Profile

Faculty

Pulak Ghosh

Pulak Ghosh  Print Bio

Quantitative Methods & Information Systems

Professor

Pulak Ghosh is Professor in the Quantitative Methods & Information Systems area at IIMB. His key specializations are in various fields of Quantitative Marketing, Big Data, Analytics, Bayesian Nonparametric, Health analytics, Econometrics. He is an accomplished researcher of international repute.

He is an accomplished researcher of international repute. Prior to joining IIMB, he served as Associate Director, Novartis Pharmaceuticals, USA, Assistant Professor, Department of Statistics, Georgia State University, and Associate Professor at Emory University, USA. He is a visiting faculty at several institutes of international repute.

Professor Ghosh’s research areas are

Marketing

Quantitative Marketing, Political Marketing, Choice Modeling, Probability Models for Marketing Data, Marketing-Information systems Interface

Analytics

Big data, Machine Learning, Business analytics, Marketing Analytics, Health Analytics

Statistics

Applied Bayesian Modeling, Econometrics, Asset Pricing, Health care, Survival analysis, Joint Modeling, Statistical Model for unique data structures

Recent Publications:

2015:

  • Durham, G., Geweke, J., Ghosh, P. A note on Consistent estimation of a dynamic jump intensity model with implications for option pricing. Journal of Financial Economics, 115, 210-214.
  • Voleti, S., Kopalle, P., and Ghosh, P. A Dynamic Measure of Attribute Based Inter-Product Competition: An Application to the Category Profit Maximization Problem, Management Science (Marketing Section) (Accepted)
  • Sriram, K, Shi, P., and Ghosh, P. Insurance Production Costs: An Examination Using a Bayesian Semiparametric Quantile Regression, Journal of Royal Statistical Society: Series A, (Accepted)
  • Brown, S., Ghosh, P., Taylor, K. , Household Finances and Social Interaction: Bayesian Analysis of Household Panel Data, Review of Income and Wealth, (Accepted)
  • Mukherji, A., Roychowdhury, S., and Ghosh, P. , Brown, S., A Bayesian Joint Model for Hospitalization and Out-of-Pocket Expenditures with Application to Aging Population, Journal of Applied Econometrics, (Accepted)
  • Hong, G., Ryan, Yue., Ghosh, P. Bayesian Estimation of Long- Term Health Consequences of Obese and Normal-Weight Elderly. Journal of Royal Statistical Society: Series A, (Accepted)
  • Stanley I. M. Ko, Chong, T. L., and Ghosh, P, Dirichlet Process Hidden Markov Multiple Change-point Model, Bayesian Analysis, (Accepted)

2014:

  • Brown, S., Ghosh, P., Taylor, K. , The Existence and Persistence of House- hold Financial Hardship: A Bayesian Multivariate Dynamic Logit Framework, Journal of Banking and Finance, 46: 285–298.
  • Farcomeni, A., Pareek, B., Ghosh, P. , Invited Discussion on the paper “Joint Modeling of Survival and Longitudinal Non-Survival Data: Current Methods and Issues”, By Gould et al. Statistics in Medicine, (Accepted)
  • Yu, B., O’ Malle, A. J., Ghosh, P. Linear mixed models for multiple outcomes using extended multivariate skew-t distributions, Statistics and Interface, 101-111
  • Hong, G., Roychowdhury, S., Ghosh, P. The Joint Assessment of Longitudinal Mul- tidimensional Functioning’s in Over weight and Obese Elderly with a Time Varying Covariates, Statistics and Interface, 297-305
  • Voleti, S.,and Ghosh, P. A non-parametric model of residual brand equity in hierarchical branding structures with application to US beer data, Journal of the Royal Statistical Society: Series A, 177, 135–152.
  • Ausin, C. M., Galeano, P., and Ghosh, P. , A Semiparametric Bayesian Approach to the Analysis of Financial Time Series with Applications to Value at Risk Estimation, European Journal of Operations Research, 232, 350–358.

2013:

  • Wai, M., Tu, W., Ghosh, P., and Tiwari, R. A Nested Dirichlet Process Analysis of Cluster Randomized Trial Data with Application in Geriatric Care Assessment, Journal of the American Statistical Association, 108, 48–68.
  • Voleti, S., Ghosh, P. A Robust Model to Measure Equity in Hierarchical Branding Structures Quantitative Marketing and Economics, 11, 289–319
  • Sriram, K., Ramamoorthi, R.V., and Ghosh, P. Posterior consistency of Bayesian Quantile Regression based on the Misspecified asymmetric laplace density, Bayesian Analysis, 8, 479–504. Muthukumarana, S., Ghosh, P. A semiparametric Bayesian approach for mark-recapture estimation, Model Assisted Statistics and Applications, 8, 29–39

He teaches some of the following courses:

Quantitative Methods, Marketing Analytics, Big data, Bayesian Modeling, Nonparametrics Bayes, Statistics 3, Bayesian Network , Predictive Analytics

  • PhD, Statistics, Oakland University, Michigan, USA
  • BSc & MSc, Statistics, University of Calcutta, India