The value of a "free" customer

We study the problem of a firm that faces asymmetric information about the productivity of its potential workers. In our framework, a worker’s productivity is either assigned by nature at birth, or determined by an unobservable initial action of the worker that has persistent effects over time. We provide a characterization of the optimal dynamic compensation scheme that attracts only high productivity workers: consumption –regardless of time period– is ranked according to likelihood ratios of output histories, and the inverse of the marginal utility of consumption satisfies the martingale property derived in Rogerson (1985). However, in the case of i.i.d. output and square root utility we show that, contrary to the features of the optimal contract for a repeated moral hazard problem, the level and the variance of consumption are negatively correlated, due to the influence of early luck into future compensation. Moreover, in this example long-term inequality is lower under persistent private informationCustomer lifetime value, CRM, Dynamic programming, GMM Estimation

A Dynamic Model of Sponsored Search Advertising

Sponsored search advertising is ascendant Jupiter Research reports expenditures rose 28% in 2007 to $8.9B and will continue to rise at a 15landscape. Yet little, if any empirical research focuses upon search engine marketing strategy by integrating the behavior of various agents in sponsored search advertising (i.e., searchers, advertisers, and the search engine platform). The dynamic structural model we propose serves as a foundation to explore these and other sponsored search advertising phenomena. Fitting the model to a proprietary data set provided by an anonymous search engine, we conduct several policy simulations to illustrate the bene ts of our approach. First, we explore how information asymmetries between search engines and advertisers can be exploited to enhance platform revenues. This has consequences for the pricing of market intelligence. Second, we assess the effect of allowing advertisers to bid not only on key words, but also by consumers searching histories and demographics thereby creating a more targeted model of advertising. Third, we explore several different auction pricing mechanisms and assess the role of each on engine and advertiser profits and revenues. Finally, we consider the role of consumer search tools such as sorting on consumer and advertiser behavior and engine revenues. One key finding is that the estimated advertiser value for a click on its sponsored link averages about 24 cents. Given the typical$22 retail price of the software products advertised on the considered search engine, this implies a conversion rate (sales per click) of about 1.1%, well within common estimates of 1-2% (gamedaily.com). Hence our approach appears to yield valid estimates of advertiser click valuations. Another finding is that customers appear to be segmented by their clicking frequency, with frequent clickers placing a greater emphasis on the position of the sponsored advertising link. Estimation of the policy simulations is in progress

Advertiser Learning in Direct Advertising Markets

Direct buy advertisers procure advertising inventory at fixed rates from publishers and ad networks. Such advertisers face the complex task of choosing ads amongst myriad new publisher sites. We offer evidence that advertisers do not excel at making these choices. Instead, they try many sites before settling on a favored set, consistent with advertiser learning. We subsequently model advertiser demand for publisher inventory wherein advertisers learn about advertising efficacy across publishers' sites. Results suggest that advertisers spend considerable resources advertising on sites they eventually abandon -- in part because their prior beliefs about advertising efficacy on those sites are too optimistic. The median advertiser's expected CTR at a new site is 0.23%, five times higher than the true median CTR of 0.045%. We consider how pooling advertiser information remediates this problem. Specifically, we show that ads with similar visual elements garner similar CTRs, enabling advertisers to better predict ad performance at new sites. Counterfactual analyses indicate that gains from pooling advertiser information are substantial: over six months, we estimate a median advertiser welfare gain of \$2,756 (a 15.5% increase) and a median publisher revenue gain of \$9,618 (a 63.9% increase)

RA-MAP, molecular immunological landscapes in early rheumatoid arthritis and healthy vaccine recipients

Rheumatoid arthritis (RA) is a chronic inflammatory disorder with poorly defined aetiology characterised by synovial inflammation with variable disease severity and drug responsiveness. To investigate the peripheral blood immune cell landscape of early, drug naive RA, we performed comprehensive clinical and molecular profiling of 267 RA patients and 52 healthy vaccine recipients for up to 18 months to establish a high quality sample biobank including plasma, serum, peripheral blood cells, urine, genomic DNA, RNA from whole blood, lymphocyte and monocyte subsets. We have performed extensive multi-omic immune phenotyping, including genomic, metabolomic, proteomic, transcriptomic and autoantibody profiling. We anticipate that these detailed clinical and molecular data will serve as a fundamental resource offering insights into immune-mediated disease pathogenesis, progression and therapeutic response, ultimately contributing to the development and application of targeted therapies for RA.</p

Choice Models and Customer Relationship Management

Customer relationship management (CRM) typically involves tracking individual customer behavior over time, and using this knowledge to configure solutions precisely tailored to the customers' and vendors' needs. In the context of choice, this implies designing longitudinal models of choice over the breadth of the firm's products and using them prescriptively to increase the revenues from customers over their lifecycle. Several factors have recently contributed to the rise in the use of CRM in the marketplacePeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47023/1/11002_2005_Article_5892.pd

A Dynamic Model of Sponsored Search Advertising

Sponsored search advertising is ascendant---Jupiter Research reports expenditures rose 28% in 2007 to $8.9B and will continue to rise at a 15$22 retail price of the software products advertised on the considered search engine, this implies a conversion rate (sales per click) of about 1.1%, well within common estimates of 1-2% (gamedaily.com). Hence our approach appears to yield valid estimates of advertiser click valuations. Another finding is that customers appear to be segmented by their clicking frequency, with frequent clickers placing a greater emphasis on the position of the sponsored advertising link. Estimation of the policy simulations is in progress.Sponsored Search Advertising, Two-sided Market, Dynamic Game, Structural Models, Empirical IO, Customization, Auctions

Market Roll-Out and Retailer Adoption for New Brands

This paper proposes a descriptive model of the spatial and temporal evolution of retail distribution for new packaged goods. The distribution model postulates separate processes for local market entry by manufacturers, and adoption by retailers given entry. Of special interest is whether retail adoption occurs along a competitive network with retailers as nodes and overlapping trade areas of these retailers as links. The model is calibrated on data covering the introduction of two very successful new brands in the frozen pizza category. For these brands, manufacturers sequentially enter markets based on spatial proximity to markets already entered (spatial evolution), and on whether chains in these markets adopted previously elsewhere (market selection). A retail chain adopts new brands based on the adoption timing of competing chains within its trade territory (competitive contagion) and on the fraction of its trade area in which the new brand is available (trade area coverage). The effects of market selection and of trade area coverage create dependencies between market entry and retail adoption. Because of these dependencies the attraction of a particular market as a lead market depends on its location in the geographic structure of the U.S. retail trade.spatial diffusion, network diffusion, retail distribution, new product research

The impact of collinearity on regression analysis: the asymmetric effect of negative and positive correlations

The purpose of this paper is to ascertain how collinearity in general, and the sign of correlations in specific, affect parameter inference, variable omission bias, and their diagnostic indices in regression. It is found that collinearity can reduce parameter variance estimates and that positive and negative correlation structures have an asymmetric effect on variable omission bias. It is also shown that the effects of collinearity are moderated by the relationship between the dependent variable and the regressors, a consideration not incorporated into most commonly used collinearity diagnostics. The formulae derived enable researchers to assess the sensitivity of regression results to the underlying correlation structure in the data.