Dynamic Models and Methods in the Consumer Packaged Goods Industry

Dynamic structural models capture forward looking behavior on the part of economic agents. While these models can bring new insights, the computational cost of estimating these models can be prohibitive. In the three chapters of my dissertation, I use dynamic models to capture qualitative insights into the consumer packaged goods industry, while introducing methodological innovations that expand the range of problems where dynamic models can be estimated. In the first chapter, I seek to explain counter-cyclic pricing, the phenomenon where the price of seasonal goods increases in periods of high demand. I do this by modeling consumers who may purchase without search. Consumers are more likely to purchase without search in low demand periods, which decreases estimated price sensitivity. I test this explanation using a dynamic, structural inventory model where consumers make decisions on whether to search, which reveals price promotions. I estimate this model by developing a cyclic-successive approximation algorithm, which removes the computational burden of adding cyclic variables to the state space of any dynamic model.Several recent papers develop methods to identify discount factors in dynamic models. However, in some cases, the estimation of discount factors is a computational challenge. The nested pseudo likelihood method of Agguiregabiria and Mira (2007) allows the value function to be calculated without costly contraction mapping evaluations. However, when the discount factor is being estimated, this computational efficiency is lost. In the second chapter of my dissertation, I restore this computational efficiency through an application of the eigendecomposition.The third chapter is a joint work with Ron Borkovsky, Avi Goldfarb, and Sridhar Moorthy, in which we capture the inherently dynamic nature of brand value. Firms invest in brand equity through advertising, and the value of this equity will depend on the expected decisions of rival firms. Measuring brand value then requires one to account for the current state of the market, and the evolution of the market in the future. We apply our approach by estimating brand values in the stacked potato chips industry by adapting the Pakes-McGuire quality ladder to allow firms to have a stochastic advertising decision.Ph.D

Robitaille et al. (2021), Nudging Organ Donor Registrations, J Mktg

ServiceOntario, Informational Brochure, Perspective Taking Nudges, Reciprocal Altruis

Essays on demand spillovers in the video-game industry

Thesis (Ph. D.)--University of Rochester. William E. Simon Graduate School of Business Administration, 2019.The video-game industry is an important and fast-growing entertainment business. It is estimated to have reached 43.8 billion US dollars in revenue in 2018, surpassing the projected total global box office for the film industry (Entertainment Software Association, 2019). The video-game industry features frequent new product introduction, innovation in product characteristics including achievement systems, and active interplay with streaming services such as YouTube. Therefore, the video-game industry is an ideal setting to study demand spillovers between related products and product designs and how these spillovers affect consumer and firm decisions. This thesis consists of three essays on topics related to the demand spillovers in the video-game industry. The first essay examines the effect of extending and sharing intellectual property rights of the original video-game products. Although user-generated content, and increasingly videos, have become ubiquitous in the digital age, the users who upload these videos often do not hold the intellectual property rights for the content they post. We evaluate the impact of allowing such content on the intellectual property holder’s original product. This question is especially relevant for content concerning video games. Video-game content on YouTube accounts for one third of YouTube’s total traffic, yet video-game firms can legally require any third-party videos featuring their game to be taken down. Although many firms allow third parties to freely share and extend their intellectual property on these public platforms, some, such as Nintendo, do not. We study the impact of firm decisions to share and extend intellectual property in this highly relevant context of video games. To do so, we collected a unique individual-level panel dataset on usage levels and purchases of video games as well as data on the timing of related YouTube video posts and competitive competitions. We apply both difference-in-differences (DiD) and synthetic-control methods to evaluate the causal effects of these sharing and extending activities on video-game usage and sales. We find that company-initiated competitive gaming tournaments increase game usage by up to 45%, whereas one third-party YouTube video post increases game sales by 9.4% and game usage by 12.7%. Both effects are concentrated in the heavy users, and casual gamers benefit less from YouTube video posts. These results offer an explanation for why firms would vary in allowing such content sharing and extensions, and why Nintendo, in particular, would want to set stricter content-sharing policies for its games. The second essay explores the impact of goal achievements without monetary rewards on subsequent product usage. I assemble a unique panel dataset of product usage and goal achievements from the world’s largest platform of digital PC video games. Using the difficulty level of the remaining achievements as instruments, I find achieving an extra goal increases subsequent game usage by a statistically and economically significant margin, and the uplifting effect can last as long as one month. In addition, I find supporting evidence for self-satisfaction but not social effects as the main driving mechanism. Empirical findings in this research suggest the goal achievements alone can be effective in promoting consumer engagement with the product and reducing consumer attrition. The last essay studies the intertemporal spillover effect from current software purchases to future software purchases. Many platform strategies focus on indirect network effects between sellers through platform expansion. In this essay, we show sellers on the console-video-game platform generate a positive intertemporal spillover effect and expand the demand for other sellers, holding fixed the set of platform adopters. We propose a novel identification strategy that leverages exogenous variation in the release timing of games exclusively available on a console platform, and examine how this variation affects the sales of games available on both platforms. We find a sizable intertemporal demand spillover effect between games: A 1% increase in total copies sold on a platform leads to a 0.153% increase in the sales of other games in the next month (i.e., an elasticity of 0.153). Additional analysis suggests this demand spillover effect is reminiscent of habit formation on the consumer side, in that past purchases keep end users active on the platform. Our finding provides a potential explanation for recent platform-sales events and subscription services that provide free games to consumers every month

