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John C. Liechty

Color portrait of John C. Liechty

Professor

Department Marketing
Office Address 409 Business Building
Phone Number 814-865-0621
Email Address jcl12@psu.edu

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Dr. Liechty is a Professor at the Smeal College of Business, with a courtesy appointment as a Professor of Statistics at the Eberly College of Science. He is interested in the creation of public goods and the role that universities can play in these efforts. Past initiatives include leading an effort that resulted in a provision in the Dodd-Frank Act of 2010 that creates a new Office in the U.S. Treasury, the Office of Financial Research, which has the mandate to provide better data and analytic tools to the regulatory community in order to safeguard the U.S. financial system.

He is a Fellow of the American Statistical Association and a Fellow of the Royal Statistics Society. He has published widely in top academic journals in Marketing, Statistics, Psychology and Finance, including Marketing Science, Journal of Marketing Research, Biometrika, Psychometrika, Journal of Experimental Psychology, Journal of Investment Management and Nature. In addition, he has experience in developing solutions for top Marketing Research firms and Investment Banks. He is an expert in marketing research, computational statistics and high-performance computing, and derivative pricing and asset allocation as well as financial stability. Dr. Liechty has a PhD from the Statistical Laboratory at Cambridge University.

Expertise

Marketing Research, Bayesian Statistics, Financial Systems, Geometry of Life, Economics of Public Goods.

Education

Ph D, Mathematical Statistics, Cambridge University, 1998

MS, Statistics, Brigham Young University, 1993

BS, Physics, Brigham Young University, 1991

Courses Taught

BA 815 – Business Statistics (2)
This course provides an overview of statistical concepts and methods including descriptive statistics, probability, statistical inference, hypothesis testing, ANOVA, Correlation analysis, Contingency Tables, and Simple, Multiple, and Logistic Regression. The approach to course material will be both numerical and applied in order to provide a conceptual understanding of statistics. Applications of these methods will be applied to problems in various business settings such as Marketing, Finance, Accounting and Supply Chain.

MKTG 342 – Marketing Research (3)
Research approaches, methods, and applications studied as a formal approach to problem solving for marketing decisions.

MKTG 555 – Mktg Models (3)
Topics in the model building approach to marketing decision making, focusing on current research issues.

BA 515 – Bus Statistics (2)
This course is designed to meet the entry statistical requirements for any course in the Smeal M.B.A. Program, as well as to provide job applicable skills across the entire business portfolio.

MKTG 496 – Indep Studies (1)
Creative projects, including research and design, which are supervised on an individual basis and which fall outside the scope of formal courses.

B A 515 – Business Statistics for Contemporary Decision Making (2)
Conceptual understanding of statistics through both numerical and applied approach.

MKTG 596 – Individual Studies (9)
Creative projects, including nonthesis research, which are supervised on an individual basis and which fall outside the scope of formal courses.

MKTG 450W – Marketing Management Policies and Programs (3)
Market-oriented problems of the firm; identification and selection of market opportunities; formulation of competitive strategies; marketing policies and programs.

MKTG 597A – Marketing in Challenging Times (3)
This course focuses on two aspects of Bayesian Statistics: hierarchical model building and inference using the Markov chain Monte Carlo algorithm.

B A 596 – Individual Studies (variable)
Creative projects, including nonthesis research, which are supervised on an individual basis and which fall outside the scope of formal courses.

STAT 596 – Individual Studies (variable)
Creative projects, including nonthesis research, which are supervised on an individual basis and which fall outside the scope of formal courses.

B A 303 – Marketing (2)
Introduction to customer behavior and research, service/product development, pricing and promotion in diverse and international marketing contexts.

