Below is a list of associated faculty and possible research projects, organized by academic area.
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Below is a list of associated faculty and possible research projects, organized by academic area.
Professor Blankespoor’s research focuses on firms’ communication of financial information, the role of information processing costs in disclosure choices and consequences, as well as the impact of changes in information technology on the flow of financial information in capital markets. A forthcoming paper examines firms’ use of Twitter as a dissemination tool and the impact on market liquidity.
Other recent work examines the impact of new technology requirements for financial reports (XBRL) on firm disclosure choice and information asymmetry in the market. Future work might include the study of the flow of financial information through traditional and social media outlets, the extent of visibility concerns for firms and their implications, or firms’ use of social media in financial communications.
As an example, see the forthcoming paper on dissemination through Twitter.
Professor deHaan’s research interests broadly relate to financial reporting and corporate disclosure strategies. A current study investigates the flow of firms’ financial information through traditional press and social media networks.
Other recent work examines investor relations and managers’ strategic communication with capital market participants.
Professor McNichols’ research is currently focused on three topics.
The first is conservatism in accounting and its implications for research using financial statement measures. Current work explores the implications of correcting for conservatism for tests of the diversification discount, the relation between investment and Tobin’s Q and estimates of implied cost of capital.
A second set of projects explores factors contributing to audit failures, including culture, geography and education.
A third set of projects examines how the informativeness of earnings has changed over time, and the extent to which the change is related to firm size, earnings news, concurrent disclosures and use of fair value reporting.
Professor Berk’s research is primarily theoretical in nature and covers a broad range of topics in finance including delegated money management; asset pricing (the relation between stock returns and characteristics of the firm, such as accounting numbers, investment, firm size, etc.); valuing the firm’s growth potential, the firm’s capital structure decision, and the interaction between labor markets and financial markets. He has also explored individual rationality in an experimental setting.
Professor Koudijs’ research focuses on financial markets and financial intermediaries. His work often has a historical dimension. In two recent papers, he has used a unique natural experiment from the 18th century to study the role of news in financial markets and the impact of insider trading. In another recent project he has looked at the financial crisis of 1773 to study the factors that determine the leverage of financial intermediaries and the role of beliefs. More details are on his website.
In current work, Professor Koudijs looks at the impact of different liability rules on risk taking of bankers in the 19th and early 20th centuries. In another project, he studies the economic impact of changes in bankruptcy protection in the American South during the 1830s, specifically for the owners of slave plantations.
Professor McQuade has research interests in financial economics and real estate. Recent work has analyzed the systematic factors which impact the cross-section of stock returns, especially time-varying aggregate volatility. He has also used large real estate datasets to understand the role of foreclosures during the housing crisis.
He has recently started new empirical work on the balance sheet channel and spillover effects in commercial real estate markets using micro data on real estate investment trusts (REITS).
Professor Athey’s research is in the areas of industrial organization, microeconomic theory, and applied econometrics. Her current research focuses on the design of auction-based marketplaces and the economics of the internet, primarily on online advertising and the economics of the news media.
She has also studied dynamic mechanisms and games with incomplete information, comparative statics under uncertainty, and econometric methods for analyzing auction models.
Professor Benkard’s research is in the areas of empirical industrial organization (I.O.), applied microeconomics, and econometrics, and concentrates on applying microeconomic and game theoretic models to the study of individual markets. His recent work has focused on developing methods that allow us to analyze I.O. models empirically. This includes theoretical work on how to estimate demand systems and dynamic oligopoly models, as well as empirical work that uses these techniques to analyze different industries. Recently empirical projects include a dynamic analysis of airline mergers, and a empirical study of network evolution.
Professor Diamond’s research studies the causes and consequences of households’ and firm’s geographic location choices across neighborhoods and cities.
A recent project analyzes why US households have become increasingly geographically segregated by education level and how this segregation led to increased economic well-being inequality. Her work uses large datasets related to local labor and real-estate markets and a combination of structural and reduced-form estimation techniques.
Professor Imbens’ research focuses on developing methods for drawing causal inferences in observational studies, using matching, instrumental variables, and regression discontinuity designs.
Professor Reguant works in the field of empirical industrial organization, with a focus on energy and environmental applications. She studies how strategic behavior, market structure, and firm dynamics affect the performance of energy and environmental policies. Professor Reguant also studies how energy and environmental regulation can be improved through better market design.
In a current project, Professor Reguant is analyzing the costs of integrating renewable energy in the electricity market, taking into account strategic behavior. She finds that wind farms distort their forecasts due to price incentives in the market place, which arise due to market power. These distortions highlight that market structure can have substantial impact on the effective costs of integrating renewable energy.
Peter Reiss’ research covers topics in industrial organization, applied econometrics, finance and marketing. Much of his work uses large consumer and firm datasets to explore specific industries, markets and practices, including: pricing policies, consumer demand, innovation, competition issues, and firm turnover.
