different products in the same category. Two mechanisms are consistent with these patterns: consumers retrieve memory of the ad only when interacting with the category or only consumers wanting to purchase the brand choose to consume the ad.

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.

Winner

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.

Honorable Mention

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.

The Dick Wittink Prize Committee is pleased to announce the 2016 winner of the 10th Annual Dick Wittink prize for the best paper published in the Quantitative Marketing and Economics journal.

Winner

Effect of Temporal Spacing between Advertising Exposures: Evidence from Online Field Experiments, by Navdeep S. Sahni, Stanford Graduate School of Business

This paper aims to understand the impact of temporal spacing between ad exposures on the likelihood of a consumer purchasing the advertised product. I create an individual-level data set with exogenous variation in ad exposure and its spacing by running online field experiments. Using this data set, I first show that (1) ads significantly increase the likelihood of the consumers purchasing from the advertiser and (2) this increase carries over to future purchase occasions.

Importantly, I also find evidence for the spacing effect: the likelihood of a product's purchase increases if it's ads are spread apart rather than bunched together, even if spreading apart involves shifting some ads away from the purchase occasion. Accounting for the spacing effect is important to detect the effects of repeated advertising. Because the traditional models of advertising do not explain the data patterns, I build a new memory-based model of how advertising influences consumer behavior. Using a nested test, I reject the restrictions imposed by the canonical goodwill stock model (Nerlove and Arrow [1962]), in favor of the memory-based model I propose. Additionally, I use the estimated parameters to simulate counterfactual scenarios and show that the advertisers' profits might be lower if the features of the memory model are not accounted for.

The Dick Wittink Prize Committee is pleased to announce the 2015 winner of the 9th Annual Dick Wittink prize for the best paper published in the Quantitative Marketing and Economics journal.

Winner

Online Ads and Offline Sales: Measuring the Effect of Retail Advertising via a Controlled Experiment on Yahoo!, by Randall A. Lewis and David H. Reiley

This paper was among the first to demonstrate online advertising effectiveness using experiments. It highlights the challenges of identifying advertising effects. It is already a foundational paper in the literature on online advertising effects. A randomized experiment with 1.6 million customers measures positive causal effects of online advertising for a major retailer. The advertising profitably increases purchases by 5%. 93% of the increase occurs in brick-and-mortar stores; 78% of the increase derives from consumers who never click the ads. The large sample reaches the statistical frontier for measuring economically relevant effects. They improve econometric efficiency by supplementing our experimental variation with non-experimental variation caused by consumer browsing behavior. Their experiment provides a specification check for observational difference-in-differences and cross-sectional estimators; the latter exhibits a large negative bias three times the estimated experimental effect.

The Dick Wittink Prize Committee is pleased to announce the 2014 winner of the 8th Annual Dick Wittink prize for the best paper published in the Quantitative Marketing and Economics journal.

Winner

The Impact of Search Costs on Consumer Behavior: A Dynamic Approach, by Stephan Seiler

Prices for grocery items differ across stores and time because of promotion periods. Consumers therefore have an incentive to search for the lowest prices. However, when a product is purchased infrequently, the effort to check the price every shopping trip might outweigh the benefit of spending less. I propose a structural model for storable goods that takes into account inventory holdings and search. The model is estimated using data on laundry detergent purchases. I find search costs play a large role in explaining purchase behavior, with consumers unaware of the price of detergent on 70 % of their shopping trips. Therefore, from the retailer’s point of view raising awareness of a promotion through advertising and displays is important. I also find a promotion for a particular product increases the consumer’s incentive to search. This change in incentives leads to an increase in category traffic, which from the store manager’s perspective is a desirable side effect of the promotion.