Selected Publications

Benthall S., Caroll C., David Z., Liechty J. C., Lujan A., McComb C., Skar-Gislinge N., "Simulating Heterogeneous Portfolio Choices and Financial Market Outcomes." Agent-based Modeling and Policy-Making Workshop, 2023
Yakovlev M. A., Liang K., Zaino C. R., Vanselow D. J., Sugarman A. L., Lin A. Y., La Riviere P. J., Zheng Y., Silverman J. D., Liechty J. C., Huang S., Cheng K., "Quantiative Geometric Modeling of Blood Cells from X-ray Histotomograms of Whole Zebrafish Larvae." eLife, 2023
Wright I. D., Reimherr M., Liechty J. C., "A Machine Learning Approach to Classification for Traders in Financial Markets." Stat, 2022
Liechty J. C., Howell J., Ebbes P., Jenkins P., "Gremlins in the Data: Identifying the Information Content of Research Subjects." Journal of Marketing Research, vol. 58, no. 1, 2021
Liechty J., Wuyts S., "If I Had a Hedge Fund, I Would Cure Diabetes Endogenous Mechanisms for Creating Public Goods." Science &Nature Business and Economics, vol. 1, no. 10, 2021, pp. 18
Rossi M., Liechty J., Huang J., "Return Smoothing and its Implications for Performance Analysis of Hedge Funds." Journal of Finance and Data Science, 2018
Ebbes P., Liechty J. C., Grewal R., "Attribute Level Heterogeneity." Management Science, vol. 61, no. 4, 2015, pp. 885-897
Tibbits M. M., Groendyke C., Haran M., Liechty J. C., "Automated Factor Slice Sampling." Journal of Computational and Graphical Statistics, vol. 23, no. 2, 2014, pp. 543-563
Allenby G. M., Bradlow E. T., George E. L., Liechty J. C., McCulloch R. E., "Perspectives on Bayesian Methods and Big Data." Customer Needs and Solutions, vol. 1, no. 3, 2014, pp. 169-175
Liechty J. C., "Regime Switching Models and Risk Management Tools." The Handbook of Systemic Risk, (Cambridge University Press), 2012
King A., Liechty J. C., Rossi C., Taylor C., "Frameworks for Systemic Risk Monitoring." (Cambridge University Press), 2012
Eds. JP Fouque and Joseph Langsam
Liechty J. C., "Scientists and Bankers - a New Model Army." Nature, vol. 484, 2012, pp. 143
World View Article
Liechty J. C., Foster R., "Financial Hurricanes." Significance, 2011
Cheng W., Costanzino N., Liechty J. C., Mazzucato A. L., Nistor V., "Closed-form Asymptotics for Local Volatility Models." SIAM Journal on Fiancial Mathematics, vol. 2, 2011, pp. 901-934
Liechty J. C., Liechty M. W., Muller P., "MCMC for Constrained Parameter and Sample Spaces." Frontier of Statistical Decision Making and Bayesian Analysis, 2010
Liechty J. C., Liechty M. W., Harvey C. R., "Parameter Uncertainty and Asset Allocation." The [Oxford] Handbook of Quantitative Asset Management, (Oxford University Press), 2010
Tibbits M., Haran M., Liechty J. C., "Parallel Multivariate Slice Sampling." Statistics and Computing, vol. 21, no. 3, 2010, pp. 415-430
Harvey C. R., Liechty J. C., Liechty M., Muller P., "Portfolio Selection with Higher Moments." Quantitative Finance, vol. 10, no. 5, 2010, pp. 469-485
Mendelowitz A. I., Liechty J. C., "New Tools Mean Regulations Will No Longer Be Flying Blind." Financial Times, 2010
Liechty J. C., Liechty M., "The Shadow Prior." Journal of Graphical and Computational Statistics, vol. 18, no. 2, 2009, pp. 368-383
Mendelowitz A. I., Liechty J. C., "Financial Regulators Need Better Data." American Banker, 2009
Desarbo W., Liechty J. C., Park J., "A hierarchical bayesian multidimensional scaling methodology for accommodating both structural and preference heterogeneity." Psychometrika, vol. 73, no. 3, 2008, pp. 451-472
Liechty J. C., Lilien G. L., DeBruyn A., Huizingh E., "Offering online recommendations with minimal customer input through conjoint-based decision aids.." Marketing Science, vol. 27, no. 3, 2008, pp. 443-460
Liechty J. C., Wedel M., Pieters R., "How Goals Influence the Time Course of Eye Movements Across Advertisements." Journal of Experimental Psychology: Applied, vol. 14, no. 2, 2008, pp. 129-138