Purified E255L Mutant SERCA1a and Purified PfATP6 Are Sensitive to SERCA-type Inhibitors but Insensitive to Artemisinins*

The antimalarial drugs artemisinins have been described as inhibiting Ca2+-ATPase activity of PfATP6 (Plasmodium falciparum ATP6) after expression in Xenopus oocytes. Mutation of an amino acid residue in mammalian SERCA1 (Glu255) to the equivalent one predicted in PfATP6 (Leu) was reported to induce sensitivity to artemisinin in the oocyte system. However, in the present experiments, we found that artemisinin did not inhibit mammalian SERCA1a E255L either when expressed in COS cells or after purification of the mutant expressed in Saccharomyces cerevisiae. Moreover, we found that PfATP6 after expression and purification from S. cerevisiae was insensitive to artemisinin and significantly less sensitive to thapsigargin and 2,5-di(tert-butyl)-1,4-benzohydroquinone than rabbit SERCA1 but retained higher sensitivity to cyclopiazonic acid, another type of SERCA1 inhibitor. Although mammalian SERCA and purified PfATP6 appear to have different pharmacological profiles, their insensitivity to artemisinins suggests that the mechanism of action of this class of drugs on the calcium metabolism in the intact cell is complex and cannot be ascribed to direct inhibition of PfATP6. Furthermore, the successful purification of PfATP6 affords the opportunity to develop new antimalarials by screening for inhibitors against PfATP6

Two diseases, one approach: multitarget drug discovery in Alzheimer's and neglected tropical diseases

In the past decade, scientific advances in network pharmacology have laid the foundations for a polypharmacological approach to discover new drugs for complex diseases. There is now a comprehensive understanding that many incurable diseases are multifactorial in nature and, consequently, conventional drugs directed to a single molecular target are inadequate. To achieve a desired clinical outcome, a polypharmacological approach seeks to intervene in the diseased network using either combinations of multiple drugs or single small molecules modulating multiple targets. Both these approaches are equally feasible from a clinical standpoint. However, for various reasons which will be discussed in this review, the latter approach may be favoured for Alzheimer's disease (AD) and neglected tropical diseases (NTDs). With each passing year, an increasing number of multitarget drugs and drug candidates are being identified, and several proof-of-concepts for treating these two diseases have emerged. Herein, with an awareness of the obstacles and challenges faced, we explore small molecules that seek to modulate multiple targets with the ultimate goal of harnessing network pharmacology for therapeutic applications in AD and NTDs