Honorable Mention

Buying and Selling Information Under Competition, by Yi Xiang and Miklos Sarvary

Markets for information products exhibit varying degrees of competition on both the supply and the demand side. This paper studies the potential complementarity of information products, equilibrium information buying behaviors and information price setting in such markets. Our game-theoretic model consists of two information providers selling imperfect information to two competing clients and allows for different information quality levels as well as varying degrees of client competition. Absent of client competition, information providers compete on the statistical properties of the information they supply (i.e., the accuracy of the information). The competitive price can be high because of potential complementarity among information products when these are not very reliable. However, this may change when the clients are competing against each other. We adopt a reduced-form model of buyer competition that reflects situations where information buyers face discrete alternatives. We find that a buyer gains more through information acquisition when its competitor is less informed, suggesting a first mover advantage in information acquisition. More importantly, we also find that intense client competition can make the information products more substitutable, resulting in a lower equilibrium price for information. Furthermore, this effect leads to harsh competition between information providers and consequently provides incentives for exclusive contracting. In summary, it is found that the “quality” of information has a very different impact on sellers’ profits depending on the degree of client competition.

The Dick Wittink Prize Committee is pleased to announce the 2013 winner of the 7th Annual Dick Wittink prize for the best paper published in the Quantitative Marketing and Economics journal.

Winner

Enriching Interactions: Incorporating Outcome Data into Static Discrete Games, (PDF) by Paul B. Ellickson and Sanjog Misra

When modeling the behavior of firms, marketers and micro-economists routinely confront complex problems of strategic interaction. In competitive environments, firms make strategic decisions that not only depend on the features of the market, but also on their beliefs regarding the reactions of their rivals. Structurally modeling these interactions requires formulating and estimating a discrete game, a task which, until recently, was considered intractable. Fortunately, two-step estimation methods have cracked the problem, fueling a growing literature in both marketing and economics that tackles a host of issues from the optimal design of ATM networks to the choice of pricing strategy. However, most existing methods have focused on only the discrete choice of actions, ignoring a wealth of information contained in post-choice outcome data and severely limiting the scope for performing informative counterfactuals or identifying the deep structural parameters that drive strategic decisions. The goal of this paper is to provide a method for incorporating post-choice outcome data into static discrete games of incomplete information. In particular, our estimation approach adds a selection correction to the two-step games approach, allowing the researcher to use revenue data, for example, to recover the costs associated with alternative actions. Alternatively, a researcher might use R&D expenses to back out the returns to innovation.

Honorable Mention

A Dynamic Quality Ladder Model with Entry and Exit: Exploring the Equilibrium Correspondence using the Homotopy Method, (PDF) by Ron N. Borkovsky, Ulrich Doraszelski, and Yaroslav Kryukov

This paper explores the equilibrium correspondence of a dynamic quality ladder model with entry and exit using the homotopy method. This method is ideally suited for systematically investigating the economic phenomena that arise as one moves through the parameter space and is especially useful in games that have multiple equilibria. We briefly discuss the theory of the homotopy method and its application to dynamic stochastic games. We then present three main findings: First, the more costly and/or less beneficial it is to achieve or maintain a given quality level, the more a leader invests in striving to induce the follower to give up; the more quickly the follower does so; and the more asymmetric is the industry structure that arises. Second, the possibility of entry and exit gives rise to predatory and limit investment. Third, we illustrate and discuss the multiple equilibria that arise in the quality ladder model, highlighting the presence of entry and exit as a source of multiplicity

The Dick Wittink Prize Committee is pleased to announce the 2012 winner of the 6th Annual Dick Wittink prize for the best paper published in the Quantitative Marketing and Economics journal.

