Pulak Ghosh

Professor at Indian Institute of Management Bangalore

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  • Indian Institute of Management Bangalore

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Biography

Indian Institute of Management Bangalore

Pulak Ghosh is Professor in the Decision Sciences and Information Systems Area at IIMB. His key specializations are in intersection of Big data, Machine learning, Artificial Intelligence and its use in Economics, Finance, Policy and Social Value Creation. He did serve in the editorial board of Journal of the American statistical Association, Journal of the Royal statistical Society and currently serves in the editorial board of Biometrics.

Based on his outstanding and innovative contribution to research, the International Indian Statistical Association awarded him with the ``Young Scientist Award” in 2011. Govt of India awarded him the prestigious CR Rao award in 2015 and Econometric Society awarded him the Mahalanobis Award in 2016. Professor Ghosh’s research interest areas are:

Big Data, Machine Learning & Artificial Intelligence: Business Analytics, Artificial Intelligence, Statistical learning, Machine Learning, Deep Learning, Bayesian Optimization, Models for Big Data.

Fintech, Finance & Economics ​FinTech, Blockchain, Financial Inclusion, Digital Economy, Household Finance, Advanced Econometrics, Macroeconometrics

Public Policy Big data for Data Gap, Analytics in Policy & Social Value Creation, Data Driven Policy Making and Evaluation, Big data in development

Statistics High-Dimensional Regression, Sparse Model, Bayesian Modeling, Nonparametric Bayes, Scalable Hierarchical Bayesian Models, Bayesian Network, Copula, Survival analysis, Statistical Model for unique data structures, Joint Modeling.

Big data in Counting Employment Towards payroll reporting in India

India is perhaps one of the few countries that does not have a reliable employment (formal and informal) data that could be used as an input for policy making. Currently, Labour Bureau conducts Quarterly Employment Survey (QES) to access employment situation in India. Though the QES provides sector-wise employment situation, its coverage like other survey is limited to only 8 sectors against an universe of 190 sectors. All such limitations allow us to believe that a payroll report for India on the same vein as it is currently being prepared in the US could solve the missing middle. The report for the first time provides an estimate of payroll creation in India for the formal sector based on real time data analytics and suggests ways to enlarge the formal and informal payroll capture through use of big data analytics. The report busts many of the so called myths of payroll creation in Indian context.

The report has been authored by Professor Pulak Ghosh, of Indian Institute of Management Bangalore and Dr. Soumya Kanti Ghosh, Group Chief Economic Advisor, State Bank of India.

For summary of the report, click here.

For full report, click here.

Beginning of Payroll in India

Payroll reporting works

Primitive assumptions don't alter our payroll results

Budget 2018: In Conversation With V Anantha Nageswaran

The jobs statistics debate: A good starting point

Formal Sector Jobs On A Rise? In Conversation With Soumyakanti Ghosh

Change the glasses

Towards a Payroll Reporting in India

Payroll Reporting in India

Publications

Working paper:

Agarwal, S., Ghosh, P., Ghosh, S. K., Seru, A., Shashwat, A. Banking the Unbanked: what do 255 million new Bank accounts reveal about financial Access? Chen, D., Pareek, B., Zhu, H, Ghosh, P., Where do you spent the next dollar: A Bayesian nonparametric deep learning Approach Agarwal, S., Chomsisengphet, S., Ghosh, P., Gupta , S., Do consumers with facebook connections default more? Evidence from a fintech experiment Agarwal, S., Basu, D., Ghosh, P., Pareek , B., and Zhang, J. Demonitization and Digitization: Evidence from the Demonitization in India Agarwal, S., Chomsisengphet, S., Ghosh, P., Zhang, M. Income Tax Exemption Policy and Consumers Consumption and Saving Response Agarwal, V., Ghosh, P., Zhao, H., Fight or Flight: Terrorist attacks and investor trading behaviour Zhang, Y, Fong, D, Ghosh, P., Variable Selection and Hidden Markov Model estimation in massive data using Stochastic MCMC Karmakar, B, Pareek, B., Small, D., Ghosh, P., The Effect of Demonetization on Digital Payments in India: Causal Inference in the Absence of Controls Under Revision:

Banerjee, T., Mukherjee, G., Dutta, S., and Ghosh, P., A Large-scale Constrained Joint Modeling Approach For Predicting User Activity, Engagement And Churn With Application To Freemium Mobile Games. Journal of the American Statistical Association Das, K., Ghosh, P., and Daniels, M. A Semiparametric Bayesian Approach for the analysis of longitudinal data from multiple time-varying related groups. Journal of the American Statistical Association Accepted/Published

2018:

Bhuyan, P., Biswas, J., , Ghosh, P., and Das, K., A Bayesian two-stage regression approach of analysing longitudinal outcomes with endogeneity and incompleteness, Statistical Modelling (Accepted: Available Online) Pareek, B, Liu, Q., Ghosh, P., Ask Your Doctor if This Product is Right for You: A Bayesian Zero Inflated Multinomial Joint Model for Drug Requests and Physicians' Prescriptions. Journal of Royal Statistical Society: Series A, (Accepted)

Pareek, B., Ghosh, P., Wilson, H., Macdonalds, E., Real-Time Consumer Experience Tracking and the Dynamics of Brand Choice: An Application to the UK General Elections, Journal of the American Statistical Association (Accepted: Available Online)

2017:

Voleti, S., Srinivasan, S., and Ghosh, P. An Approach to Improve the Predictive Power of Choice-Based Conjoint Analysis. International Journal of Research in Marketing, 34 (2), 325-335. 2016:

Bhagat, S., Ghosh, P., Rangan, S. Economic Policy Uncertainty and Economic Growth in India, Economic and Political Weekly, Vol 51, 72-81. Sriram, K, Ramamoorthi, R.V., and Ghosh, P.. Simultaneous Bayesian Estimation of Multiple Quantiles with an Extension to Hierarchical Models Sankhya, 78, 87-104 Brown, S., Ghosh, P., Taylor, K., Household Finances and Social Interaction: Bayesian Analysis of Household Panel Data, Review of Income and Wealth, 62, 467-488. 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, 31, 1140-1158. 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, 177-202. 2015:

Brown, S., Ghosh, P., and Taylor, K., Modelling Household Finances: A Bayesian Approach to a Multivariate two-part model, Journal of Empirical Finance (Accepted) Stober, J., Czado, C., Hong, G., and Ghosh, P. Modeling Multiple Chronic Diseases in the Elderly: Longitudinal Patterns Identified by Copula Design for Mixed Responses, Computational Statistics & Data Analysis (Accepted) 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., and 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., and 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., and 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., and Taylor, K. The Existence and Persistence of Household Financial Hardship: A Bayesian Multivariate Dynamic Logit Framework, Journal of Banking and Finance, 46: 285–298. Farcomeni, A., Pareek, B., and 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., and Ghosh, P. Linear Mixed Models for Multiple Outcomes using Extended Multivariate Skew-t Distributions, Statistics and Interface, 101-111. Hong, G., Roychowdhury, S., and Ghosh, P. The Joint Assessment of Longitudinal Multidimensional Functioning’s in Overweight 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. and 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., and Ghosh, P. A Semiparametric Bayesian Approach for Mark-Recapture Estimation, Model Assisted Statistics and Applications, 8, 29–39.

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

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