Raluca Mihaela Ursu rursu@uchicago.edu - home.uchicago.edu/~rursu/ University of Chicago, Department of Economics 1126 East 59 th Street Chicago, IL 60637 Education Ph.D., Economics, University of Chicago, expected June 2016 M.A., Economics, University of Chicago, 2012 B.A., Economics and Mathematics Summa Cum Laude, Mount Holyoke College, 2010 Research Interests Quantitative Marketing Empirical Industrial Organization Consumer Search Digital Marketing Applied Theory Working Papers Choice (Job Market Paper) The Consumer Never Rings Twice: Theory and Evidence of the Competitive Role of Consumer Work in Progress Estimating Sequential Search Models using MPEC Joint with Pradeep K. Chintagunta Search Method? Optimal Search Publications News Posting by Strategic Users in a Social Network Joint with M. Gupte, M.T. Hajiaghayi, L. Han, L. Iftode, and P. Shankar Proceedings of the 5 th Workshop on Internet and Network Economics, 2009, pp. 632-639, Springer. Conference Presentations Choice o Rising Star Session on Search at the 13 th Annual International Industrial Organization Conference (IIOC), Boston (April 2015) o 6 th Workshop on Search and Switching Costs, Groningen, Netherlands (May 2015) o 6 th Annual Searle Conference on Internet Search and Innovation, Chicago (June 2015)
The Consumer Never Rings Twice: Theory and Evidence of the Competitive Role of Consumer o 25 th International Conference on Game Theory, Stony Brook (July 2014) Non-scientific Presentation Understanding Online Consumer Search: A PhD Tale of Math and Econ from a Recent MHC Alumna o Mount Holyoke College, Department of Mathematics (April 2015) Honors, Scholarships and Fellowships Theodore W. and Esther Schultz Economics Fellowship, University of Chicago, 2015-2016 Social Sciences Fellowship, University of Chicago, 2010-2015 Virginia Galbraith Graduate Fellowship, Mount Holyoke College, 2010 Rutgers DIMACS Summer REU Fellowship, 2009 Teaching Experience Lecturer - Department of Economics, University of Chicago o Elements of Economics Analysis II, Undergraduate, 2015 Teaching Assistant - Booth School of Business, University of Chicago o Applied Regression Analysis, MBA, Professor Cynthia Wu, 2014 Teaching Assistant - Department of Economics, University of Chicago o Price Theory II, PhD, Professor Phil Reny, 2013 o Price Theory III, PhD, Professor Roger Myerson and Professor Phil Reny, 2013 o Honors Game Theory, Undergraduate, Professor Hugo Sonnenschein, 2012-2013 PhD Coursework Economics Price Theory I, II, III Empirical Analysis I, II, III Advanced IO I, II, III The Economics of Information Topics in Theoretical Economics Economic Model of Politics Empirical Micro. Research Evolutionary Game Theory Social Interactions and Inequality Theory of Income I, II, III Gary Becker, Kevin Murphy, Phil Reny, Roger Myerson Ali Hortaçsu, Derek Neal, Harald Uhlig, Lars Hansen Chad Syverson, Ali Hortaçsu, Dennis Carlton Milton Harris Phil Reny Roger Myerson, Richard Van Weelden Steven Levitt Balazs Szentes Steven Durlauf Fernando Alvarez, Nancy Stokey, Casey Mulligan Marketing Marketing Strategy (audit) Chris Nosko Marketing Literature Seminar (audit) Gunther Hitsch, Chris Nosko
References Professor Ali Hortaçsu Professor Pradeep K. Chintagunta University of Chicago Univ. of Chicago Booth School of Business Phone: (773) 702-5841 Phone: (773) 702-8015 Email: hortacsurecs2015@gmail.com Email: pradeep.chintagunta2015@gmail.com Professor Hugo F. Sonnenschein Professor Régis Renault University of Chicago Université Paris Dauphine Phone: (773) 834-5960 Phone: (33)(0) 6 60 17 32 90 Email: hfsonnen@uchicago.edu Email: regis.renault@dauphine.fr
Research Abstracts Choice (Job Market Paper) The Internet has led to an explosion of product choices facing consumers. When consumers face many options, intermediaries can help by ranking them, which in turn can influence how consumers search and what they ultimately purchase. To understand the role of intermediaries' rankings, it is important to separate the effect of the position in which a firm is displayed in an intermediary's listing and the characteristics of the firm. However, as intermediaries choose rankings to maximize their profits, rankings are endogenous, thus separately identifying their role is challenging. In this paper, I identify the causal effect of rankings by using a data set on hotel searches from Expedia that includes searches from an experiment where rankings were randomly generated. First, using detailed clickstream and purchase data, I show that (1) top positions lead to more clicks and purchases, but conditional on a click, higher ranked hotels do not generate more purchases and (2) that rankings mainly affect choices by reducing search costs, rather than expectations or direct utility. I then turn to quantifying the effect of rankings on consumer choices. To this end, I estimate a sequential search model and find lower position effects than those typically found without experimental variation. Finally, I construct three counterfactuals to show how companies can use these