Winner

A Structural Model of Salesforce Compensation Dynamics: Estimation and Field Implementation, (PDF) by Sanjog Misra and Harikesh S. Nair

We present an empirical framework to analyze real-world salesforce compensation schemes, and report on a multi-million dollar, multiyear project involving a large contact lens manufacturer at the US, where the model was used to improve sales-force contracts. The model is built on agency theory, and solved using numerical dynamic programming techniques. The model is flexible enough to handle quotas and bonuses, output-based commission schemes, as well as "ratcheting" of compensation based on past performance, all of which are ubiquitous in actual contracts. The model explicitly incorporates the dynamics induced by these aspects in agent behavior. We apply the model to a rich dataset that comprises the complete details of sales and compensation plans for the firm's US sales-force. We use the model to evaluate profit-improving, theoretically-preferred changes to the extant compensation scheme. These recommendations were then implemented at the focal firm. Agent behavior and output under the new compensation plan is found to change as predicted. The new plan resulted in a 9% improvement in overall revenues, which translates to about $12 million incremental revenues annually, indicating the success of the field-implementation. The results bear out the face validity of dynamic agency theory for real-world compensation design. More generally, our results fit into a growing literature that illustrates that dynamic programming-based solutions, when combined with structural empirical specifications of behavior, can help significantly improve marketing decision-making, and firms' profitability.

The Dick Wittink Prize Committee is pleased to announce the 2011 winner of the 5th Annual Dick Wittink prize for the best paper published in the Quantitative Marketing and Economics journal.

Winner

Switching Costs, Experience Goods and Dynamic Price Competition, (PDF) by Toker Doganoglu

I analyze a dynamic duopoly with an infinite horizon where consumers are uncertain about their potential satisfaction from the products and face switching costs. I derive sufficient conditions for the existence of a Markov Perfect Equilibrium (MPE) where switching takes place each period. I show that when switching costs are sufficiently low, the prices in the steady state are lower than what they would have been when they are absent. This result is in contrast to those found in the literature. In the presence of low switching costs competition can be fiercer.

Honorable Mention

The Effects of Detailing on Prescribing Decisions under Quality Uncertainty, (PDF) by Andrew Ching and Masakazu Ishihara

Motivated by recent empirical findings on the relationship between new clinical evidence and the effectiveness of detailing, this paper develops a new structural model of detailing and prescribing decisions under the environment where both manufacturers and physicians are uncertain about drug qualities. Our model assumes (1) a representative opinion leader is responsible for updating the prior belief about the quality of drugs via consumption experiences and clinical trial outcomes, and (2) manufacturers use detailing as a means to build/maintain the measure of physicians who are informed of the current information sets. Unlike previous learning models with informative detailing, our model directly links the effectiveness of detailing to the current information sets and the measures of well-informed physicians. To illustrate the empirical implications of the new model, we estimate our model using a product level panel data on sales volume, prices, detailing minutes, and clinical trial outcomes for ACE-inhibitors with diuretics in Canada. Using our estimates, we demonstrate how the effectiveness of detailing depends on the information sets and the measures of well-informed physicians. Furthermore, we conduct a policy experiment to examine how a public awareness campaign, which encourages physicians/patients to report their drug experiences, would affect managerial incentives to detail. The results demonstrate that the empirical and managerial implications of our model can be very different from those of previous models. We argue that our results point out the importance of developing a structural model that captures the mechanism of how detailing/advertising conveys information in the market under study.

The Dick Wittink Prize Committee is pleased to announce the 2010 winner of the 4th Annual Dick Wittink prize for the best paper published in the Quantitative Marketing and Economics journal.

Winner

A New Use of Importance Sampling to Reduce Computational Burden in Simulation Estimation, (PDF) by Dan Ackerberg

Simulation estimators (Lerman and Manski 1981; McFadden, Econometrica 57(5):995–1026, 1989; Pakes and Pollard, Econometrica 57:1027–1057, 1989) have been of great use to applied economists and marketers. They are simple and relatively easy to use, even for very complicated empirical models. That said, they can be computationally demanding, since these complicated models often need to be solved numerically, and these models need to be solved many times within an estimation procedure. This paper suggests methods that combine importance sampling techniques with changesof-variables to address this caveat. These methods can dramatically reduce the number of times a particular model needs to be solved in an estimation procedure, significantly decreasing computational burden. The methods have other advantages as well, e.g. they can smooth otherwise non-smooth objective functions and can allow one to compute derivatives analytically. There are also caveats—if one is not careful, they can magnify simulation error. We illustrate with examples and a small Monte-Carlo study.