Liechty J. C., Fong D., Huizingh E., De Bruyn A., "Hierarchical Bayesian Conjoint Models Incorporating Measurement Uncertainty." Marketing Letters, vol. 19, 2008
Harvey C. R., Liechty J. C., Liechty M. W., "Comments on Bayes vs. Markowitz: a Rematch." Journal of Investment Management, vol. 6, no. 2, 2008, pp. 1-2
Liechty J. C., Netzer O., Toubia O., "Beyond Conjoint Analysis: Advances in Preference Measurement." Marketing Letters, vol. 19, no. 3, 2008, pp. 337-354
Liechty J. C., Harvey C., Liechty M., "Bayes vs. resampling: A rematch.." Journal of Investment Management, vol. 6, no. 1, 2008, pp. 29
Liechty J. C., Chakravarty A., Ding M., Liechty J., "Counting chickens before the eggs hatch: Associating new product development portfolios with shareholder expectations in the pharmaceutical sector." International Journal of Research in Marketing, vol. 25, 2008, pp. 261-272
Lin D. K., McDermott J., Babu G., Liechty J. C., "Data Skeletons: Simultaneous Estimation on Multiple Quantities Massive Streaming Datasets with Applications to Density Estimation." Journal of Statistics & Computing, vol. 17, 2007, pp. 311-321
Liechty J. C., Fong D., Desarbo W., "Dynamic Models with Individual Level Heterogeneity: Applied to Evolution During Conjoint Studies." Marketing Science, vol. 24, no. 2, 2005, pp. 285-293
Desarbo W., Fong D., Liechty J. C., Coupland J. C., "Evolutionary Preferences/Utility Functions: A Dynamic Perspective." Psychometrika, no. 70, 2005, pp. 179-202
Ding M., Grewal R. S., Liechty J. C., "Incentive-Aligned Conjoint Analysis." Journal of Marketing Research, vol. 42, 2005, pp. 67-82
Finalist for Paul Green Award and Finalist for William O'Dell Award
Desarbo W., Fong D., Liechty J. C., Saxon M., "A Hierarchical Bayesian Procedure for Two-mode Cluster Analysis." Psychometrika, vol. 69, no. 1, 2004, pp. 547-572
Lead Article
Montomgery A., Li S., Srinivasan K., Liechty J. C., "Modeling Online Browsing and Path Analysis Using Clickstream Data." Marketing Science, vol. 23, no. 4, 2004, pp. 579-595
Finalist for John D.C. Little Award
Liechty J. C., Liechty M. W., Muller P., "Bayesian Correlation Estimation." Biometrika, vol. 91, no. 1, 2004, pp. 1-14
Lead Article
Desarbo W., Fong D., Liechty J. C., "Two-mode cluster analysis via hierarchical Bayes procedure." 2003
27th Annual GfKl Conference, University of Cottbus. Daniel Baier, Klaus-Dieter Wernecke (eds.): Innovations in Classification, Data Science, and Information Systems. Springer-Verlag, Heidelberg-Berlin.
Wedel M., Pieters R., Liechty J. C., "Evidence for Covert Attention Switching From Eye-Movements: Reply on Commentaries on Liechty." Psychometrika, vol. 68, no. 4, 2003, pp. 557-562
Liechty J. C., Wedel M., Pieters R., "Global and Local Covert Visual Attention: Evidence from a Bayesian Hidden Markov Market." Psychometrika, vol. 68, no. 4, 2003, pp. 519-541
Psychometrika's Inaugural Discussion Paper
Liechty J. C., Lin D. K., McDermott J. P., "Single-pass Low-storage Arbitrary Quantile Estimation for Massive Datasets." Statistics and Computing, vol. 13, no. 2, 2003, pp. 91-100
Liechty J. C., Ramaswamy V., Cohen S., "Choice Menus for Mass Customization: An Experimental Approach for Analyzing Customer Demand with an Application to a Web-based Information Service." Jounral of Marketing Research, vol. 38, no. 2, 2001, pp. 183-196
Liechty J. C., Roberts G. O., "Markov Chain Monte Carlo Methods for switching Diffusion Models." Biometrika, vol. 88, no. 2, 2001, pp. 229-315

Research Impact and Media Mentions

"Financial hurricanes", Significance, Journal or Magazine
"New tools mean regulators will no longer be flying blind", Financial Times, Journal or Magazine

Editorships

Jornal of Marketing Research, Editorial Board, January 2019 - Present
Marketing Science, Editorial Board, May 2007 - December 2011