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Professor of Marketing and Statistics
John Liechty


John Liechty is a Professor of Marketing and Statistics at Penn State.

Liechty received his Ph.D. in Mathematical Statistics from the University of Cambridge in 1998. He received his MS in Statistics from Brigham Young University in 1993, and his BS in Applied Physics from Brigham Young University in 1991.

Most of his research is divided between developing statistical methods and models and applying these methods to problems in Marketing and Finance. In Marketing, he has made important contributions by providing methods that help improve the quality of data coming from marketing research studies. In Finance, Liechty has made contributions with regards to both providing better mathematical methods for approximating the price of options, assuming a complex underlying stochastic price process, as well as creating models that provide better asset allocation (e.g. better strategies for purchasing and holding stocks). In Statistics, he has focused on Markov Chain Monte Carlo approaches to inference, and on selectively reducing the size of a dataset while maintaining a high level of the information content. Liechty's recent work has focused on issues related to broader problems in society. Some of this led to establishing better data and analytic capacities for the U.S. Financial regulatory infrastructure. Future work will focus on how society can best organize capital to produce public goods; finding incentive aligned approaches to both reduce Health Care costs; and model large scale (distributional) phenomics based on the geometric structure of the biology of life as revealed through high-resolution images.

2010 – Present Professor of Marketing and Statistics, Smeal College of Business, Pennsylvania State University

2005 – 2010 Associate Professor of Marketing and Statistics, Smeal College of Business,Pennsylvania State University

1999 – 2005 Assistant Professor of Marketing and Statistics, Smeal College of Business, Pennsylvania State University

1996 – 1999 Visiting Assistant Professor, University of Michigan Business School

2013 – 2016 Researcher, Office of Financial Research, U.S. Department of Treasury

2010 – 2012 IBM Research Fellow, affiliated with the IBM Research, T.J. Watson Laboratory

2004 – 2009 Morgan Stanley

2001 – 2002 Goldman Sachs

Liechty is a founding member of the Committee to Establish the National Institute of Finance (; this effort brought together over 150 experts from academia, industry and the regulatory community, including six Nobel Laureates, and resulted in the provision to create an Office of Financial Research, in the U.S. Treasury, as part of the S.3217, the Restoring American Stability Act of 2010. Liechty has been theStatistical Section Editor for the Handbook of Systemic Risk, the Guest Area Editor for Marketing Science, the Editorial Board Marketing Science, and an Adhoc Reviewer for Quantitative Finance; Biometrika; Journal of Marketing Research; Marketing Science; Management Science; Psychometrika


Honors and Awards

  • Alfred P. Sloan Grant to Study the Dynamics of High Frequency Stock Exchanges
  • 2018 Fellow of the American Statistical Association, from 2011
  • IBM Faculty Fellow, 2011
  • Finalist, William O’Dell Award, Best Long-Term Impact, 2005, J. of Marketing Research, 2010
  • Fellow of the Royal Statistical Society, from 1999



  • Markov Chain Monte Carlo Methods for Switching Diffusion Models, Liechty, John C. and Gareth O. Roberts, (2001), Biometrika, 88(2), pp. 229-315.
  • Global and Local Covert Visual Attention: Evidence from a Bayesian Hidden Markov Model, Liechty, John C., Michel Wedel, and Rik Pieters, (2003), Psychometrika, 68(4), pp. 519-541.
  • Modeling Online Browsing and Path Analysis Using Clickstream Data, Montgomery, Alan, Shibo Li, Kannan Srinivasan, and John C. Liechty, (2004), Marketing Science, 23(4), pp. 579-595.
  • Incentive Aligned Conjoint, Ding, Min, Rajdeep Grewal, and John C. Liechty, (2005), Journal of Marketing Research, 42(1), pp. 67-82.
  • Data skeletons: Simultaneous Estimation of Multiple Quantiles for Massive Streaming Data Sets with Application to Density Estimation, McDermott, James P., John C. Liechty, and Dennis K. J. Lin, (2007) Statistics and Computing, 17(4) pp. 311-321.
  • The Shadow Prior, Liechty, John C., Merrill Liechty and Peter Müller (2009), Journal of Graphical and Computational Statistics, 18(2), pp. 368-383.
  • Parallel Multivariate Slice Sampling, Tibbits, Matthew M., Murali Haran, and John C. Liechty, (2010) Statistics and Computing, 21(3), pp. 415-430.
  • Automated Factor Slice Sampling, Tibbits, Matthew M., Groendyke, Chris, Haran, Murali and Liechty, John C., (2014) Journal of Computational and Graphical Statistics, 23:2, 543-563.
  • Bayesian Correlation Estimation, Liechty, John C., Merrill W. Liechty, and Peter Müller, (2004), Biometrika, 91(1), pp. 1-14.
  • Portfolio Selection with Higher Moments, Harvey, C. R., Liechty, J. C., Liechty, M. W., and Müller, P. (2010), Quantitative Finance, 10(5), pp. 469-485.
  • Scientists and Bankers - a New Model Army, Liechty, John (2012), Nature, 484, pp. 143.



  • MKTG 342 - Marketing Research
  • MKTG 450W - Marketing Strategy
  • MKTG 550 - Marketing Models
  • BA 815 - Business Statsitics