Honorable Mention

Beyond Plan Vanilla: Modeling Joint Product Assortment and Pricing Decisions, (PDF) by Michaela Draganska, Michael Mazzeo, and Katja Seim

This paper investigates empirically the product assortment strategies of oligopolistic firms. We develop a framework that integrates product choice and price competition in a differentiated product market. The present model significantly improves upon the reduced-form profit functions typically used in the entry and location choice literature, because the variable profits that enter the product-choice decision are derived from a structuralmodel of demand and price competition. Given the heterogeneity in consumers' product valuations and responses to price changes, this is a critical element in the analysis of product assortment decisions. Relative to the literature on structural demand models, our results show that incorporating endogenous product choice is essential for policy simulations and may entail very different conclusions from settings where product assortment choices are held fixed.

The Dick Wittink Prize Committee is pleased to announce the 2009 winner of the 3rd Annual Dick Wittink prize for the best paper published in the Quantitative Marketing and Economics journal.

Winner

The Discriminatory Incentives to Bundle in the Cable Television Industry, by Gregory Crawford

An influential theoretical literature supports a discriminatory explanation for product bundling: it reduces consumer heterogeneity, extracting surplus in a manner similar to second-degree price discrimination. This paper tests this theory and quantifies its importance in the cable television industry. The results provide qualified support for the theory. While bundling of general interest cable networks is estimated to have no discriminatory effect, bundling an average top-15 special-interest cable network significantly increases the estimated elasticity of cable demand. Calibrating these results to a simple model of bundle demand with normally distributed tastes suggests that such bundling yields a heterogeneity reduction equal to a 4.7% increase in firm profits (and 4.0% reduction in consumers surplus). The results are robust to alternative explanations for bundling.

Honorable mention

A Model of the Effect of Affect on Economic Decision Making, by Benjamin E. Hermalin and Alice M. Isen

The standard economic model of decision making assumes a decision maker’s current emotional state has no impact on his or her decisions. Yet there is a large psychological literature that shows that current emotional state, in particular mild positive effect, has a significant effect on decision making, problem solving, and behavior. This paper offers a way to incorporate this insight from psychology into economic modeling. Moreover, this paper shows that this simple insight can parsimoniously explain a wide variety of behaviors.

The Dick Wittink Prize Committee is pleased to announce the 2008 winner of the 2nd Annual Dick Wittink prize for the best paper published in the Quantitative Marketing and Economics journal.

Winner

Intertemporal Price Discrimination with Forward-Looking Consumers: Application to the US Market for Console Video-Games, by Harikesh Nair

Firms in durable good product markets face incentives to intertemporally price discriminate, by setting high initial prices to sell to consumers with the highest willingness to pay, and cutting prices thereafter to appeal to those with lower willingness to pay. A critical determinant of the profitability of such pricing policies is the extent to which consumers anticipate future price declines, and delay purchases. I develop a framework to investigate empirically the optimal pricing over time of a firm selling a durable-good product to such strategic consumers. Prices in the model are equilibrium outcomes of a game played between forward-looking consumers who strategically delay purchases to avail of lower prices in the future, and a forward-looking firm that takes this consumer behavior into account in formulating its optimal pricing policy. The model outlines first, a dynamic model of demand incorporating forward-looking consumer behavior, and second, an algorithm to compute the optimal dynamic sequence of prices given these demand estimates. The model is solved using numerical dynamic programming techniques. I present an empirical application to the market for video-games in the US. The results indicate that consumer forward-looking behavior has a significant effect on optimal pricing of games in the industry. Simulations reveal that the profit losses of ignoring forward-looking behavior by consumers are large and economically significant, and suggest that market research that provides information regarding the extent of discounting by consumers is valuable to video-game firms.