results to design more effective rankings. First, I find that using the model's estimates to construct a utility-based ranking leads to a sizable increase in consumer valuation of as much as $38.36 (21% of the purchase price). Second, I simulate consumer choices when search costs increase (as on mobile devices) and show that this would cost consumers as much as $16.23 (9% of the purchase price) in poorer matches and higher prices, highlighting the tension between consumer search costs and the impact of the ranking. Third, I evaluate the merits of a recently adopted approach at Amazon of only ranking independent hotels. Contrary to existing concerns about reducing the diversity of the listed hotels, I find that such a ranking benefits consumers by as much as $9.20 (5% of the purchase price), suggesting new avenues for improving the performance of a ranking. The Consumer Never Rings Twice: Theory and Evidence of the Competitive Role of Consumer This paper examines how the order in which consumers sample products affects competition. I present a model where firms are searched by an exogenous fraction of consumers, which I call a firm s search share, and show how equilibrium prices depend on this fraction. This model unifies two strands of the theoretical consumer search literature. More precisely, it combines models where consumers search randomly (i.e. each firm is searched by an equal fraction of consumers) and models where one firm is prominent (i.e. all consumers begin by searching the prominent firm). Consistent with the existing theory, a prominent firm charges a lower price than a less prominent firm. However, unlike previous results, I show that a prominent firm s price may increase in its search share if consumers search costs are large. Using data on consumers online search for hotels at a leading online travel agent, I provide the first test of the predictions of this theory. Interpreting the firm s search share as its expected position in the ranking of the online travel agent, I find evidence consistent with the prominence model: the higher the firm s search share, the lower the price it charges. Since consumers increasingly buy products online where firms can effectively change the order in which consumers sample them, understanding how this order affects competition is important.
Estimating Sequential Search Models using MPEC The dynamic programming approach of Weitzman (1979) has recently been used in several papers estimating consumer sequential search. The popularity of this method owes to its ability to exactly characterize the sequence of choices made by consumers. However, in order to characterize this sequence, knowledge of reservation values is required. Reservation values are values that make consumers indifferent between searching and stopping at each stage in their search process and are solutions to structural equations relating consumer utilities and their search costs. Inverting these equations to solve for reservation values for each draw of the structural parameters makes estimation of the model using nested fixed point (NFXP) methods computationally challenging. In this paper, we follow Su and Judd (2012) and show how to recast the optimal sequential search problem as a mathematical program with equilibrium constraints (MPEC). Instead of computing reservation values for each draw, this method augments the likelihood function with these reservation values and imposes the structural equation defining reservation values as a constraint. The main advantage of this method is that it only requires checking this equation once, without solving it, thereby significantly reducing computational time. Search Method? Optimal Search Understanding the method that consumers use to sample through alternatives is paramount to correctly estimating their preference and search cost parameters. Identifying consumers' search method has been the subject of at least two recent papers (De los Santos et al. 2012; Honka and Chintagunta, 2014, which find that the simultaneous search model more accurately describes consumers' search patterns. However, Morgan and Manning (1985) present a model of optimal search that includes both search models as special cases. In this paper, I use ComScore browsing data to test whether consumers are searching using this optimal search rule, exploiting preliminary evidence that consumers search in phases. News Posting by Strategic Users in a Social Network We argue that users in social networks are strategic in how they post and propagate information. We propose two models - greedy and courteous - and study information propagation both analytically and through simulations. For a suitable random graph model of a social network, we prove that news propagation follows a threshold phenomenon, hence, high-quality information provably spreads throughout the network assuming users are greedy. Starting from a sample of the Twitter graph, we show through simulations that the threshold phenomenon is exhibited by both the greedy and courteous user models.