Two current projects are looking at airline pricing using ticket datasets and product attribute changes in video and online media.
Professor Shaw’s most recent research focuses on managing talent in high performance organizations. She studies how firms attract and build star talent in the software industry and in a wide range of knowledge-intensive industries.
More broadly, Professor Shaw studies how companies can achieve measurable rates of return from investing in human resource management practices that are aimed at improving the performance of workers or teams of workers.
Professor Hartmann is currently working on projects related to advertising effectiveness and optimal advertising allocation. As new distribution channels for advertising emerge (internet, mobile and social), research is needed to assess their relative effectiveness and complementarities with traditional channels (e.g. TV). Given an understanding of ad effectiveness, we also develop models to assess firms’ optimal advertising strategies. A recent working paper illustrates how equilibrium advertising in presidential elections would change in the absence of the Electoral College.
An ongoing project seeks to understand when and why advertisers might seek exclusive ad distribution, such as Budweiser’s 20+ year exclusive role as the only beer advertiser during the Super Bowl. New data sets that combine individual-level exposure to both direct advertisements and indirect “earned” exposures through social media platforms with in-store sales data also provide opportunities to better assess the complete effect of an ad exposure and can provide insights into how advertisers might participate in the “social” conversation about their brands.
See the working paper on advertising competition in presidential elections as an example.
Professor Nair is interested in marketing analytics, and the use of data to improve marketing resource allocation within firms. One stream of his research studies empirically the dynamic effects of marketing actions. A second focuses on empirical analysis of contracts and incentives. A third stream investigates empirically contexts with network effects.
Current projects include analysis of salesforce compensation contracts combining firms’ internal HR datasets with customer transaction data; a project on the empirical investigation of advertising content on online social networks combining tools from text analysis and econometrics; and a project on measuring complementarities between advertising and product consumption using detailed panel data on consumer product choice and TV-ad viewing decisions.
Professor Sahni’s research focuses on understanding online markets. His studies employ various methodologies ranging from building empirical models to running field experiments to make inferences from data.
His PhD dissertation focused on the effect of online search advertising on consumer decision-making. For this study Navdeep executed a randomized field experiment and used innovative techniques to estimate the impact of repetition and timing of ads on advertisers’ returns. To compare counterfactual advertising strategies, he built a memory-based model of learning through multiple ad exposures.
His current work in progress investigates whether ads can benefit an advertiser’s competitors, and how this phenomenon can affect the returns from advertising.
Professor Stephan Seiler’s research focuses on analyzing consumer choice in various markets. He analyzes issues ranging from the choice of hospital for a bypass operation to the reaction of consumers to promotions on laundry detergent. He is particularly interested in understanding consumer search behavior, i.e., how informed consumers are about prices or other product characteristics when making a purchase decision.
A recent project uses a large-scale data-set obtained from radio frequency identification tags attached to shopping carts. This allows a very detailed tracking of the consumer’s journey through the store and his interaction with marketing activity such as pricing and displays.
Professor Szu-chi Huang’s research focuses on consumer motivation, documenting how consumers have different concerns in different stages of goal pursuit, and thus derive motivation in very distinct ways. Professor Huang uses experiments to tightly examine causal processes, field studies to test these findings in the real world (e.g., launching loyalty programs and donation drives), as well as secondary data from companies and organizations (e.g., Sports data, gamer data).
Her recent projects examine consumer motivation in social settings, including shared goal-pursuit context (e.g., Weight Watchers, video-game players) and competitive context (e.g., sports game, sales competition).
Professor Bayati has two main research interests: machine learning and statistical models for large data, and their applications in healthcare. In particular, he has been focusing on building statistical models from large amount of electronic health records for predicting adverse events in hospital environment.
Learn more about Professor Bayati’s research.
Professor Iancu’s research is focused on problems at the interface of finance and operations that typically involve taking actions in rapidly changing environments, under high degrees of risk and uncertainty.
His work deals with both the development of innovative algorithms and data-driven analytical support tools, as well as with understanding how these interact with business decision making. Specific applications include multiaccount portfolio optimization, strategic and tactical supply chain management, and dynamic pricing.
Professor Casey’s research explores political economy issues in developing countries. Current projects focus on the role of information in elections, under the hypothesis that providing voters with better information about candidates and policy can facilitate more informed voting and greater accountability. Her approach combines applied theory, original data collection and randomized trials. Ongoing field work focuses on Sierra Leone.
For an example of Professor Casey’s research, see this research paper.
Professor Malhotra has been working on three main data-intensive projects. The first analyzes online dating data to explore how political predispositions influence social sorting. The second examines earnings call and news reports to assess the financial returns to corporate social responsibility. The third analyzes comment threads on political websites to better understand “issue publics,” or groups of people passionate about single political issues.