Honorable mention

(Noisy) Communication, by Bharat N. Anand & Ron Shachar

Communication is central to many settings in marketing and economics.

A focal attribute of communication is miscommunication. We model this key characteristic as a noise in the messages communicated, so that the sender of a message is uncertain about its perception by the receiver, and then identify the strategic consequences of miscommunication. We study a model where competing senders (of different types) can invest in improving the precision of the informative but noisy message they send to a receiver, and find that there exists a separating equilibrium where senders' types are completely revealed. Thus, although communication is noisy it delivers perfect results in equilibrium. This result stems from the fact that a sender's willingness to invest in improving the precision of their messages can itself serve as a signal. Interestingly, the content of the messages is ignored by the receiver in such a signaling equilibrium, but plays a central role by shaping her beliefs off the equilibrium path (and thus, enables separation between the types). This result also illustrates the uniqueness of the signaling model presented here. Unlike other signaling models, the suggested model does not require that the costs and benefits of the senders will be correlated with their types to achieve separation.

Committee Members: Pradeep Chintagunta, Miguel Villas-Boas and Michel Wedel

The Dick Wittink Prize Committee is pleased to announce the 2007 winner of the 2nd Annual Dick Wittink prize for the best paper published in the Quantitative Marketing and Economics journal.

Winner

Intertemporal Effects of Consumption and their Implications for Demand Elasticity Estimates, by Wesley Hartmann

Marketers have typically looked at stockpiling of goods as a source of inter-temporal substitution effects. Hartmann shows that such effects could also occur for non-durable and non-storable goods when consumption of a good in one period substitutes for consumption in another period by consumption producing a stock that provides utility over time and thus diminishes the marginal utility of future consumption. The dynamic discrete choice model of demand formulated and estimated in the paper, using actual golf consumption data from a panel of players, is also the first to specify a rich, multidimensional, continuous distribution of heterogeneity within the context of dynamic structural models. Further, it also separates out the effects of such heterogeneity from state dependence. The empirical findings indicate that consumption does have a lasting effect on utility that induces substitutability across time and that this state dependence effect is incorrectly estimated when forward looking behavior of consumers is ignored. Further, the paper quantifies cross-time price elasticities and finds these to be positive, suggesting that rounds of golf on the days before and after a price change are substitutes for the round experiencing the price change. Using counterfactual analysis, the paper answers interesting questions such as: how changes in price can influence the distribution of demand for rounds of golf over time? The model and insights developed in the paper can be a useful input to revenue management at capacity constrained firms such as movie theaters and electric utilities since temporary price changes can shift demand to or from capacity constrained time periods. These insights go beyond those previously identified by research on storable goods that used dynamic structural models.

Honorable Mention

Pass-Through Timing, by Sergio Meza & K. Sudhir

A topic of continuing interest to marketers is the measurement of trade promotion pass through. Previous research has focused on documenting the extent of pass through across various product categories. Meza and Sudhir tackle the issue of how pass through of trade promotions for a given category varies over time - an issue of particular relevance for seasonal products that face varying demand conditions in different time periods. In higher demand periods, retail prices may fall simply because of high price elasticity rather than due to a reduction in wholesale price and this needs to be accounted for to correctly estimate the extent of pass through. Using data from the beer and tuna categories, the paper also distinguishes between pass through for loss-leader and for regular products. The paper reports an interesting dichotomy in its results - during regular demand periods only loss-leader products receive a high pass-through for trade promotions; whereas both loss-leader and regular products receive some pass-through in high demand periods. A key implication of this research is that estimating an average pass-through over the entire year may seriously misrepresent the nature of retailer behavior over the course of the year.

Committee Members: Pradeep Chintagunta, Miguel Villas-Boas and Michel Wedel.